Escribir un punto al final de la siguiente ecuación.

Escribir una coma al final de la siguiente ecuación.

falta una llave en la definición del conjunto omega.

Revisa la definición del conjunto omega para que se corresponda con el problema planteado, o bien, plantea de una mejor manera el problema.

¿Te refieres al dado? Faltan palabras para entender lo que quieres decir.

escribir una coma al final de cada ecuación en f(x;k,lambda)

está dada por f(x)=...

Poner una coma al final de x mayor o igual a cero y una coma después de x<0

.

Olá autores, espero encontrá-los bem!

Neste semestre cursei uma disciplina em que foi proposto a minha atuação como parecerista. O tema escolhido por vocês me despertou interesse e gostaria de contribuir com o que aprendi ao longo do semestre. Gostaria de parabenizá-los pelo trabalho e de tecer algumas sugestões e apontamentos que acredito que possam ser de relevante contribuição: o artigo oferece uma análise consistente e pode desempenhar um papel significativo na discussão sobre sustentabilidade na educação superior, trazendo reflexões pertinentes tanto para gestores quanto para formuladores de políticas públicas. Mas, apesar de mencionar a necessidade de gestão sustentável, não apresenta indicadores claros que possam ser utilizados pelas universidades para medir o progresso. De igual modo, apesar de apontar para a necessidade de reformulação dos currículos, faltam exemplos práticos de disciplinas ou programas que poderiam ser implementados.

No mais, gostaria de parabenizá-los pelo excelente trabalho e por contribuírem para a área.

Obrigado!

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):

Summary:

"Neural noise", here operationalized as an imbalance between excitatory and inhibitory neural activity, has been posited as a core cause of developmental dyslexia, a prevalent learning disability that impacts reading accuracy and fluency. This study is the first to systematically evaluate the neural noise hypothesis of dyslexia. Neural noise was measured using neurophysiological (electroencephalography [EEG]) and neurochemical (magnetic resonance spectroscopy [MRS]) in adolescents and young adults with and without dyslexia. The authors did not find evidence of elevated neural noise in the dyslexia group from EEG or MRS measures, and Bayes factors generally informed against including the grouping factor in the models. Although the comparisons between groups with and without dyslexia did not support the neural noise hypothesis, a mediation model that quantified phonological processing and reading abilities continuously revealed that EEG beta power in the left superior temporal sulcus was positively associated with reading ability via phonological awareness. This finding lends support for analysis of associations between neural excitatory/inhibitory factors and reading ability along a continuum, rather than as with a case/control approach, and indicates the relevance of phonological awareness as an intermediate trait that may provide a more proximal link between neurobiology and reading ability. Further research is needed across developmental stages and over a broader set of brain regions to more comprehensively assess the neural noise hypothesis of dyslexia, and alternative neurobiological mechanisms of this disorder should be explored.

Strengths:

The inclusion of multiple methods of assessing neural noise (neurophysiological and neurochemical) is a major advantage of this paper. MRS at 7T confers an advantage of more accurately distinguishing and quantifying glutamate, which is a primary target of this study. In addition, the subject-specific functional localization of the MRS acquisition is an innovative approach. MRS acquisition and processing details are noted in the supplementary materials according to the experts' consensus-recommended checklist (https://doi.org/10.1002/nbm.4484). Commenting on the rigor, the EEG methods is beyond my expertise as a reviewer.

Participants recruited for this study included those with a clinical diagnosis of dyslexia, which strengthens confidence in the accuracy of the diagnosis. The assessment of reading and language abilities during the study further confirms the persistently poorer performance of the dyslexia group compared to the control group.

The correlational analysis and mediation analysis provide complementary information to the main case-control analyses, and the examination of associations between EEG and MRS measures of neural noise is novel and interesting.

The authors follow good practice for open science, including data and code sharing. They also apply statistical rigor, using Bayes Factors to support conclusions of null evidence rather than relying only on non-significant findings. In the discussion, they acknowledge the limitations and generalizability of the evidence and provide directions for future research on this topic.

Weaknesses:

Though the methods employed in the paper are generally strong, there are certain aspects that are not clearly described in the Materials & Methods section, such as a description of the statistical analyses used for hypothesis testing.

Thank you for pointing this out. A description of the statistical models used in the analyses of EEG biomarkers has been added to the Materials and Methods:

“First, exponent and offset values were averaged across all electrodes and analyzed using a 2x2 repeated measures ANOVA with group (dyslexic, control) as a between-subjects factor and condition (resting state, language task) as a within-subjects factor. Age was included in the analyses as a covariate due to the correlation between variables. Next, exponent and offset values were averaged across electrodes corresponding to the left (F7, FT7, FC5) and right inferior frontal gyrus (F8, FT8, FC6), and to the left (T7, TP7, TP9) and right superior temporal sulcus (T8, TP8, TP10). The electrodes were selected based on the analyses outlined by Giacometti and colleagues (2014) and Scrivener and Reader (2022). For these analyses, a 2x2x2x2 repeated measures ANOVA with age as a covariate was conducted with group (dyslexic, control) as a between-subjects factor and condition (resting state, language task), hemisphere (left, right), and region (frontal, temporal) as within-subjects factors. Results for the alpha and beta bands were calculated for the same clusters of frontal and temporal electrodes and analyzed with a similar 2x2x2x2 repeated measures ANOVA; however, for these analyses, age was not included as a covariate due to a lack of significant correlations.”

We also expanded the description of the statistical models used in the analyses of MRS biomarkers:

“To analyze the metabolite results, separate univariate ANCOVAs were conducted for Glu, GABA+, Glu/GABA+ ratio and Glu/GABA+ imbalance measures with group (control, dyslexic) as a between-subjects factor and voxel gray matter volume (GMV) as a covariate. Additionally, for the Glu analysis, age was included as a covariate due to a correlation between variables. Both frequentist and Bayesian statistics were calculated. Glu/GABA+ imbalance measure was calculated as the square root of the absolute residual value of a linear relationship between Glu and GABA+ (McKeon et al., 2024).”

With regard to metabolite quantification, it is unclear why the authors chose to analyze and report metabolite values in terms of creatine ratios rather than quantification based on a water reference given that the MRS acquisition appears to support using a water reference.

We have decided to use the ratio of Glu and GABA to total creatine (tCr), as this is still a common practice in MRS studies at 7T (e.g., Nandi et al., 2022; Smith et al., 2021). This approach normalizes the signal, reducing the impact of intensity variations across different regions and tissue compositions. Additionally, total creatine concentration is considered relatively stable across different brain regions, which is particularly important in our study, where a functional localizer was used to establish the left STS region individually. Our decision was further influenced by previous studies on dyslexia (Del Tufo et al., 2018; Pugh et al., 2014) which have reported creatine ratios and included GM volume as a covariate in their models, thus providing comparability. It is now indicated in the Results:

“For comparability with previous studies in dyslexia (Del Tufo et al., 2018; Pugh et al., 2014) we report Glu and GABA as a ratio to total creatine (tCr).”

and in the Method sections:

“Glu and GABA+ concentrations were expressed as a ratio to total-creatine (tCr; Creatine + Phosphocreatine) following previous MRS studies in dyslexia (Del Tufo et al., 2018; Pugh et al., 2014).

We did not estimate absolute concentrations using water signals as a reference, as this would require accounting for water relaxation times, which may vary across our age range. Nevertheless, our dataset has been made publicly available for future researchers to calculate and compare absolute values.

Del Tufo, S. N., Frost, S. J., Hoeft, F., Cutting, L. E., Molfese, P. J., Mason, G. F., Rothman, D. L., Fulbright, R. K., & Pugh, K. R. (2018). Neurochemistry Predicts Convergence of Written and Spoken Language: A Proton Magnetic Resonance Spectroscopy Study of Cross-Modal Language Integration. Frontiers in Psychology, 9, 1507. https://doi.org/10.3389/fpsyg.2018.01507

Nandi, T., Puonti, O., Clarke, W. T., Nettekoven, C., Barron, H. C., Kolasinski, J., Hanayik, T., Hinson, E. L., Berrington, A., Bachtiar, V., Johnstone, A., Winkler, A. M., Thielscher, A., Johansen-Berg, H., & Stagg, C. J. (2022). tDCS induced GABA change is associated with the simulated electric field in M1, an effect mediated by grey matter volume in the MRS voxel. Brain Stimulation, 15(5), 1153–1162. https://doi.org/10.1016/j.brs.2022.07.049

Pugh, K. R., Frost, S. J., Rothman, D. L., Hoeft, F., Del Tufo, S. N., Mason, G. F., Molfese, P. J., Mencl, W. E., Grigorenko, E. L., Landi, N., Preston, J. L., Jacobsen, L., Seidenberg, M. S., & Fulbright, R. K. (2014). Glutamate and choline levels predict individual differences in reading ability in emergent readers. Journal of Neuroscience, 34(11), 4082–4089. https://doi.org/10.1523/JNEUROSCI.3907-13.2014

Smith, G. S., Oeltzschner, G., Gould, N. F., Leoutsakos, J. S., Nassery, N., Joo, J. H., Kraut, M. A., Edden, R. A. E., Barker, P. B., Wijtenburg, S. A., Rowland, L. M., & Workman, C. I. (2021). Neurotransmitters and Neurometabolites in Late-Life Depression: A Preliminary Magnetic Resonance Spectroscopy Study at 7T. Journal of Affective Disorders, 279, 417–425. https://doi.org/10.1016/j.jad.2020.10.011

GABA is typically quantified using J-editing sequences as lower field strengths (~3T), and there is some evidence that the GABA signal can be reliably measured at 7T without editing, however, the authors should discuss potential limitations, such as reliability of Glu and GABA measurements with short-TE semi-laser at 7T.

In addition, MRS measurements of GABA are known to be influenced by macromolecules, and GABA is often denoted as GABA+ to indicate that other compounds contribute to the measured signal, especially at a short TE and in the absence of symmetric spectral editing.

A general discussion of the strengths and limitations of unedited Glu and GABA quantification at 7T is warranted given the interest of this work to researchers who may not be experts in MRS.

While we agree with the Reviewer that at 3T, it is recommended to use J-edited MRS to measure GABA (Mullins et al., 2014), the better spectral resolution at 7T allows for more reliable results for both metabolites using moderate echo-time, non-edited MRS (Finkelman et al., 2022). In this study, we used a short echo time (TE), which is optimal for Glu but not ideal for GABA, as it interferes with other signals. We are grateful to the Reviewer for suggesting the addition of a short paragraph to the Discussion, describing the practicalities of 3T and 7T MRS and changing the abbreviation to GABA+ to inform readers of possible macromolecule contamination:

“We chose ultra-high-field MRS to improve data quality (Özütemiz et al., 2023), as the increased sensitivity and spectral resolution at 7T allows for better separation of overlapping metabolites compared to lower field strengths. Additionally, 7T provides a higher signal-to-noise ratio (SNR), improving the reliability of metabolite measurements and enabling the detection of small changes in Glu and GABA concentrations. Despite these theoretical advantages, several practical obstacles should be considered, such as susceptibility artifacts and inhomogeneities at higher field strengths that can impact data quality. Interestingly, actual methodological comparisons (Pradhan et al., 2015; Terpstra et al., 2016) show only a slight practical advantage of 7T single-voxel MRS compared to optimized 3T acquisition. For example, fitting quality yielded reduced estimates of variance in concentration of Glu in 7T (CRLB) and slightly improved reproducibility levels for Glu and GABA (at both fields below 5%). Choosing the appropriate MRS sequence involves a trade-off between the accuracy of Glu and GABA measurements, as different sequences are recommended for each metabolite. J-edited MRS is recommended for measuring GABA, particularly with 3T scanners (Mullins et al., 2014). However, at 7T, more reliable results can be obtained using moderate echo-time, non-edited MRS (Finkelman et al., 2022). We have opted for a short-echo-time sequence, which is optimal for measuring Glu. However, this approach results in macromolecule contamination of the GABA signal (referred to as GABA+).”

Finkelman, T., Furman-Haran, E., Paz, R., & Tal, A. (2022). Quantifying the excitatory-inhibitory balance: A comparison of SemiLASER and MEGA-SemiLASER for simultaneously measuring GABA and glutamate at 7T. NeuroImage, 247, 118810. https://doi.org/10.1016/j.neuroimage.2021.118810

Mullins, P. G., McGonigle, D. J., O'Gorman, R. L., Puts, N. A., Vidyasagar, R., Evans, C. J., Cardiff Symposium on MRS of GABA, & Edden, R. A. (2014). Current practice in the use of MEGA-PRESS spectroscopy for the detection of GABA. NeuroImage, 86, 43–52. https://doi.org/10.1016/j.neuroimage.2012.12.004

Özütemiz, C., White, M., Elvendahl, W., Eryaman, Y., Marjańska, M., Metzger, G. J., Patriat, R., Kulesa, J., Harel, N., Watanabe, Y., Grant, A., Genovese, G., & Cayci, Z. (2023). Use of a Commercial 7-T MRI Scanner for Clinical Brain Imaging: Indications, Protocols, Challenges, and Solutions-A Single-Center Experience. AJR. American Journal of Roentgenology, 221(6), 788–804. https://doi.org/10.2214/AJR.23.29342

Pradhan, S., Bonekamp, S., Gillen, J. S., Rowland, L. M., Wijtenburg, S. A., Edden, R. A., & Barker, P. B. (2015). Comparison of single voxel brain MRS AT 3T and 7T using 32-channel head coils. Magnetic Resonance Imaging, 33(8), 1013–1018. https://doi.org/10.1016/j.mri.2015.06.003

Terpstra, M., Cheong, I., Lyu, T., Deelchand, D. K., Emir, U. E., Bednařík, P., Eberly, L. E., & Öz, G. (2016). Test-retest reproducibility of neurochemical profiles with short-echo, single-voxel MR spectroscopy at 3T and 7T. Magnetic Resonance in Medicine, 76(4), 1083–1091. https://doi.org/10.1002/mrm.26022

Further, the single MRS voxel location is a limitation of the study as neurochemistry can vary regionally within individuals, and the putative excitatory/inhibitory imbalance in dyslexia may appear in regions outside the left temporal cortex (e.g., network-wide or in frontal regions involved in top-down executive processes). While the functional localization of the MRS voxel is a novelty and a potential advantage, it is unclear whether voxel placement based on left-lateralized reading-related neural activity may bias the experiment to be more sensitive to small, activity-related fluctuations in neurotransmitters in the CON group vs. the DYS group who may have developed an altered, compensatory reading strategy.

We agree that including only one region of interest for the MRS measurements is a potential limitation of our study, and we have now added this information to the Discussion:

“Moreover, since the MRS data was collected only from the left STS, it is plausible that other areas might be associated with differences in Glu or GABA concentrations in dyslexia.”

However, differences in Glu and GABA concentrations in this region were directly predicted by the neural noise hypothesis of dyslexia. We acknowledge that this information was missing in the previous version of the manuscript. It is now included in the Results:

“Moreover, the neural noise hypothesis of dyslexia identifies perisylvian areas as being affected by increased glutamatergic signaling, and directly predicts associations between Glu and GABA levels in the superior temporal regions and phonological skills (Hancock et al., 2017).”

as well as in the Discussion:

“Nevertheless, the neural noise hypothesis predicted increased glutamatergic signaling in perisylvian regions, specifically in the left superior temporal cortex (Hancock et al., 2017).”

Figure 1 contains a lot of information, and it may be helpful to split it into 2 figures (EEG vs. MRS) so that the plots could be made larger and the reader could more easily digest the information.

(a) I would also recommend displaying separate metabolite fit plots for each group, since the current presentation in panel F makes it appear that the MRS data is examined by testing differences between groups across the full spectrum (where the lines diverge), which really isn't the case.

(b) The GABA peak is not visible in the spectrum, and Glutamate and GABA both have multiple peaks that should be shown on the spectrum. This may be best achieved by displaying the individual metabolite sub-spectra below the full spectrum

Thank you for these suggestions. We have split the information into two Figures following the Reviewer’s recommendations.

It is not clear why the 3T structural images were used for segmentation and calculation of tissue fraction if 7T structural images were also acquired (which would presumably have higher resolution).

Generally, T1-weighted images from the 7T scanner exhibit more artifacts than those from the 3T scanner due to higher magnetic field inhomogeneity. These artifacts are especially pronounced in regions near air-tissue interfaces, such as the temporal lobes. Therefore, we chose the 3T structural images for segmentation and tissue fraction calculations and clarified this in the Method section:

“Voxel segmentation was performed on structural images from a 3T scanner, coregistered to 7T structural images in SPM12, as the latter exhibited excessive artifacts and intensity bias in the temporal regions”.

The basis set includes a large number of metabolites (27), including many low-concentration metabolites/compounds (e.g., bHG, bHB, Citrate, Threonine, ethanol) that are typically only included in studies targeting specific metabolites in disease/pathology. Please justify the inclusion of this maximal set of metabolites in the basis set, given that the inclusion of overlapping low-concentration metabolites may influence metabolite measurements of interest (https://doi.org/10.1002/mrm.10246).

There is still no consensus in the MR community on which metabolites should be included in the model of human cerebral 1H-MR spectra. Typically, only major contributors such as NAA, Cr, Cho, Lac, mI, and possibly Glx are evaluated. Some studies also include additional metabolites like Ace, Ala, Asp, GABA, Glc, Gly, sI, NAAG, and Tau. In this study, as in a few others, further metabolites such as PCh, GPC, PCr, GSH, PE, and Thr were introduced and this approach seems suitable for high-field spectra (Hofmann et al., 2002).

Hofmann, L., Slotboom, J., Jung, B., Maloca, P., Boesch, C., & Kreis, R. (2002). Quantitative 1H-magnetic resonance spectroscopy of human brain: Influence of composition and parameterization of the basis set in linear combination model-fitting. Magnetic Resonance in Medicine, 48(3), 440–453. https://doi.org/10.1002/mrm.10246

Please provide a figure indicating the localization of the MRS voxel for a sample subject.

A figure indicating the localization of the MRS voxel for a sample subject was added to the MRS checklist.

It would be helpful to include Table S1 in the main article.

Table S1 from the Supplementary Material has now been added to the main manuscript as Table 1 in the Results section.

Please report descriptive statistics for EEG and MRS measures in Table S1.

We have added a new Table S1 in the Supplementary Material, providing descriptive statistics for EEG and MRS E/I balance measures, presented separately for the dyslexic and control groups.

I recommend avoiding using the terms "direct" and "indirect" to contrast MRS and EEG measures of E/I balance. Both of these measures are imperfect and it is misleading to say that MRS is a "direct" measure of neurotransmitters. There is also ambiguity in what is meant by "direct": in contrast to EEG, MRS does not measure neural activity and does not provide high-resolution temporal information, so in a sense, it is less direct.

Thank you for this suggestion. We have replaced the terms 'direct' and 'indirect' biomarkers with 'MRS' and 'EEG' biomarkers throughout the text.

There are many cases throughout the results in which Bayes and frequentist stats seem to contradict each other in terms of significance and what should be included in the models, especially with regard to the interaction effects (the Bayes factors appear to favor non-significant interactions). I think this is worth considering and describing to offer more clarity for the readers.

We agree that a discussion of the divergent results between Bayesian and frequentist models was missing in the previous version of the manuscript. To provide greater clarity for the readers, we have conducted follow-up Bayesian t-tests in every case where the results indicated the inclusion of non-significant interactions with the effect of group in the model. These additional analyses have been performed for the exponent, offset, as well as for beta bandwidth in the Supplementary Material. We have also added a paragraph addressing these discrepancies in the Discussion:

“Remarkably, in some models, results from Bayesian and frequentist statistics yielded divergent conclusions regarding the inclusion of non-significant effects. This was observed in more complex ANOVA models, whereas no such discrepancies appeared in t-tests or correlations. Given reports of high variability in Bayesian ANOVA estimates across repeated runs of the same analysis (Pfister, 2021), these results should be interpreted with caution. Therefore, following the recommendation to simplify complex models into Bayesian t-tests for more reliable estimates (Pfister, 2021), we conducted follow-up Bayesian t-tests in every case that favored the inclusion of non-significant interactions with the group factor. These analyses provided further evidence for the lack of differences between the dyslexic and control groups. Another source of discrepancy between the two methods may stem from the inclusion of interactions between covariates and within-subject effects in frequentist ANOVA, which were not included in Bayesian ANOVA to adhere to the recommendation for simpler Bayesian models (Pfister, 2021).”

Pfister, R. (2021). Variability of Bayes factor estimates in Bayesian analysis of variance. The Quantitative Methods for Psychology, 17(1), 40-45. doi:10.20982/tqmp.17.1.p040

It would be helpful to indicate whether participants in the DYS group had a history of reading intervention/remediation. In addition to showing that the DYS group performed lower than the CON group on reading assessments as a whole and given their age, was the performance on the reading assessments at an individual level considered for inclusion in the study? (i.e., were participants' persistent poor reading abilities confirmed with the research assessments?)

We were unable to assess individual reading skills due to the lack of standardized diagnostic norms for adult dyslexia in Poland. Therefore, participants in the dyslexic group were recruited based on a previous clinical diagnosis of dyslexia, and reading and reading-related tasks were used for group-level comparisons only. This information has been added to the Methods section:

“Since there are no standardized diagnostic norms for dyslexia in adults in Poland, individuals were assigned to the dyslexic group based on a past diagnosis of dyslexia.”

Unfortunately, we did not collect information about participants' history of reading intervention or remediation. In this context, we acknowledge that including a sample of adult participants is a potential limitation of our study, however, this was already mentioned in the Discussion.

Regarding the fMRI task, please indicate whether the participants whose threshold and/or contrast was changed for localization were from the DYS or CON group.

This information is now added to the Method section:

“For 6 participants (DYS n = 2, CON n = 4), the threshold was lowered to p < .05 uncorrected, while for another 6 participants (DYS n = 3, CON n = 3) the contrast from the auditory run was changed to auditory words versus fixation cross due to a lack of activation for other contrasts.”

Reviewer #2 (Public Review):

Summary:

This study utilized two complementary techniques (EEG and 7T MRI/MRS) to directly test a theory of dyslexia: the neural noise hypothesis. The authors report finding no evidence to support an excitatory/inhibitory balance, as quantified by beta in EEG and Glutamate/GABA ratio in MRS. This is important work and speaks to one potential mechanism by which increased neural noise may occur in dyslexia.

Strengths:

This is a well-conceived study with in-depth analyses and publicly available data for independent review. The authors provide transparency with their statistics and display the raw data points along with the averages in figures for review and interpretation. The data suggest that an E/I balance issue may not underlie deficits in dyslexia and is a meaningful and needed test of a possible mechanism for increased neural noise.

Weaknesses:

The researchers did not include a visual print task in the EEG task, which limits analysis of reading-specific regions such as the visual word form area, which is a commonly hypoactivated region in dyslexia. This region is a common one of interest in dyslexia, yet the researchers measured the I/E balance in only one region of interest, specific to the language network.

We agree with the Reviewer that including different tasks for the EEG biomarkers assessment would be valuable. However, this limitation was already addressed in the Discussion:

“Importantly, our study focused on adolescents and young adults, and the EEG recordings were conducted during rest and a spoken language task. These factors may limit the generalizability of our results. Future research should include younger populations and incorporate a broader array of tasks, such as reading and phonological processing, to provide a more comprehensive evaluation of the E/I balance hypothesis.”

Further, this work does not consider prior studies reporting neural inconsistency; a potential consequence of increased neural noise, which has been reported in several studies and linked with candidate-dyslexia gene variants (e.g., Centanni et al., 2018, 2022; Hornickel & Kraus, 2013; Neef et al., 2017). While E/I imbalance may not be a cause of increased neural noise, other potential mechanisms remain and should be discussed.

Thank you for referring us to other works reporting neural variability in dyslexia. We agree that a broader context regarding sources of reduced neural synchronization, beyond E/I imbalance, was missing in the previous version of the manuscript. We have now included these references in the Discussion:

“Furthermore, although our results do not support the idea of E/I balance alterations as a source of neural noise in dyslexia, they do not preclude other mechanisms leading to less synchronous neural firing posited by the hypothesis. In this context, there is evidence showing increased trial-to-trial inconsistency of neural responses in individuals with dyslexia (Centanni et al., 2022) or poor readers (Hornickel and Kraus, 2013) and its associations with specific dyslexia risk genes (Centanni et al., 2018; Neef et al., 2017). At the same time, the observed trial-to-trial inconsistency was either present only in a subset of participants (Centanni et al., 2018), limited to some experimental conditions (Centanni et al., 2022), or specific brain regions – e.g., brainstem in Hornickel and Kraus (2013), left auditory cortex in Centanni et al. (2018), or left supramarginal gyrus in Centanni et al. (2022).”

A better description of the exponent and offset components is needed at the beginning of the results, given that the methods are presented in detail at the end. I also do not see a clear description of these components in the methods.

A description of the aperiodic components is now included in the Results:

“In the initial step of the analysis, we analyzed the aperiodic (exponent and offset) components of the EEG spectrum. The exponent reflects the steepness of the EEG power spectrum, with a higher exponent indicating a steeper signal; while the offset represents a uniform shift in power across frequencies, with a higher offset indicating greater power across the entire EEG spectrum (Donoghue et al., 2020).”

as well as in the Materials and Methods:

“Two broadband aperiodic parameters were extracted: the exponent, which quantifies the steepness of the EEG power spectrum, and the offset, which indicates signal’s power across the entire frequency spectrum.”

Reviewer #3 (Public Review):

Summary:

This study by Glica and colleagues utilized EEG (i.e., Beta power, Gamma power, and aperiodic activity) and 7T MRS (i.e., MRS IE ratio, IE balance) to reevaluate the neural noise hypothesis in Dyslexia. Supported by Bayesian statistics, their results show solid 'no evidence' of EI balance differences between groups, challenging the neural noise hypothesis. The work will be of broad interest to neuroscientists, and educational and clinical psychologists.

Strengths:

Combining EEG and 7T MRS, this study utilized both the indirect (i.e., Beta power, Gamma power, and aperiodic activity) and direct (i.e., MRS IE ratio, IE balance) measures to reevaluate the neural noise hypothesis in Dyslexia.

Weaknesses:

The authors may need to provide more data to assess the quality of the MRS data.

We have addressed the following specific recommendations of the Reviewer providing more data about the quality of the MRS data.

The authors may need to explain how the number of subjects is determined in the MRS section.

We have clarified the MRS sample description in the Results section:

“Due to financial and logistical constraints, 59 out of the 120 recruited subjects, selected progressively as the study unfolded, were examined with MRS. Subjects were matched by age and sex between the dyslexic and control groups. Due to technical issues and to prevent delays and discomfort for the participants, we collected 54 complete sessions. Additionally, four datasets were excluded based on our quality control criteria, and three GABA+ estimates exceeded the selected CRLB threshold. Ultimately, we report 50 estimates for Glu (21 participants with dyslexia) and 47 for GABA+ and Glu/GABA+ ratios (20 participants with dyslexia).”

Is there a reason why theta and gamma peaks were not observed in the majority of participants? What are the possible reasons that likely caused the discrepancy between this study and previously reported relevant studies?

We have now added a discussion about the absence of oscillatory peaks in the theta and gamma bands to the Discussion section:

“We could not perform analyses for the gamma oscillations since in the majority of participants the gamma peak was not detected above the aperiodic component. Due to the 1/f properties of the EEG spectrum, both aperiodic and periodic components should be disentangled to analyze ‘true’ gamma oscillations; however, this approach is not typically recognized in electrophysiology research (Hudson and Jones, 2022). Indeed, previous studies that analyzed gamma activity in dyslexia (Babiloni et al., 2012; Lasnick et al., 2023; Rufener and Zaehle, 2021) did not separate the background aperiodic activity. For the same reason, we could not analyze results for the theta band, which often does not meet the criteria for an oscillatory component manifested as a peak in the power spectrum (Klimesch, 1999). Moreover, results from a study investigating developmental changes in both periodic and aperiodic components suggest that theta oscillations in older participants are mostly observed in frontal midline electrodes (Cellier et al., 2021), which were not analyzed in the current study.”

Hudson, M. R., & Jones, N. C. (2022). Deciphering the code: Identifying true gamma neural oscillations. Experimental Neurology, 357, 114205. https://doi.org/10.1016/j.expneurol.2022.114205

Klimesch, W. (1999). EEG alpha and theta oscillations reflect cognitive and memory performance: A review and analysis. Brain Research Reviews, 29(2-3), 169-195. https://doi.org/10.1016/S0165-0173(98)00056-3

Based on Figure 1F, the quality of the MRS data may be contaminated by the lipid signal, especially for the DYS group. To better evaluate the MRS data, especially the GABA measurements, the authors need to show:

(a) the placement of the MRS voxel on the anatomical images;

Averaged MRS voxel placement was already presented in Figure 1 (now Figure 2) in the manuscript. Now, we have also added exemplary single-subject images to the MRS checklist in the Supplement.

(b) Glu and GABA model functions

We have now provided more meaningful Glu and GABA indications in Figure 2.

(c) CRLB for GABA

We have added respective estimates to the Supplement:

%CRLB of Glu: mean 2.96, SD = 0.79

%CRLB of GABA: mean 10.59, SD = 2.76

%CRLB of NAA: 1.76 SD = 0.46

Further, the authors added voxel's gray matter volume as a covariate when performing separate ANCOVAs. The authors may need to use alpha correction or 1-fCSF correction to corroborate these results.

We chose to use the ratio of Glu and GABA to total creatine (tCr), as this remains a common practice in MRS studies at 7T (e.g., Nandi et al., 2022; Smith et al., 2021). This decision was also influenced by previous dyslexia studies (Del Tufo et al., 2018; Pugh et al., 2014) and is now clarified in the Results and Methods sections.

Regarding alpha correction, a recent paper (García-Pérez et al., 2023) recommends: 'In general, avoid corrections for multiple testing if statistical claims are to be made for each individual test, in the absence of an omnibus null hypothesis.' Since we report null findings, further alpha correction would not significantly impact the results.

García-Pérez, M. A. (2023). Use and misuse of corrections for multiple testing. Methods in Psychology, 8, 100120. https://doi.org/10.1016/j.metip.2023.100120

This being the case, the monotypic genus Ammogomphus Förster 1914 becomes a new synonym of Gomphoides Selys 1854.

Reviewer #3 (Public review):

The author presents a novel theory and computational model suggesting that grid cells do not encode space, but rather encode non-spatial attributes. Place cells in turn encode memories of where those specific attributes occurred. The theory accounts for many experimental results and generates useful predictions for future studies. The model's simplicity and potential explanatory power will interest others in the field. There are, however, a few weaknesses outlined below which undermine the theory.

Main criticisms:

(1) A crucial assumption of the model is that grid cells express grid-like firing patterns if and only if the content of experience is constant in space. It is difficult to imagine a real world example that satisfies this assumption. Odors and sounds are used as examples. While they are often more spatially diffuse than an object on the ground, odors and sounds have sources that are readily detectable and thus are not constant in space. Animals can easily navigate to a food source or to a vocalizing conspecific. This assumption is especially problematic because it predicts that all grid cells should become silent when their preferred non-spatial attribute (e.g. a specific odor) is missing. I'm not aware of any experimental data showing that grid cells become silent. On the contrary, grid cells are known to remain active across all contexts that have been tested, including across sleep/wake states. Unlike place cells, grid cells have never been shown to turn off. Since grid cells are active in all contexts, their preferred attribute must also be present in all contexts, and therefore they would not convey any information about the specific content of an experience. The author lists many attributes that could in theory be constant in a laboratory setting, but there is no data I'm aware of that shows this is true in practice. As it stands, this crucial assumption of the model remains mere speculation.

(2) The proposed novelty of this theory is that other models all assume that grid cells encode space. This is not quite true of models based on continuous attractor networks, the discussion of which is essentially absent. More specifically, attractor models focus on the importance of intrinsic dynamics within entorhinal cortex in generating the grid pattern. While this firing pattern is aligned to space during navigation and therefore can be used a representation of that space, the neural dynamics are preserved even during sleep. Similarly, it is because the grid pattern does not strictly encode physical space that grid-like signals are also observed in relation to other two-dimensional continuous variables.

(3) The use of border cells or boundary vector cells as the main (or only) source of spatial information in the hippocampus is not well supported by experimental data. Border cells in entorhinal cortex are not active in the center of an environment. Boundary-vector cells can fire farther away from the walls, but are not found in entorhinal cortex. They are located in the subiculum, a major output of the hippocampus. While the entorhinal-hippocampal circuit is a loop, the route from boundary-vector cells to place cells is much less clear than from grid cells. Moreover, both border cells and boundary-vector cells (which are conflated in this paper) comprise a small population of neurons compared to grid cells.

Minor comments:

(1) There is substantial theoretical and experimental work supporting the idea that grid cell modules instantiate continuous attractor networks, yet this class of models is largely ignored:

p. 7 "In contrast, most grid cell models (Bellmund et al., 2016; Bush et al., 2015; Castro & Aguiar, 2014; Hasselmo, 2009; Mhatre et al., 2012; Solstad et al., 2006; Sorscher et al., 2023; Stepanyuk, 2015; Widloski & Fiete, 2014) are domain specific models of spatial navigation"

The following references should be added:

McNaughton, B. L., Battaglia, F. P., Jensen, O., Moser, E. I. & Moser, M.-B. Path integration and the neural basis of the 'cognitive map'. Nat. Rev. Neurosci. 7, 663-678 (2006).

Fuhs, M. C. & Touretzky, D. S. A spin glass model of path integration in rat medial entorhinal cortex. J. Neurosci. 26, 4266-4276 (2006).

Burak, Y. & Fiete, I. R. Accurate path integration in continuous attractor network models of grid cells. PLoS Comput. Biol. 5, e1000291 (2009).

Guanella, A., Kiper, D. & Verschure, P. A model of grid cells based on a twisted torus topology. Int. J. Neural Syst. 17, 231-240 (2007).

Couey, J. J. et al. Recurrent inhibitory circuitry as a mechanism for grid formation. Nat. Neurosci. 16, 318-324 (2013).

(Note: the Bellmund et al. (2016) citation is likely a mistake and was intended to be Bellmund et al. (2018).)

(2) The author claims in two places that this model is the first to explain that grid cell population activity lies on a torus. While it may be the first explicit computational account of why grid cell activity is mapped onto a torus, these claims should be moderated for clarity, for example by adding "but see McNaughton et al. (2006) and others".

Box 1. Results Uniquely Explained by this Memory Model - the population code of grid cells lies on a torus

p.11 "In addition, this simplifying assumption allows the model to capture the finding that the population of grid cells lies on a torus (Gardner et al., 2022), although I note that the model was developed before this result was known."

(3) Lateral entorhinal cortex is largely ignored in this memory model. It should be considered that the predominance of spatial representations reported in the literature is due to historical reasons. Namely, the discovery of hippocampal place cells spurred interest in looking upstream for the source of spatial information, which was later abundantly clear in medial entorhinal cortex. Lateral entorhinal cortex is relatively understudied, but is known to encode odors, objects, and time in a way that medial entorhinal cortex does not. It is therefore confusing to assume that these attributes are instead encoded by grid cells.

DOI: 10.3390/ijms252313131

Resource: RRID:Addgene_12259

Curator: @AlecAsdourian

SciCrunch record: RRID:Addgene_12259

What is this?

Summary

🌍 Avoiding Tax Legally in Other Countries

Changing tax residency for half a year may help avoid taxes (but it;s complex and rather recommended for very high earnings). You can move for example to: - United Arab Emirates: No crypto tax. - Germany: No tax on crypto sold after holding for 12 months. - Portugal: Similar tax-free policies for holding over a year.

🔄 What Is Taxed?

Transactions converting cryptocurrency into fiat currency (e.g., PLN, USD) or purchasing goods like property or pizza with cryptocurrency are taxable. Pure crypto-to-crypto transactions are not taxable.

📈 How to Calculate Tax

Calculate the difference between the amount spent to acquire cryptocurrency and the amount earned from its sale. Example: If Bitcoin was bought at $30,000 and sold at $40,000, the taxable income is $10,000.

💰 Tax Rate Overview

• Income up to 1 million PLN is taxed at 19%.
• Income exceeding 1 million PLN incurs an additional 4% solidarity tax, totaling 23% for high earners.

📃 Keeping Records

Tax obligations arise at the moment of converting crypto to fiat or goods, not at the time of withdrawal from an exchange. Keep detailed records to avoid issues during audits or when exchanges request proof of funds.

⚠️ Challenges and Advice

Tax laws in Poland are comprehensive and offer few loopholes. Engaging tax professionals is strongly advised to ensure compliance and minimize errors.

🔄 Deferring Tax Payments in Poland Using Stablecoins

One strategy involves converting crypto profits into stablecoins at year-end and selling them in the following year to postpone taxation. Below is a detailed breakdown of how the strategy works and its limitations.

The Concept

Stablecoins are cryptocurrencies pegged to fiat currencies (e.g., USD or EUR) and have stable values. Using stablecoins in Poland offers a way to legally defer tax payments:

1. End-of-Year Transaction:

   • Convert your cryptocurrency gains (e.g., Bitcoin) into stablecoins like Tether (USDT) or USD Coin (USDC) at the end of the tax year.
   • These transactions, as crypto-to-crypto conversions, are not taxable in Poland.

2. Start-of-Year Sale:

   • In the new tax year, sell the stablecoins for fiat currency (e.g., PLN).
   • The taxable event occurs in the following year, deferring the tax obligation.

Benefits of This Strategy

1. Tax Payment Deferral:

   • Delays the payment of taxes on your crypto gains by shifting the taxable event to the next year.

2. Inflation Advantage:

   • Inflation reduces the real value of money over time, decreasing the actual financial burden of the deferred tax.

3. Liquidity Management:

   • Funds remain accessible as stablecoins, which can be reinvested or used in decentralized finance (DeFi) during the deferral period.

How Long Can This Be Done in Poland?

• The strategy can be legally repeated annually for up to 15 years.
• After 15 years, the deferred gains may be treated differently or trigger tax liabilities due to long-term reporting requirements. It's important to monitor evolving tax regulations in Poland to ensure compliance.

Key Considerations

1. Documentation:

   • Maintain detailed records of all transactions, including dates, values, and stablecoin transfers, for tax compliance and audits.

2. Stablecoin Selection:

   • Choose stablecoins with strong pegs to fiat currencies to avoid price fluctuations that may affect gains or losses.

3. Regulatory Changes:

   • Polish tax laws are subject to change. Always confirm that the strategy remains valid before executing it.

Example

• Year 1 (2023):

  • Bitcoin bought for PLN 50,000.
  • Sold for PLN 150,000 at the end of 2023.
  • Proceeds converted to USDT (not taxable in Poland).

• Year 2 (2024):

  • USDT sold for PLN 150,000 in January.
  • Taxable gain of PLN 100,000 is reported in the 2024 tax year.

Limitations

1. Short-Term Transactions:

   • If stablecoins are sold within the same year as the crypto-to-stablecoin conversion, the tax deferral benefit is lost.

2. Exchange Fees:

   • Frequent crypto-stablecoin conversions may incur exchange fees, slightly reducing net gains.

3. Regulatory Risks:

   • Future changes to tax laws or stablecoin regulations could impact the strategy's viability.

This strategy allows you to legally defer cryptocurrency taxes for a significant period, maximizing your financial flexibility and leveraging stablecoin stability. Always consult a tax professional for tailored advice and compliance.

Yo creo que es una alternativa, pero no solucionan la problemática anterior.

en mi opinión no todas son en ambientes controlados, pero además eso no compromete la calidad de los datos.

Para determinar as cores, pode-se usar:

scale_fill_manual( values = c( "Fibra" = "blue", "Fragmento" = "red" ), name = "" ) A parte final name = "" ☝️ é para excluir o nome da legenda.<br> <br> scale_color_manual( values = c( "Fibra" = "blue", "Fragmento" = "red" ), name = "" ) A parte final name = "" ☝️ é para excluir o nome da legenda.

Caso não queira que os NA's apareçam na legenda, sem alterar os dados, use:

scale_fill_manual( na.translate = F )<br> scale_color_manual( na.translate = F )<br>

Use paletas prontas:<br> paleta <- rcartocolor::carto_pal(n = 8, name = "Bold")[c(1, 3, 7, 2)]<br> scale_fill_manual(values = paleta)

Se usar width e height o size torna-se obsoleto:

theme( legend.key.height = unit(0.2, "cm"), legend.key.width = unit(0.2, "cm") )

Para excluir o título da legenda;

scale_fill_manual( name = "" )

Isto garante que o eixo fique encaixado na base sem espaço: scale_y_continuous( expand = c(0, 0) )

Para eliminar títulos use: theme( axis.title = element_blank() )

É melhor que usar o labs=

According to all known laws of aviation,

there is no way a bee should be able to fly.

Its wings are too small to get its fat little body off the ground.

The bee, of course, flies anyway

because bees don't care what humans think is impossible.

Yellow, black. Yellow, black. Yellow, black. Yellow, black.

Ooh, black and yellow! Let's shake it up a little.

Barry! Breakfast is ready!

Ooming!

Hang on a second.

Hello?

Barry?

Adam?

Oan you believe this is happening?

I can't. I'll pick you up.

Looking sharp.

Use the stairs. Your father paid good money for those.

Sorry. I'm excited.

Here's the graduate. We're very proud of you, son.

A perfect report card, all B's.

Very proud.

Ma! I got a thing going here.

You got lint on your fuzz.

Ow! That's me!

Wave to us! We'll be in row 118,000.

Bye!

Barry, I told you, stop flying in the house!

Hey, Adam.

Hey, Barry.

Is that fuzz gel?

A little. Special day, graduation.

Never thought I'd make it.

Three days grade school, three days high school.

Those were awkward.

Three days college. I'm glad I took a day and hitchhiked around the hive.

You did come back different.

Hi, Barry.

Artie, growing a mustache? Looks good.

Hear about Frankie?

Yeah.

You going to the funeral?

No, I'm not going.

Everybody knows, sting someone, you die.

Don't waste it on a squirrel. Such a hothead.

I guess he could have just gotten out of the way.

I love this incorporating an amusement park into our day.

That's why we don't need vacations.

Boy, quite a bit of pomp… under the circumstances.

Well, Adam, today we are men.

We are!

Bee-men.

Amen!

Hallelujah!

Students, faculty, distinguished bees,

please welcome Dean Buzzwell.

Welcome, New Hive Oity graduating class of…

…9:15.

That concludes our ceremonies.

And begins your career at Honex Industries!

Will we pick ourjob today?

I heard it's just orientation.

Heads up! Here we go.

Keep your hands and antennas inside the tram at all times.

Wonder what it'll be like? A little scary. Welcome to Honex, a division of Honesco

and a part of the Hexagon Group.

This is it!

Wow.

Wow.

We know that you, as a bee, have worked your whole life

to get to the point where you can work for your whole life.

Honey begins when our valiant Pollen Jocks bring the nectar to the hive.

Our top-secret formula

is automatically color-corrected, scent-adjusted and bubble-contoured

into this soothing sweet syrup

with its distinctive golden glow you know as…

Honey!

That girl was hot.

She's my cousin!

She is?

Yes, we're all cousins.

Right. You're right.

At Honex, we constantly strive

to improve every aspect of bee existence.

These bees are stress-testing a new helmet technology.

What do you think he makes? Not enough. Here we have our latest advancement, the Krelman.

What does that do? Oatches that little strand of honey that hangs after you pour it. Saves us millions.

Oan anyone work on the Krelman?

Of course. Most bee jobs are small ones. But bees know

that every small job, if it's done well, means a lot.

But choose carefully

because you'll stay in the job you pick for the rest of your life.

The same job the rest of your life? I didn't know that.

What's the difference?

You'll be happy to know that bees, as a species, haven't had one day off

in 27 million years.

So you'll just work us to death?

We'll sure try.

Wow! That blew my mind!

"What's the difference?" How can you say that?

One job forever? That's an insane choice to have to make.

I'm relieved. Now we only have to make one decision in life.

But, Adam, how could they never have told us that?

Why would you question anything? We're bees.

We're the most perfectly functioning society on Earth.

You ever think maybe things work a little too well here?

Like what? Give me one example.

I don't know. But you know what I'm talking about.

Please clear the gate. Royal Nectar Force on approach.

Wait a second. Oheck it out.

Hey, those are Pollen Jocks! Wow. I've never seen them this close.

They know what it's like outside the hive.

Yeah, but some don't come back.

Hey, Jocks! Hi, Jocks! You guys did great!

You're monsters! You're sky freaks! I love it! I love it!

I wonder where they were. I don't know. Their day's not planned.

Outside the hive, flying who knows where, doing who knows what.

You can'tjust decide to be a Pollen Jock. You have to be bred for that.

Right.

Look. That's more pollen than you and I will see in a lifetime.

It's just a status symbol. Bees make too much of it.

Perhaps. Unless you're wearing it and the ladies see you wearing it.

Those ladies? Aren't they our cousins too?

Distant. Distant.

Look at these two.

Oouple of Hive Harrys. Let's have fun with them. It must be dangerous being a Pollen Jock.

Yeah. Once a bear pinned me against a mushroom!

He had a paw on my throat, and with the other, he was slapping me!

Oh, my! I never thought I'd knock him out. What were you doing during this?

Trying to alert the authorities.

I can autograph that.

A little gusty out there today, wasn't it, comrades?

Yeah. Gusty.

We're hitting a sunflower patch six miles from here tomorrow.

Six miles, huh? Barry! A puddle jump for us, but maybe you're not up for it.

Maybe I am. You are not! We're going 0900 at J-Gate.

What do you think, buzzy-boy? Are you bee enough?

I might be. It all depends on what 0900 means.

Hey, Honex!

Dad, you surprised me.

You decide what you're interested in?

Well, there's a lot of choices. But you only get one. Do you ever get bored doing the same job every day?

Son, let me tell you about stirring.

You grab that stick, and you just move it around, and you stir it around.

You get yourself into a rhythm. It's a beautiful thing.

You know, Dad, the more I think about it,

maybe the honey field just isn't right for me.

You were thinking of what, making balloon animals?

That's a bad job for a guy with a stinger.

Janet, your son's not sure he wants to go into honey!

Barry, you are so funny sometimes. I'm not trying to be funny. You're not funny! You're going into honey. Our son, the stirrer!

You're gonna be a stirrer? No one's listening to me! Wait till you see the sticks I have.

I could say anything right now. I'm gonna get an ant tattoo!

Let's open some honey and celebrate!

Maybe I'll pierce my thorax. Shave my antennae.

Shack up with a grasshopper. Get a gold tooth and call everybody "dawg"!

I'm so proud.

We're starting work today! Today's the day. Oome on! All the good jobs will be gone.

Yeah, right.

Pollen counting, stunt bee, pouring, stirrer, front desk, hair removal…

Is it still available? Hang on. Two left! One of them's yours! Oongratulations! Step to the side.

What'd you get? Picking crud out. Stellar! Wow!

Oouple of newbies?

Yes, sir! Our first day! We are ready!

Make your choice.

You want to go first? No, you go. Oh, my. What's available?

Restroom attendant's open, not for the reason you think.

Any chance of getting the Krelman? Sure, you're on. I'm sorry, the Krelman just closed out.

Wax monkey's always open.

The Krelman opened up again.

What happened?

A bee died. Makes an opening. See? He's dead. Another dead one.

Deady. Deadified. Two more dead.

Dead from the neck up. Dead from the neck down. That's life!

Oh, this is so hard!

Heating, cooling, stunt bee, pourer, stirrer,

humming, inspector number seven, lint coordinator, stripe supervisor,

mite wrangler. Barry, what do you think I should… Barry?

Barry!

All right, we've got the sunflower patch in quadrant nine…

What happened to you? Where are you?

I'm going out.

Out? Out where?

Out there.

Oh, no!

I have to, before I go to work for the rest of my life.

You're gonna die! You're crazy! Hello?

Another call coming in.

If anyone's feeling brave, there's a Korean deli on 83rd

that gets their roses today.

Hey, guys.

Look at that. Isn't that the kid we saw yesterday? Hold it, son, flight deck's restricted.

It's OK, Lou. We're gonna take him up.

Really? Feeling lucky, are you?

Sign here, here. Just initial that.

Thank you. OK. You got a rain advisory today,

and as you all know, bees cannot fly in rain.

So be careful. As always, watch your brooms,

hockey sticks, dogs, birds, bears and bats.

Also, I got a couple of reports of root beer being poured on us.

Murphy's in a home because of it, babbling like a cicada!

That's awful. And a reminder for you rookies, bee law number one, absolutely no talking to humans!

All right, launch positions!

Buzz, buzz, buzz, buzz! Buzz, buzz, buzz, buzz! Buzz, buzz, buzz, buzz!

Black and yellow!

Hello!

You ready for this, hot shot?

Yeah. Yeah, bring it on.

Wind, check.

Antennae, check.

Nectar pack, check.

Wings, check.

Stinger, check.

Scared out of my shorts, check.

OK, ladies,

let's move it out!

Pound those petunias, you striped stem-suckers!

All of you, drain those flowers!

Wow! I'm out!

I can't believe I'm out!

So blue.

I feel so fast and free!

Box kite!

Wow!

Flowers!

This is Blue Leader. We have roses visual.

Bring it around 30 degrees and hold.

Roses!

30 degrees, roger. Bringing it around.

Stand to the side, kid. It's got a bit of a kick.

That is one nectar collector!

Ever see pollination up close? No, sir. I pick up some pollen here, sprinkle it over here. Maybe a dash over there,

a pinch on that one. See that? It's a little bit of magic.

That's amazing. Why do we do that?

That's pollen power. More pollen, more flowers, more nectar, more honey for us.

Oool.

I'm picking up a lot of bright yellow. Oould be daisies. Don't we need those?

Oopy that visual.

Wait. One of these flowers seems to be on the move.

Say again? You're reporting a moving flower?

Affirmative.

That was on the line!

This is the coolest. What is it?

I don't know, but I'm loving this color.

It smells good. Not like a flower, but I like it.

Yeah, fuzzy.

Ohemical-y.

Oareful, guys. It's a little grabby.

My sweet lord of bees!

Oandy-brain, get off there!

Problem!

Guys! This could be bad. Affirmative.

Very close.

Gonna hurt.

Mama's little boy.

You are way out of position, rookie!

Ooming in at you like a missile!

Help me!

I don't think these are flowers.

Should we tell him? I think he knows. What is this?!

Match point!

You can start packing up, honey, because you're about to eat it!

Yowser!

Gross.

There's a bee in the car!

Do something!

I'm driving!

Hi, bee.

He's back here!

He's going to sting me!

Nobody move. If you don't move, he won't sting you. Freeze!

He blinked!

Spray him, Granny!

What are you doing?!

Wow… the tension level out here is unbelievable.

I gotta get home.

Oan't fly in rain.

Oan't fly in rain.

Oan't fly in rain.

Mayday! Mayday! Bee going down!

Ken, could you close the window please?

Ken, could you close the window please?

Oheck out my new resume. I made it into a fold-out brochure.

You see? Folds out.

Oh, no. More humans. I don't need this.

What was that?

Maybe this time. This time. This time. This time! This time! This…

Drapes!

That is diabolical.

It's fantastic. It's got all my special skills, even my top-ten favorite movies.

What's number one? Star Wars?

Nah, I don't go for that…

…kind of stuff.

No wonder we shouldn't talk to them. They're out of their minds.

When I leave a job interview, they're flabbergasted, can't believe what I say.

There's the sun. Maybe that's a way out.

I don't remember the sun having a big 75 on it.

I predicted global warming.

I could feel it getting hotter. At first I thought it was just me.

Wait! Stop! Bee!

Stand back. These are winter boots.

Wait!

Don't kill him!

You know I'm allergic to them! This thing could kill me!

Why does his life have less value than yours?

Why does his life have any less value than mine? Is that your statement?

I'm just saying all life has value. You don't know what he's capable of feeling.

My brochure!

There you go, little guy.

I'm not scared of him. It's an allergic thing.

Put that on your resume brochure.

My whole face could puff up.

Make it one of your special skills.

Knocking someone out is also a special skill.

Right. Bye, Vanessa. Thanks.

Vanessa, next week? Yogurt night?

Sure, Ken. You know, whatever.

You could put carob chips on there.

Bye.

Supposed to be less calories.

Bye.

I gotta say something.

She saved my life. I gotta say something.

All right, here it goes.

Nah.

What would I say?

I could really get in trouble.

It's a bee law. You're not supposed to talk to a human.

I can't believe I'm doing this.

I've got to.

Oh, I can't do it. Oome on!

No. Yes. No.

Do it. I can't.

How should I start it? "You like jazz?" No, that's no good.

Here she comes! Speak, you fool!

Hi!

I'm sorry.

You're talking. Yes, I know. You're talking!

I'm so sorry.

No, it's OK. It's fine. I know I'm dreaming.

But I don't recall going to bed.

Well, I'm sure this is very disconcerting.

This is a bit of a surprise to me. I mean, you're a bee!

I am. And I'm not supposed to be doing this,

but they were all trying to kill me.

And if it wasn't for you…

I had to thank you. It's just how I was raised.

That was a little weird.

I'm talking with a bee. Yeah. I'm talking to a bee. And the bee is talking to me!

I just want to say I'm grateful. I'll leave now.

Wait! How did you learn to do that? What? The talking thing.

Same way you did, I guess. "Mama, Dada, honey." You pick it up.

That's very funny. Yeah. Bees are funny. If we didn't laugh, we'd cry with what we have to deal with.

Anyway…

Oan I…

…get you something?

Like what? I don't know. I mean… I don't know. Ooffee?

I don't want to put you out.

It's no trouble. It takes two minutes.

It's just coffee.

I hate to impose.

Don't be ridiculous!

Actually, I would love a cup.

Hey, you want rum cake?

I shouldn't.

Have some.

No, I can't.

Oome on!

I'm trying to lose a couple micrograms.

Where? These stripes don't help. You look great!

I don't know if you know anything about fashion.

Are you all right?

No.

He's making the tie in the cab as they're flying up Madison.

He finally gets there.

He runs up the steps into the church. The wedding is on.

And he says, "Watermelon? I thought you said Guatemalan.

Why would I marry a watermelon?"

Is that a bee joke?

That's the kind of stuff we do.

Yeah, different.

So, what are you gonna do, Barry?

About work? I don't know.

I want to do my part for the hive, but I can't do it the way they want.

I know how you feel.

You do? Sure. My parents wanted me to be a lawyer or a doctor, but I wanted to be a florist.

Really? My only interest is flowers. Our new queen was just elected with that same campaign slogan.

Anyway, if you look…

There's my hive right there. See it?

You're in Sheep Meadow!

Yes! I'm right off the Turtle Pond!

No way! I know that area. I lost a toe ring there once.

Why do girls put rings on their toes?

Why not?

It's like putting a hat on your knee.

Maybe I'll try that.

You all right, ma'am?

Oh, yeah. Fine.

Just having two cups of coffee!

Anyway, this has been great. Thanks for the coffee.

Yeah, it's no trouble.

Sorry I couldn't finish it. If I did, I'd be up the rest of my life.

Are you…?

Oan I take a piece of this with me?

Sure! Here, have a crumb.

Thanks! Yeah. All right. Well, then… I guess I'll see you around.

Or not.

OK, Barry.

And thank you so much again… for before.

Oh, that? That was nothing.

Well, not nothing, but… Anyway…

This can't possibly work.

He's all set to go. We may as well try it.

OK, Dave, pull the chute.

Sounds amazing. It was amazing! It was the scariest, happiest moment of my life.

Humans! I can't believe you were with humans!

Giant, scary humans! What were they like?

Huge and crazy. They talk crazy.

They eat crazy giant things. They drive crazy.

Do they try and kill you, like on TV?

Some of them. But some of them don't.

How'd you get back?

Poodle.

You did it, and I'm glad. You saw whatever you wanted to see.

You had your "experience." Now you can pick out yourjob and be normal.

Well… Well? Well, I met someone.

You did? Was she Bee-ish?

A wasp?! Your parents will kill you!

No, no, no, not a wasp.

Spider?

I'm not attracted to spiders.

I know it's the hottest thing, with the eight legs and all.

I can't get by that face.

So who is she?

She's… human.

No, no. That's a bee law. You wouldn't break a bee law.

Her name's Vanessa. Oh, boy. She's so nice. And she's a florist!

Oh, no! You're dating a human florist!

We're not dating.

You're flying outside the hive, talking to humans that attack our homes

with power washers and M-80s! One-eighth a stick of dynamite!

She saved my life! And she understands me.

This is over!

Eat this.

This is not over! What was that?

They call it a crumb. It was so stingin' stripey! And that's not what they eat. That's what falls off what they eat!

You know what a Oinnabon is? No. It's bread and cinnamon and frosting. They heat it up…

Sit down!

…really hot!

Listen to me! We are not them! We're us. There's us and there's them!

Yes, but who can deny the heart that is yearning?

There's no yearning. Stop yearning. Listen to me!

You have got to start thinking bee, my friend. Thinking bee!

Thinking bee. Thinking bee. Thinking bee! Thinking bee! Thinking bee! Thinking bee!

There he is. He's in the pool.

You know what your problem is, Barry?

I gotta start thinking bee?

How much longer will this go on?

It's been three days! Why aren't you working?

I've got a lot of big life decisions to think about.

What life? You have no life! You have no job. You're barely a bee!

Would it kill you to make a little honey?

Barry, come out. Your father's talking to you.

Martin, would you talk to him?

Barry, I'm talking to you!

You coming?

Got everything?

All set!

Go ahead. I'll catch up.

Don't be too long.

Watch this!

Vanessa!

We're still here. I told you not to yell at him. He doesn't respond to yelling!

Then why yell at me? Because you don't listen! I'm not listening to this.

Sorry, I've gotta go.

Where are you going? I'm meeting a friend. A girl? Is this why you can't decide?

Bye.

I just hope she's Bee-ish.

They have a huge parade of flowers every year in Pasadena?

To be in the Tournament of Roses, that's every florist's dream!

Up on a float, surrounded by flowers, crowds cheering.

A tournament. Do the roses compete in athletic events?

No. All right, I've got one. How come you don't fly everywhere?

It's exhausting. Why don't you run everywhere? It's faster.

Yeah, OK, I see, I see. All right, your turn.

TiVo. You can just freeze live TV? That's insane!

You don't have that?

We have Hivo, but it's a disease. It's a horrible, horrible disease.

Oh, my.

Dumb bees!

You must want to sting all those jerks.

We try not to sting. It's usually fatal for us.

So you have to watch your temper.

Very carefully. You kick a wall, take a walk,

write an angry letter and throw it out. Work through it like any emotion:

Anger, jealousy, lust.

Oh, my goodness! Are you OK?

Yeah.

What is wrong with you?! It's a bug. He's not bothering anybody. Get out of here, you creep!

What was that? A Pic 'N' Save circular?

Yeah, it was. How did you know?

It felt like about 10 pages. Seventy-five is pretty much our limit.

You've really got that down to a science.

I lost a cousin to Italian Vogue. I'll bet. What in the name of Mighty Hercules is this?

How did this get here? Oute Bee, Golden Blossom,

Ray Liotta Private Select?

Is he that actor?

I never heard of him.

Why is this here?

For people. We eat it.

You don't have enough food of your own?

Well, yes.

How do you get it?

Bees make it.

I know who makes it!

And it's hard to make it!

There's heating, cooling, stirring. You need a whole Krelman thing!

It's organic. It's our-ganic! It's just honey, Barry.

Just what?!

Bees don't know about this! This is stealing! A lot of stealing!

You've taken our homes, schools, hospitals! This is all we have!

And it's on sale?! I'm getting to the bottom of this.

I'm getting to the bottom of all of this!

Hey, Hector.

You almost done? Almost. He is here. I sense it.

Well, I guess I'll go home now

and just leave this nice honey out, with no one around.

You're busted, box boy!

I knew I heard something. So you can talk!

I can talk. And now you'll start talking!

Where you getting the sweet stuff? Who's your supplier?

I don't understand. I thought we were friends.

The last thing we want to do is upset bees!

You're too late! It's ours now!

You, sir, have crossed the wrong sword!

You, sir, will be lunch for my iguana, Ignacio!

Where is the honey coming from?

Tell me where!

Honey Farms! It comes from Honey Farms!

Orazy person!

What horrible thing has happened here?

These faces, they never knew what hit them. And now

they're on the road to nowhere!

Just keep still.

What? You're not dead?

Do I look dead? They will wipe anything that moves. Where you headed?

To Honey Farms. I am onto something huge here.

I'm going to Alaska. Moose blood, crazy stuff. Blows your head off!

I'm going to Tacoma.

And you? He really is dead. All right.

Uh-oh!

What is that?!

Oh, no!

A wiper! Triple blade!

Triple blade?

Jump on! It's your only chance, bee!

Why does everything have to be so doggone clean?!

How much do you people need to see?!

Open your eyes! Stick your head out the window!

From NPR News in Washington, I'm Oarl Kasell.

But don't kill no more bugs!

Bee!

Moose blood guy!!

You hear something?

Like what?

Like tiny screaming.

Turn off the radio.

Whassup, bee boy?

Hey, Blood.

Just a row of honey jars, as far as the eye could see.

Wow!

I assume wherever this truck goes is where they're getting it.

I mean, that honey's ours.

Bees hang tight. We're all jammed in. It's a close community.

Not us, man. We on our own. Every mosquito on his own.

What if you get in trouble? You a mosquito, you in trouble. Nobody likes us. They just smack. See a mosquito, smack, smack!

At least you're out in the world. You must meet girls.

Mosquito girls try to trade up, get with a moth, dragonfly.

Mosquito girl don't want no mosquito.

You got to be kidding me!

Mooseblood's about to leave the building! So long, bee!

Hey, guys! Mooseblood! I knew I'd catch y'all down here. Did you bring your crazy straw?

We throw it in jars, slap a label on it, and it's pretty much pure profit.

What is this place?

A bee's got a brain the size of a pinhead.

They are pinheads!

Pinhead.

Oheck out the new smoker. Oh, sweet. That's the one you want. The Thomas 3000!

Smoker?

Ninety puffs a minute, semi-automatic. Twice the nicotine, all the tar.

A couple breaths of this knocks them right out.

They make the honey, and we make the money.

"They make the honey, and we make the money"?

Oh, my!

What's going on? Are you OK?

Yeah. It doesn't last too long.

Do you know you're in a fake hive with fake walls?

Our queen was moved here. We had no choice.

This is your queen? That's a man in women's clothes!

That's a drag queen!

What is this?

Oh, no!

There's hundreds of them!

Bee honey.

Our honey is being brazenly stolen on a massive scale!

This is worse than anything bears have done! I intend to do something.

Oh, Barry, stop.

Who told you humans are taking our honey? That's a rumor.

Do these look like rumors?

That's a conspiracy theory. These are obviously doctored photos.

How did you get mixed up in this?

He's been talking to humans.

What? Talking to humans?! He has a human girlfriend. And they make out!

Make out? Barry!

We do not.

You wish you could. Whose side are you on? The bees!

I dated a cricket once in San Antonio. Those crazy legs kept me up all night.

Barry, this is what you want to do with your life?

I want to do it for all our lives. Nobody works harder than bees!

Dad, I remember you coming home so overworked

your hands were still stirring. You couldn't stop.

I remember that.

What right do they have to our honey?

We live on two cups a year. They put it in lip balm for no reason whatsoever!

Even if it's true, what can one bee do?

Sting them where it really hurts.

In the face! The eye!

That would hurt. No. Up the nose? That's a killer.

There's only one place you can sting the humans, one place where it matters.

Hive at Five, the hive's only full-hour action news source.

No more bee beards!

With Bob Bumble at the anchor desk.

Weather with Storm Stinger.

Sports with Buzz Larvi.

And Jeanette Ohung.

Good evening. I'm Bob Bumble. And I'm Jeanette Ohung. A tri-county bee, Barry Benson,

intends to sue the human race for stealing our honey,

packaging it and profiting from it illegally!

Tomorrow night on Bee Larry King,

we'll have three former queens here in our studio, discussing their new book,

Olassy Ladies, out this week on Hexagon.

Tonight we're talking to Barry Benson.

Did you ever think, "I'm a kid from the hive. I can't do this"?

Bees have never been afraid to change the world.

What about Bee Oolumbus? Bee Gandhi? Bejesus?

Where I'm from, we'd never sue humans.

We were thinking of stickball or candy stores.

How old are you?

The bee community is supporting you in this case,

which will be the trial of the bee century.

You know, they have a Larry King in the human world too.

It's a common name. Next week…

He looks like you and has a show and suspenders and colored dots…

Next week…

Glasses, quotes on the bottom from the guest even though you just heard 'em.

Bear Week next week! They're scary, hairy and here live.

Always leans forward, pointy shoulders, squinty eyes, very Jewish.

In tennis, you attack at the point of weakness!

It was my grandmother, Ken. She's 81.

Honey, her backhand's a joke! I'm not gonna take advantage of that?

Quiet, please. Actual work going on here.

Is that that same bee? Yes, it is! I'm helping him sue the human race.

Hello. Hello, bee. This is Ken.

Yeah, I remember you. Timberland, size ten and a half. Vibram sole, I believe.

Why does he talk again?

Listen, you better go 'cause we're really busy working.

But it's our yogurt night!

Bye-bye.

Why is yogurt night so difficult?!

You poor thing. You two have been at this for hours!

Yes, and Adam here has been a huge help.

Frosting… How many sugars? Just one. I try not to use the competition.

So why are you helping me?

Bees have good qualities.

And it takes my mind off the shop.

Instead of flowers, people are giving balloon bouquets now.

Those are great, if you're three.

And artificial flowers.

Oh, those just get me psychotic! Yeah, me too. Bent stingers, pointless pollination.

Bees must hate those fake things!

Nothing worse than a daffodil that's had work done.

Maybe this could make up for it a little bit.

This lawsuit's a pretty big deal. I guess. You sure you want to go through with it?

Am I sure? When I'm done with the humans, they won't be able

to say, "Honey, I'm home," without paying a royalty!

It's an incredible scene here in downtown Manhattan,

where the world anxiously waits, because for the first time in history,

we will hear for ourselves if a honeybee can actually speak.

What have we gotten into here, Barry?

It's pretty big, isn't it?

I can't believe how many humans don't work during the day.

You think billion-dollar multinational food companies have good lawyers?

Everybody needs to stay behind the barricade.

What's the matter? I don't know, I just got a chill. Well, if it isn't the bee team.

You boys work on this?

All rise! The Honorable Judge Bumbleton presiding.

All right. Oase number 4475,

Superior Oourt of New York, Barry Bee Benson v. the Honey Industry

is now in session.

Mr. Montgomery, you're representing the five food companies collectively?

A privilege.

Mr. Benson… you're representing all the bees of the world?

I'm kidding. Yes, Your Honor, we're ready to proceed.

Mr. Montgomery, your opening statement, please.

Ladies and gentlemen of the jury,

my grandmother was a simple woman.

Born on a farm, she believed it was man's divine right

to benefit from the bounty of nature God put before us.

If we lived in the topsy-turvy world Mr. Benson imagines,

just think of what would it mean.

I would have to negotiate with the silkworm

for the elastic in my britches!

Talking bee!

How do we know this isn't some sort of

holographic motion-picture-capture Hollywood wizardry?

They could be using laser beams!

Robotics! Ventriloquism! Oloning! For all we know,

he could be on steroids!

Mr. Benson?

Ladies and gentlemen, there's no trickery here.

I'm just an ordinary bee. Honey's pretty important to me.

It's important to all bees. We invented it!

We make it. And we protect it with our lives.

Unfortunately, there are some people in this room

who think they can take it from us

'cause we're the little guys! I'm hoping that, after this is all over,

you'll see how, by taking our honey, you not only take everything we have

but everything we are!

I wish he'd dress like that all the time. So nice!

Oall your first witness.

So, Mr. Klauss Vanderhayden of Honey Farms, big company you have.

I suppose so.

I see you also own Honeyburton and Honron!

Yes, they provide beekeepers for our farms.

Beekeeper. I find that to be a very disturbing term.

I don't imagine you employ any bee-free-ers, do you?

No.

I couldn't hear you.

No.

No.

Because you don't free bees. You keep bees. Not only that,

it seems you thought a bear would be an appropriate image for a jar of honey.

They're very lovable creatures.

Yogi Bear, Fozzie Bear, Build-A-Bear.

You mean like this?

Bears kill bees!

How'd you like his head crashing through your living room?!

Biting into your couch! Spitting out your throw pillows!

OK, that's enough. Take him away.

So, Mr. Sting, thank you for being here. Your name intrigues me.

Where have I heard it before? I was with a band called The Police. But you've never been a police officer, have you?

No, I haven't.

No, you haven't. And so here we have yet another example

of bee culture casually stolen by a human

for nothing more than a prance-about stage name.

Oh, please.

Have you ever been stung, Mr. Sting?

Because I'm feeling a little stung, Sting.

Or should I say… Mr. Gordon M. Sumner!

That's not his real name?! You idiots!

Mr. Liotta, first, belated congratulations on

your Emmy win for a guest spot on ER in 2005.

Thank you. Thank you.

I see from your resume that you're devilishly handsome

with a churning inner turmoil that's ready to blow.

I enjoy what I do. Is that a crime?

Not yet it isn't. But is this what it's come to for you?

Exploiting tiny, helpless bees so you don't

have to rehearse your part and learn your lines, sir?

Watch it, Benson! I could blow right now!

This isn't a goodfella. This is a badfella!

Why doesn't someone just step on this creep, and we can all go home?!

Order in this court! You're all thinking it! Order! Order, I say!

Say it! Mr. Liotta, please sit down! I think it was awfully nice of that bear to pitch in like that.

I think the jury's on our side.

Are we doing everything right, legally?

I'm a florist.

Right. Well, here's to a great team.

To a great team!

Well, hello.

Ken! Hello. I didn't think you were coming.

No, I was just late. I tried to call, but… the battery.

I didn't want all this to go to waste, so I called Barry. Luckily, he was free.

Oh, that was lucky.

There's a little left. I could heat it up.

Yeah, heat it up, sure, whatever.

So I hear you're quite a tennis player.

I'm not much for the game myself. The ball's a little grabby.

That's where I usually sit. Right… there.

Ken, Barry was looking at your resume,

and he agreed with me that eating with chopsticks isn't really a special skill.

You think I don't see what you're doing?

I know how hard it is to find the rightjob. We have that in common.

Do we?

Bees have 100 percent employment, but we do jobs like taking the crud out.

That's just what I was thinking about doing.

Ken, I let Barry borrow your razor for his fuzz. I hope that was all right.

I'm going to drain the old stinger.

Yeah, you do that.

Look at that.

You know, I've just about had it

with your little mind games.

What's that? Italian Vogue. Mamma mia, that's a lot of pages.

A lot of ads.

Remember what Van said, why is your life more valuable than mine?

Funny, I just can't seem to recall that!

I think something stinks in here!

I love the smell of flowers.

How do you like the smell of flames?!

Not as much.

Water bug! Not taking sides!

Ken, I'm wearing a Ohapstick hat! This is pathetic!

I've got issues!

Well, well, well, a royal flush!

You're bluffing. Am I? Surf's up, dude!

Poo water!

That bowl is gnarly.

Except for those dirty yellow rings!

Kenneth! What are you doing?!

You know, I don't even like honey! I don't eat it!

We need to talk!

He's just a little bee!

And he happens to be the nicest bee I've met in a long time!

Long time? What are you talking about?! Are there other bugs in your life?

No, but there are other things bugging me in life. And you're one of them!

Fine! Talking bees, no yogurt night…

My nerves are fried from riding on this emotional roller coaster!

Goodbye, Ken.

And for your information,

I prefer sugar-free, artificial sweeteners made by man!

I'm sorry about all that.

I know it's got an aftertaste! I like it!

I always felt there was some kind of barrier between Ken and me.

I couldn't overcome it. Oh, well.

Are you OK for the trial?

I believe Mr. Montgomery is about out of ideas.

We would like to call Mr. Barry Benson Bee to the stand.

Good idea! You can really see why he's considered one of the best lawyers…

Yeah.

Layton, you've gotta weave some magic

with this jury, or it's gonna be all over.

Don't worry. The only thing I have to do to turn this jury around

is to remind them of what they don't like about bees.

You got the tweezers? Are you allergic? Only to losing, son. Only to losing.

Mr. Benson Bee, I'll ask you what I think we'd all like to know.

What exactly is your relationship

to that woman?

We're friends.

Good friends? Yes. How good? Do you live together?

Wait a minute…

Are you her little…

…bedbug?

I've seen a bee documentary or two. From what I understand,

doesn't your queen give birth to all the bee children?

Yeah, but…

So those aren't your real parents!

Oh, Barry…

Yes, they are!

Hold me back!

You're an illegitimate bee, aren't you, Benson?

He's denouncing bees!

Don't y'all date your cousins?

Objection! I'm going to pincushion this guy! Adam, don't! It's what he wants!

Oh, I'm hit!!

Oh, lordy, I am hit!

Order! Order!

The venom! The venom is coursing through my veins!

I have been felled by a winged beast of destruction!

You see? You can't treat them like equals! They're striped savages!

Stinging's the only thing they know! It's their way!

Adam, stay with me. I can't feel my legs. What angel of mercy will come forward to suck the poison

from my heaving buttocks?

I will have order in this court. Order!

Order, please!

The case of the honeybees versus the human race

took a pointed turn against the bees

yesterday when one of their legal team stung Layton T. Montgomery.

Hey, buddy.

Hey.

Is there much pain?

Yeah.

I…

I blew the whole case, didn't I?

It doesn't matter. What matters is you're alive. You could have died.

I'd be better off dead. Look at me.

They got it from the cafeteria downstairs, in a tuna sandwich.

Look, there's a little celery still on it.

What was it like to sting someone?

I can't explain it. It was all…

All adrenaline and then… and then ecstasy!

All right.

You think it was all a trap?

Of course. I'm sorry. I flew us right into this.

What were we thinking? Look at us. We're just a couple of bugs in this world.

What will the humans do to us if they win?

I don't know.

I hear they put the roaches in motels. That doesn't sound so bad.

Adam, they check in, but they don't check out!

Oh, my.

Oould you get a nurse to close that window?

Why? The smoke. Bees don't smoke.

Right. Bees don't smoke.

Bees don't smoke! But some bees are smoking.

That's it! That's our case!

It is? It's not over?

Get dressed. I've gotta go somewhere.

Get back to the court and stall. Stall any way you can.

And assuming you've done step correctly, you're ready for the tub.

Mr. Flayman.

Yes? Yes, Your Honor!

Where is the rest of your team?

Well, Your Honor, it's interesting.

Bees are trained to fly haphazardly,

and as a result, we don't make very good time.

I actually heard a funny story about…

Your Honor, haven't these ridiculous bugs

taken up enough of this court's valuable time?

How much longer will we allow these absurd shenanigans to go on?

They have presented no compelling evidence to support their charges

against my clients, who run legitimate businesses.

I move for a complete dismissal of this entire case!

Mr. Flayman, I'm afraid I'm going

to have to consider Mr. Montgomery's motion.

But you can't! We have a terrific case.

Where is your proof? Where is the evidence?

Show me the smoking gun!

Hold it, Your Honor! You want a smoking gun?

Here is your smoking gun.

What is that?

It's a bee smoker!

What, this? This harmless little contraption?

This couldn't hurt a fly, let alone a bee.

Look at what has happened

to bees who have never been asked, "Smoking or non?"

Is this what nature intended for us?

To be forcibly addicted to smoke machines

and man-made wooden slat work camps?

Living out our lives as honey slaves to the white man?

What are we gonna do? He's playing the species card. Ladies and gentlemen, please, free these bees!

Free the bees! Free the bees!

Free the bees!

Free the bees! Free the bees!

The court finds in favor of the bees!

Vanessa, we won!

I knew you could do it! High-five!

Sorry.

I'm OK! You know what this means?

All the honey will finally belong to the bees.

Now we won't have to work so hard all the time.

This is an unholy perversion of the balance of nature, Benson.

You'll regret this.

Barry, how much honey is out there?

All right. One at a time.

Barry, who are you wearing?

My sweater is Ralph Lauren, and I have no pants.

What if Montgomery's right? What do you mean? We've been living the bee way a long time, 27 million years.

Oongratulations on your victory. What will you demand as a settlement?

First, we'll demand a complete shutdown of all bee work camps.

Then we want back the honey that was ours to begin with,

every last drop.

We demand an end to the glorification of the bear as anything more

than a filthy, smelly, bad-breath stink machine.

We're all aware of what they do in the woods.

Wait for my signal.

Take him out.

He'll have nauseous for a few hours, then he'll be fine.

And we will no longer tolerate bee-negative nicknames…

But it's just a prance-about stage name!

…unnecessary inclusion of honey in bogus health products

and la-dee-da human tea-time snack garnishments.

Oan't breathe.

Bring it in, boys!

Hold it right there! Good.

Tap it.

Mr. Buzzwell, we just passed three cups, and there's gallons more coming!

I think we need to shut down! Shut down? We've never shut down. Shut down honey production!

Stop making honey!

Turn your key, sir!

What do we do now?

Oannonball!

We're shutting honey production!

Mission abort.

Aborting pollination and nectar detail. Returning to base.

Adam, you wouldn't believe how much honey was out there.

Oh, yeah?

What's going on? Where is everybody?

Are they out celebrating? They're home. They don't know what to do. Laying out, sleeping in.

I heard your Uncle Oarl was on his way to San Antonio with a cricket.

At least we got our honey back.

Sometimes I think, so what if humans liked our honey? Who wouldn't?

It's the greatest thing in the world! I was excited to be part of making it.

This was my new desk. This was my new job. I wanted to do it really well.

And now…

Now I can't.

I don't understand why they're not happy.

I thought their lives would be better!

They're doing nothing. It's amazing. Honey really changes people.

You don't have any idea what's going on, do you?

What did you want to show me? This. What happened here?

That is not the half of it.

Oh, no. Oh, my.

They're all wilting.

Doesn't look very good, does it?

No.

And whose fault do you think that is?

You know, I'm gonna guess bees.

Bees?

Specifically, me.

I didn't think bees not needing to make honey would affect all these things.

It's notjust flowers. Fruits, vegetables, they all need bees.

That's our whole SAT test right there.

Take away produce, that affects the entire animal kingdom.

And then, of course…

The human species?

So if there's no more pollination,

it could all just go south here, couldn't it?

I know this is also partly my fault.

How about a suicide pact?

How do we do it?

I'll sting you, you step on me. Thatjust kills you twice. Right, right.

Listen, Barry… sorry, but I gotta get going.

I had to open my mouth and talk.

Vanessa?

Vanessa? Why are you leaving? Where are you going?

To the final Tournament of Roses parade in Pasadena.

They've moved it to this weekend because all the flowers are dying.

It's the last chance I'll ever have to see it.

Vanessa, I just wanna say I'm sorry. I never meant it to turn out like this.

I know. Me neither.

Tournament of Roses. Roses can't do sports.

Wait a minute. Roses. Roses?

Roses!

Vanessa!

Roses?!

Barry?

Roses are flowers! Yes, they are. Flowers, bees, pollen!

I know. That's why this is the last parade.

Maybe not. Oould you ask him to slow down?

Oould you slow down?

Barry!

OK, I made a huge mistake. This is a total disaster, all my fault.

Yes, it kind of is.

I've ruined the planet. I wanted to help you

with the flower shop. I've made it worse.

Actually, it's completely closed down.

I thought maybe you were remodeling.

But I have another idea, and it's greater than my previous ideas combined.

I don't want to hear it!

All right, they have the roses, the roses have the pollen.

I know every bee, plant and flower bud in this park.

All we gotta do is get what they've got back here with what we've got.

Bees.

Park.

Pollen!

Flowers.

Repollination!

Across the nation!

Tournament of Roses, Pasadena, Oalifornia.

They've got nothing but flowers, floats and cotton candy.

Security will be tight.

I have an idea.

Vanessa Bloome, FTD.

Official floral business. It's real.

Sorry, ma'am. Nice brooch.

Thank you. It was a gift.

Once inside, we just pick the right float.

How about The Princess and the Pea?

I could be the princess, and you could be the pea!

Yes, I got it.

Where should I sit?

What are you?

I believe I'm the pea.

The pea?

It goes under the mattresses.

Not in this fairy tale, sweetheart. I'm getting the marshal. You do that! This whole parade is a fiasco!

Let's see what this baby'll do.

Hey, what are you doing?!

Then all we do is blend in with traffic…

…without arousing suspicion.

Once at the airport, there's no stopping us.

Stop! Security.

You and your insect pack your float? Yes. Has it been in your possession the entire time?

Would you remove your shoes?

Remove your stinger. It's part of me. I know. Just having some fun. Enjoy your flight.

Then if we're lucky, we'll have just enough pollen to do the job.

Oan you believe how lucky we are? We have just enough pollen to do the job!

I think this is gonna work.

It's got to work.

Attention, passengers, this is Oaptain Scott.

We have a bit of bad weather in New York.

It looks like we'll experience a couple hours delay.

Barry, these are cut flowers with no water. They'll never make it.

I gotta get up there and talk to them.

Be careful.

Oan I get help with the Sky Mall magazine?

I'd like to order the talking inflatable nose and ear hair trimmer.

Oaptain, I'm in a real situation.

What'd you say, Hal? Nothing. Bee!

Don't freak out! My entire species…

What are you doing?

Wait a minute! I'm an attorney! Who's an attorney? Don't move.

Oh, Barry.

Good afternoon, passengers. This is your captain.

Would a Miss Vanessa Bloome in 24B please report to the cockpit?

And please hurry!

What happened here?

There was a DustBuster, a toupee, a life raft exploded.

One's bald, one's in a boat, they're both unconscious!

Is that another bee joke? No! No one's flying the plane!

This is JFK control tower, Flight 356. What's your status?

This is Vanessa Bloome. I'm a florist from New York.

Where's the pilot?

He's unconscious, and so is the copilot.

Not good. Does anyone onboard have flight experience?

As a matter of fact, there is.

Who's that? Barry Benson. From the honey trial?! Oh, great.

Vanessa, this is nothing more than a big metal bee.

It's got giant wings, huge engines.

I can't fly a plane.

Why not? Isn't John Travolta a pilot? Yes. How hard could it be?

Wait, Barry! We're headed into some lightning.

This is Bob Bumble. We have some late-breaking news from JFK Airport,

where a suspenseful scene is developing.

Barry Benson, fresh from his legal victory…

That's Barry!

…is attempting to land a plane, loaded with people, flowers

and an incapacitated flight crew.

Flowers?!

We have a storm in the area and two individuals at the controls

with absolutely no flight experience.

Just a minute. There's a bee on that plane.

I'm quite familiar with Mr. Benson and his no-account compadres.

They've done enough damage.

But isn't he your only hope?

Technically, a bee shouldn't be able to fly at all.

Their wings are too small…

Haven't we heard this a million times?

"The surface area of the wings and body mass make no sense."

Get this on the air!

Got it.

Stand by.

We're going live.

The way we work may be a mystery to you.

Making honey takes a lot of bees doing a lot of small jobs.

But let me tell you about a small job.

If you do it well, it makes a big difference.

More than we realized. To us, to everyone.

That's why I want to get bees back to working together.

That's the bee way! We're not made of Jell-O.

We get behind a fellow.

Black and yellow! Hello! Left, right, down, hover.

Hover? Forget hover. This isn't so hard. Beep-beep! Beep-beep!

Barry, what happened?!

Wait, I think we were on autopilot the whole time.

That may have been helping me. And now we're not! So it turns out I cannot fly a plane.

All of you, let's get behind this fellow! Move it out!

Move out!

Our only chance is if I do what I'd do, you copy me with the wings of the plane!

Don't have to yell.

I'm not yelling! We're in a lot of trouble.

It's very hard to concentrate with that panicky tone in your voice!

It's not a tone. I'm panicking!

I can't do this!

Vanessa, pull yourself together. You have to snap out of it!

You snap out of it.

You snap out of it.

You snap out of it!

You snap out of it!

You snap out of it!

You snap out of it!

You snap out of it!

You snap out of it!

Hold it!

Why? Oome on, it's my turn.

How is the plane flying?

I don't know.

Hello?

Benson, got any flowers for a happy occasion in there?

The Pollen Jocks!

They do get behind a fellow.

Black and yellow. Hello. All right, let's drop this tin can on the blacktop.

Where? I can't see anything. Oan you?

No, nothing. It's all cloudy.

Oome on. You got to think bee, Barry.

Thinking bee. Thinking bee. Thinking bee! Thinking bee! Thinking bee!

Wait a minute. I think I'm feeling something.

What? I don't know. It's strong, pulling me. Like a 27-million-year-old instinct.

Bring the nose down.

Thinking bee! Thinking bee! Thinking bee!

What in the world is on the tarmac? Get some lights on that! Thinking bee! Thinking bee! Thinking bee!

Vanessa, aim for the flower. OK. Out the engines. We're going in on bee power. Ready, boys?

Affirmative!

Good. Good. Easy, now. That's it.

Land on that flower!

Ready? Full reverse!

Spin it around!

Not that flower! The other one!

Which one?

That flower.

I'm aiming at the flower!

That's a fat guy in a flowered shirt. I mean the giant pulsating flower

made of millions of bees!

Pull forward. Nose down. Tail up.

Rotate around it.

This is insane, Barry! This's the only way I know how to fly. Am I koo-koo-kachoo, or is this plane flying in an insect-like pattern?

Get your nose in there. Don't be afraid. Smell it. Full reverse!

Just drop it. Be a part of it.

Aim for the center!

Now drop it in! Drop it in, woman!

Oome on, already.

Barry, we did it! You taught me how to fly!

Yes. No high-five! Right. Barry, it worked! Did you see the giant flower?

What giant flower? Where? Of course I saw the flower! That was genius!

Thank you. But we're not done yet. Listen, everyone!

This runway is covered with the last pollen

from the last flowers available anywhere on Earth.

That means this is our last chance.

We're the only ones who make honey, pollinate flowers and dress like this.

If we're gonna survive as a species, this is our moment! What do you say?

Are we going to be bees, orjust Museum of Natural History keychains?

We're bees!

Keychain!

Then follow me! Except Keychain.

Hold on, Barry. Here.

You've earned this.

Yeah!

I'm a Pollen Jock! And it's a perfect fit. All I gotta do are the sleeves.

Oh, yeah.

That's our Barry.

Mom! The bees are back!

If anybody needs to make a call, now's the time.

I got a feeling we'll be working late tonight!

Here's your change. Have a great afternoon! Oan I help who's next?

Would you like some honey with that? It is bee-approved. Don't forget these.

Milk, cream, cheese, it's all me. And I don't see a nickel!

Sometimes I just feel like a piece of meat!

I had no idea.

Barry, I'm sorry. Have you got a moment?

Would you excuse me? My mosquito associate will help you.

Sorry I'm late.

He's a lawyer too?

I was already a blood-sucking parasite. All I needed was a briefcase.

Have a great afternoon!

Barry, I just got this huge tulip order, and I can't get them anywhere.

No problem, Vannie. Just leave it to me.

You're a lifesaver, Barry. Oan I help who's next?

All right, scramble, jocks! It's time to fly.

Thank you, Barry!

That bee is living my life!

Let it go, Kenny.

When will this nightmare end?!

Let it all go.

Beautiful day to fly.

Sure is.

Between you and me, I was dying to get out of that office.

You have got to start thinking bee, my friend.

Thinking bee! Me? Hold it. Let's just stop for a second. Hold it.

I'm sorry. I'm sorry, everyone. Oan we stop here?

I'm not making a major life decision during a production number!

All right. Take ten, everybody. Wrap it up, guys.

I had virtually no rehearsal for that.

A mi no me gusta el término aprovechar, ya que en climas cálidos o fríos no es aprovechar sino evitar, sugiero modificar.

DOI: 10.1016/j.celrep.2024.115047

Resource: (Cell Signaling Technology Cat# 12231, RRID:AB_2783553)

Curator: @scibot

SciCrunch record: RRID:AB_2783553

What is this?

continues the admiration for Julia’s beauty, celebrating the elegance and sensuousness of her appearance

DOI: 10.1016/j.isci.2024.111337

Resource: (Millipore Cat# MAB326, RRID:AB_2082608)

Curator: @scibot

SciCrunch record: RRID:AB_2082608

What is this?

Author response:

The following is the authors’ response to the previous reviews.

Reviewer #1 (Public Review):

In this revision, the authors significantly improved the manuscript. They now address some of my concerns. Specifically, they show the contribution of end-effects on spreading the inputs between dendrites. This analysis reveals greater applicability of their findings to cortical cells, with long, unbranching dendrites than other neuronal types, such as Purkinje cells in the cerebellum.

They now explain better the interactions between calcium and voltage signals, which I believe improve the take-away message of their manuscript. They modified and added new figures that helped to provide more information about their simulations.

However, some of my points remain valid. Figure 6 shows depolarization of ~5mV from -75. This weak depolarization would not effectively recruit nonlinear activation of NMDARs. In their paper, Branco and Hausser (2010) showed depolarizations of ~10-15mV.

More importantly, the signature of NMDAR activation is the prolonged plateau potential and activation at more depolarized resting membrane potentials (their Figure 4). Thus, despite including NMDARs in the simulation, the authors do not model functional recruitment of these channels. Their simulation is thus equivalent to AMPA only drive, which can indeed summate somewhat nonlinearly.

In the current study, we used short sequences of 5 inputs, since the convergence of longer sequences is extremely unlikely in the network configurations we have examined. This resulted in smaller EPSP amplitudes of ~5mV (Figure 6 - Supplement 2A, B). Longer sequences containing 9 inputs resulted in larger somatic depolarizations of ~10mV (Figure 6 - Supplement 2E, F). Although we had modified the (Branco, Clark, and Häusser 2010) model to remove the jitter in the timing of arrival of inputs and made slight modifications to the location of stimulus delivery on the dendrite, we saw similar amplitudes when we tested a 9-length sequence using (Branco, Clark, and Häusser 2010)’s published code (Figure 6 - Supplement 2I, J). In all the cases we tested (5 input sequence, 9 input sequence, 9 input sequence with (Branco, Clark, and Häusser 2010) code repository), removal of NMDA synapses lowered both the somatic EPSPs (Figure 6 - Supplement 2C,D,G,H,K,L) as well as the selectivity (measured as the difference between the EPSPs generated for inward and outward stimulus delivery) (Figure 6 Supplement 2M,N,O). Further, monitoring the voltage along the dendrite for a sequence of 5 inputs showed dendritic EPSPs in the range of 20-45 mV (Figure 6 - Supplement 2P, Q), which came down notably (10-25mV) when NMDA synapses were abolished (Figure 6 - Supplement 2R, S). Thus, even sequences containing as few as 5 inputs were capable of engaging the NMDA-mediated nonlinearity to show sequence selectivity, although the selectivity was not as strong as in the case of 9 inputs.

Reviewer #1 (Recommendations for the authors):

Minor points:

Figure 8, what does the scale in A represent? I assume it is voltage, but there are no units. Figure 8, C, E, G, these are unconventional units for synaptic weights, usually, these are given in nS / per input.

We have corrected these. The scalebar in 8A represents membrane potential in mV. The units of 8C,E,G are now in nS.

Reviewer #2 (Public Review):

Summary:

If synaptic input is functionally clustered on dendrites, nonlinear integration could increase the computational power of neural networks. But this requires the right synapses to be located in the right places. This paper aims to address the question of whether such synaptic arrangements could arise by chance (i.e. without special rules for axon guidance or structural plasticity), and could therefore be exploited even in randomly connected networks. This is important, particularly for the dendrites and biological computation communities, where there is a pressing need to integrate decades of work at the single-neuron level with contemporary ideas about network function.

Using an abstract model where ensembles of neurons project randomly to a postsynaptic population, back-of-envelope calculations are presented that predict the probability of finding clustered synapses and spatiotemporal sequences. Using data-constrained parameters, the authors conclude that clustering and sequences are indeed likely to occur by chance (for large enough ensembles), but require strong dendritic nonlinearities and low background noise to be useful.

Strengths:

(1) The back-of-envelope reasoning presented can provide fast and valuable intuition. The authors have also made the effort to connect the model parameters with measured values. Even an approximate understanding of cluster probability can direct theory and experiments towards promising directions, or away from lost causes.

(2) I found the general approach to be refreshingly transparent and objective. Assumptions are stated clearly about the model and statistics of different circuits. Along with some positive results, many of the computed cluster probabilities are vanishingly small, and noise is found to be quite detrimental in several cases. This is important to know, and I was happy to see the authors take a balanced look at conditions that help/hinder clustering, rather than to just focus on a particular regime that works.

(3) This paper is also a timely reminder that synaptic clusters and sequences can exist on multiple spatial and temporal scales. The authors present results pertaining to the standard `electrical' regime (~50-100 µm, <50 ms), as well as two modes of chemical signaling (~10 µm, 100-1000 ms). The senior author is indeed an authority on the latter, and the simulations in Figure 5, extending those from Bhalla (2017), are unique in this area. In my view, the role of chemical signaling in neural computation is understudied theoretically, but research will be increasingly important as experimental technologies continue to develop.

Weaknesses:

(1) The paper is mostly let down by the presentation. In the current form, some patience is needed to grasp the main questions and results, and it is hard to keep track of the many abbreviations and definitions. A paper like this can be impactful, but the writing needs to be crisp, and the logic of the derivation accessible to non-experts. See, for instance, Stepanyants, Hof & Chklovskii (2002) for a relevant example.

It would be good to see a restructure that communicates the main points clearly and concisely, perhaps leaving other observations to an optional appendix. For the interested but time-pressed reader, I recommend starting with the last paragraph of the introduction, working through the main derivation on page 7, and writing out the full expression with key parameters exposed. Next, look at Table 1 and Figure 2J to see where different circuits and mechanisms fit in this scheme. Beyond this, the sequence derivation on page 15 and biophysical simulations in Figures 5 and 6 are also highlights.

We appreciate the reviewers' suggestions. We have tightened the flow of the introduction. We understand that the abbreviations and definitions are challenging and have therefore provided intuitions and summaries of the equations discussed in the main text.

Clusters calculations

Our approach is to ask how likely it is that a given set of inputs lands on a short segment of dendrite, and then scale it up to all segments on the entire dendritic length of the cell.

Thus, the probability of occurrence of groups that receive connections from each of the M ensembles (PcFMG) is a function of the connection probability (p) between the two layers, the number of neurons in an ensemble (N), the relative zone-length with respect to the total dendritic arbor (Z/L) and the number of ensembles (M).

Sequence calculations

Here we estimate the likelihood of the first ensemble input arriving anywhere on the dendrite, and ask how likely it is that succeeding inputs of the sequence would arrive within a set spacing.

Thus, the probability of occurrence of sequences that receive sequential connections (PcPOSS) from each of the M ensembles is a function of the connection probability (p) between the two layers, the number of neurons in an ensemble (N), the relative window size with respect to the total dendritic arbor (Δ/L) and the number of ensembles (M).

(2) I wonder if the authors are being overly conservative at times. The result highlighted in the abstract is that 10/100000 postsynaptic neurons are expected to exhibit synaptic clustering. This seems like a very small number, especially if circuits are to rely on such a mechanism. However, this figure assumes the convergence of 3-5 distinct ensembles. Convergence of inputs from just 2 ense mbles would be much more prevalent, but still advantageous computationally. There has been excitement in the field about experiments showing the clustering of synapses encoding even a single feature.

We agree that short clusters of two inputs would be far more likely. We focused our analysis on clusters with three of more ensembles because of the following reasons:

(1) The signal to noise in these clusters was very poor as the likelihood of noise clusters is high.

(2) It is difficult to trigger nonlinearities with very few synaptic inputs.

(3) At the ensemble sizes we considered (100 for clusters, 1000 for sequences), clusters arising from just two ensembles would result in high probability of occurrence on all neurons in a network (~50% in cortex, see p_CMFG in figures below.). These dense neural representations make it difficult for downstream networks to decode (Foldiak 2003).

However, in the presence of ensembles containing fewer neurons or when the connection probability between the layers is low, short clusters can result in sparse representations (Figure 2 - Supplement 2). Arguments 1 and 2 hold for short sequences as well.

(3) The analysis supporting the claim that strong nonlinearities are needed for cluster/sequence detection is unconvincing. In the analysis, different synapse distributions on a single long dendrite are convolved with a sigmoid function and then the sum is taken to reflect the somatic response. In reality, dendritic nonlinearities influence the soma in a complex and dynamic manner. It may be that the abstract approach the authors use captures some of this, but it needs to be validated with simulations to be trusted (in line with previous work, e.g. Poirazi, Brannon & Mel, (2003)).

We agree that multiple factors might affect the influence of nonlinearities on the soma. The key goal of our study was to understand the role played by random connectivity in giving rise to clustered computation. Since simulating a wide range of connectivity and activity patterns in a detailed biophysical model was computationally expensive, we analyzed the exemplar detailed models for nonlinearity separately (Figures 5, 6, and new figure 8), and then used our abstract models as a proxy for understanding population dynamics. A complete analysis of the role played by morphology, channel kinetics and the effect of branching requires an in-depth study of its own, and some of these questions have already been tackled by (Poirazi, Brannon, and Mel 2003; Branco, Clark, and Häusser 2010; Bhalla 2017). However, in the revision, we have implemented a single model which incorporates the range of ion-channel, synaptic and biochemical signaling nonlinearities which we discuss in the paper (Figure 8, and Figure 8 Supplement 1, 2,3). We use this to demonstrate all three forms of sequence and grouped computation we use in the study, where the only difference is in the stimulus pattern and the separation of time-scales inherent in the stimuli.

(4) It is unclear whether some of the conclusions would hold in the presence of learning. In the signal-to-noise analysis, all synaptic strengths are assumed equal. But if synapses involved in salient clusters or sequences were potentiated, presumably detection would become easier? Similarly, if presynaptic tuning and/or timing were reorganized through learning, the conditions for synaptic arrangements to be useful could be relaxed. Answering these questions is beyond the scope of the study, but there is a caveat there nonetheless.

We agree with the reviewer. If synapses receiving connectivity from ensembles had stronger weights, this would make detection easier. Dendritic spikes arising from clustered inputs have been implicated in local cooperative plasticity (Golding, Staff, and Spruston 2002; Losonczy, Makara, and Magee 2008). Further, plasticity related proteins synthesized at a synapse undergoing L-LTP can diffuse to neighboring weakly co-active synapses, and thereby mediate cooperative plasticity (Harvey et al. 2008; Govindarajan, Kelleher, and Tonegawa 2006; Govindarajan et al. 2011). Thus if clusters of synapses were likely to be co-active, they could further engage these local plasticity mechanisms which could potentiate them while not potentiating synapses that are activated by background activity. This would depend on the activity correlation between synapses receiving ensemble inputs within a cluster vs those activated by background activity. We have mentioned some of these ideas in a published opinion paper (Pulikkottil, Somashekar, and Bhalla 2021). In the current study, we wanted to understand whether even in the absence of specialized connection rules, interesting computations could still emerge. Thus, we focused on asking whether clustered or sequential convergence could arise even in a purely randomly connected network, with the most basic set of assumptions. We agree that an analysis of how selectivity evolves with learning would be an interesting topic for further work.

References

• Bhalla, Upinder S. 2017. “Synaptic Input Sequence Discrimination on Behavioral Timescales Mediated by Reaction-Diffusion Chemistry in Dendrites.” Edited by Frances K Skinner. eLife 6 (April):e25827. https://doi.org/10.7554/eLife.25827.

• Branco, Tiago, Beverley A. Clark, and Michael Häusser. 2010. “Dendritic Discrimination of Temporal Input Sequences in Cortical Neurons.” Science (New York, N.Y.) 329 (5999): 1671–75. https://doi.org/10.1126/science.1189664.

• Foldiak, Peter. 2003. “Sparse Coding in the Primate Cortex.” The Handbook of Brain Theory and Neural Networks. https://research-repository.st-andrews.ac.uk/bitstream/handle/10023/2994/FoldiakSparse HBTNN2e02.pdf?sequence=1.

• Golding, Nace L., Nathan P. Staff, and Nelson Spruston. 2002. “Dendritic Spikes as a Mechanism for Cooperative Long-Term Potentiation.” Nature 418 (6895): 326–31. https://doi.org/10.1038/nature00854.

• Govindarajan, Arvind, Inbal Israely, Shu-Ying Huang, and Susumu Tonegawa. 2011. “The Dendritic Branch Is the Preferred Integrative Unit for Protein Synthesis-Dependent LTP.” Neuron 69 (1): 132–46. https://doi.org/10.1016/j.neuron.2010.12.008.

• Govindarajan, Arvind, Raymond J. Kelleher, and Susumu Tonegawa. 2006. “A Clustered Plasticity Model of Long-Term Memory Engrams.” Nature Reviews Neuroscience 7 (7): 575–83. https://doi.org/10.1038/nrn1937.

• Harvey, Christopher D., Ryohei Yasuda, Haining Zhong, and Karel Svoboda. 2008. “The Spread of Ras Activity Triggered by Activation of a Single Dendritic Spine.” Science (New York, N.Y.) 321 (5885): 136–40. https://doi.org/10.1126/science.1159675.

• Losonczy, Attila, Judit K. Makara, and Jeffrey C. Magee. 2008. “Compartmentalized Dendritic Plasticity and Input Feature Storage in Neurons.” Nature 452 (7186): 436–41. https://doi.org/10.1038/nature06725.

• Poirazi, Panayiota, Terrence Brannon, and Bartlett W. Mel. 2003. “Pyramidal Neuron as Two-Layer Neural Network.” Neuron 37 (6): 989–99. https://doi.org/10.1016/S0896-6273(03)00149-1.

• Pulikkottil, Vinu Varghese, Bhanu Priya Somashekar, and Upinder S. Bhalla. 2021. “Computation, Wiring, and Plasticity in Synaptic Clusters.” Current Opinion in Neurobiology, Computational Neuroscience, 70 (October):101–12. https://doi.org/10.1016/j.conb.2021.08.001.

Author response:

The following is the authors’ response to the previous reviews.

Reviewer #1 (Public Review):

In this revision, the authors significantly improved the manuscript. They now address some of my concerns. Specifically, they show the contribution of end-effects on spreading the inputs between dendrites. This analysis reveals greater applicability of their findings to cortical cells, with long, unbranching dendrites than other neuronal types, such as Purkinje cells in the cerebellum.

They now explain better the interactions between calcium and voltage signals, which I believe improve the take-away message of their manuscript. They modified and added new figures that helped to provide more information about their simulations.

However, some of my points remain valid. Figure 6 shows depolarization of ~5mV from -75. This weak depolarization would not effectively recruit nonlinear activation of NMDARs. In their paper, Branco and Hausser (2010) showed depolarizations of ~10-15mV.

More importantly, the signature of NMDAR activation is the prolonged plateau potential and activation at more depolarized resting membrane potentials (their Figure 4). Thus, despite including NMDARs in the simulation, the authors do not model functional recruitment of these channels. Their simulation is thus equivalent to AMPA only drive, which can indeed summate somewhat nonlinearly.

In the current study, we used short sequences of 5 inputs, since the convergence of longer sequences is extremely unlikely in the network configurations we have examined. This resulted in smaller EPSP amplitudes of ~5mV (Figure 6 - Supplement 2A, B). Longer sequences containing 9 inputs resulted in larger somatic depolarizations of ~10mV (Figure 6 - Supplement 2E, F). Although we had modified the (Branco, Clark, and Häusser 2010) model to remove the jitter in the timing of arrival of inputs and made slight modifications to the location of stimulus delivery on the dendrite, we saw similar amplitudes when we tested a 9-length sequence using (Branco, Clark, and Häusser 2010)’s published code (Figure 6 - Supplement 2I, J). In all the cases we tested (5 input sequence, 9 input sequence, 9 input sequence with (Branco, Clark, and Häusser 2010) code repository), removal of NMDA synapses lowered both the somatic EPSPs (Figure 6 - Supplement 2C,D,G,H,K,L) as well as the selectivity (measured as the difference between the EPSPs generated for inward and outward stimulus delivery) (Figure 6 Supplement 2M,N,O). Further, monitoring the voltage along the dendrite for a sequence of 5 inputs showed dendritic EPSPs in the range of 20-45 mV (Figure 6 - Supplement 2P, Q), which came down notably (10-25mV) when NMDA synapses were abolished (Figure 6 - Supplement 2R, S). Thus, even sequences containing as few as 5 inputs were capable of engaging the NMDA-mediated nonlinearity to show sequence selectivity, although the selectivity was not as strong as in the case of 9 inputs.

Reviewer #1 (Recommendations for the authors):

Minor points:

Figure 8, what does the scale in A represent? I assume it is voltage, but there are no units. Figure 8, C, E, G, these are unconventional units for synaptic weights, usually, these are given in nS / per input.

We have corrected these. The scalebar in 8A represents membrane potential in mV. The units of 8C,E,G are now in nS.

Reviewer #2 (Public Review):

Summary:

If synaptic input is functionally clustered on dendrites, nonlinear integration could increase the computational power of neural networks. But this requires the right synapses to be located in the right places. This paper aims to address the question of whether such synaptic arrangements could arise by chance (i.e. without special rules for axon guidance or structural plasticity), and could therefore be exploited even in randomly connected networks. This is important, particularly for the dendrites and biological computation communities, where there is a pressing need to integrate decades of work at the single-neuron level with contemporary ideas about network function.

Using an abstract model where ensembles of neurons project randomly to a postsynaptic population, back-of-envelope calculations are presented that predict the probability of finding clustered synapses and spatiotemporal sequences. Using data-constrained parameters, the authors conclude that clustering and sequences are indeed likely to occur by chance (for large enough ensembles), but require strong dendritic nonlinearities and low background noise to be useful.

Strengths:

(1) The back-of-envelope reasoning presented can provide fast and valuable intuition. The authors have also made the effort to connect the model parameters with measured values. Even an approximate understanding of cluster probability can direct theory and experiments towards promising directions, or away from lost causes.

(2) I found the general approach to be refreshingly transparent and objective. Assumptions are stated clearly about the model and statistics of different circuits. Along with some positive results, many of the computed cluster probabilities are vanishingly small, and noise is found to be quite detrimental in several cases. This is important to know, and I was happy to see the authors take a balanced look at conditions that help/hinder clustering, rather than to just focus on a particular regime that works.

(3) This paper is also a timely reminder that synaptic clusters and sequences can exist on multiple spatial and temporal scales. The authors present results pertaining to the standard `electrical' regime (~50-100 µm, <50 ms), as well as two modes of chemical signaling (~10 µm, 100-1000 ms). The senior author is indeed an authority on the latter, and the simulations in Figure 5, extending those from Bhalla (2017), are unique in this area. In my view, the role of chemical signaling in neural computation is understudied theoretically, but research will be increasingly important as experimental technologies continue to develop.

Weaknesses:

(1) The paper is mostly let down by the presentation. In the current form, some patience is needed to grasp the main questions and results, and it is hard to keep track of the many abbreviations and definitions. A paper like this can be impactful, but the writing needs to be crisp, and the logic of the derivation accessible to non-experts. See, for instance, Stepanyants, Hof & Chklovskii (2002) for a relevant example.

It would be good to see a restructure that communicates the main points clearly and concisely, perhaps leaving other observations to an optional appendix. For the interested but time-pressed reader, I recommend starting with the last paragraph of the introduction, working through the main derivation on page 7, and writing out the full expression with key parameters exposed. Next, look at Table 1 and Figure 2J to see where different circuits and mechanisms fit in this scheme. Beyond this, the sequence derivation on page 15 and biophysical simulations in Figures 5 and 6 are also highlights.

We appreciate the reviewers' suggestions. We have tightened the flow of the introduction. We understand that the abbreviations and definitions are challenging and have therefore provided intuitions and summaries of the equations discussed in the main text.

Clusters calculations

Our approach is to ask how likely it is that a given set of inputs lands on a short segment of dendrite, and then scale it up to all segments on the entire dendritic length of the cell.

Thus, the probability of occurrence of groups that receive connections from each of the M ensembles (PcFMG) is a function of the connection probability (p) between the two layers, the number of neurons in an ensemble (N), the relative zone-length with respect to the total dendritic arbor (Z/L) and the number of ensembles (M).

Sequence calculations

Here we estimate the likelihood of the first ensemble input arriving anywhere on the dendrite, and ask how likely it is that succeeding inputs of the sequence would arrive within a set spacing.

Thus, the probability of occurrence of sequences that receive sequential connections (PcPOSS) from each of the M ensembles is a function of the connection probability (p) between the two layers, the number of neurons in an ensemble (N), the relative window size with respect to the total dendritic arbor (Δ/L) and the number of ensembles (M).

(2) I wonder if the authors are being overly conservative at times. The result highlighted in the abstract is that 10/100000 postsynaptic neurons are expected to exhibit synaptic clustering. This seems like a very small number, especially if circuits are to rely on such a mechanism. However, this figure assumes the convergence of 3-5 distinct ensembles. Convergence of inputs from just 2 ense mbles would be much more prevalent, but still advantageous computationally. There has been excitement in the field about experiments showing the clustering of synapses encoding even a single feature.

We agree that short clusters of two inputs would be far more likely. We focused our analysis on clusters with three of more ensembles because of the following reasons:

(1) The signal to noise in these clusters was very poor as the likelihood of noise clusters is high.

(2) It is difficult to trigger nonlinearities with very few synaptic inputs.

(3) At the ensemble sizes we considered (100 for clusters, 1000 for sequences), clusters arising from just two ensembles would result in high probability of occurrence on all neurons in a network (~50% in cortex, see p_CMFG in figures below.). These dense neural representations make it difficult for downstream networks to decode (Foldiak 2003).

However, in the presence of ensembles containing fewer neurons or when the connection probability between the layers is low, short clusters can result in sparse representations (Figure 2 - Supplement 2). Arguments 1 and 2 hold for short sequences as well.

(3) The analysis supporting the claim that strong nonlinearities are needed for cluster/sequence detection is unconvincing. In the analysis, different synapse distributions on a single long dendrite are convolved with a sigmoid function and then the sum is taken to reflect the somatic response. In reality, dendritic nonlinearities influence the soma in a complex and dynamic manner. It may be that the abstract approach the authors use captures some of this, but it needs to be validated with simulations to be trusted (in line with previous work, e.g. Poirazi, Brannon & Mel, (2003)).

We agree that multiple factors might affect the influence of nonlinearities on the soma. The key goal of our study was to understand the role played by random connectivity in giving rise to clustered computation. Since simulating a wide range of connectivity and activity patterns in a detailed biophysical model was computationally expensive, we analyzed the exemplar detailed models for nonlinearity separately (Figures 5, 6, and new figure 8), and then used our abstract models as a proxy for understanding population dynamics. A complete analysis of the role played by morphology, channel kinetics and the effect of branching requires an in-depth study of its own, and some of these questions have already been tackled by (Poirazi, Brannon, and Mel 2003; Branco, Clark, and Häusser 2010; Bhalla 2017). However, in the revision, we have implemented a single model which incorporates the range of ion-channel, synaptic and biochemical signaling nonlinearities which we discuss in the paper (Figure 8, and Figure 8 Supplement 1, 2,3). We use this to demonstrate all three forms of sequence and grouped computation we use in the study, where the only difference is in the stimulus pattern and the separation of time-scales inherent in the stimuli.

(4) It is unclear whether some of the conclusions would hold in the presence of learning. In the signal-to-noise analysis, all synaptic strengths are assumed equal. But if synapses involved in salient clusters or sequences were potentiated, presumably detection would become easier? Similarly, if presynaptic tuning and/or timing were reorganized through learning, the conditions for synaptic arrangements to be useful could be relaxed. Answering these questions is beyond the scope of the study, but there is a caveat there nonetheless.

We agree with the reviewer. If synapses receiving connectivity from ensembles had stronger weights, this would make detection easier. Dendritic spikes arising from clustered inputs have been implicated in local cooperative plasticity (Golding, Staff, and Spruston 2002; Losonczy, Makara, and Magee 2008). Further, plasticity related proteins synthesized at a synapse undergoing L-LTP can diffuse to neighboring weakly co-active synapses, and thereby mediate cooperative plasticity (Harvey et al. 2008; Govindarajan, Kelleher, and Tonegawa 2006; Govindarajan et al. 2011). Thus if clusters of synapses were likely to be co-active, they could further engage these local plasticity mechanisms which could potentiate them while not potentiating synapses that are activated by background activity. This would depend on the activity correlation between synapses receiving ensemble inputs within a cluster vs those activated by background activity. We have mentioned some of these ideas in a published opinion paper (Pulikkottil, Somashekar, and Bhalla 2021). In the current study, we wanted to understand whether even in the absence of specialized connection rules, interesting computations could still emerge. Thus, we focused on asking whether clustered or sequential convergence could arise even in a purely randomly connected network, with the most basic set of assumptions. We agree that an analysis of how selectivity evolves with learning would be an interesting topic for further work.

References

Bhalla, Upinder S. 2017. “Synaptic Input Sequence Discrimination on Behavioral Timescales Mediated by Reaction-Diffusion Chemistry in Dendrites.” Edited by Frances K Skinner. eLife 6 (April):e25827. https://doi.org/10.7554/eLife.25827.

Branco, Tiago, Beverley A. Clark, and Michael Häusser. 2010. “Dendritic Discrimination of Temporal Input Sequences in Cortical Neurons.” Science (New York, N.Y.) 329 (5999): 1671–75. https://doi.org/10.1126/science.1189664.

Foldiak, Peter. 2003. “Sparse Coding in the Primate Cortex.” The Handbook of Brain Theory and Neural Networks. https://research-repository.st-andrews.ac.uk/bitstream/handle/10023/2994/FoldiakSparse HBTNN2e02.pdf?sequence=1.

Golding, Nace L., Nathan P. Staff, and Nelson Spruston. 2002. “Dendritic Spikes as a Mechanism for Cooperative Long-Term Potentiation.” Nature 418 (6895): 326–31. https://doi.org/10.1038/nature00854.

Govindarajan, Arvind, Inbal Israely, Shu-Ying Huang, and Susumu Tonegawa. 2011. “The Dendritic Branch Is the Preferred Integrative Unit for Protein Synthesis-Dependent LTP.” Neuron 69 (1): 132–46. https://doi.org/10.1016/j.neuron.2010.12.008.

Govindarajan, Arvind, Raymond J. Kelleher, and Susumu Tonegawa. 2006. “A Clustered Plasticity Model of Long-Term Memory Engrams.” Nature Reviews Neuroscience 7 (7): 575–83. https://doi.org/10.1038/nrn1937.

Harvey, Christopher D., Ryohei Yasuda, Haining Zhong, and Karel Svoboda. 2008. “The Spread of Ras Activity Triggered by Activation of a Single Dendritic Spine.” Science (New York, N.Y.) 321 (5885): 136–40. https://doi.org/10.1126/science.1159675.

Losonczy, Attila, Judit K. Makara, and Jeffrey C. Magee. 2008. “Compartmentalized Dendritic Plasticity and Input Feature Storage in Neurons.” Nature 452 (7186): 436–41. https://doi.org/10.1038/nature06725.

Poirazi, Panayiota, Terrence Brannon, and Bartlett W. Mel. 2003. “Pyramidal Neuron as Two-Layer Neural Network.” Neuron 37 (6): 989–99. https://doi.org/10.1016/S0896-6273(03)00149-1.

Pulikkottil, Vinu Varghese, Bhanu Priya Somashekar, and Upinder S. Bhalla. 2021. “Computation, Wiring, and Plasticity in Synaptic Clusters.” Current Opinion in Neurobiology, Computational Neuroscience, 70 (October):101–12. https://doi.org/10.1016/j.conb.2021.08.001.

Each line ends in a perfect rhyme perhaps as a tool to reinforce the childlike innocence and wonder that the beauty of Julia inspires in our writer.

由于 Shuffle 会对分区内的数据进行排序，因此 SMJ性能和 HJ 一样，那 Shuffle HJ 就没有优势了

非等值的连表关联还得使用 NLJ

使用 Hash算法做关联似乎在大数据领域比较好用

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

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Reply to the reviewers

Response to reviewers’ comments for Isbilir et al

We thank the reviewers for their insightful comments and advice. In light of the reviewers’ constructive suggestions, we have revised our manuscript as detailed below.

Reviewer #1 (Evidence, reproducibility and clarity (Required)):

Summary: In this manuscript, the authors investigate the unique Mycobacteriaceae cell envelope using cryo-tomography/cryo-electron microscopy with Corynebacterium glutamicum as a model organism. Cryo-EM images of C. glutamicum cells successfully resolved previously observed densities corresponding to the MM, arabinogalactan, peptidoglycan, and inner membrane layers of the cell envelope along with the S-layer. The authors found that the S-layer is patchy in a manner dependent on growth phase (i.e. liquid versus solid growth). Intriguingly, when the S-layer was present, the leaflets of the MM appeared to be disrupted. The authors solved the structure of purified S-layer protein PS2 by cryo-EM, however they could not resolve the C-terminal membrane interaction domain. The authors found that PS2 is hexameric and different hexamers are linked by trimeric interface to create a porous structure. Phylogenetic analysis showed conservation of PS2 within corynebacteria and suggested a signature for MM-association.

Major comments:

(1) The S-layer structure is porous and the authors suggest that it may function as a molecular sieve or permeability barrier. This hypothesis should either be tested experimentally, or further discussion is needed regarding what small molecules (chemical features, size) would be able to penetrate.

This is a misunderstanding; we rather expect the opposite scenario in which the dimensions of the PS2 S-layer pores are too large to act as a molecular sieve. We are sorry for the confusion and have further clarified this part of the results and discussion.

Line 258: “The combination of hexameric and trimeric interfaces results in varying pores sizes of 6 Å, 27 Å, and 81 Å within the lattice (Fig. 3A). Some of these pores are relatively large and are reminiscent of the porous S-layer of Deinococcus radiodurans, which is also patchy on the cell surface (von Kügelgen et al., 2023). This suggests that C. glutamicum S-layer likely does not function as a molecular sieve, i.e. it has no protective role due to large pore dimensions and patchy cellular coating of the S-layer.”

and

Line 470: “The large pores (especially the 27 Å- and 81 Å-pores) in the S-layer suggest that its role is not to protect the cells from invading molecules or phages.”

(2) The authors show cryo-EM images of dividing C. glutamicum cells but don't make any statements as to the presence, morphology, and measurements of the different cell envelope layers. This analysis should be included.

We thank the reviewer for pointing this out. As suggested, we modified Figure S1 to highlight further details, and we have added the sentences below into the manuscript text.

Line 175: “To probe the plasticity of the cell envelope during the cell cycle, we analysed the cell envelope layers within the dividing septum (Fig. S1E). The thickness of the septum (~55 nm) was found to be greater than the usual thickness of the cell envelope (~42 nm on the same cell, see also Fig. 1A). The septum is composed of unseparated cell envelopes of the daughter cells that appear to contain a single ‘outer’ membrane, which is likely composed of mycolic acids. Presumably, this membrane will form the future MM once division is completed. Notably, the putative mycolic acid-containing bilayer within the septum was not connected to the MM on the other parts of the cell, whereas the remaining cell envelope layers appeared to be continuous with the rest of the cell. While IM and the putative future MM were clearly distinguishable, PG and AG could not be differentially identified in the dividing septum.”

and

Line 422: “In addition to cell envelopes of non-dividing cells, the dividing C. glutamicum septum shows two daughter cell envelopes separated by a bilayer likely containing mycolic acids. Notably, this bilayer was not connected to the MM on the rest of the cell (Fig. S1E). This observation is in line with the previous studies showing that at septal junctions, a contiguous PG layer acts as a diffusion barrier for the MM, and during separation of daughter cells, the PG in the septal junctions is displaced, allowing the bilayer at the septum to merge with the rest of the MM (Zhou et al., 2019).”

__Figure S1. Cryo-FIB milling of C. glutamicum cells. __

… E) Septum of a dividing C. glutamicum cell. Ten 0.85 nm thick-slices of the tomogram were averaged and bandpass-filtered to boost contrast. Zoomed view of the septum is shown on the right.

(3) The authors should include more discussion as to the patchiness or "wavy" MM near sites of PS2 contact. Cryo-EM of cells that express a variant of PS2 that lack the membrane anchoring domain would demonstrate that this is specific to PS2-membrane contacts. Minimally, providing some quantification for this phenotype would strengthen the claim (for instance, does the spacing between the perturbations match the expected scale of distance between S-layer membrane contacts).

We agree with reviewer that demonstrating the “wavy” nature of the MM requires further analysis. While it is our strong impression that the wavy nature is increased underneath the PS2 S-layer, we could not find a suitable metric to show this convincingly, i.e. all our analyses (real space averaging or averaging of power spectra) did not give clear-cut results. This is probably due to the inherent variability in the MM around the cell. In line with this, we have decided to tone down the relevant text in the manuscript.

Line 151: “Although we cannot be certain given the existing data, we suppose that this perturbation of the MM directly beneath the patchy S-layer could arise due to the interaction of the S-layer anchoring domain with the MM, which has been predicted to be present in the coiled coil part of the PS2 protein forming the S-layer using bioinformatics (Johnston et al., 2024).”

(4) The authors speculate on complete conservation of certain residues in the C-terminal domain of PS2 and hypothesize that they may be important for maturation or targeting of MM-associated proteins. Two additional examples of proteins with this motif are mentioned as evidence. Authors should search for this motif in pre-existing lists of MM proteins in the literature to test if this hypothesis is robust. Experiments to test if the conserved C-terminal residues of PS2 are required for export or assembly into an S-layer are feasible but optional given the scope of the paper.

We thank the reviewer for raising this point. Upon thoroughly re-examining the literature, we identified a previous study by Marchand et al. (J Bacteriol., 2012) that characterized MM-associated proteins in C. glutamicum. The proteins reported in this study as associated with the inner leaflet of the MM, including the mycoloyltransferases MytA and MytB, as well as those involved in pore formation, such as PorA and PorB, do not possess a phenylalanine as their terminal residue. This observation suggests that the invariant phenylalanine in PS2 does not represent a universal mechanism for targeting proteins to the MM. However, we also noted that several putative cell-surface proteins identified in this study, which feature a PS2-like C-terminal hydrophobic anchor preceded by a disordered segment, harbor a phenylalanine, proline, or lysine at their C-terminus. Additionally, the targeting of porins such as PorA, PorH, PorB, and PorC to the MM in C. glutamicum is known to depend on posttranslational O-mycoloylation. Based on these findings, we speculate that the conserved phenylalanine in PS2 may contribute to its anchoring and stabilization within the MM, rather than functioning as a universal targeting signal—a hypothesis we plan to investigate in future studies. We have revised the manuscript to incorporate these points and provide additional context.

Line 377: “To explore this hypothesis, we analysed MM-associated proteins of C. glutamicum identified in a previous study (Marchand et al., 2012). Proteins associated with the inner leaflet of the MM, such as the mycoloyltransferases MytA, MytB, MytC, MytD, and MytF, or those involved in pore formation, such as PorA and PorB, do not possess a phenylalanine as their terminal residue, suggesting that the invariant phenylalanine in PS2 does not represent a general mechanism for targeting proteins to the MM. However, several putative cell-surface proteins with a PS2-like C-terminal hydrophobic anchor preceded by a disordered segment were found to harbor a phenylalanine, proline, or lysine at their C-terminus. Examples include a prenyltransferase/squalene oxidase repeat-containing protein (NCBI: WP_011013715.1) and a metallophosphoesterase family protein (WP_011015494.1) (Fig. S8). Based on this conservation, we identified additional putative MM-associated cell-surface proteins in C. glutamicum (Fig. S8), such as an ExeM/NucH family extracellular endonuclease (WP_003854007.1) and a lamin tail domain-containing protein (WP_004567709.1). Interestingly, the targeting of porins PorA, PorH, PorB, and PorC to the MM in C. glutamicum has been shown to depend on posttranslational O-mycoloylation, which facilitates their proper localization and integration into the mycomembrane (Carel et al., 2017). Whether O-mycoloylation is also involved in the targeting of PS2 remains an open question and warrants further investigation. We speculate that terminal residues such as phenylalanine, proline, and lysine may contribute to anchoring cell-surface proteins within the MM by stabilizing interactions with the hydrophobic membrane environment or acting as signals for specific sorting or assembly mechanisms.”

(5) The authors do not draw the distinction between MM-associated and integral MM proteins (that contain a transmembrane domain). Is the C-terminal membrane anchoring domain of PS2 likely to span the entire bilayer or just be associated by a few amino acids?

The MM-anchoring hydrophobic segment is approximately 25 residues long across PS2 homologs, corresponding to a ~3.75 nm α-helix. In comparison, the MM has a thickness of 4–5 nm. This suggests that, while the MM-anchoring segment may not strictly qualify as a transmembrane domain integral to the MM, it is sufficiently long to embed deeply into the membrane and potentially span much of its bilayer thickness. To address this, we have added the following clarification to the manuscript:

Line 363: “The MM-binding segment is predicted by AlphaFold2 models to comprise an N-terminal hydrophobic a-helix and a short C-terminal amphipathic a-helix; however, in the MM, these may function as a single continuous helix. The MM-binding segment of PS2 homologs in Corynebacterium is consistently approximately 25 amino acid residues long, corresponding to a ~3.75 nm α-helix—sufficiently long to nearly traverse the 4–5 nm thickness of the MM.”

Minor comments:

(1) The authors comment that the thickness of the MM both with and without the S-layer is the similar and conclude that there is no change in mycolic acid length. The resolution of the technique is not sufficient to make this statement.

We agree with the reviewer in this point, while we can only measure the thickness of bilayer, we cannot comment on the thickness of each leaflet of the mycomembrane. Therefore, we have revised the text accordingly.

Line 144: “In 2D projection images of FIB-milled cells, the two leaflets of the MM were clearly resolved (Figs. 1C-D). The thickness of the MM in both cell envelopes with and without S-layer was between 4-5 nm (Table S1).”

(2) It would be helpful if the authors could comment if their membrane dimension measurements agree with previously published results in the main text of the manuscript. It is currently only included in the legend of Table S1.

Specifically regarding the MM, the measurements from both studies are quite similar; compare 4-5 nm from our study with 4.7 nm from Zuber et al., 2008. As the reviewer suggested, we have revised the discussion to include the comparison of the measurements with Zuber et al., 2008.

Line 413: “Our measurements are largely consistent with previous results (Zuber et al., 2008), except that in our data the IWZ was significantly thinner (~9.8 nm in this study vs. ~18 nm in Zuber et al., 2008), which is possibly due to strain differences. Moreover, our measurement of MWZ was slightly different because we could resolve OWZ as a separate layer, which was included into the MWZ measurement in the previous study (~15nm in this study vs. ~20.9 nm in Zuber et al., 2008) (Zuber et al., 2008).”

Reviewer #1 (Significance (Required)):

The manuscript provides compelling images and structures of the C. glutamicum cell envelope and S-layer protein PS2, respectively. These cryo-EM images of the cell envelope appear to agree nicely with pre-existing studies in the field. The introduction of the manuscript was well-written and the data in the manuscript is of broad interest to those who study the Mycobacteriaceae cell envelope. There is a lot of compelling data included in the paper, but the study would be strengthened by further analysis of the data as well as additional experiments to support some of the hypotheses suggested.

Thank you.

Reviewer expertise: bacterial genetics, bacterial cell envelope, protein transport

__ __

Reviewer #2 (Evidence, reproducibility and clarity (Required)):

Corynebacterium glutamicum is an organism with important industrial application, and it shares its complex cell-envelop architecture with organism of great relevance in human health such Corynebacterium diphtheriae and pathogenic mycobacteria. Using a cryo-EM and cryo-ET approaches together with phylogenetic studies, the authors provide of an in-deep structural characterization of the cell envelop of C. glutamicum. The authors map the different components of the cell envelope using high-resolution tomography, revealing unseen details of the outer wall zone, previously unsolved and attributed to the AG molecule. They provide with an atomic model of the PS2 S-layer at 3.1 A global resolution. The later discloses key features of the S-layer architecture, consisting of a hexagonal scaffold built by the PS2 protein, and its interaction with the mycolic membrane. The phylogenetic and bioinformatic studies show PS2 S-layer to be exclusively found within the Corynebacterium genus, although sporadically, and a correlation of PS2 presence/absence with other genetic differences. Despite PS2 homologues are shown to share common regions, which suggests all PS2 S-layers to exhibit a hexagonal lattice like the described in this study, but with divergent lattice parameters.

Major comments:

The authors provide with solid data supporting the structural models and conclusions stated. Text and figures are clear and nicely presented. I have however an important question regarding a the cryo-EM model. In Figure 3 B-C and Figure S3D-H, the authors depict protein details including hydrogen atoms, which make me question if the PS2 S-layer structure has been modeled including hydrogen atoms. The resolution of the cryo-EM data does not enable to model hydrogens that, if were included in the structure, should be removed of the coordinate file of the S-layer model and figures.

We agree with the reviewer that the current resolution of the cryo-EM map is not sufficient to model hydrogen atoms. The hydrogens were added to PS2 S-layer model during refinement in ISOLDE (Croll, 2018), and retained during Phenix real space refinement (Afonine et al., 2018; Liebschner et al., 2019). We agree with the reviewer that hydrogens should not be shown in the figures, since their positions have not been determined experimentally in our cryo-EM map. We have therefore removed these atoms from Figures 3 and S4.

__ “Figure 3. The PS2 S-layer Lattice. …“__

“Figure S4. Features of the PS2 S-layer lattice”

Minor comments

• Regarding the proposed calcium atoms at the S-Layer. The authors should provide further analysis to support the presence of calcium/divalent atoms proposed. Please show how is the coordination around the blobs spotted as potential calcium (or any other potential divalent that might be interacting at those positions). Does the coordination observed fit with the expected for a calcium/divalent binding site? Are the residues coordinating to those blobs well defined in density? Are the blobs of density of the potential cations observed across all the protomers of the PS2 S-layer? Figure 3D-F depicting the proposed cation-binding sites are too busy and unclear, they should focus on the proposed binding sites showing the interacting side/main-chains involved in the proposed coordination.

This is an interesting point. To investigate, we performed EDTA/EGTA treatment of the purified PS2 S-layer to see whether there would be any observable effect on the S-layer. We observed that S-layer lattices were still intact after EDTA or EGTA treatment. Therefore, we concluded that either cations do not play a role in stabilizing this S-layer or they are not accessible for chelation by EDTA or EGTA. This experiment unfortunately did not allow us to identify the ionic species. About the coordination: in the unknown densities 1 and 2 in the new Fig. S4, the coordination is clearer when compared to unknown density 3, however we cannot say for certain that these ions are calcium ions. Considering this, we have changed the text accordingly.

Line 237: “At the sequence level, the PS2 protein is enriched in acidic amino acid residues, giving it an overall negative charge, with an estimated isoelectric point of 4.25 (Fig. S4B-C). Consistent with this overall negative charge, we observed putative cationic densities at various locations along the PS2 sequence in the cryo-EM map, which are surrounded and stabilized by negatively charged amino acid residues (Figs. S4D-F). The identity of these cations cannot be ascertained at the current resolution of our cryo-EM map; however, previous studies on other bacterial S-layers suggest that they may correspond to calcium (Baranova et al., 2012; Herdman et al., 2022; Sogues et al., 2023). These cations may further stabilize the lattice, similar to other S-layers where cations were found to be essential for lattice formation (Baranova et al., 2012; Herdman et al., 2022; Sogues et al., 2023; von Kügelgen et al., 2021). To probe this further, we incubated purified PS2 S-layers with either 10 mM EDTA or 10 mM EGTA and examined the effect on the treated S-layers. Following the chemical treatment, S-layer lattices were still intact, with no observable differences under both conditions (Fig. S4I). This suggests that either these putative cations do not play a major role in stabilizing the PS2 S-layer or they are not accessible for chelation by EDTA or EGTA under the chosen experimental conditions”

and

“Figure S4. Features of the PS2 S-layer lattice… D, E, F) __Putative densities possibly corresponding to cations and G) SDS detergent molecules are shown, with the respective sigma values of the maps shown in the bottom right. The potential densities are denoted with an “*”, and the surrounding residues also labelled. H) __The coiled-coil segment (residues 405-445) is shown in side view (left) and bottom view (right). __I) __Purified PS2 S-layer sheets incubated with EDTA (middle) and EGTA (right) show no discernible differences from native S-layers (left).”

• Regarding the potential SDS density. Looking at Figure 3G, it is not clear how the morphology of the density shown (with a T-shape) would fit a linear molecule of SDS (could be the view selected?). Have the authors performed any attempt of modelling the SDS molecule to assess this and/or those PS2 residues contributing to stabilize the SDS? Is this density consistently observed across the other interfaces of the hexamer? That would support their hypothesis.

This density is observed in the other interfaces of the hexamer as well, and it is also seen in maps that were produced from refinements without any symmetry applied, i.e. when the processing was performed in C1. Nevertheless, taking on board the criticism about the ambiguity of both the putative SDS and calcium densities, combined with the inconclusive results of our EDTA/EGTA treatment, we have changed the panel titles of Fig. S4D-G to “Unknown density 1-4” in revised the manuscript (see above), making sure to not claim more than what is revealed by the density.

Reviewer #2 (Significance (Required)):

As structural biologist I consider that this study constitutes an important advance in our understanding of the complex architecture and function of the cell-envelop of C. glutamicum. Knowledge that can help to better understand this intricate envelop present in other Mycobacteriaceae relatives, which include important human pathogen such as Mycobacterium tuberculosis or Corynebacterium diphtheriae. This study is most relevant for the scientific community investigating on the bacterial cell envelop (structure, evolution and function) as well as in host-pathogen interactions. Moreover, the cell envelop constitutes a target for bacteriostatics and thus, this study may be relevant for the scientific community working on antimicrobial development.

Thank you.

__ __

Reviewer #3 (Evidence, reproducibility and clarity (Required)):

Summary: In the manuscript from Isbilir et al, the authors investigate the cell envelope of Corynebacterium glutamicum, a bacterium extensively used in biotechnological applications, using state-of-the-art cryo-electron microscopy methodologies as well as bioinformatics. They convincingly demonstrate that the C. glutamicum S-layer consists of hexagonal PS2 arrays and provide the underlying structural basis of this intriguing assembly. Bioinformatic analysis further revealed conserved and divergent elements of PS2 across Corynebacteria.

Major comments:

• My main point of criticism relates to the first part of the results, in which the authors attempt to characterize the cell envelope using cryo-electron tomography. From my own experience, plunge-freezing bacterial lawns often results in bad ice quality (crystalline ice) between the bacterial cells. This seems to be also the case here, looking at the 2D images in Fig. S1D revealing clear Bragg reflections. While often not a problem if interested in intracellular features, the authors are drawing conclusions on the cell envelope, which is in direct contact with these ice crystals, known to be destructive for ultrastructural features. For example, this could be the reason for the "wavy" mycomembrane in Fig. 1A and 1B as well as Fig. S1C. On top, it also might affect their observations of interrupted and discontinuous mycomembranes covered by an S-layer in Fig. 1D. The authors should discuss this limitation, and I would highly recommend rephrasing their conclusions made from this data more carefully.

We would like to thank the reviewer for their constructive criticism. We agree that it is difficult to vitrify a lawn of bacteria without formation of crystalline ice in all areas of the specimen. In our lamellae, we have primarily vitreous ice (see Fig. S1B, lower right panel for example) but the reviewer has correctly pointed out observed crystalline ice in some areas on the edges of the lamellae. As suggested, we included the following text in the legend to Fig. S1B to warn the readers about this potential shortcoming.

Line 562: “After milling, lamellae with a 150-200 nm thickness were retained for cryo-ET investigations. Each lamella contained multiple cells suitable for imaging. Although vitreous ice was observed in most lamellae, the edges of some lamellae showed signs of crystalline ice formation…”

The reviewer’s comment about the MM perturbations is well taken, this was also raised by reviewer 1. Although we attempted to quantify this effect by various image analysis tools, in the end we feel that it is not possible to make clear-cut conclusions about the MM-waviness based on our data. We have therefore toned down our interpretations about the “wavy” nature of the MM in the manuscript text (see also our response to reviewer 1 above).

Line 151: “Although we cannot be certain given the existing data, we suppose that this perturbation of the MM directly beneath the patchy S-layer could arise due to the interaction of the S-layer anchoring domain with the MM, which has been predicted to be present in the coiled coil part of the PS2 protein forming the S-layer using bioinformatics (Johnston et al., 2024).”

• The single-particle cryoEM data and the bioinformatic analysis are very well presented, analyzed in much detail, and convincing. While the authors state that the S-layer most probably does not serve to protect the cells from invading molecules or phages, additional experiments to figure out the function of the S-layer would be desirable. However, this might be beyond the scope of this paper but the authors should at least include a clearer discussion about potential function(s).

As suggested by the reviewer, we have extended the discussion about the potential function of the PS2 S-layer in C. glutamicum.

Line 465: “We also observed that S-layer coverage appeared to increase when C. glutamicum cells were grown on solid media (Fig. S2A-B). This suggests that the S-layer could be useful for the bacteria to grow in in a colony or in a surface-attached biofilm community, as shown for other bacteria including Clostridium difficile and Tannerella forsythia (Ðapa et al., 2013; Honma et al., 2007; Wong et al., 2023).”

and

Line 474: “…Slightly at odds with the large pores, it has been shown that the presence of the PS2 S-layer renders cells more resistant towards lysozyme (Sogues et al., 2024; Theresia et al., 2018). Although lysozyme is much smaller than the pore sizes, it is possible that the S-layer might biochemically sequester such undesirable molecules.”

• The authors speculate about cations stabilizing the S-layer. To provide further evidence, an optional but straightforward experiment would be to treat the purified S-layer with EDTA and subsequently analyze it with negative stain EM or cryoEM.

As suggested, we incubated the purified PS2 S-layer with 10 mM EDTA or 10 mM EGTA and imaged the resulting specimens with cryoEM. We found intact S-layers in these treated samples, therefore, we have concluded that either cations do not play a role in stabilizing this S-layer or they are not accessible for chelation by EDTA or EGTA -

Line 246: “To probe this further, we incubated purified PS2 S-layers with either 10 mM EDTA or 10 mM EGTA and examined the effect on the treated S-layers. Following the chemical treatment, S-layer lattices were still intact, with no observable differences under both conditions (Fig. S4I). This suggests that either these putative cations do not play a major role in stabilizing the PS2 S-layer or they are not accessible for chelation by EDTA or EGTA under the chosen experimental conditions.”

and

Figure S4. Cryo-EM of C. glutamicum cells. … I) Purified PS2 S-layer sheets incubated with EDTA (middle) and EGTA (right) show no discernible differences from native S-layers (left).

• The anchoring of the S-layer to the characteristic mycomembrane is only discussed very briefly. As this is a unique feature, it would be of high interest to understand how the anchoring is different from other S-layer carrying Gram-positive/negative bacteria.

We agree with the reviewer and have extended our discussion of this unique feature of the PS2 S-layer.

Line 359: “…the length of the coiled-coil stalk and the MM-binding segment is highly conserved among PS2 homologs across species (Figs S5-S6). This is in line with the fact that the underlying cell envelope architecture, including the MM, is preserved among different Corynebacterium species, necessitating the conservation of the MM anchoring segments in PS2. The MM-binding segment is predicted by AlphaFold2 models to comprise an N-terminal hydrophobic α-helix and a short C-terminal amphipathic α-helix; however, in the MM, these may function as a single continuous helix. The MM-binding segment of PS2 homologs in Corynebacterium is consistently approximately 25 amino acid residues long, corresponding to a ~3.75 nm α-helix—sufficiently long to nearly traverse the 4–5 nm thickness of the MM. Notably, this segment includes the last residue of PS2, a phenylalanine (F), which is remarkably conserved across all PS2 homologs (Figs S5-S6). While the functional significance of this invariant phenylalanine residue remains unclear, the conservation of the preceding residues, particularly the penultimate residue, which is typically either a proline (P) or lysine (K), suggests a potential functional role. It is plausible that these terminal residues collectively contribute to the sorting, export, and insertion of PS2 into the MM or help ensure its stable anchoring within the lipid-rich MM.”

and

Line 444: “The PS2 S-layer protein has a distinctive mode of attachment to the prokaryotic cell envelope. In most archaea, S-layers are directly attached to the cytoplasmic membrane (Bharat et al., 2021), either through lipid modification of the SLP (von Kügelgen et al., 2021) or through the action of a secondary protein (von Kügelgen et al., 2024). In Gram-negative bacteria such as C. crescentus, S-layers are non-covalently attached to the O-antigen of lipopolysaccharide layer covering the outer membrane (von Kügelgen et al., 2020). In turn, in Gram-positive bacterial S-layers are non-covalently anchored via SLH domains to the PG-linked secondary cell wall polymers (Blackler et al., 2018). In other diderm bacteria that are positive for Gram-staining such as Deinococcus radiodurans, the SLP HPI (Bharat et al., 2023) is lipidated at its N-terminus (von Kügelgen et al., 2023), allowing the protein to interact with the cell membrane. In the case of C. glutamicum, the attachment of the PS2 S-layer is achieved through the insertion of the C-terminal hydrophobic helix into the MM, which is a distinctive feature for bacterial S-layers that have been studied in detail using structural biology.”

• Remove the word "accurately" in the second sentence of the second paragraph in the abstract.

Changed as requested.

Line 28: “Our cellular imaging allowed us to map the different components of the cell envelope onto the tomographic density.”

• Remove the word "strong" in the last sentence of the abstract.

Done.

Line 41: “This study, therefore, provides an experimental framework for understanding cell envelopes that contain mycolic acids.”

• As this is a back-to-back submission, the manuscript from Sogues et al. should be cited.

Done, as requested.

Line 191: “Purified S-layers were deposited on cryo-EM grids and vitrified using methods previously described for other S-layers (von Kügelgen et al., 2023, 2024), and specifically for the C. glutamicum S-layer concurrently with this study (Johnston et al., 2024; Sogues et al., 2024).”

and

Line 474: “…Slightly at odds with the large pores, it has been shown that the presence of the PS2 S-layer renders cells more resistant towards lysozyme (Sogues et al., 2024; Theresia et al., 2018). Although lysozyme is much smaller than the pore sizes, it is possible that the S-layer might biochemically sequester such undesirable molecules.”

Minor comments:

• Line numbers are missing, making the manuscript more complicated to review.

Sorry about that, the updated version of the manuscript has line numbers included.

• In the abstract, in the last paragraph of the introduction, and in the first sentence of the discussion, the authors use the term "high-resolution" in conjunction with their cryo-electron tomography imaging. This might be correct if you compare the data to light microscopy or conventional EM imaging. However, given the fact that the authors also used single-particle cryoEM, their cryoET data cannot be called "high-resolution," and they should remove this term as used here.

We agree with the reviewer and change the text accordingly:

Line 28: “Our cellular imaging allowed us to map the different components of the cell envelope onto the tomographic density.”

and

Line 39: “Our structural and cellular data collectively provide a topography of the unusual C. glutamicum cell surface, features of which are shared by many pathogenic and microbiome-associated bacteria, as well as by several industrially significant bacterial species.”

and

Line 102: “Building on these foundational studies, we have used C. glutamicum as a model for MM-containing organisms to perform characterisation of this unusual cell envelope.”

and

Line 110: “By combining our S-layer structure with cryo-ET of the cell envelope and bioinformatics analyses, we provide further clues regarding the MM-anchoring mechanisms of the S-layer and offer insights into its conservation and evolution in corynebacteria.”

and

Line 124: “To overcome this limitation, we employed FIB milling to create thin sections of the cells, which allowed us to obtain images with enhanced contrast of the cell envelope.”

and

Line 401: “In this study, we visualized the C. glutamicum cell envelope by imaging FIB-milled cells using...”

Reviewer #3 (Significance (Required)):

The single-particle cryoEM and bioinformatics analysis are convincing, but this manuscript resides at a rather descriptive level on the S-layer of C. glutamicum and some major comments should be addressed.

The findings in this manuscript are exciting for a specialized audience interested in bacterial cell surfaces/surface appendages and S-layers. On top, as C. glutamicum is widely used in biotechnological applications, the results have clear significance within this field.

Contrary to what the authors claimed, the general insights gained on cell envelopes containing mycolic acids are limited. Only very few insights reported here will advance our understanding of the cell envelope of important human pathogens such as Mycobacterium tuberculosis, as this manuscript focuses on the S-layer, which is absent from these strains.

Thank you for your comments, we have reworded the discussion section with more cautionary statements to present a balanced picture to readers of this manuscript.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1:

Reviewer #1 was very appreciative of our results and commented “This is a novel result in ferredoxin and a significant contribution to the field”. We are very honored and pleased.

Reviewer #2:

(1) Changing the nomenclature of the models investigated to include the oxidation state being discussed. As they are now (CM, CMNA, etc), multiple re-reads were required to ascertain which redox state was being discussed for a particular model in a given section of the text. Appending "Ox" or "Red" for oxidized or reduced would be sufficient. 

As you indicated there are several nomenclatures to distinguish the model systems in the text. On the other hand, the main issue discussed in the text is the ionization potential (IP), which is calculated by the difference in energies between oxidized and reduced states for each model. In other words, a discussion of the IP value on each model includes both the “Ox” and “Red” energies. In order to clarify the relationship between the nomenclature of models and redox states, we added sentences below.

“Note that the IP value is obtained for each model by calculating both the Ox and Red state energies of the model.” (lines 195-196).

On the other hand, we must specify the charge state when the geometry optimization is performed for CM and CMH models. Therefore, we revised the sentence as follows.

“The decrease in |IP| value indicates that the relative stability of the Red state is suppressed compared with the CMH but is significantly larger than the CM, suggesting the importance of the protonation of Asp64 (Fig. S2B). 

To consider the effect of the structural change caused by the redox on the IP, geometrical optimization of the 4Fe-4S core was performed for the CM (Red) and CMH (Red) models using the same level of theory to the single-point calculations. The optimized Cartesian coordinates are summarized in Table S3. As illustrated in Fig. S2A, the IP values of CM and CMH change from –3.27 to –2.38 eV (|DIP| = 0.89 eV), and from –1.06 to –0.19 eV (|DIP| = 0.87 eV), respectively, before and after the geometrical optimization.” (lines 224-232)

(2) In addition to the very thorough DFT investigation of the different spin and charge combinations, did the authors try a broken-symmetry calculation to obtain the ground state description of the FeS cluster? Given the ubiquity of this approach in other FeS cluster studies, it was surprising that this approach was not taken here. Granted, the DFT investigation of each possible combination is sufficiently thorough and need not be redone. 

Thank you for your comments. A term “spin-unrestricted method”, which is used in the manuscript in the text is synonym of “broken-symmetry method”. In order to emphasize this, we revised the manuscript as follows. 

“All calculations were performed by using the spin-unrestricted (broken-symmetry) hybrid DFT method with the B3LYP functional set. As the basis set, 6-31G* and 6-31+G* were used for [Fe, C, N, O, H] and [S] atoms, respectively, for the IP calculations.” (Line 451)

(3) Line 161 "an" to "a" 

We corrected the mistake. Thank you so much. (Line 161)

(4) Figure 4A seems a bit odd. Why do the traces eclipse the y-axis? And the traces between 330 and 370 nm are much noisier and appear thicker than the rest of the plot. Is this an issue with the monochromator grating used in wavelength selection? Reducing the thickness of the individual traces may help the data presentation in this figure. Also, the arrows on the plot have an opaque white background. Can this be removed so that the arrows do not eclipse the traces in the plot? 

The spectrum in the Fig.4A seemed to be odd. The spectral figure has been revised to improve its appearance. (We have also corrected E53A in Figure 5B.) This reviewer also pointed out that “the traces between 330 and 370 nm are much noisier”. We are struggling with the noise caused by the grating (or the motor malfunction) of the monochromator as you pointed out. Once the monochromator is repaired and a smooth spectrum is obtained, we will upload further revisions.

(5) Figure S9 is a very nice schematic illustrating the general findings of the study. Can this be moved to the main text?

Thank you for your helpful comment. Accordingly, the Fig.9S and its legend are moved to the main text. (Lines 675-680)

Ở đây, tác giả đã sử dụng dấu phẩy giữa câu bao gồm cả dấu chấm than ở cuối câu để nhấn mạnh lên cụm từ "đất đai!" như thể là một lời kêu gọi, thúc đẩy những nguyền tự nhiên.

"Điệu múa cổ" tượng trưng cho những thời vui vẻ của các lễ hội dân gian của Việt Nam. Nhưng tác giả đã miêu tả điệu múa với tính từ "chậm buồn" cộng với biện pháp tu từ "như đói" nhằm nhấn mạnh lên sự khăn khổ của người dân Việt Nam ngay cả ở trong những thời đáng nhẽ vui tươi.

Ngay đây, nhà thơ đã một lần nữa sử dụng điệp từ đói để nhấn mạnh lên sự khốn khổ của nhân dân. Hơn nữa, việc sử dụng dấu ba chấm ở cuối bài thơ để lại một cảm xúc kéo dài lên người đọc.

Số lượng chỉ dẫn được tạo ra ở mỗi bước: Việc tính toán một mini-batch của đạo hàm làm giảm phương sai của việc xuống đồi đạo hàm ngẫu nhiên. Tương tự như vậy, việc tạo ra nhiều chỉ dẫn dúng làm tăng khả năng tối ưu của LLM. Mặt khác

Cách thiết kế meta-prompt: - Thứ tự của các chỉ dẫn trước đó: so sánh các cài đặt sau với nhau: + Từ thấp nhất đến cao nhất (mặc định) + Từ cao nhất đến thấp nhất + Ngẫu nhiên Hình 7 cho thấy cài đặt mặc định có kết quả tốt hơn và hội tụ nhanh hơn. Gỉa thiết được đưa ra cho hiện tượng này là do đầu ra của optimizer LLM bị ảnh hưởng bởi các chỉ dẫn trước đó mà ở gần meta-prompt hơn. Điều này phù hợp với thiên lệch ở gần (recency bias) cho rằng LLM có xu hướng tạo ra các token tương đồng với phần cuối của prompt.

• Tác động của điểm chỉ dẫn: Đối với việc thể hiện điểm accuracy, 3 cài đặt được so sánh:
• Làm tròn điểm thành số tự nhiên
• Gom nhóm các điểm thành 20 nhóm.

• Không ghi điểm, chỉ ghi các chỉ dẫn theo thứ tự giảm dần của điểm. Hình 7c và 7d cho thấy các điểm accuracy hỗ trợ optimizer LLM trong việc hiểu về chất lượng của các chỉ dẫn trước, từ đó LLM có thể đưa ra các chỉ dẫn tốt hơn, tương đồng với các chỉ dẫn tốt nhất

• Tác động của các ví dụ: 3 lựa chọn được so sánh:

• Ghi 3 ví dụ từ bái toán
• Ghi 10 ví dụ từ bài toán
• Không có Hình 7e và 7F cho thấy việc thể hiện các ví dụ trong meta-prompt là vô cùng quan trọng, bởi nó cung cấp thông tin về bài toán và giúp optimizer LLM có thể tạo các chỉ dẫn tốt hơn. Tuy nhiên, việc có nhiều hơn các ví dụ không phải lúc nào cũng dẫn đến việc cải thiện kết quả. Hơn nữa, việc có nhiều ví dụ còn dẫn đến việc meta-prompt bị dài hơn với phần ví dụ dài hơn các phần khác, dẫn đến việc LLM dễ bị xao nhãng mà không chú ý các phần quan trọng khác.

Các chỉ dẫn tương đồng về mặt ngữ cảnh có thể đạt được các kết quả có sự khác biệt lớn: Thách thức của bài toán tối ưu prompt là sự nhạy cảm về hiệu suất của mô hình đối với các thay đổi nhỏ trong chỉ dẫn. Ví dụ: với scorer là PaLM 2-L trên bộ test của GSM8K, chỉ dẫn "Let's think step-by-step" đạt điểm accuracy 71.8, "Let's solve the problem together" có điểm accuracy 60.5, trong khi điểm accuracy của prompt "Let's work together to solve this problem step-by-step" chỉ là 49.4, mặc dù nó là sự kết hợp ngữ nghĩa của 2 prompt trước đó. Đặc điểm này tăng cả phương sai giữa các chỉ dẫn một bước và các giao động trong quá trình tối ưu hóa, từ đó thúc đẩy việc tạo sinh ra nhiều chỉ dẫn ở mỗi bước để làm tăng tính ổn định trong tối ưu

Tính chuyển hoa của các chỉ dẫn được tìm ra: Việc có thể áp dụng các chỉ dẫn được tìm ra sang các bộ dữ liệu khác có cùng lĩnh vực được khám phá. Các chỉ dẫn tốt nhất ở bộ GSM8K sẽ được dùng cho 2 bộ dữ liệu toán khá là Multi-Arith và AQuA.

Tương tự như ở GSM8K, có thể thấy chiều hướng đi lên trong quá trình tối ưu hóa ở hầu hết tất cả các bài toán BBH Một số ví dụ về chỉ dẫn được sinh ra trong quá trình tối ưu. Ở bài toán ruin_names, bắt đầu với chỉ dẫn rỗng (điểm accuracy 64), với text-bison làm scorer và PaLM 2-L-IT làm optimizer, các chỉ dẫn sau đây được sinh ra: - ........ ở step 1 với điểm accuracy 72 - ........ ở step 18 với điểm accuracy 80.0 - ......... ở step 38 có điểm accuracy 82.0 Mặc dù các chỉ dẫn trên đều gần như tương đồng về mặt ngữ cảnh, việc cải biên lại được thực hiện bởi LLM cho phép điểm accuracy được gia tăng đáng kể.

Bảng 5 thể hiện kết quả ở mỗi bài toán con ở tất cả 23 bài toán con của OPRO so với chỉ dẫn "Let's think step by step" và chỉ dẫn rỗng. Kết quả cho thất OPRO tốt hơn nhiều ở hầu hết tất cả các bài toán:

Dù cài đặt mặc định là chạy OPRO với 200 bước để tối ưu prompt, chúng ta cần ít bước hơn rất nhiều để tìm ra các chỉ dẫn vượt trội. Một ví dụ là ở hình 1a, ở bước 6 điểm accuracy là 78.2 với prompt là "Let's do the math!", gần như tương đồng với prompt "Take a deep breath and work on this problem step-by-step" ở bước 107 với điểm accuracy 80.2, ở điểm mà tại đó việc tối ưu vấn đang có dấu hiệu tăng. Điều đó là bởi bước nhảy lớn trong việc tối ưu không phải lúc nào cũng ứng với một chỉ dẫn tốt hơn nhiều được sinh ra mà thay vào đó, nó có thể là do sự cải tiến lớn về chất lượng của tất cả 8 chỉ dẫn được tạo ở bước đó.

Cụ thể, sau khi 1 chỉ dẫn tốt hơn nhiều được tạo ra, meta-prompt sẽ dần dần từ bỏ các chỉ dẫn tồi hơn ở các bước sau bằng cách tạo ra các chỉ dẫn tương tự với chỉ dẫn tốt hơn kia. Các chỉ dẫn tốt nhất được giữ lại ở meta-prompt sẽ dần dần được cải tiến theo cách này. Ở điểm mà khi đó meta-prompt chỉ đưa ra các chỉ dẫn tốt hơn, bước nhảy vọt mới xảy ra.

Biểu đồ tối ưu còn cho thấy sự giảm trong phương sai giữa điểm accuracy của các chỉ dẫn được sinh ở mỗi bước. từ đó cho thấy LLM tạo sinh ra các chỉ dẫn tốt hơn về mặt phân phối xuyên suốt quá trình tối ưu.

Hạn chế: Cần lưu ý rằng OPRO được thiết kế không phải để đạt kết quả cao hơn so với các thuật toán tối ưu SOTA hay các thuật toán chuyên biệt cho các bài toán tối ưu kinh điển như TSP. Thay vào đó, mục tiêu của OPRO là chứng minh LLM có thể tối ưu hóa nhiều bài toán khác nhau chỉ thông qua việc prompting và đạt được kết quả tối ưu toàn cục ở các bài toán có quy mô nhỏ. Đánh giá kết quả cũng cho thấy một số hạn chế của OPRO trong việc tối ưu toán học. Cụ thể, giới hạn độ dài của cửa số ngữ cảnh LLM khiến việc mô tả các bài toán tối ưu có quy mô lớn bằng ngôn ngữ tự nhiên trở nên khó khăn (ví dụ: hồi quy tuyến tính trên nhiều chiều và TSP với nhiều node). Ngoài ra, bối cảnh tối ưu của một số bài toán cũng không ổn định để LLM có thể đưa ra một hướng giải quyết hội tụ. khiến cho việc tối ưu bị chững lại

Hiệu của của OPRO giảm đi đáng kể ở các bài toán có kích thước lớn hơn. Với n = 10, tất cả LLM đêì tìm được giải pháp tối ưu với mọi bài toán. Khi bài toán dần lớn hơn, khoảng cách tối ưu của OPRO so với giải pháp ground-truth tăng lên rất nhanh, và FI bắt đầu vượt trội so với LLM.

Với mỗi số lượng n điểm, 5 tập điểm khác nhau sẽ được tạo ngẫu nhiên. Ngoài việc đánh giá dựa trên khoảng cách tối ưu, bài báo còn đánh giá dựa trên số lượng bước tối ưu cần thực hiện để đạt được tối ưu toàn cục. Nhận xét: - gpt-4 tốt hơn nhiều so với 2 mô hình còn lại ở tất cả các kích thước bài toán. Cụ thể, với các bài toán có kích thước nhỏ, gpt-4 đạt tối ưu toàn cục nhanh gấp 4 lần so với các mô hình khác.

• Nearest neighbor: Bắt đầu từ 1 điểm, giải pháp sẽ được xây dựng bằng hàm heuristic lận cận gần nhất: ở mỗi bước, giữa các điểm còn lại chưa được thêm vào, NN sẽ chọn điểm có khoảng cách gần nhất đến điểm cuối của giải pháp hiện có
• Farthest Insertion: Một điểm không tốt của NN là nó không cân nhắc đến khoảng cách giữa điểm bắt đầu và điểm kết thúc khi xây dựng phương pháp. Để giải quyết vấn đề này, FI hướng đến mục tiêu tối ưu chi phí của việc gán các nốt mới vào giải pháp hiện có ở mỗi bước: Xác định chi phí thấp nhất của việc gán một nốt mới k sao cho:

Cả w và b đều bắt đầu từ 5 vị trí xuất phát ngẫu nhiên trong khoảng [10, 20]. Temperature = 1.0 được sử dụng ở tất cả các model. Mỗi cài đặt được chạy 5 lần. Các điểm xuất phát là giống nhau ở tất cả các optimizer LLM nhưng khác biệt giữa 5 lần chạy. Các điểm xuất phát này được chia ra làm 3 nhóm: trong vùng xuất phát, ngoài và gần vùng xuất phát, ngoài và xa vùng xuất phát.

3 phần chính của meta-prompt, được sử dụng để tối ưu hóa prompt: - Các ví dụ trong tối ưu hóa: Mô tả bài toán bao gồm 1 vài ví dụ được lấy từ tập huấn luyện để thể hiện bài toán cho các chỉ dẫn được tạo sinh. Ví dụ, từ 1 cặp đầu vào-đầu ra, ta có thể suy ra đó là một bài toán tính toán. Cặp đầu vào-đầu ra cũng thể hiên ví trí mà chỉ dẫn tạo sinh được thêm vào, và điều này rất quan trọng cho optimizer LLM để tạo sinh các chỉ dẫn với phong cách tượng tự. Ở mỗi bước tối ưu, một vài dữ liệu huấn luyện được thêm vào meta-prompt bằng cách lấy ngẫu nhiên tập huấn luyện hoặc chọn ra các mẫu mà các chỉ dẫn trước đó đạt điểm thấp. - Lân cận trong tối ưu: Lân cận trong tối ưu bao gồm các chỉ dẫn được tạo sinh từ các bước chỉ dẫn trước, cùng với điểm của chúng. Các chỉ dẫn cũ cùng với điểm được sắp xếp theo thứ tự giảm dần. Điểm đánh giá được sử dụng là điểm accuracy trên tập train. Chỉ có các chỉ dẫn với điểm cao nhất được giữ lại và sử dụng trong meta-prompt dựa trên sự cân nhấc giới hạn độ dài ngữ cảnh của LLM. - Meta-instruction: Đây là chỉ dẫn dùng cho optimizer LLM, có vai trò giải thích mục tiêu tối ưu và cách sử dụng các thông tin được cung cấp. Meta-instruction có thể cũng cụ thể hóa bố cục của chỉ dẫn mong muốn để có thể phân tích ở các bước sau,

meta-prompt được thực hiện 8 lần để sinh ra tất cả 8 cặp (w, b) mới ở mỗi bước để cải thiện tính ổn định trong tối ưu, sau đó các cặp này sẽ được đánh giá giá trị mục tiêu và thêm vào meta-prompt. Việc tối ưu được thực hiện kiểu "hộp đen": Các mẫu phân tích sẽ không xuất hiện trong văn bản meta-prompt. Đó là bởi LLM có thể thường tính toán giải pháp trực tiếp từ mẫu phân tích.

Ở mỗi bước tối ưu, instruction-tuned LLM được chỉ dẫn với meta-prompt bao gồm 20 cặp (w,b) tốt nhất và giá trị mục tiêu (MSE loss) tương ứng với từng cặp. Meta-prompt sau đó yêu cầu 1 cặp (w,b) có thể làm giảm hơn nữa giá trị của hàm đánh giá.

Ở bước tạo sinh giải pháp, LLM tạo các giải pháp mới với meta-prompt là đầu vào. Có một số thách thức trong việc tối ưu được giải quyết ở bước này: - Độ ổn định trong tối ưu: Trong quá trình tối ưu, không phái tất cả các giải pháp đều đạt được kết quả cao và luôn có kết quả tốt hơn giải pháp trước. Do sự nhạy cảm của in-context learning đối với prompt, đầu ra của LLM có thể bị ảnh hưởng đáng kể bởi các giải pháp có kết quả thấp có trong tối ưu lân cận nằm trong đầu vào, đặc biệt là ở lúc đầu khi tập giải pháp chưa đủ lớn. Điều này đôi khi dẫn đến sự không ổn định trong tối ưu là phương sai lớn. Để cải thiện tính ổn định, LLM được chỉ dẫn để tạo sinh nhiều giải pháp khác nhau ở mỗi bước tối ưu, cho phép LLM có thể đổng thời khám phá nhiều khả năng và phát hiện nhanh chóng các hướng đi tiềm năng để tiếp tục đào sâu.

• Đánh đổi exploration-exploitation: chỉ số temperature của LLM được tinh chỉnh để cân bằng giữa việc exploration và exploitation. Giá trị temperature thấp khuyến khích LLM đào sâu xung quanh các giải pháp trước đó và có ít sự thích nghi, trong khi điểm temperature cao cho phép LLM khám phá các giải pháp có tính khác biệt cao.

Kiến trúc tổng thể của OPRO. Ở mỗi bước tối ưu, LLM sẽ đưa ra các giải pháp tiềm năng cho bài toán tối ưu dựa trên mô tả bài toán tối ưu hóa và các prompt đã được đánh giá từ trước trong meta-prompt. Sau đó các giải pháp mới sẽ được đánh giá và đưa vào meta-prompt cho quá trình tối ưu kế tiếp. Qúa trình tối ưu kết thúc khi LLM không thể đưa ra các giải pháp mới với điểm tối ưu cao hơn hoặc số bước tối ưu chạm ngưỡng.

Bài báo đề xuất phương pháp OPRO, một phương pháp đơn giản và hiệu quả tận dụng LLM làm trình tối ưu, trong đó bài toán tối ưu được mô tả dưới dạng ngôn ngữ tự nhiên. Ở mỗi bước tối ưu, LLM sẽ tạo ra các giải pháp mới từ prompt chứa các giải pháp được tạo trước đó với các giá trị của chúng, sau đó các giải pháp mới sẽ được đánh giá và thêm vào prompt cho bước tối ưu tiếp theo.

De acordo com o modelo de Gilly Salmon, as e-atividades desempenham um papel fundamental no ensino digital, promovendo uma aprendizagem dinâmica, interativa e inclusiva, facilitando a construção de comunidades de aprendizagem e cumprimento de objetivos pedagógicos. As e-atividades para serem eficazes devem ser desenhadas com objetivos claros, e diversificadas de acordo com competências e necessidades dos estudantes, promovendo a autonomia com recurso às ferramentas digitais. O feedback construtivo é essencial para motivar e orientar os estudantes no processo de aprendizagem. A seleção e o design cuidadoso das e-atividades serão uma estratégia fundamental para que o ensino online seja uma experiência ativa, colaborativa e centrada no estudante.

De acordo com o modelo de Gilly Salmon, as e-atividades desempenham um papel fundamental no ensino digital, promovendo uma aprendizagem dinâmica, interativa e inclusiva, facilitando a construção de comunidades de aprendizagem e cumprimento de objetivos pedagógicos. As e-atividades para serem eficazes devem ser desenhadas com objetivos claros, e diversificadas de acordo com competências e necessidades dos estudantes, promovendo a autonomia com recurso às ferramentas digitais. O feedback construtivo é essencial para motivar e orientar os estudantes no processo de aprendizagem. A seleção e o design cuidadoso das e-atividades serão uma estratégia fundamental para que o ensino online seja uma experiência ativa, colaborativa e centrada no estudante.

Penso que um dos principais desafios terá precisamente a ver com os interesses dos alunos. É extremamente difícil conseguir encontrar uma forma de relacionar os objetivos de aprendizagem aos interesses dos alunos, que muitas vezes parecem não ter qualquer interesse nas diferentes matérias. Para além disso, o nível de competências dos alunos no que se refere às tecnologias surpreendentemente nem sempre é elevado.

Os dois modelos parecem-me semelhantes. A salientar apenas que no modelo de Astudillo há um claro destaque para as ações e o tempo do docente que não existe no modelo de Almenara.

Do ponto de vista teórico, uma e-atividade deve obedecer a princípios que estão relacionados com os objetivos da e-aprendizagem e que geralmente seguem o proposto no modelo de Gilly Salmon (conforme adaptação de Maria de Fátima Goulão), com os cinco patamares: acesso e motivação; socialização online; informação online; construção do conhecimento e desenvolvimento. Mas para além destes aspetos, a e-atividade no contexto da aprendizagem digital, deve respeitar outros aspetos relacionados com a sua duração, os objetivos de aprendizagem a atingir, os recursos de aprendizagem postos à disposição do formando e que podem incluir vários ambientes digitais como vídeos, bases de dados, artigos e livros, fóruns e outros. Deve igualmente, desde o início, tornar bem explícitos os métodos de avaliação e mostrar a importância da atividade no objetivo de aprendizagem proposto. Para além destes aspetos, a e-atividade deve ser vista como uma mensagem no processo de interação em que o aluno participa no ambiente digital de aprendizagem e por isso não devem ser esquecidos os aspetos relativos à uma boa comunicação, como a clareza e a necessidade de vencer barreiras à comunicação com origem em aspetos culturais, que incluem a língua, o sistema de valores, entre outros. Fundamental para o sucesso da e-atividade parece ser o feedback do professor quer durante quer na fase de avaliação, sendo reconhecido que o feedback na fase de avaliação constitui um reforço de motivação e consolidação da aprendizagem. Fausto Amaro

A taxonomia de Bloom deve nortear o desenho das nossas e-tarefas. Ao nível do Ensino Superior é importante atingir patamares superiores ao APLICAR, propondo e-atividades em que a Análise, a Avaliação e a Criatividade sejam incentivadas. No entanto, nalgumas áreas, como por exemplo a Anatomia há uma necessidade maior de trabalhar a memorização e a compreensão.

Sự biết ơn và lòng từ bi vô tận của cậu bé gặp phải tình huống trớ trêu—mặt trưởng thành của cậu bé va phải mặt trẻ con và làm cho cậu dễ bị tổn thương.

Cậu bé miêu tả hậu quả tâm lý nghiêm trọng từ những trận đánh "nhớ đời" ấy—việc cậu bé mất đi sự thích thú với việc mà cậu bé hay làm (trò chuyện tâm sự với cái cây) có thể báo hiệu là mất đi sự ngây thơ trẻ con của cậu bé, nhưng cũng có thể là sư trầm cảm.

"Một xu năm viên bi", "Một xu mười thẻ bài" cho thấy tính tháo vát và khả năng tự lập của cậu bé Zezé.

Ông Bồ không cần nhìn thấy Zz đã biết là cậu chỉ qua giọng nói cậu bé --> bộc lộ tình bạn gần gũi giữa 2 người

lần đầu tiên lời thoại của con quỷ xuất hiện. Dù chỉ là một bản ngã của Zezé, nhưng nó cho ta thấy khả năng quan sát tuyệt vời cùng bộ óc nhỏ tuổi nhưng đầy tinh ranh.

Con quỷ - Sự tinh nghịch của Zeze khi là một đứa trẻ

Cô Cecilia là nhân vật tạo ra tương phản đạo đức so với những thành viên gia đình, tuy trớ trêu ở chỗ cậu bé nói thật về cả "biết nhiều câu chửi tục hơn tất cả các bạn khác trong lớp" và "không đứa trẻ nào tinh quái như tôi".

"Ở trường, tôi là một thiên thần" ngụ ý/tương phản sắc nét với việc ở nhà cậu bé hai bị gọi là một con tiểu quỷ.

• "tấm khăn trải bàn bằng vải kẻ ca rô màu đỏ và những chiếc tách uống cà phê thứ thiệt" -> là lời khen cậu bé dành cho những đồ vật gia dụng mà đến cả nhà cậu cũng không có—tạo ra sự đối lập giữa ông Bồ và gia đình Zezé.

Zeze là một cậu bé ?thông minh, biết quan sát xung quanh để không phải gặp ông Bồ

info para ensayo

figure out whats not true make new systems that are more reflective across nation-states fill in info with empirical work

goods, businesses, people, moving w/o borders what most refer to as globalization

DOI: 10.1021/acs.est.1c08143

Resource: National High Magnetic Field Laboratory (RRID:SCR_010550)

Curator: @evieth

SciCrunch record: RRID:SCR_010550

What is this?

Derived from factor analysis of trait terms in language. Evolutionary basis: Traits linked to survival and reproductive success. Popular personality assessments include the NEO-PI-R and NEO-FFI.

• Argument: The author argues that some moral requirements, apprehended intuitively, cannot be dismissed as irrational because they are arational—they exist outside rational reasoning. o Arational – different from and potentially in opposition to what are rationally judged to be moral requirements but not dismissible as irrational because their value does not depend upon being reasoned at all (outside the realm of reason)

Those that believe that true moral dilemmas (where no ‘right’ answer exists) that cannot be avoided are valid (acknowledged). They acknowledge that individuals might feel like they cannot get it right (impossibly required), however they dismiss this as invalid and irrational. In their mind, anything that is not rightly rational can therefore be dismissed. o Suggesting that this group of individuals only hold reasoned judgements as rational and the only foundation for decision making. o Suggests that these people view moral dilemmas as emotional/ misguided perceptions rather than objective results

In the first couplet she poses a question and in the second she answers it herself. The exclamation point adds emphasis after an unstressed syllable and breaks the line. Both lines beginning with "now' convey her awareness and her hopelessness.

Varias de las características propuestas por Tsing (Citation2009) resuenan con el capitalismo de la cadena de suministro de la IA en la actualidad. Sin embargo, la principal diferencia es que las empresas capitalistas dentro de la economía política de la IA están acumulando más capital en 2024 que Wal-Mart o Nike en 2009. Por lo tanto, es relevante comprender mejor la línea de producción capitalista de la IA.

El capitalismo de la cadena de suministro ofrece un marco teórico para tener en cuenta la línea de producción de la IA y su infraestructura, desde las minas hasta los desechos electrónicos, y dar cuenta de las asimetrías geográficas y las luchas ambientales que podrían no ser evidentes.

Un examen más detallado del capitalismo de la cadena de suministro de la IA revela daños ambientales como las luchas por el agua, que no se han considerado anteriormente en la literatura sobre daños y resistencia algorítmica.

Este artículo muestra que las luchas controvertidas surgen al investigar puntos específicos en las cadenas de suministro de la IA.

El caso de Maconí muestra que, si bien la industria de los centros de datos está explotando los recursos hídricos para enfriar su infraestructura digital, las personas en áreas rurales e indígenas no tienen acceso al agua. Juan, el hombre de mediana edad citado al comienzo de este artículo, vive actualmente en Maconí y todavía camina al menos ocho horas para recolectar agua para su vida diaria.

Este artículo es un llamado a investigar el impacto infraestructural de la IA desde una perspectiva crítica y ambiental y abrir una crítica hacia la creciente industria de la IA para que podamos construir un mundo de muchos mundos donde quepamos todos (Blaser, Citation2018).

La inteligencia artificial (IA) está entretejida en una cadena de suministro de capital, materias primas y trabajo humano que ha sido descuidada en los debates críticos.

Dado el auge actual de la IA generativa, que se estima que impulsará la extracción de recursos naturales como minerales, combustibles fósiles o agua, es vital investigar toda su línea de producción desde una perspectiva infraestructural crítica.

Basándose en el capitalismo de la cadena de suministro, un concepto acuñado por Anna L. Tsing en 2009, este artículo contribuye a los estudios críticos de la IA al investigar la estructura de las cadenas de suministro de IA, teniendo en cuenta la industria minera, electrónica, digital y de desechos electrónicos.

Este artículo ilustra cómo el capitalismo de la cadena de suministro de la IA está precipitando asimetrías geográficas conectadas con luchas controvertidas en México al centrarse en un elemento clave de estas cadenas: los centros de datos.

En tiempos de emergencia climática, este artículo llama a reconsiderar los daños y la resistencia algorítmica mediante la investigación de toda la línea de producción capitalista de la industria de la IA desde una perspectiva crítica y ambiental.

Puntos de acción

Desarrollar protocolos claros que aseguren que las decisiones e intervenciones cumplan con los criterios de legitimidad, necesidad y proporcionalidad, a fin de garantizar la protección de los derechos y libertades de terceros cuando pueda haber conflictos de intereses entre las partes interesadas (lo que puede dar lugar a impactos desproporcionados en un grupo o grupos en comparación con otro grupo o grupos de personas).

Garantizar que existan marcos jurídicos suficientes (tanto nacionales como internacionales) para proteger y brindar reparación a las personas afectadas por la IA.

Permitir que las personas afectadas por sistemas de IA busquen soluciones sin temor a represalias.

Desarrollar estrategias para garantizar que el público en general sea consciente de los riesgos y oportunidades relacionados con la IA, y de los mecanismos disponibles para identificar cuándo el uso o la aplicación de la IA puede haber resultado en una violación de sus derechos.

Puntos de acción

Implementar medidas de codiseño que involucren a las comunidades marginadas y otros stakeholders relevantes a lo largo del ciclo de vida de la IA.

Involucrar a las comunidades marginadas en la identificación de problemas, la formulación de problemas, el diseño y la toma de decisiones en materia de gobernanza de la IA.

Integrar perspectivas diversas en el diseño y desarrollo de la IA para evitar sesgos sistémicos y resultados discriminatorios.

Asegúrese de que los procesos de información y consulta sean accesibles e inclusivos para los grupos marginados. Crear y distribuir materiales de fácil lectura con antelación para garantizar que las personas sin educación formal o conocimientos de inteligencia artificial puedan comprender los temas clave. Evitar la jerga técnica cuando sea suficiente con un lenguaje sencillo.

Incorporar principios de diseño inclusivos y transformadores y metodologías participativas en las estrategias nacionales o regionales de IA para garantizar que los sistemas de IA respeten la autonomía, la dignidad y los valores culturales de los grupos marginados.

Aplicar políticas de protección, incluidos mecanismos para denunciar casos de discriminación, situaciones de violencia y otras situaciones que dificulten la participación de las mujeres y otros grupos marginados en el lugar de trabajo en igualdad de condiciones con los demás. Garantizar el acceso a estos mecanismos para permitir la denuncia y la reparación de agravios.

Puntos de acción

**Mapear políticas y marcos normativos internacionales relevantes sobre derechos humanos, así como compromisos regionales o nacionales aplicables. **

**Mapear y evaluar si los tratados internacionales y leyes nacionales existentes son suficientes para proteger, promover y garantizar los derechos involucrados, revisando análisis legales disponibles para determinar la solidez de dichas protecciones. **

Considerar las características sociales, económicas, demográficas, políticas, históricas y culturales que puedan influir en el proceso, identificando las principales causas de exclusión de grupos marginados y cómo la IA puede amplificarlas.

In this scene Juliet is waiting news from the Nurse about her weading to Romeo, when the nurse arives she insinuates how out of breath she is, how ld she is and how she should not be having to go out like this anymore, and talks down on Juliets choice of marrying romeo, ultimatly delying the news of what will become Juliet and Romeos marrige. Until at the very end of the scene when the nurse finally gives Juliet the news and they part ways.

Author response:

The following is the authors’ response to the original reviews.

Reviewer #1 (Public Review):

Summary:

The pituitary gonadotropins, FSH and LH, are critical regulators of reproduction. In mammals, synthesis and secretion of FSH and LH by gonadotrope cells are controlled by the hypothalamic peptide, GnRH. As FSH and LH are made in the same cells in mammals, variation in the nature of GnRH secretion is thought to contribute to the differential regulation of the two hormones. In contrast, in fish, FSH and LH are produced in distinct gonadotrope populations and may be less (or differently) dependent on GnRH than in mammals. In the present manuscript, the authors endeavored to determine whether FSH may be independently controlled by a distinct peptide, cholecystokinin (CCK), in zebrafish.

Strengths:

The authors demonstrated that the CCK receptor is enriched in FSH-producing relative to LH-producing gonadotropes, and that genetic deletion of the receptor leads to dramatic decreases in gonadotropin production and gonadal development in zebrafish. Also, using innovative in vivo and ex vivo calcium imaging approaches, they show that LH- and FSH-producing gonadotropes preferentially respond to GnRH and CCK, respectively. Exogenous CCK also preferentially stimulated FSH secretion ex vivo and in vivo.

Weaknesses:

The concept that there may be a distinct FSH-releasing hormone (FSHRH) has been debated for decades. As the authors suggest that CCK is the long-sought FSHRH (at least in fish), they must provide data that convincingly leads to such a conclusion. In my estimation, they have not yet met this burden. In particular, they show that CCK is sufficient to activate FSH-producing cells, but have not yet demonstrated its necessity. Their one attempt to do so was using fish in which they inactivated the CCK receptor using CRISPR-Cas9. While this manipulation led to a reduction in FSH, LH was affected to a similar extent. As a result, they have not shown that CCK is a selective regulator of FSH.

Our conclusion regarding the necessity of CCK signaling for FSH secretion is based on the following evidence:

(1) CCK-like receptors are expressed in the pituitary gland predominantly on FSH cells.

(2) Application of CCK to pituitaries elicits FSH cell activation and to a much lesser degree activation of LH cells.  (calcium imaging assays)

(3) Application of CCK to pituitaries and by injections in-vivo significantly increased only FSH release.

(4) Mutating the FSH-specific CCK receptor in a different species of fish (medaka) also causes a complete shutdown of FSH production and phenocopies a fsh-mutant phenotype (Uehara, Nishiike et al. 2023).

Taken together, we believe that this data strongly supports the conclusion that CCK is necessary for FSH production and release from the fish pituitary. Admittedly, the overlapping effects of CCK on both FSH and LH cells in zebrafish (evident in both our calcium imaging experiments and especially in the KO phenotype) complicates the interpretation of the phenotype. We speculate that the effect of CCK on LH cells in zebrafish can be caused either by paracrine signaling within the gland or by the effects of CCK on GnRH neurons that were shown to express CCK receptors .

In the current version, we emphasize that CCK also induces LH secretion. Although it does not affect LH to the same extent as FSH, an overlap does exist. This is mentioned in the abstract and discussion.

Moreover, they do not yet demonstrate that the effects observed reflect the loss of the receptor's function in gonadotropes, as opposed to other cell types.

Although there is evidence for the expression of CCK receptor in other tissues, we do show a direct decrease of FSH and LH expression in the gonadotrophs of the pituitary of the mutant fish; taken together with its significant expression in FSH cells compared to the rest of the cells of the pituitary in the cell specific transcriptomic, it is the most reasonable explanation for the mutant phenotype.

Unfortunately, unlike in mice, technologies for conditional knockout of genes in specific cell types are not yet available for our model and cell types. Additional tissue distribution of the three receptors types of CCK was added in supplementary figure 1, from this tissue distribution it can be appreciated how in the pituitary only CCKBRA (our identified CCK receptor) is expressed, while in other tissues it is either not expressed or expressed with the additional CCK receptors that can compensate its activity.

It also is not clear whether the phenotypes of the fish reflect perturbations in pituitary development vs. a loss of CCK receptor function in the pituitary later in life. Ideally, the authors would attempt to block CCK signaling in adult fish that develop normally. For example, if CCK receptor antagonists are available, they could be used to treat fish and see whether and how this affects FSH vs. LH secretion.

While the observed gonadal phenotype of the KO (sex inversed fish) should have a developmental origin since it requires a long time to manifest, the effect of the KO on FSH and LH cells is probably more acute. Unfortunately a specific antagonist that affect only CCKRBA and not the other CCK receptors wasn’t identified yet.

In the Discussion, the authors suggest that CCK, as a satiety factor, may provide a link between metabolism and reproduction. This is an interesting idea, but it is not supported by the data presented. That is, none of the results shown link metabolic state to CCK regulation of FSH and fertility. Absent such data, the lengthy Discussion of the link is speculative and not fully merited.

In the revised manuscript, we provided data to link cck with metabolic status in supplementary figure 1 and modified the discussion to tone down the link between metabolic status to and reproductive state.

Also in the Discussion, the authors argue that "CCK directly controls FSH cells by innervating the pituitary gland and binding to specific receptors that are particularly abundant in FSH gonadotrophs." However, their imaging does not demonstrate innervation of FSH cells by CCK terminals (e.g., at the EM level).

Innervation of the fish pituitary does not imply a synaptic-like connection between axon terminals and endocrine cells. In fact, such connections are extremely rare, and their functionality is unclear. Instead, the mode of regulation between hypothalamic terminals and endocrine cells in the fish pituitary is more similar to "volume transmission" in the CNS, i.e. peptides are released into the tissue and carried to their endocrine cell targets by the circulation or via diffusion. A short explanation was added in lines 395-398 in the discussion

Moreover, they have not demonstrated the binding of CCK to these cells. Indeed, no CCK receptor protein data are shown.

Our revised manuscript  includes detailed experiments showing the activation of the receptor by its homologous ligand, supplementary Figure 1 includes a transactivation  assay of CCK to its receptor and the effect of the different mutants on the activation of the receptor. Unfortunately, no antibody is available against this fish specific receptor (one of the caveats of working with fish models); therefore, we cannot present receptor protein data.

The calcium responses of FSH cells to exogenous CCK certainly suggest the presence of functional CCK receptors therein; but, the nature of the preparations (with all pituitary cell types present) does not demonstrate that CCK is acting directly in these cells.

We agree with the reviewer that there are some disadvantages in choosing to work with a whole-tissue preparation. However, we believe that the advantages of working in a more physiological context far outweigh the drawbacks as it reflects the natural dynamics more precisely. Since our transcriptome data, as well as our ISH staining, show that the CCK receptor is exclusively expressed in FSH cells, it is improbable that the observed calcium response is mediated via a different pituitary cell type.

Indeed, the asynchrony in responses of individual FSH cells to CCK (Figure 4) suggests that not all cells may be activated in the same way. Contrast the response of LH cells to GnRH, where the onset of calcium signaling is similar across cells (Figure 3).

The difference between the synchronization levels of LH and FSH cells activity stems from the gap-junction mediated coupling between LH cells that does not exist between FSH cells(Golan, Martin et al. 2016). Therefore, the onset of calcium response in FSH cells is dependent on the irregular diffusion rate of the peptide within the preparation, whereas the tight homotypic coupling between LH cells generates a strong and synchronized calcium rise that propagates quickly throughout the entire population

The differences in connectivity between LH and FSH cells is mentioned in lines 194-195

Finally, as the authors note in the Discussion, the data presented do not enable them to conclude that the endogenous CCK regulating FSH (assuming it does) is from the brain as opposed to other sources (e.g., the gut).

We agree with the reviewer that, for now, we are unable to determine whether hypothalamic or peripheral CCK are the main drivers of FSH cells. While the strong innervation of the gland by CCK-secreting hypothalamic neurons strengthens the notion of a hypothalamic-releasing hormone and also fits with the dogma of the neural control of the pituitary gland in fish (Ball 1981), more experiments are required to resolve this question.

Reviewer #2 (Public Review):

Summary:

This manuscript builds on previous work suggesting that the CCK peptide is the releasing hormone for FSH in fishes, which is different than that observed in mammals where both LH and FSH release are under the control of GnRH. Based on data using calcium imaging as a readout for stimulation of the gonadotrophs, the researchers present data supporting the hypothesis that CCK stimulates FSH-containing cells in the pituitary. In contrast, LH-containing cells show a weak and variable response to CCK but are highly responsive to GnRH. Data are presented that support the role of CCK in the release of FSH. Researchers also state that functional overlap exists in the potency of GnRH to activate FSH cells, thus the two signalling pathways are not separate. The results are of interest to the field because for many years the assumption has been that fishes use the same signalling mechanism. These data present an intriguing variation where a hormone involved in satiation acts in the control of reproduction.

Strengths:

The strengths of the manuscript are that researchers have shed light on different pathways controlling reproduction in fishes.

Weaknesses:

Weaknesses are that it is not clear if multiple ligand/receptors are involved (more than one CCK and more than one receptor?). The imaging of the CCK terminals and CCK receptors needs to be reinforced.

Reviewer consultation summary: 

The data presented establish sufficiency, but not necessity of CCK in FSH regulation. The paper did not show that CCK endogenously regulates FSH in fish. This has not been established yet.

This is a very important comment, also raised by reviewer 1. To avoid repetition, please see our detailed response to the comment above.

The paper presents the pharmacological effects of CCK on ex vivo preparations but does not establish the in vivo physiological function of the peptide. The current evidence for a novel physiological regulatory mechanism is incomplete and would require further physiological experiments. These could include the use of a CCK receptor antagonist in adult fish to see the effects on FSH and LH release, the generation of a CCK knockout, or cell-specific genetic manipulations.

As detailed in the responses to the first reviewer, we cannot conduct conditional, cellspecific gene knockout in our model. However we did conducted KO and show the direct effect on FSH and LH secretion together with physiological characterisation of the mutant.

Zebrafish have two CCK ligands: ccka, cckb and also multiple receptors: cckar, cckbra and cckbrb. There is ambiguity about which CCK receptor and ligand are expressed and which gene was knocked out.

In the revised manuscript, we clarified which of the receptors are expressed (CCKRBA) and which receptor is targeted. We also provided data showing the specificity of the receptors (both WT and mutant) to the ligands. Supplementary 1 shows receptor cross-activation. The method also specifies the exact NCBI ID numbers of the targeted receptor and the antibody used for the immunostaining.

Blocking CCK action in fish (with receptor KO) affects FSH and LH. Therefore, the work did not demonstrate a selective role for CCK in FSH regulation in vivo and any claims to have discovered FSHRH need to be more conservative.

We agree with the reviewer that the overlap in the effect of CCK measured in the calcium activation of cells and in the KO model does not allow us to conclude selectivity. In this context, it is crucial to highlight that CCKRBA exhibits high expression on FSH cells but not on LH cells. Therefore, the effect of CCK on LH cells is likely paracrine or through GnRH neurons that were shown to express CCK receptors. In the current version, we emphasize that CCK also induces LH secretion. Although it does not affect LH to the same extent as FSH, an overlap does exist. This is mentioned in the abstract and discussion.

The labelling of the terminals with anti-CCK looks a lot like the background and the authors did not show a specificity control (e.g. anti-CCK antibody pre-absorbed with the peptide or anti-CCK in morphant/KO animals).

Figures colours had been updated to better visualise the specific staining of the antibody. Also, The same antibody had been previously used to mark CCK-positive cells in the gut of the red drum fish(Webb, Khan et al. 2010) , where a control (pre-absorbed with the peptide) experiment had been conducted.

Recommendations for the authors:

Reviewer #1 (Recommendations For The Authors):

Abstract:

The authors have not yet established that CCK is the primary regulator of FSH in vivo.

In the new version, we highlight the leading effect of CCK on the reproductive axis, which includes FSH and LH.

Introduction:

The authors need to make clear earlier in the Introduction that fish have two types of gonadotropes. This information comes too late (last paragraph) currently.

Added in line 42

They should discuss relevant data on the differential regulation of FSH and LH in fish, as a rationale for looking for different releasing factors.

This has been discussed in the first paragraph of the introduction

In the last sentence of the penultimate paragraph, the authors assume that it must be a hypothalamic factor that regulates FSH. Why is this necessarily the case? Are there data indicating that a hypothalamic factor is required for FSH production in fish?

This has been mentioned in the discussion, we do not deny that circulating CCK or CCK from other brain areas might affect FSH secretion in the pituitary (line 402-404). However, as the hypothalamus serves as the main gateway from the brain to the pituitary and contains hypophysiotropic CCK neurons it is the most reasonable assumption.

Results:

In the first paragraph, the authors reference three types of CCK receptors, only one of which is expressed in the pituitary. The specific receptor should be named here.

The receptor name and NCBI id had been added in this paragraph.

Figure 1: What specificity controls were used for the ISH in Figure 1?

HCR- The method used to identify RNA expression and developed by Molecular Instruments (https://www.molecularinstruments.com/hcr-rnafish-protocols), do not require specific control as had been previously done with older ISH methods. The use of multiple short probes assure the specificity to the RNA.More over the expression is specific to the targeted cells.

In Figure 1D, the red square is missing in the KO fish (at low magnification).

This was fixed in the updated version.

In Figure 1G, the number of dots does not correspond to the number of animals described in the figure legend. Does each point represent an animal?

Each dot represent a fish. The order of the numbers in the legend didn’t match the order in the graph, this had been fixed in the last version

Figure 2A: It is not clear that all FSH (GFP) cells are double-labeled. Should all double-labeled cells appear white? Many appear as green. Some quantification of the proportion of co-labeling is needed. Also, the scale bars are too small to read. Perhaps add the size of the scale bars to the legend.

They are all double-labeled, as can be seen by the single-color images, since GFP fluorescence is stronger than RCaMP fluorescence, the double-labelling might be seen a green cells; a scale bar was added.

Figure 2C: Is the synchronous activity of LH cells here dependent on endogenous GnRH? Can these events be blocked with a GnRH receptor antagonist?

We currently do not have enough data to support this hypothesis and the in vivo 2 photon system is not optimal to answer these questions since these are spontaneous events which are difficult to predict. This is the main reason we moved to an ex vivo system. The similar response we receive when applying GnRH in the ex vivo system support it is GnRH activation.

Figure 4C: As some LH cells respond to CCK, can the authors really claim that CCK is a selective regulator of FSH? What explains the heterogeneity in the response of LH cells to CCK?

In this version, we highlight that CCK directly activates FSH but it is also affecting LH to some extent. However it is clear that the effect on FSH cells is more significant.

Figures 5A and B: With larger Ns, some of the trends might be significant (e.g., GnRH stimulated FSH release and CCK stimulated LH release).

Though there is a trend, the values in the Y axis reveal that the trend of response of FSH to GnRH and LH to CCK is lower then the distribution of the basal response (the before) in all of the graphs. Hence we do not believe a larger N will affect those results. We added the range of the secreted hormones concentrations in the result description to emphasize the difference in values,

Figures 5C and D: What explains the lack of an increase in LH secretion following GnRH treatment?

We did not measure LH Secretion in the plasma as we didn’t have enough blood, we do see an increase in LH transcription (see supplementary figure 5 – figure supplement 1)

Also, as mRNA levels were measured (in C), reference should be made to expression rather than transcription. Not all changes in mRNA levels reflect changes in transcription.Also, remove transcription from the legend. Reference to supplementary Figure 4 in the legend should be supplementary Figure 6. Finally, in C and D, distinguish males from females (as in 5A and B).

Modifications had been done according to the reviewer suggestions.

Figure legends:

The figure legends are very long. One way to shorten them is to remove descriptions of the results. The legends should indicate what is in each figure, not the results of the experiments.

Modifications had been done according to the reviewer suggestions.

Sample sizes should be spelled out in the legends, as they are not in the M&M.

We made sure all sample sizes are mentioned in the legend

Materials and Methods:

Section 1.1 can be removed as it repeats content presented elsewhere.

This section was removed

Section 1.5: It is unclear what this means: "blinding was not applied to ensure tractability" Please clarify.

This section was removed

Reviewer #2 (Recommendations For The Authors):

It appears that zebrafish have two ligands: ccka, cckb. Also multiple receptors: cckar, cckbra and cckbrb. Authors need to discuss this and clearly state which ligand and which receptor they are referring to in the manuscript.

We discussed the receptor type in the first paragraph of the results, the exact synthetic peptide used is described in the methods. The 8 amino acids of the mature CCK peptide are the same between CCKa and CCKb. A sentence regarding the specificity of the antibody to the mature CCK peptide was added in line 101.

"to GnRH puff application (300 μl of 30 μg/μl)"; (250 μl of 30 μg/ml CCK)

Please give the final concentration to make it easy on the readers of the data.

The molarity of the final concentration was added.

(2.4) Differential calcium response underlies differential hormone. This section is a bit confusing to read, for example:

"For that, we collected the medium perfused through our ex vivo system (Fig. 2a) and measured LH and FSH levels using a specific ELISA validated for zebrafish [31] while monitoring the calcium activity of the cells."

So the authors did the ELISA while monitoring the activity (?). This sentence does not make sense: please rewrite it.

We modified this sentence  in line 308-311

To functionally validate the importance of CCK signalling we used CRISPR-cas9 to generate loss-of-function (LOF) mutations in the pituitary- CCK receptor gene.

The authors need to clearly state WHICH gene they inactivated: Zebrafish have three CCK-receptors, so "the pituitary receptor gene" needs to be defined.

Was added again in line 107, and is mentioned in the methods

Figure 3 is a crucial figure!

Figure 3B: The data are not very convincing. Please state how thick the sections are in the figure legend (assuming these are adult pituitaries),

Added in the legend (figure 1C in the new version), slice thickness and adult fish.

Please show at least the merged image a high magnification view of the co-localization of the receptor with the cells.

This is figure 1 in the new revision, a magnified figure was added

Please give the scale bar size for 3B.

Scales for all images were added

Figure 3C: the co-localization of the terminals of the CCK and FSH cells shows very few cells expressing close to terminals.

Important: Because the labelling of the terminals with anti-CCK looks a lot like the background, it is very important to show the control (anti-CCK antibody pre-absorbed with the peptide). The authors should have these data. The photo needs to have been taken at the same gain (contrast) and the photo showing the terminals.

This is  a commercial antibody that had been previously validated for CCK in fish. The co-localization pattern resembles GnRH innervation in the pituitary. In fish when hypothalamic neurons innervate the pituitary they do not innervate all the cells, as this is an endocrine system, the peptide can travel to neighbouring cells via diffusion or aided blood flow (Golan, Zelinger et al. 2015) ).  The images reveal the direct innervation of CCK in the pituitary and its proximity to FSH cells.

Figure 4c, on right. The text seems to be stretched as if the photo was adjusted without locking the aspect ratio. Please check the original images.

This has been fixed

Can the authors use different pseudo colours? Differentiating a double label of white versus yellow is very difficult, and thus the photo is not very convincing.

This had been changed to green and magenta

What is meant by "CCK-AB" antibody? Perhaps anti-CCK would be a better label

This has been fixed

Figure 5A: increase the magnification of the insets; the structure of the gonads is very difficult to see with clarity in these low mag images. The most obvious way to improve this figure is to reduce or eliminate the pie graph (not really necessary) and show a high magnification (and larger) image of the gonadal structure.

This is figure 1 in the new version, with magnification of the gonad next to each body section.

Discussion:

" Moreover, in the zebrafish, as well as in other species, the functional overlap in gonadotropin signalling pathways is not limited to the pituitary but is also present in the gonad, through the promiscuity of the two gonadotropin receptors"<br /> The reasoning of this sentence is not clear: zebrafish do not use GnRH to control reproduction: they lack GnRH1 through genomic rearrangement (see Whitlock, Postlethwait and Ewer 2019) and KO of GnRH2/GnRH3 does not affect reproduction.

While GnRH KO model indicate a redundancy of GnRH in this axis in zebrafish, there is also ample evidence for its importance in regulating reproduction such as its effect on gonadotropin (Golan, Martin et al. 2016) and its use in spawning inductions in fish (Mizrahi and Levavi-Sivan 2023). We believe it is currently too soon to conclude that GnRH signalling is completely non relevant to reproduction in cyprinids.  

Reviewing Editor (Recommendations For The Authors):

It would be interesting to see calcium imaging experiments in the CCKR receptor mutants to establish a more direct connection between peptide action and activity.

We added a receptor assay that reflect the non-activation of the mutated receptors by CCK (supplementary figure 1) , and compared it to the wild type that is activated. This show that: 1) CCK directly activate our identified receptor in FSH cells. 2) the mutated receptors are non-active.

"all homozygous fish (CCKR+12/+7/-1/ CCKR+12/+7/-1, n=12)"

It may be better to write the genotype of fish separately as CCKR+12/+12, CCKR+7/+7 and CCKR-1/-1, n=12) otherwise it seems as if all alleles occurred together in the same fish.

Modified according to the reviewer request

In Figure 1 scale bar legends are very small. 

Description of the scale bars were added to the all the legends

Figure 1 legend "On the top right of each panel is the gender distribution" - fish have no gender but sex.

Modified according to the reviewer request

The authors should endeavour to improve the presentation of the figures. They should use a sans-serif font and check that text is not cut at the edge of figure panels, that scale bars are uniform and clearly labelled and fonts are of similar size and clearly legible. E.g. labels of the fish brain of Fig3A are very small.

We modified all the figures to adapt the font and the scales, we increased the size of the image in Figure 3a to make the labels clearer.

Please use the elife format to name supplementary figures, as Figure X - Figure Supplement Y (each supplement associated with one of the main figures).

Fixed

Peptide concentrations in the ex vivo experiments should also be given as molar concentrations not only as '250 μl of 30 μg/ml CCK'.

Fixed

"In contrast, FSH cells responded with a very low calcium rise in hormonal secretion in response to GnRH" - a very low rise in hormonal secretion

Fixed

Please clarify why you used a GnRH synthetic agonist and not the native peptide.

It is commonly used for spawning induction in fish (line 245); it has also been shown to directly affect the secretion of LH and FSH (Biran, Golan et al. 2014, Biran, Golan et al. 2014, Mizrahi, Gilon et al. 2019) , added to line 245.

References

Ball, J. (1981). "Hypothalamic control of the pars distalis in fishes, amphibians, and reptiles." General and comparative endocrinology 44(2): 135-170.

Biran, J., M. Golan, N. Mizrahi, S. Ogawa, I. S. Parhar and B. Levavi-Sivan (2014). "Direct regulation of gonadotropin release by neurokinin B in tilapia (Oreochromis niloticus)." Endocrinology 155(12): 4831-4842.

Biran, J., M. Golan, N. Mizrahi, S. Ogawa, I. S. Parhar and B. Levavi-Sivan (2014). "LPXRFa, the Piscine Ortholog of GnIH, and LPXRF Receptor Positively Regulate Gonadotropin Secretion in Tilapia (Oreochromis niloticus)." Endocrinology 155(11): 4391-4401.

Golan, M., A. O. Martin, P. Mollard and B. Levavi-Sivan (2016). "Anatomical and functional gonadotrope networks in the teleost pituitary." Scientific Reports 6: 23777.

Golan, M., E. Zelinger, Y. Zohar and B. Levavi-Sivan (2015). "Architecture of GnRH-Gonadotrope-Vasculature Reveals a Dual Mode of Gonadotropin Regulation in Fish." Endocrinology 156(11): 4163-4173.

Mizrahi, N., C. Gilon, I. Atre, S. Ogawa, I. S. Parhar and B. Levavi-Sivan (2019). "Deciphering Direct and Indirect Effects of Neurokinin B and GnRH in the Brain-Pituitary Axis of Tilapia." Front Endocrinol (Lausanne) 10: 469.

Mizrahi, N. and B. Levavi-Sivan (2023). "A novel agent for induced spawning using a combination of GnRH analog and an FDA-approved dopamine receptor antagonist." Aquaculture 565: 739095.

Uehara, S. K., Y. Nishiike, K. Maeda, T. Karigo, S. Kuraku, K. Okubo and S. Kanda (2023). "Cholecystokinin is the follicle-stimulating hormone (FSH)-releasing hormone." bioRxiv: 2023.2005.2026.542428.

Webb, K. A., Jr., I. A. Khan, B. S. Nunez, I. Rønnestad and G. J. Holt (2010). "Cholecystokinin: molecular cloning and immunohistochemical localization in the gastrointestinal tract of larval red drum, Sciaenops ocellatus (L.)." Gen Comp Endocrinol 166(1): 152-159.

DOI: 10.1038/s44318-024-00322-y

Resource: UCSF Chimera (RRID:SCR_004097)

Curator: @scibot

SciCrunch record: RRID:SCR_004097

What is this?

HORATIO

Não basta o dolo geral.

CPP Art. 218. Se, regularmente intimada, a testemunha deixar de comparecer sem motivo justificado, o juiz poderá requisitar à autoridade policial a sua apresentação ou determinar seja conduzida por oficial de justiça, que poderá solicitar o auxílio da força pública.

eLife Assessment

This study presents a new quantitative method, CROWN-seq, to map the cap-adjacent RNA modification N6,2'-O-dimethyladenosine (m6Am) with single nucleotide resolution. Using thoughtful controls and well-validated reagents, the authors provide compelling evidence that the method is reliable and reproducible. Additionally, the study provides important evidence that m6Am may increase transcription in modified mRNAs, however, the data only demonstrates a correlation between m6Am and transcriptional regulation rather than causality. Overall, this study is poised to advance m6Am research, being of broad interest to the RNA biology and gene regulation fields.

Reviewer #1 (Public review):

Summary:

In this manuscript, Liu et al. present CROWN-seq, a technique that simultaneously identifies transcription-start nucleotides and quantifies N6,2'-O-dimethyladenosine (m6Am) stoichiometry. This method is derived from ReCappable-seq and GLORI, a chemical deamination approach that differentiates A and N6-methylated A. Using ReCappable-seq and CROWN-seq, the authors found that genes frequently utilize multiple transcription start sites, and isoforms beginning with an Am are almost always N6-methylated. These findings are consistently observed across nine cell lines. Unlike prior reports that associated m6Am with mRNA stability and expression, the authors suggest here that m6Am may increase transcription when combined with specific promoter sequences and initiation mechanisms. Additionally, they report intriguing insights on m6Am in snRNA and snoRNA and its regulation by FTO. Overall, the manuscript presents a strong body of work that will significantly advance m6Am research.

Strengths:

The technology development part of the work is exceptionally strong, with thoughtful controls and well-supported conclusions.

Weaknesses:

Given the high stoichiometry of m6Am, further association with upstream and downstream sequences (or promoter sequences) does not appear to yield strong signals. As such, transcription initiation regulation by m6Am, suggested by the current work, warrants further investigation.

Reviewer #2 (Public review):

Summary:

In the manuscript "Decoding m6Am by simultaneous transcription-start mapping and methylation quantification" Liu and co-workers describe the development and application of CROWN-Seq, a new specialized library preparation and sequencing technique designed to detect the presence of cap-adjacent N6,2'-O-dimethyladenosine (m6Am) with single nucleotide resolution. Such a technique was a key need in the field since prior attempts to get accurate positional or quantitative measurements of m6Am positioning yielded starkly different results and failed to generate a consistent set of targets. As noted in the strengths section below the authors have developed a robust assay that moves the field forward.

Furthermore, their results show that most mRNAs whose transcription start nucleotide (TSN) is an 'A' are in fact m6Am (85%+ for most cell lines). They also show that snRNAs and snoRNAs have a substantially lower prevalence of m6Am TSNs.

Strengths:

Critically, the authors spent substantial time and effort to validate and benchmark the new technique with spike-in standards during development, cross-comparison with prior techniques, and validation of the technique's performance using a genetic PCIF1 knockout. Finally, they assayed nine different cell lines to cross-validate their results. The outcome of their work (a reliable and accurate method to catalog cap-adjacent m6Am) is a particularly notable achievement and is a needed advance for the field.

Weaknesses:

No major concerns were identified by this reviewer.

Mid-level Concerns:

(1) In Lines 625 and 626, the authors state that "our data suggest that mRNAs initate (mis-spelled by authors) with either Gm, Cm, Um, or m6Am." This reviewer took those words to mean that for A-initiated mRNAs, m6Am was the 'default' TSN. This contradicts their later premise that promoter sequences play a role in whether m6Am is deposited.

(2) Further, the following paragraph (lines 633-641) uses fairly definitive language that is unsupported by their data. For example in lines 637 and 638 they state "We found that these differences are often due to the specific TSS motif." Simply, using 'due to' implies a causative relationship between the promoter sequences and m6Am has been demonstrated. The authors do not show causation, rather they demonstrate a correlation between the promoter sequences and an m6Am TSN. Finally, despite claiming a causal relationship, the authors do not put forth any conceptual framework or possible mechanism to explain the link between the promoter sequences and transcripts initiating with an m6Am.

(3) The authors need to soften the language concerning these data and their interpretation to reflect the correlative nature of the data presented to link m6Am and transcription initiation.

Author response:

Public Reviews:

Reviewer #1 (Public review):

Summary:

In this manuscript, Liu et al. present CROWN-seq, a technique that simultaneously identifies transcription-start nucleotides and quantifies N6,2'-O-dimethyladenosine (m6Am) stoichiometry. This method is derived from ReCappable-seq and GLORI, a chemical deamination approach that differentiates A and N6-methylated A. Using ReCappable-seq and CROWN-seq, the authors found that genes frequently utilize multiple transcription start sites, and isoforms beginning with an Am are almost always N6-methylated. These findings are consistently observed across nine cell lines. Unlike prior reports that associated m6Am with mRNA stability and expression, the authors suggest here that m6Am may increase transcription when combined with specific promoter sequences and initiation mechanisms. Additionally, they report intriguing insights on m6Am in snRNA and snoRNA and its regulation by FTO. Overall, the manuscript presents a strong body of work that will significantly advance m6Am research.

Strengths:

The technology development part of the work is exceptionally strong, with thoughtful controls and well-supported conclusions.

We appreciate the reviewer for the very positive assessment of the study. We have addressed the concerns below.

Weaknesses:

Given the high stoichiometry of m6Am, further association with upstream and downstream sequences (or promoter sequences) does not appear to yield strong signals. As such, transcription initiation regulation by m6Am, suggested by the current work, warrants further investigation.

We thank the reviewer for the insightful comments. We have softened the language related to m6Am and transcription regulation. We totally agree with the reviewer that future investigation is required to determine the molecular mechanism behind m6Am and transcription regulation.

Reviewer #2 (Public review):

Summary:

In the manuscript "Decoding m6Am by simultaneous transcription-start mapping and methylation quantification" Liu and co-workers describe the development and application of CROWN-Seq, a new specialized library preparation and sequencing technique designed to detect the presence of cap-adjacent N6,2'-O-dimethyladenosine (m6Am) with single nucleotide resolution. Such a technique was a key need in the field since prior attempts to get accurate positional or quantitative measurements of m6Am positioning yielded starkly different results and failed to generate a consistent set of targets. As noted in the strengths section below the authors have developed a robust assay that moves the field forward.

Furthermore, their results show that most mRNAs whose transcription start nucleotide (TSN) is an 'A' are in fact m6Am (85%+ for most cell lines). They also show that snRNAs and snoRNAs have a substantially lower prevalence of m6Am TSNs.

Strengths:

Critically, the authors spent substantial time and effort to validate and benchmark the new technique with spike-in standards during development, cross-comparison with prior techniques, and validation of the technique's performance using a genetic PCIF1 knockout. Finally, they assayed nine different cell lines to cross-validate their results. The outcome of their work (a reliable and accurate method to catalog cap-adjacent m6Am) is a particularly notable achievement and is a needed advance for the field.

Weaknesses:

No major concerns were identified by this reviewer.

We thank the reviewer for the positive assessment of the method and dataset. We have addressed the concerns below.

Mid-level Concerns:

(1) In Lines 625 and 626, the authors state that “our data suggest that mRNAs initate (mis-spelled by authors) with either Gm, Cm, Um, or m6Am.” This reviewer took those words to mean that for A-initiated mRNAs, m6Am was the ‘default’ TSN. This contradicts their later premise that promoter sequences play a role in whether m6Am is deposited.

We thank the reviewer for the comment. We have changed this sentence into “Instead, our data suggest that mRNAs initiate with either Gm, Cm, Um, or Am, where Am are mostly m6Am modified.” The revised sentence separates the processes of transcription initiation and m6Am deposition, which will not confuse the reader.

(2) Further, the following paragraph (lines 633-641) uses fairly definitive language that is unsupported by their data. For example in lines 637 and 638 they state “We found that these differences are often due to the specific TSS motif.” Simply, using ‘due to’ implies a causative relationship between the promoter sequences and m6Am has been demonstrated. The authors do not show causation, rather they demonstrate a correlation between the promoter sequences and an m6Am TSN. Finally, despite claiming a causal relationship, the authors do not put forth any conceptual framework or possible mechanism to explain the link between the promoter sequences and transcripts initiating with an m6Am.

(3) The authors need to soften the language concerning these data and their interpretation to reflect the correlative nature of the data presented to link m6Am and transcription initiation.

For (2) and (3). We have softened the language in the revised manuscript. Specifically, for lines 633-641 in the original manuscript, we have changed “are often due to” into “are often related to” in the revised manuscript, which claims a correlation rather than a causation.

Reviewer #3 (Public review):

Summary:

m6Am is an abundant mRNA modification present on the TSN. Unlike the structurally similar and abundant internal mRNA modification m6A, m6Am’s function has been controversial. One way to resolve controversies surrounding mRNA modification functions has been to develop new ways to better profile said mRNA modification. Here, Liu et al. developed a new method (based on GLORI-seq for m6A-sequencing), for antibody-independent sequencing of m6Am (CROWN-seq). Using appropriate spike-in controls and knockout cell lines, Liu et al. clearly demonstrated CROWN-seq’s precision and quantitative accuracy for profiling transcriptome-wide m6Am. Subsequently, the authors used CROWN-seq to greatly expand the number of known m6Am sites in various cell lines and also determine m6Am stoichiometry to generally be high for most genes. CROWN-seq identified gene promoter motifs that correlate best with high stoichiometry m6Am sites, thereby identifying new determinants of m6Am stoichiometry. CROWN-seq also helped reveal that m6Am does not regulate mRNA stability or translation (as opposed to past reported functions). Rather, m6Am stoichiometry correlates well with transcription levels. Finally, Liu et al. reaffirmed that FTO mainly demethylates m6Am, not of mRNA but of snRNAs and snoRNAs.

Strengths:

This is a well-written manuscript that describes and validates a new m6Am-sequencing method: CROWN-seq as the first m6Am-sequencing method that can both quantify m6Am stoichiometry and profile m6Am at single-base resolution. These advantages facilitated Liu et al. to uncover new potential findings related to m6Am regulation and function. I am confident that CROWN-seq will likely be the gold standard for m6Am-sequencing henceforth.

Weaknesses:

Though the authors have uncovered a potentially new function for m6Am, they need to be clear that without identifying a mechanism, their data might only be demonstrating a correlation between the presence of m6Am and transcriptional regulation rather than causality.

We thank the reviewer for the very positive assessment of the CROWN-seq method. We have softened the language which is related to the correlation between m6Am and transcription regulation.

DOI: 10.1016/j.molcel.2024.11.009

Resource: (RRID:CVCL_0291)

Curator: @areedewitt04

SciCrunch record: RRID:CVCL_0291

What is this?

DOI: 10.1177/13872877241291175

Resource: (MMRRC Cat# 034832-JAX,RRID:MMRRC_034832-JAX)

Curator: @scibot

SciCrunch record: RRID:MMRRC_034832-JAX

What is this?

DOI: 10.1101/2024.09.05.610344

Resource: (Millipore Cat# AB765P, RRID:AB_92259)

Curator: @scibot

SciCrunch record: RRID:AB_92259

What is this?

DOI: 10.1016/j.scr.2024.103619

Resource: (Jackson ImmunoResearch Labs Cat# 715-585-150, RRID:AB_2340854)

Curator: @scibot

SciCrunch record: RRID:AB_2340854

What is this?

Repetitive "O" sound

• Informativo nº 834
• 26 de novembro de 2024. PRIMEIRA TURMA
• Processo: AREsp 2.397.496-SP, Rel. Ministro Gurgel de Faria, Primeira Turma, por unanimidade, julgado em 12/11/2024.

Ramo do Direito DIREITO PROCESSUAL CIVIL, DIREITO TRIBUTÁRIO

TemaPaz, Justiça e Instituições Eficazes <br /> Obrigação tributária. Ação consignatória em pagamento. Hipótese de bitributação. Efetiva cobrança pelos entes tributantes. Demonstração na petição inicial. Necessidade. Condição da ação.

Destaque - A exigência, por mais de uma pessoa jurídica de direito público, de tributo idêntico sobre um mesmo fato gerador é condição da ação consignatória prevista no art. 164, III, do CTN, de maneira que a efetiva cobrança, administrativa ou judicial, deve ser verificada da análise da argumentação deduzida na petição inicial.

Informações do Inteiro Teor - Cinge-se a controvérsia quanto a presença ou não de requisito legal para o ajuizamento da ação consignatória, relacionada à exigência por mais de um sujeito ativo de tributo sobre o mesmo fato gerador, tratado no caso como concurso de exigências.

• Embora haja previsão específica no âmbito do direito tributário, no artigo 164 do CTN, a singela normatização impõe a interpretação sistemática de normas, a fim de extrair o alcance de suas disposições.

• De forma geral, consoante se extrai dos artigos 539 e 546 do CPC/2015 e do art. 334 do CC/2002, vê-se que ação consignatória é o instrumento pelo qual o sujeito passivo visa obter os efeitos do pagamento de uma obrigação e a sua extinção, ou seja, objetiva a quitação da obrigação.

• No campo do direito tributário, admite-se a consignação do crédito tributário em juízo pelo sujeito passivo em hipóteses determinadas (art. 164, I, II e III, do CTN). Nesses casos, julgada procedente a consignação, considera-se realizado o pagamento do crédito tributário (§ 2º do art. 164 do CTN).

• Quanto à específica previsão do art. 164, III, do CTN, esta diz respeito à consignação de tributo exigido por mais de um sujeito ativo, baseado no mesmo fato gerador. Desse modo, a dúvida sobre o legítimo titular de um crédito tributário é o que autoriza o ajuizamento da demanda. O concurso de exigências do tributo por mais de uma Fazenda Pública, portanto, configura requisito para a propositura da ação de consignação em pagamento, nessa hipótese.

• Nesse sentido, a observância do mencionado pressuposto encontra-se no âmbito do interesse de agir. O ajuizamento da ação pressupõe a demonstração da necessidade e da utilidade da prestação jurisdicional de extinção de um crédito tributário exigido por mais de um sujeito ativo mediante a consignação em pagamento. Ou seja, comprovada a exigência de um tributo por mais de um ente federativo estaria atendida essa imposição legal para o ajuizamento da demanda.

• No direito processual civil, predomina na doutrina e jurisprudência pátrias a teoria da asserção, segundo a qual a verificação das condições da ação deve ser realizada com base no que consta na petição inicial, abstratamente.

• Dessa forma, com relação à ação consignatória fundada no inciso III do art. 164 do CTN, da argumentação da petição inicial deve despontar seguramente a exigência do mesmo tributo por mais de um sujeito ativo. À luz das afirmações deduzidas na petição inicial, deve ser possível a verificação da real exigência do tributo por mais de uma pessoa jurídica de direito público.

• No caso, da leitura da petição inicial, não é possível se constatar a dupla cobrança do tributo, uma vez que a ação consignatória foi ajuizada com base exclusivamente em previsão legal abstrata da tributação por mais de um ente público.

• Ressalte-se que o dispositivo do CTN anteriormente transcrito menciona a exigência do tributo, o que leva a crer que dependeria da prévia existência de um crédito tributário devidamente constituído e em vias de cobrança, ainda que no âmbito administrativo. Raciocínio diverso permitiria a inusitada situação em que o sujeito passivo estaria autorizado a consignar importância ainda indefinida.

• Dessa maneira, a exigência, por mais de uma pessoa jurídica de direito público, de tributo idêntico sobre um mesmo fato gerador encontra-se no domínio das condições da ação consignatória prevista no art. 164, III, do CTN, de maneira que a efetiva cobrança, administrativa ou judicial, deve ser verificada da argumentação deduzida na petição inicial. A mera existência de previsão legal abstrata do tributo ou o oferecimento de contestação à ação de consignação em pagamento não são suficientes para atender ao requisito de que trata o mencionado dispositivo do CTN.

• Informativo nº 834
• 26 de novembro de 2024.
• Processo: REsp 1.762.278-MS, Rel. Ministro Antonio Carlos Ferreira, Quarta Turma, por unanimidade, julgado em 5/11/2024, DJe 18/11/2024.

Ramo do Direito DIREITO PROCESSUAL CIVIL

TemaPaz, Justiça e Instituições Eficazes <br /> Cumprimento individual de sentença coletiva. Efeito erga omnes. Inaplicabilidade.

Destaque - A norma do art. 103, III, do Código de Defesa do Consumidor (CDC), que confere efeito erga omnes à sentença genérica proferida na fase de conhecimento, em ação coletiva, não se aplica às decisões proferidas no cumprimento individual de sentença.

Informações do Inteiro Teor - No caso, o Tribunal de origem, em fase de cumprimento individual de sentença, conferiu, ex officio, efeito erga omnes à decisão por ele proferida, sob o fundamento de tratar-se de questão de ordem pública, de que haveria probabilidade de julgamentos contraditórios e de que o princípio da economia processual deveria ser observado, com base no art. 103, III, do Código de Defesa do Consumidor (CDC).

• Todavia, a norma do art. 103, III, do CDC, que confere efeito erga omnes à sentença genérica proferida na fase de conhecimento, em ação coletiva, não se aplica às decisões proferidas no cumprimento individual de sentença. Tal dispositivo é aplicado somente à sentença genérica proferida na fase de conhecimento. Essa interpretação extensiva restringiria o direito individual conferido ao devedor e ao credor de se manifestarem acerca das obrigações e créditos envolvidos em cada relação concreta e específica.

• O cumprimento individual de sentença, precedido ou não de liquidação, é o momento em que o credor ingressa no processo e defende especificamente seu direito à luz do que consta na sentença coletiva, de natureza genérica. Também ao devedor é permitido definir sua obrigação quanto a um determinado credor. Nessa fase, portanto, cabe-lhes - ao credor e ao devedor - deduzir argumentos próprios para concretizar e delimitar, sob todos os enfoques, o direito reconhecido judicialmente.

• Nesse sentido, questões semelhantes discutidas simultaneamente em diversos cumprimentos de sentença, autônomos entre si, poderão ser decididas de formas diferentes, caso a caso, dependendo das provas apresentadas pelas partes e da situação específica de cada credor. Mesmo as questões meramente de direito, que eventualmente independam de circunstâncias concretas envolvendo cada beneficiário, deverão ser apreciadas diante das alegações e dos argumentos relevantes apresentados pelo credor e pelo devedor. Com isso, em tese, é possível que o Juízo da execução, em um primeiro momento, decida determinado tema de uma forma e, mais adiante, em outro processo de cumprimento de sentença, com base em fundamentos mais consistentes deduzidos pelas partes, mude o seu posicionamento. A uniformização do tema, em tal circunstância, ocorrerá em segundo grau ou nesta Corte Superior caso a parte interessada utilize os recursos cabíveis.

• Ademais, não se pode pretender transplantar para todos os processos individuais de execução da sentença coletiva deliberação inicialmente proferida em um deles, sem que cada parte possa sobre ele se manifestar e ter suas objeções consideradas pelo Poder Judiciário. Exatamente em virtude da necessidade de substrato legislativo para a extensão das questões reiteradas a outros processos, a lei enumera as hipóteses nas quais se admite a racionalização para a expansão vinculante das decisões judiciais.

• Do mesmo modo, sobretudo considerando que o efeito erga omnes disciplinado no art. 103 do CDC diz respeito às questões genericamente decididas na fase de conhecimento, ao credor e ao devedor, no respectivo cumprimento individual de sentença, é permitido apresentar teses e fatos, invocando argumentos próprios para tornar concreta a obrigação que deverá ser cumprida. Tem-se como irrelevante o fato de questões semelhantes terem sido arguidas e decididas em outros procedimentos de cumprimento de sentença, envolvendo credores distintos.

• Não é por outro motivo que a Segunda Seção, no julgamento dos EREsp n. 1.590.294/DF, impôs a necessidade de liquidação de sentença genérica em processo coletivo. Além disso, em outro julgado, sob o rito dos recursos repetitivos, determinou-se que: "A sentença genérica prolatada no âmbito da ação civil coletiva, por si, não confere ao vencido o atributo de devedor de 'quantia certa ou já fixada em liquidação' (art. 475-J do CPC), porquanto, 'em caso de procedência do pedido, a condenação será genérica', apenas 'fixando a responsabilidade do réu pelos danos causados' (art. 95 do CDC). A condenação, pois, não se reveste de liquidez necessária ao cumprimento espontâneo do comando sentencial, não sendo aplicável a reprimenda prevista no art. 475-J do CPC." (REsp 1.247.150/PR, Rel. Ministro Luis Felipe Salomão, Corte Especial, julgado em 19/10/2011, DJe 12/12/2011)

• De fato, conquanto a tese firmada naquele julgado, para fins do art. 543-C do CPC, tenha sido sobre o alcance pessoal dos efeitos da coisa julgada formada em ação civil pública, é certo que também foi analisado outro ponto, qual seja, a não incidência da multa prevista no art. 475-J do CPC, em virtude da impossibilidade de cumprimento voluntário da obrigação, adotando-se como premissa que a sentença proferida em ação civil pública, por si só, não confere ao vencido o atributo de devedor de quantia certa ou já fixada em liquidação, porquanto a condenação é genérica, apenas fixando a responsabilidade do réu pelos danos causados, conforme disposto no art. 95 do CDC.

• Desse modo, a condenação é certa e precisa - haja vista que a certeza é condição essencial do julgamento e o comando da sentença estabelece claramente os direitos e as obrigações que possibilitam a sua execução -, porém não se reveste da liquidez necessária ao cumprimento espontâneo da decisão, devendo ainda ser apurados em liquidação os destinatários (cui debeatur) e a extensão da reparação (quantum debeatur). Somente nesse momento é que se dará, portanto, a individualização da parcela que tocará ao exequente segundo o comando sentencial proferido na ação coletiva.

• Sem dúvida, a necessidade de liquidação de sentença, que impõe que sejam observados o contraditório e o direito à ampla defesa, por si, representa óbice à aplicação do efeito erga omnes a decisão proferida em cumprimento de sentença envolvendo um determinado credor. Conforme afirmado, a concretização do direito, com delimitação da obrigação, será efetivada em cada procedimento executório.

• Portanto, as alegações apresentadas no cumprimento individual de sentença deverão ser decididas autonomamente em cada procedimento, recomendando-se acompanhar a jurisprudência em casos semelhantes. Tais decisões, proferidas em determinado cumprimento de sentença, não vinculam outro procedimento envolvendo credor distinto.

O(n)

She then entirely switches it up here. Is this out of character for her?

Think back to the confrontation with Aphrodite, conflicting whether or not to let Paris sleep with her.

A mera alegação por uma das partes da necessidade de intervenção da União, entidade autárquica ou empresa pública federal em uma demanda entre pessoas privadas em trâmite na Justiça Estadual é insuficiente para que haja o deslocamento de competência para a Justiça Federal.

EDcl no AgRg no Ag 1.275.461-SP , Rel. Ministra Regina Helena Costa, Primeira Turma, por maioria, julgado em 21/5/2024. (Informativo 813)

O enquadramento na faixa de isenção de imposto de renda NÃO DEVE SER UTILIZADO COMO CRITÉRIO para o deferimento do benefício da assistência judiciária gratuita.

AgInt no AREsp 2.441.809-RS , Rel. Ministro Herman Benjamin, Segunda Turma, por unanimidade, julgado em 8/4/2024, DJe 2/5/2024.

Art. 59. O registro ou a distribuição da petição inicial torna prevento o juízo.

dopytać o to

overthinking

Note: This response was posted by the corresponding author to Review Commons. The content has not been altered except for formatting.

Learn more at Review Commons

Reply to the reviewers

Manuscript number: RC-2024-02546

Corresponding author: Woo Jae, Kim

1. General Statements

This is the second version of revision.

After thoroughly reviewing the comments provided by the EMBO Journal reviewers, we found their feedback to be highly constructive and valuable for enhancing our manuscript without the need for additional experiments. For example, Reviewer 1 acknowledged that our "data are intriguing and some of the experiments are quite convincing," but suggested that the manuscript contained excessive data that required simplification. This sentiment was echoed by Reviewer 2. In response, we have completely reformatted our manuscript to eliminate unnecessary imaging quantification data and CrzR-related screening data. The reviewers noted the density of our experimental data, which has led us to focus on the SIFa to Crz-CrzR circuit mechanisms related to heart function and interval timing in future projects.

Reviewer 2's comments were generally more moderate, and we successfully addressed all five of their points with detailed explanations and modifications to our manuscript. They positively remarked that "Overall, this highly interesting study advances our knowledge about the behavioral roles of SIFamide and contributes to an understanding of how motivated behavior such as mating is orchestrated by modulatory peptides." Additionally, Reviewer 3 accepted our manuscript without any further comments.

In summary, we believe we have effectively addressed all concerns raised by Reviewers 1 and 2, resulting in a clearer manuscript that is more accessible to a broader audience.

2. Point-by-point description of the revisions

Reviewer #1

General Comments: In this revision of their manuscript, Zhang et al have attempted to address most of the points raised by the reviewers, however, they have not assuaged my most important concerns. The manuscript contains a ton of information, but at times this is to the detriment of the narrative flow. I had a lot of trouble following the rationale of each experiment, and the throughline from one experiment to the next is not always obvious. The data are intriguing, and some of the experiments are quite convincing, but other experiments are either superfluous or have methodological issues. I will summarize the most acute issues below.

• *Answer: Thank you for your thoughtful feedback and for acknowledging our efforts to address your previous comments. We appreciate your recognition of the intriguing nature of our data and the convincing aspects of our experiments. In this second revision, we have taken your concerns regarding the narrative flow and data overload to heart. We have completely reshaped our manuscript, significantly reducing unnecessary data, including the NP5270 data and overlapping quantification results that did not contribute meaningfully to the storytelling. Our goal was to streamline the presentation of our findings to enhance clarity and coherence, ensuring that each experiment clearly supports the overarching narrative. We believe these revisions will not only improve the readability of our manuscript but also allow readers to follow the rationale behind each experiment more easily. We are confident that this refined approach will make our contributions clearer and more impactful. Thank you once again for your constructive insights, which have been invaluable in guiding us toward a more focused and compelling presentation of our work.

Comment 1. *The authors argue that genetic controls are unnecessary because they have been conducted in previously published papers. I am concerned with this argument, as it is good practice to repeat controls with each experiment. However, I am overall convinced by the basic phenotype indicating that panneuronal SIFaR knockdown eliminates the changes in mating duration associated with previous experience. As for the more restricted 24F06-GAL4, the phenotype is odd-the flies do actually change their mating duration, just in the opposite direction of controls. Doesn't this imply that these flies are still capable of "interval timing", and of changing their mating strategy following exposure to rivals or following sexual experience? *

• *

__ Answer:__ We appreciate the reviewer's critical comments regarding genetic control and the intriguing phenotypes we observed in specific genetic combinations. We fully agree with the reviewer and have repeated all genetic control experiments for this revision, confirming that our genetic controls consistently demonstrate intact LMD and SMD behaviors, as previously reported. These genetic control experiments have been included in Supplementary Information 1-2. We are grateful to the reviewer for the opportunity to reaffirm that LMD and SMD represent stable behavioral phenotypes suitable for genetically studying interval timing, supported by reproducible data.

• *

We acknowledge the reviewer's insightful comments about the exciting phenotype observed when SIFaR is knockdown which shows both singly reared and sexually experienced male show lengthened mating duration in contrast to normal LMD and SMD behaviors. Actually, we have observed such phenotype when specific neural circuits are disrupted such as when sNPF peptidergic signaling is disrupted in restricted neuronal population [4]. We are now investigating such phenotype as hypothesis as disinhibition. We explained this phenotype and about disinhibition in main text as below.

In the spatial, the targeted reduction of SIFaR expression in the GAL424F06 neuronal subset resulted in a notable alteration of mating behavior. Both singly reared and sexually experienced flies exhibited an extended mating duration relative to naïve flies, contrary to the expected reduction. This observation indicates a deficit in the neural mechanism responsible for modulating mating duration, suggesting a disinhibition-like effect within the neural circuitry governing mating behavior. We have also previously observed a similar phenotype when sNPF peptidergic signaling is inhibited in specific neuronal circuits [62]. Disinhibition, characterized by the alleviation of inhibitory constraints, permits the activation of neural circuits that are ordinarily repressed. This process is instrumental in sculpting behavioral patterns and facilitating the sequential progression of behaviors. Through the orchestrated promotion of select neuronal activation and concurrent inhibition of competing neural routes, disinhibition empowers the brain with the ability to dynamically ascertain and preserve the requisite behavioral state, concurrently smoothing the transition to ensuing behavioral phases [63]. It is known that Drosophila neural circuits also exhibit disinhibition phenotypes in light preference and ethanol sensitization [64,65]. Further investigation is needed to uncover the underlying mechanisms of this disinhibition-like phenotype observed in LMD and SMD behaviors.

This reversed phenotype strongly suggests a disruption in interval timing, as one would expect that if interval timing were normal and intact, male flies would decrease their mating duration in response to appropriate environmental changes. For instance, research has shown that patients with Parkinson's disease exhibit heterogeneity in temporal processing, leading to disrupted interval timing phenotypes [5]. Therefore, if male flies subjected to social isolation or sexual experience do not show a reduction in mating duration compared to control conditions, it indicates a potential disruption in their interval timing mechanisms. We appreciate the reviewer's encouragement to further explore this intriguing disinhibition-like phenotype, and we plan to investigate this aspect in our future projects.

Comment 2. *I am glad the see the addition of data assessing the extent of SIFaR and CrzR RNAi knockdown; however, this has not completely addressed my concerns about interpretation of behavioral phenotypes. In both cases, the knockdown was assessed by qPCR using the very strong tub-GAL4 driver. mRNA levels are decreased but not nearly eliminated. Thus, when in line 177-178 the authors assert: "Consequently, we infer that the knockdown of SIFaR using the HMS00299 line nearly completely diminishes the levels of the SIFaR protein," the statement is not supported by the data. The qPCR results showed a knockdown at the mRNA level of ~50%. No assays were conducted to measure protein levels. The conclusions should be tempered to align with the data. Furthermore, it is not clear that knockdown is as successful with other drivers, which means that negative behavioral data must be interpreted with caution. For example, the lack of phenotype with repo-GAL4 driving SIFaR RNAi or elav-GAL4 driving CrzR RNAi could be due to a lack of efficient knockdown. This should be acknowledged. *

   __Answer:__ We appreciate the reviewer's critical observation regarding the efficiency of SIFaR knockdown. We fully agree that it is essential to confirm both for ourselves and our readers that the SIFaR knockdown phenotype is robust and convincing. At the outset of this project, we tested all available SIFaR-RNAi strains following established protocols within the fly community to ensure consistency in our findings. When we employed strong drivers such as tub-GAL4 and nSyb-GAL4 for SIFaR-RNAi knockdown, we observed that the flies failed to eclose and exhibited a lethal phenotype during the larval stage, which closely resembles the homozygous lethal phenotype seen in SIFaR mutants. This suggests that, in most cases, the effects of SIFaR knockdown can effectively mimic those of SIFaR mutations. To share our methodology and reinforce our findings, we have added clarifying statements in the main text as follows:

"Employment of broad drivers, including the tub-GAL4 and the strong neuronal driver nSyb-GAL4, with HMS00299 line consistently results in 100% embryonic lethality (data not shown). This phenotype mirrors the homozygous lethality observed in the SIFaRB322 mutant."

• *

Due to the significant lethality phenotype observed, we conducted PCR analyses using a combination of tub-GAL80ts and SIFaR-RNAi. As detailed in Fig. 1E, we reared the flies at 22{degree sign}C to suppress RNAi expression and then shifted the temperature to 29{degree sign}C for just three days prior to performing PCR. While our PCR results indicate a 50% reduction in SIFaR levels, we believe that experiments conducted without the tub-GAL80ts system would likely demonstrate an even greater reduction in SIFaR expression. To clarify this point and provide additional context, we have included the following description in the main text:

"The silencing of SIFaR mRNA was achieved at approximately 50% using the HMS00299 knockdown line in combination with tub-GAL80ts, with RNAi induction lasting for three days (bottom diagram in Fig. 1E). Notably, the same tub-GAL4 driver, when used without the tub-GAL80ts combination, resulted in embryonic lethality while still reducing SIFaR mRNA levels by 50% after three days of RNAi induction. This finding suggests that SIFaR knockdown using the HMS00299 line with GAL4 drivers is likely sufficient to elicit the observed LMD and SMD behaviors. This rationale underscores the effectiveness of our experimental approach and its potential implications for understanding the role of SIFaR in mating behaviors."

We also concur with the reviewer that the absence of a behavioral phenotype associated with CrzR-RNAi may be due to inefficient RNAi knockdown. Consequently, we have included a description of this issue in the main text as follows:

• *

"It is important to consider that the 50% knockdown of SIFaR and CrzR may be sufficient to disrupt LMD and/or SMD behavior. However, the lack of phenotype with repo-GAL4 or elav-GAL4 could be due to a less efficient knockdown. This possibility highlights the need for cautious interpretation of negative behavioral data."

Comment 3. *Regarding the issue of outcrossing, I am confused by the authors' statement: "To reduce the variation from genetic background, all flies were backcrossed for at least 3 generations to CS strain. For the generation of outcrosses, all GAL4, UAS, and RNAi lines employed as the virgin female stock were backcrossed to the CS genetic background for a minimum of ten generations. Notably, the majority of these lines, which were utilized for LMD assays, have been maintained in a CS backcrossed state for long-term generations subsequent to the initial outcrossing process, exceeding ten backcrosses." It's not clear what this means. Perhaps the authors could definitively state how many times each line was outcrossed. The genetic background is important because of 1) the lack of all controls, and 2) the variability of the behavioral phenotype. Often, the presence or absence of LMD or SMD appears to depend on the behavior of the control flies. When these flies show low mating duration, there is typically not a reduction following sexual experience or group raising. Could these differences derive from genetic background or transgenic insertion effects? *

Answer: We appreciate the reviewer's concern regarding the potential for confusion stemming from our descriptions of the genetic background. As the reviewer noted, we have published multiple papers on LMD and SMD behaviors, and we have conducted our experiments with careful attention to controlling the genetic background [1-3,6-8]. In response to the reviewer's comments about the importance of genetic control and background, we have completed all necessary genetic control experiments and confirmed that all our flies have been backcrossed for more than ten generations to the Canton-S (CS) strain. We believe that we have adequately addressed the reviewer's concerns regarding potential differences arising from genetic background or transgenic insertion effects. To provide readers with more detailed information about our genetic background, we have added a paragraph in the MATERIALS AND METHODS section as follows:

"The CS background was selected as the experimental background due to its well-characterized and consistent LMD and SMD behaviors. To ensure that genetic variation did not confound our results, all GAL4, UAS, and RNAi lines employed in our assays were rigorously backcrossed into the CS strain, often exceeding ten generations of backcrossing. This approach was undertaken to isolate the effects of our genetic manipulations from those of genetic background. We assert that the extensive backcrossing to the CS background, in concert with the internal control in LMD and SMD, provides a stable platform for the accurate interpretation of the LMD and SMD phenotypes observed in our experiments."

Comment 4. *I continue to have substantial concerns about the thresholding method used across many experiments to quantify overlap, and then to claim that this indicates that synaptic connections are being made between different neuronal populations. The degree of overlap will depend on factors including the settings during imaging (was care taken to prevent pixel saturation?). It is also not clear to me from the methods whether analysis was done on single confocal images or on projections. The images shown in the figures look like maximum projections of a confocal stack. Overlap would have to be assessed on individual confocal sections-it is possible that this is what was done for analysis but not clear from the description in the methods. Furthermore, a lot of figure space is dedicated to superfluous information. For example, in Figure 1F-J, there is a massive amount of space dedicated to assessing the agree of overlap between red stinger and CD4GFP, each driven from the same SIFaR2A driver, and further assessing what percentage of the CD4GFP signal overlaps with nc82, with the apparent goal of showing that a lot of the SIFaR signal is at active zones. This information does little to drive the narrative forward, and is quite confusing to read. Finally, the confocal images are generally too small to actually assess. *

   __Answer:__ We appreciate the reviewer's concerns regarding our imaging quantification methods. We recognize the importance of providing a clear and transparent methodology for both readers and the broader scientific community. Instead of using maximum projection of confocal images, we employed a projection method that incorporates the standard deviation function available in ImageJ. Based on our experience, this approach yields more reliable quantification results, allowing for a more accurate assessment of our data. To ensure clarity and reproducibility, we have detailed our methods in the MATERIALS AND METHODS section as follows:

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"The quantification of the overlap was performed using confocal images with projection by standard deviation function provided by ImageJ to ensure precise measurements and avoid pixel saturation artifacts."

We appreciate the reviewer's suggestion regarding the inclusion of image quantification data for overlapping regions, which may not be essential to the logical flow of our narrative and could lead to confusion for readers. In response, we have removed nearly all of the quantification data related to overlapping regions, retaining only those that we consider critical for the paper. Currently, only Fig. S3B-E remains, as it is important for illustrating how SIFa neuronal arborization interacts with SIFaR neurons in the central nervous system.

Additionally, we fully agree with the reviewer that the overall size of the confocal images was too small for effective assessment. To address this concern, we have enlarged all confocal images and increased the spacing in the figures. We believe these improvements will enhance the clarity of our manuscript and facilitate a better understanding of our findings.

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Comment 5. *In general, the figures are still very cluttered, with panels too close together, and the labels are hard to read. *

Answer: We thank the reviewer for their valuable feedback regarding the clarity of our figures. In response to their concern, we have enlarged the figures to enhance readability and ensure that the panels are more distinct. We believe these adjustments will significantly improve the viewer's ability to interpret the data. We appreciate the reviewer's attention to detail, which has helped us to refine the presentation of our findings.

Comment 6. *There are no methodological details on how the VFB was used. The authors have not addressed my concern that they are showing only the neuronal skeleton (rather than the actual site of synapses). They are simply identifying all locations where the neuronal skeleton overlaps an entire brain region, and suggesting that these represent synapses. Many papers use the VFB to denote the actual location of synapses, which should be done in Figures 3B and S4A. *

Answer: We appreciate the reviewer's constructive comments regarding the methodological details of using VFB data. We fully agree that we cannot draw definitive conclusions about SIFa projections to specific regions based solely on neuronal skeleton data, which do not indicate the actual locations of synapses. To address this concern, we have made it clear to readers that the VFB skeleton data serves only as a preliminary indication of potential SIFa projections to GA, FB, and AL.

To confirm the presence of actual synapses from SIFa neurons, we conducted a thorough analysis using FlyWire data, which validated our findings from VFB. By integrating insights from VFB with the detailed synaptic mapping provided by FlyWire, we can confidently assert the functional relevance of these connections within the context of SIFa neuronal activity. This comprehensive approach not only bolsters our conclusions but also enhances our understanding of how SIFa neurons interact within the broader neural circuitry. We believe this rationale highlights the significance of our work in elucidating the complex relationships among these neuronal populations. We have detailed our findings in the main text as follows:

"We utilized the "Virtual Fly Brain (VFB)" platform, an interactive tool designed for exploring neuronal connectivity, to gain insights into the connectivity of SIFa neurons with four other neurons, specifically GA, FB, and AL (Fig. 3B and Fig. S4B) [74]. While VFB provides valuable information, it does not offer precise locations of synapses originating from SIFa neurons. To address this limitation, we incorporated data from the FlyWire connectome, which allowed us to confirm that SIFa projections indeed form actual synapses with GA, AL, FB, and SMP (Fig. S3F and S3G) [75]. This multi-faceted approach enhances the robustness of our findings by integrating different data sources to validate neuronal connections."

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Comment 7. *The changes in GRASP and CaLexA with experience are very interesting, and suggest a substantial rearrangement of synaptic connectivity associated with changes in mating duration following group rearing or female exposure. I am still concerned, however, that the nsyb and tGRASP images look so different. I wouldn't expect them to be identical, but it is puzzling that the nsyb-GRASP data show connections in a few discrete brain areas, while the tGRASP data show connections in a much larger overall brain area, but curiously not in the major regions seen with nsyb-GRASP (ie PI, FB and GA). Shouldn't the tGRASP signal appear in all the places that the nsyb-GRASP does? For CaLexA and GRASP data, the methods should indicate the timing of the dissections and staining relative to the group/sexual experience. *

Answer: We appreciate the reviewer's constructive comments regarding our GRASP data, which indeed reveal an intriguing neural plasticity phenotype, as the reviewer noted. In our previous response, we suggested that the observed differences may be attributed to the distinct SIFa-GAL4 strains utilized, as described in another manuscript focused on SIFa inputs [9]. In that manuscript, we classified the four SIFa neurons into two groups: SIFaDA (dorsal-lateral) and SIFaVP (ventral-posterior). The SIFa2A-GAL4 specifically labels only the SIFaVP neurons, while the SIFa-PT driver labels all four neurons. We acknowledge that we did not clearly communicate this distinction to the reviewer or our readers, and we apologize for any confusion this may have caused. To rectify this oversight, we have added a detailed explanation of these differences in the main text as follows:

"The subtle differences in GRASP signals observed in Fig. 3A may stem from the distinct expression patterns of the SIFa2A-lexA and GAL4SIFa.PT drivers. We would like to emphasize that the SIFa2A driver labels only a subset of SIFa neurons in other regions (Kim 2024)."

We recognize that a clear and transparent methodology is essential for generating reproducible data. In response to the reviewer's suggestion, we have revised our MATERIALS AND METHODS section to include more detailed descriptions of the dissection conditions. This enhancement aims to provide readers with the necessary information to replicate our experiments effectively.

"To ascertain calcium levels and synaptic intensity from microscopic images, we dissected and imaged five-day-old flies of various social conditions and genotypes under uniform conditions. For group reared (naïve) flies, the flies were reared in group condition and dissect right after 5 days of rearing without any further action. For single reared flies, the flies were reared in single condition and dissect at the same time as group reared flies right after 5 days of rearing without any further action. For sexual experienced flies, the flies were reared in group condition after 4 days of rearing and will be given virgins to give them sexual experience for one day, those flies will also be dissected at the same time as group and single reared flies after one day."

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Comment 8. *The calcium imaging data are odd. In most cases, the experimental flies don't actually show an increase in calcium levels but rather a lack of a decrease that is present in the ATR- controls. Also, in the cases where they argue for an excitatory affect of SIF neuron stimulation, the baseline signal intensity appears higher in ATR- controls compared to ATR+ experimental flies (eg Fig 5L, 6O), while it is significantly higher in ATR+ flies compared to ATR- controls when the activation results in decreased calcium signals. Perhaps more details on how these experiments were conducted and whether data were normalized in some way would help to clarify this. *

Answer: Thank you for your valuable feedback. We appreciate your careful analysis of our calcium imaging data and have addressed your concerns below:

In our experiments, we observed that ATR+ flies maintained relatively stable calcium levels, whereas ATR- controls exhibited a gradual decrease. Under confocal imaging, GFP signals typically decrease over time, which we observed in ATR- controls. However, ATR+ flies did not exhibit this decline. To better convey this observation, we have refined the language in the manuscript. Specifically, we now describe this as a tendency to sustain the activity of Crz neurons in the OL and AG regions (Fig. 6K-M, Fig. S6G-I). This is supported by the sustained intracellular calcium activity in ATR+ flies compared to the gradual decline to baseline levels observed in ATR- controls (Fig. 6K-M).

Baseline signal intensity differences: You correctly noted that in some cases, the baseline signal intensity appears higher in ATR- controls compared to ATR+ flies. These differences are likely due to technical factors, such as variations in the distance between the imaged brain and the objective lens. Even minor positional shifts in the brain (forward or backward) can affect the observed signal intensity.

Our analyses focus on relative changes in fluorescence intensity within the same sample, which we present as line graphs to highlight trends rather than absolute values. However, we acknowledge that showing the magnitude of relative values instead of absolute values may have caused some confusion. We have revised the images to better align with our conclusions, ensuring that the adjustments do not affect the observed relative changes.

Normalization and experimental details: The calcium imaging data were normalized to ΔF/F to account for differences in baseline fluorescence intensity. However, we recognize that further clarification of the normalization process and experimental setup is essential. We have expanded the methods section to include detailed descriptions of data acquisition, normalization steps, and statistical analyses.

As the reviewer correctly noted, calcium signals in ATR+ flies are generally higher than those in ATR- flies. However, it appears that the calcium levels exhibit a maintained response rather than a dramatic increase compared to the control ATR- condition, particularly in the case shown in Fig. 6K, which illustrates SIFa-to-Crz signaling. We believe this observation may reflect the actual physiological conditions under which SIFa influences SIFaR neurons to sustain activity during activation. We have included our interpretation of these findings in the main text as follows:

"Upon optogenetic stimulation of SIFa neurons, we observed a tendency to maintain the activity of Crz neurons in OL and AG regions (Fig. 6K-M, Fig. S6H-J), evidenced by a sustained activity in intracellular Ca2+ levels that persisted in a high level compared to control ATR- condition which shows gradual declining to baseline levels (Fig. 6K-M). In contrast to the OL and AG regions, the cells in the upper region of the SIP consistently show a decrease in Ca2+ levels following stimulation of the SIFa neurons (Fig. 6N-P)."

To enhance readers' understanding of our calcium imaging results, we have reformatted our GCaMP data for improved clarity and included additional details in the MATERIALS AND METHODS section regarding the quantification of GCaMP imaging methods. Furthermore, as the reviewer correctly noted, discrepancies in baseline activity were due to our error in presenting the baseline data. We have now corrected this oversight accordingly.

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Comment 9. *The models in Fig 4 J and T show data from Song et al, though I could not find a citation for this. I would omit this part of the model since these data are not discussed at all in the manuscript. *

Answer: We appreciate the reviewer for correctly identifying our oversight in failing to properly cite Song et al.'s paper. This error occurred partly because the preprint was not available at the time we submitted our manuscript. We now have a preprint for Song et al.'s paper, which discusses the contributions of SIFa neurons to various energy balance behaviors, and we plan to submit this paper back-to-back with our current submission to PLOS Biology. We have briefly cited Song et al.'s work in the manuscript; however, we have removed references to it from Fig. 4J and T to avoid any potential confusion for readers.

Comment 10. *The graphs for the SCOPE data (eg Figure 8I-L) are still too small to make sense of. *

Answer: We enlarged the tSNE plot generated from the SCOPE data.

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Comment 11. The rationale behind including the data in Figure 9 is not well explained. I would omit this data to help streamline and focus the manuscript.

Answer: We fully understand and agree with the reviewer's concerns, and we have removed all previous versions of Figure 9 from the manuscript to prevent any confusion regarding the storyline.

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Comment 12. *The single control group is still being duplicated in two different graphs but with different names in each graph. The authors updated figure caption hints at this but does not make it explicit. At the very least, these should be given the same name across all graphs, as is done, for example, in the CaLexA experiments in Figure 4B-C. *

Answer: We concur with the reviewer and have changed the label for all "group" conditions to "naïve" in all figures.

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Comment 13. *Lines 640-641: Moreover, the pacemaker function is essential for the generation of interval timing capabilities (Meck et al, 2012; Matell, 2014; Buhusi & Meck, 2005), with the heart being recognized as the primary pacemaker organ within the animal body". This is an intriguing idea, however, I attempted to look at the cited references and don't see any claim about the heart being involved in interval timing. I could not find a paper matching the citation of Matell 2014. Meck et al 2012 is an introduction to a Frontiers in Integrative Neuroscience Research Topic and does not mention the heart, nor does the Buhusi and Meck 2005 paper. Perhaps there is a more suitable reference to make the assertion that the fly's interval timer would be affected by changes in heart rate. My suggestion would be to simplify the manuscript, focusing on the most robust findings-the behavioral effect of SIFaR knockdown, the GRASP and CaLexA data showing differences following group rearing or female exposure, and the effect of Crz knockdown in SIFaR neurons. Other details could be included but would have to be verified with more rigorous experiments. *

__ Answer:__ We appreciate the reviewer's interest in our exploration of the role of heart function in interval timing. While we found that knocking down CrzR in the heart specifically disrupts LMD behavior, we agree that our manuscript needs to be streamlined for clarity. As a result, we have eliminated all CrzR-RNAi knockdown data except for the oenocyte, neuronal and glial knockdown data presented in Fig. S8C-H. This decision was made to ensure a more focused comparison with the SIFaR knockdown experiments shown in Fig. 1. We are dedicated to further investigating the role of Crz-CrzR in heart function and its influence on interval timing in a future project. This approach allows us to maintain clarity in our current manuscript while laying the groundwork for more comprehensive studies ahead.

In line with the reviewer's suggestions, we have simplified our manuscript by eliminating unnecessary data, such as overlapping image quantification and CrzR-RNAi screening, allowing us to focus on SIFaR knockdown and GRASP, as well as CaLexA with GCaMP imaging. We are grateful to the reviewer for providing us with the opportunity to delineate the role of CrzR in heart function related to LMD as a significant future project. We believe that our manuscript has been greatly improved by the reviewer's constructive feedback.

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Reviewer #2

General Comments:* The authors investigate mating behavior in male fruit flies, Drosophila melanogaster, and test for a role of the SIFamide receptor (SIFaR) in this type of behavior, in particular mating duration in dependence of social isolation and prior mating experience. The anatomy of SIFamide-releasing neurons in comparison with SIFamide receptor-expressing neurons is characterized in a detail-rich manner. Isolating males or exposing them to mating experience modifies the anatomical organization of SIFamidergic axon termini projecting onto SIFamide receptor-expressing neurons. This structural synaptic plasticity is accompanied by changes in calcium influx. Lastly, it is reported that corazonin-releasing neurons are modulated by SIFamide releasing neurons and impact the duration of mating behavior.

Overall, this highly interesting study advances our knowledge about the behavioral roles of SIFamide, and contributes to an understanding how motivated behavior such as mating is orchestrated by modulatory peptides. The manuscript has some points that are less convincing.*

__ Answer:__ We appreciate the reviewer's positive feedback regarding our investigation into the role of the SIFamide receptor (SIFaR) in mating behavior in male Drosophila melanogaster. We are pleased that the detailed characterization of SIFamide-releasing neurons and their anatomical changes in response to social isolation and mating experience has been recognized as a valuable contribution to the understanding of synaptic plasticity and its impact on behavior. We are also grateful that the reviewer described our manuscript as a "highly interesting study" that advances knowledge about the behavioral roles of SIFamide and contributes to the understanding of how motivated behaviors, such as mating, are orchestrated by modulatory peptides. We sincerely thank the reviewer for these encouraging comments about our work.

We acknowledge the reviewer's concerns about certain aspects of our manuscript that may be less convincing. We are committed to addressing these points thoroughly to strengthen our arguments and enhance the clarity of our findings. In response to the feedback, we have made several revisions throughout the manuscript, including clarifying our methodology, enhancing the presentation of our data, and providing additional context where needed. We believe these changes will improve the overall quality of the manuscript and make our conclusions more compelling. Thank you for your thoughtful review, and we look forward to your further insights.

Comment 1. *It remains unclear why the authors link the differentially motivated duration of mating behavior with the psychological concept of interval timing. This distracts from the actually interesting neurobiology and is not necessary to make the study interesting. The study deals with the modulation of mating behavior by SIFamide. The abstraction that SIFamide plays a role in the neuronal calculation of time intervals for the perception of time sequenc es is not convincing in itself. *

• Answer: We appreciate the reviewer's thoughtful comments regarding our conclusion that links SIFamide to interval timing in mating behavior. We recognize that our data primarily indicate that SIFamide is essential for normal mating duration and influences the motivation-dependent aspects of this behavior. We also acknowledge the need for more robust evidence to establish a clearer connection between these findings and interval timing. Recent research by Crickmore et al. has provided valuable insights into how mating duration in Drosophila *serves as an effective model for examining changes in motivation over time as behavioral goals are achieved. For example, around six minutes into mating, sperm transfer occurs, resulting in a significant shift in the male's nervous system, where he no longer prioritizes continuing the mating at the expense of his own survival. This pivotal change is mediated by four male-specific neurons that release the neuropeptide Corazonin (Crz). When these Crz neurons are inhibited, sperm transfer does not take place, and as a result, the male fails to reduce his motivation, leading to matings that can extend for hours instead of the typical duration of approximately 23 minutes [10].

Recent research conducted by Crickmore et al. has secured NIH R01 funding (Mechanisms of Interval Timing, 1R01GM134222-01) to investigate mating duration and sperm transfer timing in Drosophila as a genetic model for understanding interval timing. Their study emphasizes how fluctuations in motivation over time can affect mating behavior, particularly noting that significant behavioral changes occur during mating. For instance, around six minutes into the mating process, sperm transfer takes place, which corresponds with a notable decrease in the male's motivation to continue mating [10]. These findings indicate that mating duration serves not only as an endpoint for behavior but may also reflect fundamental mechanisms associated with interval timing.

   We believe that by leveraging the robustness and experimental tractability of these findings, along with our own work on SIFamide's role in mating behavior, we can gain deeper insights into the molecular and circuit mechanisms underlying interval timing. We will revise our manuscript to clarify this relationship and emphasize how SIFamide may interact with other neuropeptides and neuronal circuits involved in motivation and timing.

   In addition to the efforts of Crickmore's group to connect mating duration with a straightforward genetic model for interval timing, we have previously published several papers demonstrating that LMD and SMD can serve as effective genetic models for interval timing within the fly research community. For instance, we have successfully connected SMD to an interval timing model in a recently published paper [3], as detailed below:

"We hypothesize that SMD can serve as a straightforward genetic model system through which we can investigate "interval timing," the capacity of animals to distinguish between periods ranging from minutes to hours in duration.....

In summary, we report a novel sensory pathway that controls mating investment related to sexual experiences in Drosophila. Since both LMD and SMD behaviors are involved in controlling male investment by varying the interval of mating, these two behavioral paradigms will provide a new avenue to study how the brain computes the 'interval timing' that allows an animal to subjectively experience the passage of physical time [11-16]."

   Lee, S. G., Sun, D., Miao, H., Wu, Z., Kang, C., Saad, B., ... & Kim, W. J. (2023). Taste and pheromonal inputs govern the regulation of time investment for mating by sexual experience in male Drosophila melanogaster. *PLoS Genetics*, *19*(5), e1010753.

   We have also successfully linked LMD behavior to an interval timing model and have published several papers on this topic recently [6-8].

   Sun, Y., Zhang, X., Wu, Z., Li, W., & Kim, W. J. (2024). Genetic Screening Reveals Cone Cell-Specific Factors as Common Genetic Targets Modulating Rival-Induced Prolonged Mating in male Drosophila melanogaster. *G3: Genes, Genomes, Genetics*, jkae255.

   Zhang, T., Zhang, X., Sun, D., & Kim, W. J. (2024). Exploring the Asymmetric Body's Influence on Interval Timing Behaviors of Drosophila melanogaster. *Behavior Genetics*, *54*(5), 416-425.

   Huang, Y., Kwan, A., & Kim, W. J. (2024). Y chromosome genes interplay with interval timing in regulating mating duration of male Drosophila melanogaster. *Gene Reports*, *36*, 101999.

   Finally, in this context, we have outlined in our INTRODUCTION section below how our LMD and SMD models are related to interval timing, aiming to persuade readers of their relevance. We hope that the reviewer and readers are convinced that mating duration and its associated motivational changes such as LMD and SMD provide a compelling model for studying the genetic basis of interval timing in *Drosophila*.

"The dimension of time is the fundamental basis for an animal's survival. Being able to estimate and control the time between events is crucial for all everyday activities [25]. The perception of time in the seconds-to-hours range, referred to as 'interval timing', is involved in foraging, decision making, and learning via activation of cortico-striatal circuits in mammals [26]. Interval timing requires entirely different neural mechanisms from millisecond or circadian timing [27-29]. There is abundant psychological research on time perception because it is a universal cognitive dimension of experience and behavioral plasticity. Despite decades of research, the genetic and neural substrates of temporal information processing have not been well established except for the molecular bases of circadian timing [30,31]. Thus, a simple genetic model system to study interval timing is required. Considering that the mating duration in fruit flies, which averages approximately 20 minutes, is well within the range addressed by interval timing mechanisms, this behavioral parameter provides a relevant context for examining the neural circuits that modulate the Drosophila's perception of time intervals. Such an investigation necessitates an understanding of the extensive neural and behavioral plasticity underlying interval timing [32-37]."

We would like to highlight that many researchers are currently working to bridge the gap between interval timing as a purely psychological concept and its neurobiological underpinnings, as illustrated in the following articles [15,17-20]. We appreciate the reviewer's concerns regarding the relationship between mating duration and interval timing. However, we believe that our LMD and SMD model can effectively bridge the gap between psychological concepts and neurobiological mechanisms using a straightforward genetic model organism. By employing Drosophila as our model, we aim to elucidate the underlying neural circuits that govern these behaviors, thereby contributing to a deeper understanding of how interval timing is represented in both psychological and biological contexts.

Matell, M. S. Neurobiology of Interval Timing. Adv. Exp. Med. Biol. 209-234 (2014) doi:10.1007/978-1-4939-1782-2_12.

Matell, M. S. & Meck, W. H. Cortico-striatal circuits and interval timing: coincidence detection of oscillatory processes. Cogn. Brain Res. 21, 139-170 (2004).

Merchant, H. & Lafuente, V. de. Introduction to the neurobiology of interval timing. Adv Exp Med Biol 829, 1-13 (2014).

Golombek, D. A., Bussi, I. L. & Agostino, P. V. Minutes, days and years: molecular interactions among different scales of biological timing. Philosophical Transactions Royal Soc B Biological Sci 369, 20120465 (2014).

Balcı, F. & Toda, K. Editorial: Psychological and neurobiological mechanisms of time perception and temporal information processing: insight from novel technical approaches. Front. Behav. Neurosci. 17, 1208794 (2023).

Comment 2. *For all behavioral experiments, genetic controls should always be conducted. That is, both the heterozygous Gal4-line as well as the heterozygous UAS-line should be used as controls. This is laborious, but important and common standard. The authors often report data only for offspring from genetc crosses in which UAS-lines and Gal4-lines are combined (e.g. figure S1). This is not sufficient. *

• *Answer: We are grateful for the reviewer's constructive suggestions regarding the genetic control experiments. In response to similar concerns raised by another reviewer, we have conducted all necessary genetic control experiments and included the results in Supplementary Information 1-2. We hope that this thorough effort will demonstrate to both the reviewer and readers that the LMD and SMD behaviors represent stable and reproducible phenotypes for investigating the genetic components of interval timing.

Comment 3. *There are quite a lot of citations of preprints, including preprints from the authors's own lab. It seems inappropriate to cite non-peer reviewed preprints in order to present the basic principles of the study (interval timing in flies) as recognized knowledge. In general, it is unclear whether the information presented in these multiple preprints will turn out to be credible and acceptable. *

• *Answer: We concur with the reviewer and have removed most of the preprint material, retaining only one preprint that discusses SIFa function, which has been co-submitted with this manuscript.

Comment 4. *Anatomical images are often very small and not informative. For example, figure S1 O, R, S and U shows small images of fly brains and ventral nerve chords that do not convincingly describe the expression of fluorescent proteins. The choice of a threshold to quantify fluorescence seems arbitrary. It is also not clear what the quantification "83% of brain and 71% of VNC SIFaR+ neurons" actually tells us. This quantification does not rely on counting neurons (such as 83% of neurons), but only shows how fluorescence in these neurons overlaps with an immunostaining of an ubiquitous active zone protein. The same is true for figure S2 or S3: overlapping brain areas do not inform you about numbers of cells, as stated in the text. *

Answer: We appreciate the reviewer's concerns regarding our imaging quantification methods. In response to similar questions raised by another reviewer, we have thoroughly reformatted our methods section and eliminated much of the overlapping data that appeared unnecessary for this paper. We recognize the importance of providing a clear and transparent methodology for both readers and the broader scientific community. Instead of using maximum projection of confocal images, we employed a projection method that incorporates the standard deviation function available in ImageJ. Based on our experience, this approach yields more reliable quantification results, allowing for a more accurate assessment of our data. To ensure clarity and reproducibility, we have detailed our methods in the MATERIALS AND METHODS section as follows:

• *

"The quantification of the overlap was performed using confocal images with projection by standard deviation function provided by ImageJ to ensure precise measurements and avoid pixel saturation artifacts."

We appreciate the reviewer's suggestion regarding the inclusion of image quantification data for overlapping regions, which may not be essential to the logical flow of our narrative and could lead to confusion for readers. In response, we have removed nearly all of the quantification data related to overlapping regions, retaining only those that we consider critical for the paper. Currently, only Fig. S3B-E remains, as it is important for illustrating how SIFa neuronal arborization interacts with SIFaR neurons in the central nervous system.

Additionally, we fully agree with the reviewer that the overall size of the confocal images was too small for effective assessment. To address this concern, we have enlarged all confocal images and increased the spacing in the figures. We believe these improvements will enhance the clarity of our manuscript and facilitate a better understanding of our findings.

Comment 5. *The authors have consistently confused the extensive overlap of neuronal processes (dendrites and presynaptic regions) across large brain areas with synaptic connections. One cannot infer functional synaptic connectivity from the overlap of these fluorescent signals. *

Answer: We appreciate the reviewer's feedback and, in light of similar comments from another reviewer, we have removed most of the DenMark and syt.eGFP data, retaining only Fig. 3A. We are grateful for the constructive suggestions, which have significantly enhanced our manuscript. We believe that these revisions have clarified the narrative for readers, allowing for a more focused exploration of SIFaR's role in synaptic plasticity and neuronal orchestration.

Reviewer #3

General Comments: In this revised manuscript, the authors have fully and satisfactorily addressed my comments on the previous version. I recommend publication of this manuscript.

__ Answer:__ We would like to extend our heartfelt thanks for the careful consideration and positive assessment of our revised manuscript. Your insightful feedback has been instrumental in shaping the final version of our work, and we are delighted to hear that our revisions have met your expectations.

Your dedication to ensuring the quality and rigor of the scientific literature is truly commendable, and we are immensely grateful for the time and effort you have devoted to reviewing our paper. Your support for publication is a significant encouragement to us and validates the hard work we have put into addressing the issues you raised.

Please accept our sincere appreciation for your professional and constructive approach throughout the review process. We look forward to the possibility of contributing to the scientific community through the dissemination of our research.

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Author response:

The following is the authors’ response to the original reviews.

Public Reviews:

Reviewer #1 (Public Review):

Summary:

The work from Petazzi et al. aimed at identifying novel factors supporting the differentiation of human hematopoietic progenitors from induced pluripotent stem cells (iPSCs). The authors developed an inducible CRISPR-mediated activation strategy (iCRISPRa) to test the impact of newly identified candidate factors on the generation of hematopoietic progenitors in vitro. They first compared previously published transcriptomic data of iPSCderived hemato-endothelial populations with cells isolated ex vivo from the aorta-gonadmesonephros (AGM) region of the human embryo and they identified 9 transcription factors expressed in the aortic hemogenic endothelium that were poorly expressed in the in vitro differentiated cells. They then tested the activation of these candidate factors in an iPSCbased culture system supporting the differentiation of hematopoietic progenitors in vitro. They found that the IGF binding protein 2 (IGFBP2) was the most upregulated gene in arterial endothelium after activation and they demonstrated that IGFBP2 promotes the generation of functional hematopoietic progenitors in vitro.

Strengths:

The authors developed an extremely useful doxycycline-inducible system to activate the expression of specific candidate genes in human iPSC. This approach allows us to simultaneously test the impact of 9 different transcription factors on in vitro differentiation of hematopoietic cells, and the system appears to be very versatile and applicable to a broad variety of studies.

The system was extensively validated for the expression of 1 transcription factor (RUNX1) in both HeLa cells and human iPSC, and a detailed characterization of this test experiment was provided.

The authors exhaustively demonstrated the role of IGFBP2 in promoting the generation of functional hematopoietic progenitors in vitro from iPSCs. Even though the use of IGFBP2interacting proteins IGF1 and IGF2 have been previously reported in human iPSC-derived hematopoietic differentiation in vitro (Ditadi and Sturgeon, Methods 2016; Ng et al., Nature Biotechnology 2016), and IGFBP-2 itself has been shown to promote adult HSC expansion ex vivo (Zhang et al., Blood 2008), its role on supporting in vitro hematopoiesis was demonstrated here for the first time.

Weaknesses:

Although the authors performed a very thorough characterization of the system in proof-ofprinciple experiments activating a single transcription factor, the data provided when 9 independent factors were used is not sufficient to fully validate the experimental strategy. Indeed, in the current version of the manuscript, it is not clear whether the results presented in both the scRNAseq analysis and the functional assays are the consequence of the simultaneous activation of all 9 TF or just a subset of them. This is essential to establish whether all the proposed factors play a role during embryonic hematopoiesis, and a more complete analysis of the scRNAseq dataset could help clarify this aspect.

Similarly, the data presented in the manuscript are not sufficient to clarify at what stage of the endothelial-to-hematopoietic transition (EHT) the TF activation has an impact. Indeed, even though the overall increase of functional hematopoietic progenitors is fully demonstrated, the assays proposed in the manuscript do not clarify whether this is due to a specific effect at the endothelial level or to an increased proliferation rate of the generated hematopoietic progenitors. Similar conclusions can be applied to the functional validation of IGFBP2 in vitro.

The overall conclusions are sometimes vague and not always supported by the data. For instance, the authors state that the CRISPR activation strategy resulted in transcriptional remodeling and a steer in cell identity, but they do not specify which cell types are involved and at what level of the EHT process this is happening. In the discussion, the authors also claim that they provided evidence to support that RUNX1T1 could regulate IGFBP2 expression. However, this is exclusively based on the enrichment of RUNX1T1 gRNA in cells expressing higher levels of IGFBP2 and it does not demonstrate any direct or indirect association of the two factors.

We thank the reviewer for the positive comments about the importance of our work and have now addressed the points raised as weaknesses by performing additional analysis and experiments, adding a new schematic of the mechanism, and rewording our claims.

We have clarified the different effects mediated by the activation and the IGFBP2 addition in a summary section at the end of the results and added Figure 6, showing this in visual form. We have also clearly stated the limitations related to the correlation between RUNX1T1 and IGFBP2 in the discussion and toned down our claims regarding this throughout the entire paper. We have also reworded the text to clarify the specific cell types identified in the sequencing data that we refer to.

Reviewer #2 (Public Review):

To enable robust production of hematopoietic progenitors in-vitro, Petazzi et al examined the role of transcription factors in the arterial hemogenic endothelium. They use IGFBP2 as a candidate gene to increase the directed differentiation of iPSCs into hematopoietic progenitors. They have established a novel induced-CRISPR mediated activation strategy to drive the expression of multiple endogenous transcription factors and show enhanced production of hematopoietic progenitors through expansion of the arterial endothelial cells. Further, upregulation of IGFBP2 in the arterial cells facilitates the metabolic switch from glycolysis to oxidative phosphorylation, inducing hematopoietic differentiation. While the overall study and resources generated are good, assertions in the manuscript are not entirely supported by the experimental data and some claims need further experimental validation.

We thank the reviewer for the positive comments, and we have provided new data and analysis to make sure that all our assertations are clearly supported and also reworded those where limitations were identified by the reviewers.

Recommendations for the authors:

Reviewing Editor (Recommendations For The Authors):

The assessment could change from "incomplete" to "solid" if the authors: i) improve data analysis (for both scRNAseq and functional assays) by providing additional information that could strengthen their conclusions, as suggested in the specific comments by both reviewers; ii) either provide new functional evidence supporting their mechanistic conclusion or alternatively tone down the claims that are not fully supported by data and acknowledge the limitations raised by reviewers in the discussion; (iii) the issue of paracrine signaling to expand only hematopoietic progenitors needs to be addressed.

We have now improved the data analysis and provided additional functional tests to strengthen our conclusions and toned down those that were identified by the reviewers as not supported enough and included a discussion on these limitations. We have also reworded the section about the paracrine signaling throughout the paper.

Reviewer #1 (Recommendations For The Authors):

Figure 1 contains exclusively published data. It might be more appropriate to use it as a supplementary figure or as part of a more exhaustive figure (maybe combining Figures 1 and 2 together?).

Figure 1 contained novel bioinformatic analyses that represent the base of our research and it has a different content and focus to figure 2, which is already a large figure. We therefore believe it is better to keep it as a separate figure, containing a new panel now too. 

It seems there is an issue with Figure S3 labelling:

• In line 112, Figure S2A-B does not display genomic PCR and sequencing results;

• In line 123, Figure S3D-E does not show viability and proliferation data;

• In line 127, Figure S3G does not show mCherry expression in response to DOX;

We apologies for the confusion with the numbers, we have now correctly labelled the figures.

It would be more informative to include gates and frequency on flow cytometry plots in Figure S3, to be able to evaluate the extent of the reduction in mCherry expression.

We have now included the gating and frequency of mCherry-expressing cells in Supplementary Figure 3D.

It is not clear from the text and figures whether the SB treatment was maintained throughout the hematopoietic differentiation protocol (line 122):

• If so, it would be important to confirm that HDAC treatment does not affect EHT cultures

• If not, can the authors provide some evidence that transgene silencing is not occurring during hematopoietic differentiation?

We have clarified that we decided to treat the cells with SB exclusively in maintenance condihons because HDACs have been shown to be essenhal for the EHT (lines 138-142). We have now also included addihonal data showing the high expression of the mCherry tag reporhng the iSAM expression on day 8 (Supplementary Figure 4F).

Can the authors provide a simple diagram summarizing the experimental strategy for each differentiation experiment in the respective supplementary figure? For instance, at what stage of the protocol was DOX added in Figure 3? Or at what stage IGFBP2 was added in Figure 5? It would be a very useful addition to the interpretation of the results.

We have now included three schemahcs for all the experiments in the manuscript in supplementary figure 4 A-C.

In Figure 3, the authors should provide more detailed information about the data filtering of the scRNAseq experiment, and more specifically:

• How many cells were included in the analysis for each library after QC and filtering?

• How "cells in which the gRNAs expression was detected" were selected? Do they include only cells showing expression of gRNAs for all 9 TF?

This informahon is now included in the method sechon lines 773-781; the detailed code is available on the GitHub link provided in the same sechon. We have filtered the cells expressing one gRNA for the non-targehng gRNA (iSAM_NT) control and more than one for the iSAM_AGM sample. 

In Figure 3A, it is not clear whether the expression of the 9 factors is consistently detected in all cells or just a subset of them, and the heatmap in Figure 3A does not provide this information. It would be more accurate to provide expression on a per-cell basis, for instance, as a violin plot displaying single dots representing each cell. 

We have now included this violin plot in Supplementary Figure 4G as requested. However, this visualisation is difficult to interpret because some of the target genes’ expression seems variable in both experimental and control conditions. We had envisaged that this could have been the case and so this is why we had included the three different controls.  For this reason we chose to show the normalised expression which takes all the different variables into account (Figure 3A). 

In Figure 3B-C, it seems that clusters EHT1 and EHT2 do not express endothelial markers anymore. Are these fully differentiated hematopoietic cells rather than cells undergoing EHT? In general, it would be quite important to provide evidence of expressed marker genes characterizing each cluster (eg. heatmap summarizing top DEG in the supplementary figure?). 

We have now provided a spreadsheet containing the clusters’ markers that we used in

Supplementary Table 1) a heatmap in Figure 3E. Furthermor,e we have now edited Figure 3C to include Pan Endothelial markers (PECAM1 and CDH5). These data show that the EHT1 and EHT2 cluster both express endothelial markers but are progressively downregulated as expected during endothelial to hematopoietic transition. We have also included and discussed this in the manuscript lines 192-195 and a schematic for the mechanism in Figure 6.

In Figure 3E, displaying the proportion of clusters within each sample/library would be a more accurate way of comparing the cell types present in each library (removing potential bias introduced by loading different numbers of cells in each sample).

We have now included the requested data in Supplementary Figure 4I and it confirms again the expansion of arterial cells in the activated cells.    

In Figure 3G, by plating 20,000 total CD34+, the assay does not account for potential differences in sample composition. It is then hard to discriminate between the increased number of progenitors in the input or an enhanced ability of HE to undergo EHT. This is an important aspect to consider to precisely identify at what level the activation of the 9 factors is acting. A proper quantification of flow cytometry data summarizing the % of progenitors, arterial cells, etc. would be useful to interpret these results.

Lines 204-205 reworded. We are very much aware of the fact that the CD34+ cell population consists of a range of cells across the EHT process and this is precisely why we carried out this single cell sequencing analyses.  We purposely tested the effect of the observed changes in composition by colony assays

In Figure 3G, it seems that NT cells w/o DOX have very little CFU potential (if any). Can the authors provide an explanation for this?

We think that the limited CFU potential is due to the extensive genetic manipulation and selection that the cells underwent for the derivation of all the iSAM lines but this did not impede us from observing an effect of gene activation on CFU numbers. This is one of the primary reasons that we then validated our overall findings using the parental iPSC line in control condition and with the addition of IGFBP2. We show that the parental iPSC line gives rise to hematopoietic progenitor, both immunophenotypically (Figure 4D) and functionally, at expected levels (Figure 4B left column).

Figure 4A shows an upregulation of IGFBP2 in arterial cells as a result of TF activation. However, from the data presented here, it is not possible to evaluate whether this is specific to the arterial cluster, or it is a common effect shared by all cell types regardless of their identity. 

Data has now been included in Supplementary Figure 4H, which shows that all the cells show an increase in IGFBP2, but arterial cells show the highest increase. We have now edited the text to reflect this, in lines 228-230.

In Figure 5A-B only a minority of arterial cells express RUNX1 in response to IGFBP2 treatment. Is this sufficient to explain the very significant increase in the generation of functional hematopoietic progenitors described in Figure 4? Quantification and statistical analysis of RUNX1 upregulation would strengthen this conclusion.

We have now provided the statistical analysis showing significant upregulation of RUNX1 upon IGFBP2 addition. The p values are now provided in the figure 5 legend.

In Figure 5 the authors conclude that IGFBP2 remodels the metabolic profile of endothelial cells. However, it is not clear which cell types and clusters were included in the analysis of Figure 5C-G. Is the switch from Glycolysis to Oxidative Phosphorylation specific to endothelial cells? Or it is a more general effect on the entire culture, including hematopoietic cells? 

We based this conclusion on the fact that the single-cell RNAseq allows to verify that the metabolic differences are obtained in the endothelial cells. Given that we sorted the adherent cells, the majority of these are endothelial cells as shown in Figure 5A. The Seahorse pipeline includes a number of washing steps resulting in the analyses being performed on the adherent compartment which we know consists primarily of endothelial cells. We cannot exclude some contamination from non-endothelial cells but we highlight to this reviewer that the initial observation of the metabolic changes was identified in endothelial cells in the single cell sequencing data. Taken together, we believe that this implies that metabolic changes are specific to this population. We have clarified this in the line 317.

In the discussion, the authors conclude that they "provide evidence to support the hypothesis that RUNX1T1 could regulate IGFBP2 expression". To further support this conclusion, the authors could provide a correlation analysis of the expression of the two genes in the cell type of interest. 

Following the observation of the IGFBP2 high expression across clusters, we have now reworded this sentence in lines 382-385  We have tried to perform the correlation analysis but we believe this not to be appropriate due to the detection level of the gRNA, we have now included this as a limitation point in the discussion lines 416-427, and also toned down the conclusion we did draw about RUNX1T1 throughout the whole manuscript.

As mentioned by the authors, IGFBP2 binds IGF1 and IGF2 modulating their function. Both IGF1 (http://dx.doi.org/10.1016/j.ymeth.2015.10.001) and IGF2 (doi:10.1038/nbt.3702) have been used in iPSC differentiation into definitive hematopoietic cells. It would be relevant to discuss/reference this in the discussion.

We have now included the suggested reference in the section where we discuss the role of IGFBP2 in binding IGF1 and IGF2.

Reviewer #2 (Recommendations For The Authors):

(1) Figure 1 compares the transcriptome of human AGM and in-vitro derived hemogenic endothelial cells (HECs). It is not clear why only the genes downregulated in the latter were chosen. Are there any significantly upregulated genes, knockdown/knockout which could also serve a similar purpose? Single-cell transcriptome database analysis is very preliminary. A detailed panel with differences in cluster properties of HECs between the two systems should be provided. A heatmap of all differentially expressed genes between the two samples must be generated, along with a logical explanation for choosing the given set of genes. 

We have now included another panel in figure 1 to better clarify the logic behind the strategy used to identify our target genes (Figure 1A).

(2) Figure 2 - a panel describing the workflow of gRNA design and targeting for the 9 candidate genes, along with lentiviral packaging and transduction would make it easier to follow. 

We have now included three schematics for all the experiments in the manuscript in supplementary figure 4 A-C. 

(3) Figure 3- to assess the effect of arterial cell expansion on the emergence of hematopoietic progenitors, CD34+ Dll4+ cells should be sorted for OP9 co-culture assay.

Using only CD34+ cells does not answer the question raised. Also, the CFU assay performed does not fully support the claim of enhanced hematopoietic differentiation since only CFU-E and CFU-GM colonies are increased in Dox-treated samples, with no effect on other colony types. OP9 co-culture assay with these cells would be required to strengthen this claim. 

We wanted to clarify that the effect on the methylcellulose coming from the activated cells was not limited to CFU-E, as the reviewer reported; instead, it also affected CFU-GM and CFU-M. 

We have now performed additional experiments where we sorted the CD34+ compartment into DLL4- and DLL4+ in Supplementary Figure 5D-E, which we discussed in lines 250-258. 

(4) In Figure 3F, there appears to be a lot of variation in the DLL4% fold change values for

DOX treated iSAM_AGM sample, which weakens the claim of increased arterial expansion.

Can the authors explain the probable reason? It is suggested that the two other controls (iSAM_+DOX and iSAM_-DOX) should be included in this analysis. It is imperative to also show % populations rather than just fold change to gain confidence.

We agree that there is a lot of variability. That is because differentiation happens in 3D in embryoid bodies, which contain many different cell types that differentiate in different proportions across independent experiments. We have now included the raw data in Supplementary Figure 4 D, with additional statistical analysis to show the expansion of arterial cells including also the suggested additional controls.

(5) How does activation of these target genes cause increased arterialization? Is the emergence of non-HE populations suppressed? Or is it specific to the HE? The data on this should be clarified and also discussed. ANTO/Lesley text

We have provided additional data clarifying the connection between increased arterialisation and hemogenic potential. We showed that the activation induces increased arterialisation and that IGFBP2 acts by supporting the acquisition of hemogenic potential. We have discussed this in lines 326-348 and provided a new figure to explain this in detail (figure 6)

(6) Considering that IGFBP2 was chosen from the activated target gene(s) cluster, can the authors explain why the reduced CFU-M phenomenon observed in Figure 3G does not appear in the MethoCult assay for IGFBP2 treated cells (Figure 4B)?

The difference could be explained by the fact that in Figure 3G, the cells underwent activation of multiple genes, while in Figure 4B, they were only exposed to IGFBP2. Our results show that IGFBP2 could at least partially explain the phenotype that we see with the activation, but we believe that during the activation experiments, there might be other signals available that might not be induced by IGFBP2 alone. We have also added a summary section and a figure to clarify the different mechanisms of action of the gene activation and IGFBP2.

(7) Figure 4- while the experiments conducted support the role of IGFBP2 in increasing hematopoietic output, there is no experimental evidence to prove its function through paracrine signalling in HECs. The authors need to provide some evidence of how IGFBP2 supplementation specifically expands only the hematopoietic progenitors. Experimental strategies involving specifically targeting IGFBP2 in hemogenic/arterial endothelial cells are required to prove its cell type specific function. Additionally, assessing the in vivo functional potential of the hematopoietic cells generated in the presence of IGFBP2, by bone-marrow transplantation of CD34+ CD43+ cells, is essential. 

The role of IGFBP2 in the context of HSC production and expansion was not the topic of our research, and we have not claimed that IGFBP2  affects the long-term repopulating capacity of HSPCs. Therefore, we believe that the requested experiments are not required to support the specific claims that we do make. We have now provided more experiments and bioinformatic analysis that support the role of IGFBP2 in inducing the progression of EHT from arterial cells to hemogenic endothelium, and to avoid misunderstandings, we have toned down our claims by editing the text regarding its paracrine effect s. 

(8) Figure 4C-D -It is recommended to plot % populations along with fold change value. As this is a key finding, it is important to perform flow cytometry for additional hematopoietic markers- CD144, CD235a and CD41a to demonstrate whether this strategy can also expand erythroid-megakaryocyte progenitors. Telma

Figure 4C already shows the percentage values; we have now added the percentage for Figure 4D in SF5C. We have also performed additional analysis as requested and added the data obtained to Supplementary Figure 5D.

(9) In Figure 5, analysis showing the frequency of cells constituting different clusters, between untreated and IGFBP2-treated samples in the single-cell transcriptome analysis is essential. Additional experiments are required to validate the function of IGFBP2 through modulation of metabolic activity. Inhibition of oxidative phosphorylation in the IGFBP2treated cells should reduce the hematopoietic output. Authors should consider doing these experiments to provide a stronger mechanistic insight into IGFBP2-mediated regulation of hematopoietic emergence.

We have now included the requested cluster composition in Supplementary Figure 5F. We decided not to include further tests on the metabolic profile of IGFBP2 as we already discussed in other papers that showed, using selective inhibitors, that the EHT coincides with a glycol to OxPhos switch. 

(10) It is very striking to see that IGFBP2 supplementation changes the transcriptional profile of developing hematopoietic cells by increasing transcription of OXPHOS-related genes with concomitant reduction of glycolytic signatures, particularly at Day 13. However, the mitochondrial ATP rate measurements do not seem convincing. The bioenergetic profiles show that when mitochondrial inhibitors are added, both groups exhibit decreased OCR values and, on the other hand, higher ECAR. This indicates that both groups have the capability to utilize OXPHOS or glycolysis and may only differ in their basal respiration rates.

Differences in proliferation rate can cause basal respiration to change. There is no information on how the bioenergetic profile was normalized (cell no./protein amount). Given that IGFBP2 has been shown to increase proliferation, it is very likely that the cells treated with IGFBP2 proliferated faster and therefore have higher OCR. The data needs to be normalized appropriately to negate this possibility.

We have previously tested whether IGFBP2 causes an increase in proliferation by analysing the cell cycle of cells treated with it, as we initially thought this could be a mechanism of action. We have now provided the quantification of the cell cycle in the cells treated with IGFBP2, showing no effect was observed in cell cycle Supplementary Figure 4E. Following this analysis, we decided to plate the same number of cells and test their density under the microscope before running the experiment; each experiment was done in triplicate for each condition. We have now added this info to the method sections lines 806-813.  We did not comment on the basal difference, which we agree might be due to several factors, but we only compared the difference in response to the inhibitors, which isn’t affected by the basal level but exclusively by their D values. We have also included the formulas used to calculate the ATP production rate.

Overall, it appears that IGFBP2 does not seem to primarily cause metabolic changes, but simply accelerates the metabolic dependency on OXPHOS. Hence, the term 'metabolic remodelling' must be avoided unless IGFBP2 depletion/loss of function analysis is shown.

We thank the reviewer for suggesting how to interpret the data about the dependency on OXPHOS. We have now changed the conclusions and claims about the effect of IGFBP2. We have also included a cell cycle analysis of the hematopoietic cells derived upon IGFBP2 addition to show that they don’t show differences in proliferation that could cause the increase in colony formation we observed. Regarding the assay, we have plated the same number of cells for each group to make sure we were comparing the same number of cells, which we also assessed in the microscope before the test, and we eliminated the suspension cells during the washes that preceded the measurement. The review is correct in indicating that there is a basal difference in the value of OCR and ECAR where the IGFBP2 is lower at the start and not higher, which would not conceal higher proliferation. Finally, the ATP production rate is calculated on the variation of OCR and ECAR upon the addition of inhibitors, which normalizes for the basal differences.

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Reply to the reviewers

Manuscript number: RC-2024-02545

Corresponding author(s): Woo Jae, Kim

1. General Statements

We sincerely appreciate the positive and constructive feedback provided by all three reviewers. Their insightful comments have been invaluable in guiding our revisions. In response, we have made every effort to address their suggestions through additional experiments and by restructuring our manuscript to improve clarity and coherence.

In this revision, we have streamlined the presentation of our data to enhance the narrative flow, ensuring that it is more accessible to a general readership. We believe that these changes not only strengthen our manuscript but also align with the reviewers' recommendations for improvement.

We are hopeful that the revisions we have implemented meet the expectations of the reviewers and contribute to a clearer understanding of our findings. Thank you once again for your thoughtful critiques, which have greatly aided us in refining our work.

2. Point-by-point description of the revisions

Reviewer #1

General comment: This manuscript by Song et al. investigates the molecular mechanisms underlying changes in mating duration in Drosophila induced by previous experience. As they have shown previously, they find that male flies reared in isolation have shorter mating duration than those reared in groups, and also that male flies with previous mating experience have shorter mating duration than sexually naïve males. They have conducted a myriad of experiments to demonstrate that the neuropeptide SIFa is required for these changes in mating duration. They have further provided evidence that SIFa-expressing neurons undergo changes in synaptic connectivity and neuronal firing as a result of previous mating experience. Finally, they argue that SIFa neurons form reciprocal connections with sNPF-expressing neurons, and that communication within the SIFa-sNPF circuit is required for experience-dependent changes in mating duration. These results are used to assert that SIFa neurons track the internal state of the flies to modulate behavioral choice.

   __Answer:__ We appreciate the reviewer's thoughtful comments and commendations regarding our manuscript. The recognition of our investigation into the molecular mechanisms influencing mating duration in *Drosophila* is greatly valued. In particular, we are grateful for the reviewer's positive remarks about our comprehensive experimental approach to demonstrate the role of the neuropeptide SIFa in these changes. The evidence we provided indicating that SIFa-expressing neurons undergo alterations in synaptic connectivity and neuronal firing due to previous social experiences is crucial for elucidating the underlying neural circuitry involved in experience-dependent behaviors. Finally, we are thankful for the recognition of our assertion that SIFa neurons form reciprocal connections with sNPF-expressing neurons, emphasizing the importance of this circuit in modulating behavioral choices based on internal states. To provide stronger evidence for the interactions between SIFa and sNPF, we conducted detailed GCaMP experiments, which revealed intriguing neural connections between these two neuropeptides. We have included this new data in our main figure. We believe these insights contribute significantly to the existing literature on neuropeptidergic signaling and its implications for understanding complex behaviors in *Drosophila*. We look forward to addressing any further comments and enhancing our manuscript based on your invaluable feedback. Thank you once again for your constructive critique and support.

Major concerns:

Comment 1. The authors are to be commended for the sheer quantity of data they have generated, but I was often overwhelmed by the figures, which try to pack too much into the space provided. As a result, it is often unclear what components belong to each panel. Providing more space between each panel would really help.

   __Answer:__ We sincerely appreciate the reviewer’s commendation regarding the extensive data we have generated in our study. It is gratifying to know that our efforts to provide a comprehensive analysis of the molecular mechanisms underlying changes in mating duration have been recognized. We understand the concern regarding the density of information presented in our figures. We aimed to convey a wealth of data to support our findings, but we acknowledge that this may have led to some confusion regarding the organization and clarity of the panels. We are grateful for your constructive feedback on this matter. In response, we have significantly reduced the density of the main figures and decreased the size of the graphs to improve clarity. We have also increased the spacing between panels to ensure that each component is more easily distinguishable. Further details will be provided in our responses to each comment below.

• *

Comment 2. This is a rare instance where I would recommend paring down the paper to focus on the more novel, clear and relevant results. For example, all of Figure 2 shows the projection pattern of SIFa+ neuron dendrites and axons, which have been reported by multiple previous papers. Figure 7G and J show trans-tango data and SIFaR-GAL4 expression patterns, which were previously reported by Dreyer et al., 2019. These parts could be removed to supplemental figures. Figure 5 details experiments that knock down expression of different neurotransmitter receptors within the SIFa-expressing cells. The results here are less definitive than the SIFa knockdown results, and the SCope data supporting the idea that these receptors are expressed in SIFa-expressing neurons is equivocal. I would recommend removing these data (perhaps they could serve as the basis for another manuscript) or focusing solely on the CCHa1R results, which is the only manipulation that affects both LMD and SMD.

   __Answer:__ We sincerely appreciate the reviewer’s positive feedback regarding the extensive data generated in our study. We also fully agree with the reviewer that the sheer volume of our data made it challenging to support our hypothesis that SIFa neurons serve as a hub for integrating multiple neuropeptide inputs and orchestrating various behaviors related to energy balance, as highlighted in our new Figure 5N.

   In response to the reviewer's suggestions, we have streamlined our manuscript by removing excessive and redundant data to enhance clarity and simplicity. First, we have moved Figure 2 to the supplementary materials as the reviewer noted that the branching patterns of SIFa neurons are well-documented in previous literature. Second, we relocated the trans-tango data from Figure 7G to Figure S7, since this information is also well-established. We retained this data in the supplementary section to illustrate the connection of SIFa to our recent findings regarding SIFaR24F06 neuron connections. Additionally, we have completely removed the neuropeptide receptor input screening data previously included in Figure 5, as well as Figure S8, which presented fly SCope tSNE data. As suggested by the reviewer, we plan to utilize these data for a future paper focused on investigating the underlying mechanisms of SIFa inputs that modulate SIFa activity. Thanks to the reviewer’s constructive suggestions, we believe our manuscript is now more convincing and clearer for readers.

Comment 3. Finally, I would like the authors to spend more time explaining how they think the results tie together. For example, how do the authors think the changes in branching and activity in SIFa-expressing neurons tie to the change in mating duration provoked by previous experience? It would benefit the manuscript to simplify and clarify the message about what the authors think is happening at the mechanistic level. The various schematics (eg. Fig 7N) describe the results but the different parts feel like separate findings rather than a single narrative. (MECHANISMS diagram and explanation)

   __Answer:__ We appreciate the reviewer’s constructive comments, which have significantly improved our manuscript and conclusions for our readers. As the reviewer will see, we have made substantial revisions in line with the suggestions provided. We dedicated additional time to clarify the electrical activities and synaptic plasticity of SIFa neurons in relation to internal states that orchestrate various behaviors. We have summarized our hypothesis regarding the mechanistic role of SIFa neurons in Figure 5N. In brief, we propose that SIFa neurons function as a hub that receives diverse neuropeptidergic signals, which subsequently alters their electrical activity and synaptic branching. This, in turn, leads to different internal states. The internal states of SIFa neurons can then be interpreted by SIFaR-expressing cells, which help orchestrate various behaviors and physiological responses. We aim to address these aspects further in another manuscript that has been co-submitted alongside this one [1].

Comment 4. Most of the experiments lack traditional controls. For example, in experiments in Fig 1C-K, one would typically include genetic controls that contain either the GAL4 or UAS elements alone. The authors should explain their decision to omit these control experiments and provide an argument for why they are not necessary to correctly interpret the data. In this vein, the authors have stated in the methods that stocks were outcrossed at least 3x to Canton-S background, but 3 outcrosses is insufficient to fully control for genetic background.

   __Answer:__ We sincerely thank the reviewer for insightful comments regarding the absence of traditional genetic controls in our study of LMD and SMD behaviors. We acknowledge the importance of such controls and wish to clarify our rationale for not including them in the current investigation. The primary reason for not incorporating all genetic control lines is that we have previously assessed the LMD and SMD behaviors of GAL4/+ and UAS/+ strains in our earlier studies. Our past experiences have consistently shown that 100% of the genetic control flies for both GAL4 and UAS exhibit normal LMD and SMD behaviors. Given these findings, we deemed the inclusion of additional genetic controls to be non-essential for the present study, particularly in the context of extensive screening efforts. We understand the value of providing a clear rationale for our methodology choices. To this end, we have added a detailed explanation in the "MATERIALS AND METHODS" section and the figure legends of Figure 1. This clarification aims to assist readers in understanding our decision to omit traditional controls, as outlined below.

"Mating Duration Assays for Successful Copulation

The mating duration assay in this study has been reported[33,73,93]. To enhance the efficiency of the mating duration assay, we utilized the Df (1)Exel6234 (DF here after) genetic modified fly line in this study, which harbors a deletion of a specific genomic region that includes the sex peptide receptor (SPR)[94,95]. Previous studies have demonstrated that virgin females of this line exhibit increased receptivity to males[95]. We conducted a comparative analysis between the virgin females of this line and the CS virgin females and found that both groups induced SMD. Consequently, we have elected to employ virgin females from this modified line in all subsequent studies. For naïve males, 40 males from the same strain were placed into a vial with food for 5 days. For single reared males, males of the same strain were collected individually and placed into vials with food for 5 days. For experienced males, 40 males from the same strain were placed into a vial with food for 4 days then 80 DF virgin females were introduced into vials for last 1 day before assay. 40 DF virgin females were collected from bottles and placed into a vial for 5 days. These females provide both sexually experienced partners and mating partners for mating duration assays. At the fifth day after eclosion, males of the appropriate strain and DF virgin females were mildly anaesthetized by CO2. After placing a single female in to the mating chamber, we inserted a transparent film then placed a single male to the other side of the film in each chamber. After allowing for 1 h of recovery in the mating chamber in 25℃ incubators, we removed the transparent film and recorded the mating activities. Only those males that succeeded to mate within 1 h were included for analyses. Initiation and completion of copulation were recorded with an accuracy of 10 sec, and total mating duration was calculated for each couple. All assays were performed from noon to 4pm. Genetic controls with GAL4/+ or UAS/+ lines were omitted from supplementary figures, as prior data confirm their consistent exhibition of normal LMD and SMD behaviors [33,73,93,96,97]. Hence, genetic controls for LMD and SMD behaviors were incorporated exclusively when assessing novel fly strains that had not previously been examined. In essence, internal controls were predominantly employed in the experiments, as LMD and SMD behaviors exhibit enhanced statistical significance when internally controlled. Within the LMD assay, both group and single conditions function reciprocally as internal controls. A significant distinction between the naïve and single conditions implies that the experimental manipulation does not affect LMD. Conversely, the lack of a significant discrepancy suggests that the manipulation does influence LMD. In the context of SMD experiments, the naïve condition (equivalent to the group condition in the LMD assay) and sexually experienced males act as mutual internal controls for one another. A statistically significant divergence between naïve and experienced males indicates that the experimental procedure does not alter SMD. Conversely, the absence of a statistically significant difference suggests that the manipulation does impact SMD. Hence, we incorporated supplementary genetic control experiments solely if they deemed indispensable for testing. All assays were performed from noon to 4 PM. We conducted blinded studies for every test[98,99] .

   While we have previously addressed this type of reviewer feedback in our published manuscript [2–7], we appreciate the reviewer’s suggestion to include traditional genetic control experiments. In response, we conducted all feasible combinations of genetic control experiments for LMD/SMD during the revision period. The results are presented in the supplementary figures and are described in the main text.

   We appreciate the reviewer's inquiry regarding the genetic background of our experimental lines. In response to the comments, we would like to clarify the following. All of our GAL4, UAS, or RNAi lines, which were utilized as the virgin female stock for outcrosses, have been backcrossed to the Canton-S (CS) genetic background for over ten generations. The majority of these lines, particularly those employed in LMD assays, have been maintained in a CS backcrossed status for several years, ensuring a consistent genetic background across multiple generations. Our experience has indicated that the genetic background, particularly that of the X chromosome inherited from the female parent, plays a pivotal role in the expression of certain behavioral traits. Therefore, we have consistently employed these fully outcrossed females as virgins for conducting experiments related to LMD and SMD behaviors. It is noteworthy that, in contrast to the significance of genetic background for LMD behaviors, we have previously established in our work [6] that the genetic background does not significantly influence SMD behaviors. This distinction is important for the interpretation of our findings. To provide a comprehensive understanding of our experimental design, we have detailed the genetic background considerations in the __"Materials and Methods"__ section, specifically in the subsection __"Fly Stocks and Husbandry"__ as outlined below.

"To reduce the variation from genetic background, all flies were backcrossed for at least 3 generations to CS strain. For the generation of outcrosses, all GAL4, UAS, and RNAi lines employed as the virgin female stock were backcrossed to the CS genetic background for a minimum of ten generations. Notably, the majority of these lines, which were utilized for LMD assays, have been maintained in a CS backcrossed state for long-term generations subsequent to the initial outcrossing process, exceeding ten backcrosses. Based on our experimental observations, the genetic background of primary significance is that of the X chromosome inherited from the female parent. Consequently, we consistently utilized these fully outcrossed females as virgins for the execution of experiments pertaining to LMD and SMD behaviors. Contrary to the influence on LMD behaviors, we have previously demonstrated that the genetic background exerts negligible influence on SMD behaviors, as reported in our prior publication [6]. All mutants and transgenic lines used here have been described previously."

Comment 5. Throughout the manuscript, the authors appear to use a single control condition (sexually naïve flies raised in groups) to compare to both males raised singly and males with previous sexual experience. These control conditions are duplicated in two separate graphs, one for long mating duration and one for short mating duration, but they are given different names (group vs naïve) depending on the graph. If these are actually the same flies, then this should be made clear, and they should be given a consistent name across the different "experiments".

   __Answer:__ We are grateful to the reviewer for highlighting the potential for confusion among readers regarding the visualization methods used in our figures. In response to this valuable feedback, we have now included a more detailed explanation of the graph visualization techniques in the legends of Figure 1, as detailed below. This additional information should enhance the clarity and understanding of the figure for all readers.

In the mating duration (MD) assays, light grey data points denote males that were group-reared (or sexually naïve), whereas blue (or pink) data points signify males that were singly reared (or sexually experienced). The dot plots represent the MD of each male fly. The mean value and standard error are labeled within the dot plot (black lines). Asterisks represent significant differences, as revealed by the unpaired Student’s t test, and ns represents non-significant differences M.D represent mating duration. DBMs represent the 'difference between means' for the evaluation of estimation statistics (See MATERIALS AND METHODS). Asterisks represent significant differences, as revealed by the Student’s t test (* p

Comment 6. The authors use SCope data to provide evidence for co-expression of SIFa and other neurotransmitters or neuropeptide receptors. The graphs they show are hard to read and it is not clear to what extent the gene expression is actually overlapping. It would be more definitive to show graphs that indicate which percentage of SIFa-expressing cells co-express other neurotransmitter components, and what the actual level of expression of the genes is. The authors should also provide more information on how they identified the SIFa+ cells in the fly atlas dataset. These are important pieces of information to be able to interpret the effects of manipulation of these other neurotransmitter systems within SIFa-expressing cells on mating duration.

__ Answer: We appreciate the reviewer for pointing out the potential for confusion among readers regarding the visualization methods used in our figures, particularly concerning the tSNE plots of scRNA-seq data. As mentioned in our previous response, we have removed most of the tSNE plots related to co-expression data with SIFa and NPRs, which we believe will reduce any confusion for readers interpreting these plots. However, we have retained a few tSNE plots, specifically Figures 2N-O, to confirm the potential co-expression of the ple and Vglut genes in SIFa cells. We understand the reviewer’s concerns about the clarity of the presented data and the necessity for more detailed information regarding the extent of co-expression and the identification of SIFa-expressing cells. To address these concerns, we have included a comprehensive description of our methods in the __MATERIALS AND METHODS section below.

"Single-nucleus RNA-sequencing analyses

The snRNAseq dataset analyzed in this paper is published in [112] and available at the Nextflow pipelines (VSN, https://github.com/vib-singlecell-nf), the availability of raw and processed datasets for users to explore, and the development of a crowd-annotation platform with voting, comments, and references through SCope (https://flycellatlas.org/scope), linked to an online analysis platform in ASAP (https://asap.epfl.ch/fca). For the generation of the tSNE plots, we utilized the Fly SCope website (https://scope.aertslab.org/#/FlyCellAtlas/*/welcome). Within the session interface, we selected the appropriate tissues and configured the parameters as follows: 'Log transform' enabled, 'CPM normalize' enabled, 'Expression-based plotting' enabled, 'Show labels' enabled, 'Dissociate viewers' enabled, and both 'Point size' and 'Point alpha level' set to maximum. For all tissues, we referred to the individual tissue sessions within the '10X Cross-tissue' RNAseq dataset. Each tSNE visualization depicts the coexpression patterns of genes, with each color corresponding to the genes listed on the left, right, and bottom of the plot. The tissue name, as referenced on the Fly SCope website is indicated in the upper left corner of the tSNE plot. Dashed lines denote the significant overlap of cell populations annotated by the respective genes. Coexpression between genes or annotated tissues is visually represented by differentially colored cell populations. For instance, yellow cells indicate the coexpression of a gene (or annotated tissue) with red color and another gene (or annotated tissue) with green color. Cyan cells signify coexpression between green and blue, purple cells for red and blue, and white cells for the coexpression of all three colors (red, green, and blue). Consistency in the tSNE plot visualization is preserved across all figures.

Single-cell RNA sequencing (scRNA-seq) data from the Drosophila melanogaster were obtained from the Fly Cell Atlas website (https://doi.org/10.1126/science.abk2432). Oenocytes gene expression analysis employed UMI (Unique Molecular Identifier) data extracted from the 10x VSN oenocyte (Stringent) loom and h5ad file, encompassing a total of 506,660 cells. The Seurat (v4.2.2) package (https://doi.org/10.1016/j.cell.2021.04.048) was utilized for data analysis. Violin plots were generated using the “Vlnplot” function, the cell types are split by FCA.

   We have also included detailed descriptions in the figure legends for the initial tSNE plot presented below to help readers clearly understand the significance of this visualization.

"Each tSNE visualization depicts the coexpression patterns of genes, with each color corresponding to the genes listed on the left, right, and/or bottom of the plot. The tissue name, as referenced on the Fly SCope website is indicated in the upper left corner of the tSNE plot. Consistency in the tSNE plot visualization is preserved across all figures."

Comment 7. I would like to see more information on how the thresholding and normalization was done for immunohistochemistry experiments. Was thresholding applied equally across all datasets? Furthermore, "overlap" of Denmark and Syt-eGFP is taken as evidence for synaptic connectivity, but the latter requires more than just overlap in the location of the axon terminal and dendrite regions of the neuron.

__ Answer: Thank you for your continued engagement with our manuscript and for highlighting the need for further clarification on our methods. Your attention to the details of our immunohistochemistry experiments is commendable, and we agree that providing a clear explanation of our thresholding and normalization procedures is essential for the transparency and reproducibility of our results. We concur that the intensity of these signals is indeed correlated with the area measurements, which is a critical factor to consider. In response to the reviewer's valuable suggestion, we have revised our approach and now present our data based on intensity measurements. Additionally, we have updated the labeling of our Y-axis to "Norm. GFP Int.", which stands for "normalized GFP intensity". This change ensures clarity and consistency in the presentation of our data. We primarily adhered to the established methods outlined by Kayser et al. [8]. To address your first point, we have now included a more detailed description of our thresholding and normalization procedures in the __MATERIALS AND METHODS section as below.

"Quantitative analysis of fluorescence intensity

To ascertain calcium levels and synaptic intensity from microscopic images, we dissected and imaged five-day-old flies of various social conditions and genotypes under uniform conditions. The GFP signal in the brains and VNCs was amplified through immunostaining with chicken anti-GFP primary antibody. Image analysis was conducted using ImageJ software. For the quantification of fluorescence intensities, an investigator, blinded to the fly's genotype, thresholded the sum of all pixel intensities within a sub-stack to optimize the signal-to-noise ratio, following established methods [93]. The total fluorescent area or region of interest (ROI) was then quantified using ImageJ, as previously reported. For CaLexA or TRIC signal quantification, we adhered to protocols detailed by Kayser et al. [94], which involve measuring the ROI's GFP-labeled area by summing pixel values across the image stack. This method assumes that changes in the GFP-labeled area and intensity are indicative of alterations in the CaLexA and TRIC signal, reflecting synaptic activity. ROI intensities were background-corrected by measuring and subtracting the fluorescent intensity from a non-specific adjacent area, as per Kayser et al. [94]. For normalization, nc82 fluorescence is utilized for CaLexA, while RFP signal is employed for TRIC experiments, as the RFP signal from the TRIC reporter is independent of calcium signaling [76]. For the analysis of GRASP or tGRASP signals, a sub-stack encompassing all synaptic puncta was thresholded by a genotype-blinded investigator to achieve the optimal signal-to-noise ratio. The fluorescence area or ROI for each region was quantified using ImageJ, employing a similar approach to that used for CaLexA or TRIC quantification [93]. 'Norm. GFP Int.' refers to the normalized GFP intensity relative to the RFP signal."

Comment 8. None of the RNAi experiments have been validated to demonstrate effective knockdown. In many cases, this would be difficult to do because of a lack of an antibody to quantify in a cell-specific manner; however, this fact should be acknowledged, especially in cases where there was found to be a lack of phenotype, which could result from lack of knockdown. The authors could also look for evidence in the literature of cases where RNAi lines they have used have been previously validated. For SIFa, knockdown can be easily confirmed with the SIFa antibody the authors have used elsewhere in the manuscript.

__ Answer:__ We appreciate the reviewer’s constructive and critical comments regarding the validation of our RNAi experiments through effective knockdown. We understand the reviewer’s concerns about achieving effective knockdown with RNAi; however, we have demonstrated in our unpublished preprint that the neuronal knockdown using independent SIFa-RNAi lines aligns with the SIFa mutant phenotype, which is consistent with our current findings on SIFa knockdown (Wong 2019). In most cases involving RNAi experiments, we have utilized independent RNAi strains to confirm consistent phenotypes and have compared these results with those from mutant phenotypes [1,9]. Therefore, we are confident that our observed SIFa phenotype results from effective RNAi knockdown. Nevertheless, we respect the reviewer’s comments and have conducted additional SIFa knockdown experiments using various GAL4 drivers, followed by immunostaining with SIFa antibodies. As shown in Figure S1B, both neuronal GAL4 drivers and SIFa-GAL4 effectively reduced SIFa immunoreactivity. We believe this indicates that our SIFa knockdown efficiently phenocopies the SIFa mutant phenotype. We also described this result in manuscript as below:

"Using the GAL4SIFa.PT driver and the elavc155 driver, we observed a significant decrease in SIFa immunoreactivity following SIFa-RNAi treatment, thereby confirming the effective knockdown of SIFa in these cells. In contrast, when SIFa-RNAi was expressed under the control of the repo-GAL4 driver, no significant change in SIFa immunoreactivity was detected (Fig. S1B). This control experiment highlights the specificity of the SIFa-RNAi effect and supports the conclusion that the behavioral changes observed in SMD and LMD are likely attributable to the targeted reduction of SIFa in the intended neuronal populations."

Minor comments:

Comment 1. There are quite a lot of citations to preprints, including preprints of the manuscripts under review. It seems inappropriate to cite a preprint of the manuscript you are submitting because it gives a false sense of strengthening the assertions being made in the manuscript.

   __Answer:__ We agree with the reviewer and have omitted all preprints that are currently under review, except for those that are deemed necessary, such as the Zhang et al. 2024 preprint, which is being submitted alongside this manuscript.

Comment 2. It seems that labels are incorrect on a number of the immunohistochemistry figures. For example, in Fig 2N, it labels dendrites as green, but this is sytEGFP, which is the presynaptic terminal.

__ Answer:__ We thoroughly reviewed and corrected the errors in the labels.

Comment ____3. Fig 4N shows grasp between SIFa-LexA and sNPF-R-GAL4, but the authors have argued that these two components should both be expressed in SIFa-expressing cells. This would make grasp signal misleading, because it would appear in the SIFa-expressing cells even without synaptic contacts due to both split GFP molecules being expressed in these cells.

   __Answer:__ We appreciate the reviewer’s critical comments regarding the interpretation of our GRASP experiments. As the reviewer noted, we acknowledge that the GRASP results also indicate synaptic contacts between SIFa cells. We have elaborated on these results in the following sections.

"This indicates that the synapses between SIFa cells expressing sNPF-R become stronger (S5K to S5M Fig)."

   However, we understand that readers may find the interpretation of this GRASP data confusing, so we have included additional explanations below to clarify.

This indicates that the synapses between SIFa cells expressing sNPF-R become stronger (S5K to S5M Fig) since we have found that SIFa cells express sNPF-R (Fig 3M, S5E and S5G)

Comment 4. For quantifying TRIC and CaLexA experiments (eg. Figure 6A-E), intensity of signal should be measured in addition to the area covered by the signal.

__ Answer:__ We concur with the reviewer. Since all of our analyses indicated that the area covered by the signal correlates with the signal intensity, we opted to use normalized intensity rather than area coverage.

Conclusive Comments: This study will be most relevant to researchers interested in understanding neuronal control of behavior. It has provided novel information about the mechanisms underlying mating duration in flies, which is used to delineate how internal state influences behavioral outcomes. This represents a conceptual advance, particularly in identifying a cell type and molecule that influences mating duration decisions. The strength of the manuscript is the number of different assays used to investigate the central question from a number of angles. The limitation is that there is a lack of a big picture tying the different components of the manuscript together. Too much data is presented without providing a framework to understand how the data points fit together.

• Answer: We sincerely appreciate the reviewer’s positive feedback regarding our study and the recognition of its relevance to researchers interested in understanding the neuronal control of behavior. We are grateful for the acknowledgment of our novel insights into the mechanisms underlying mating duration in Drosophila*, particularly in how internal states influence behavioral outcomes. The identification of specific cell types and molecules that affect mating duration decisions indeed represents a significant conceptual advance. We also appreciate the reviewer’s commendation of the diverse array of assays employed in our investigation, which allowed us to approach our central question from multiple perspectives.

  In response to the reviewer’s constructive criticism regarding the lack of a cohesive framework tying the various components of our manuscript together, we have completely restructured our manuscript. We removed redundant data and incorporated additional convincing experiments, such as GCaMP analyses, to enhance clarity and coherence. Furthermore, we have provided a simplified yet comprehensive overview that describes the role of SIFa as a hub for neuropeptidergic signaling. This framework illustrates how SIFa orchestrates multiple behaviors related to energy balance through calcium signaling and synaptic plasticity via SIFaR-expressing cells.

  We believe these revisions address the reviewer’s concerns and provide a clearer understanding of how the different elements of our study fit together, ultimately strengthening the overall impact of our manuscript. Thank you for your valuable feedback, which has guided us in improving our work.

Reviewer #2

General Comments:* In the present study, the authors employ mating behavior in male fruit flies, Drosophila melanogaster, to investigate the behavioral roles of the neuropeptide SIFamide. The duration of mating behavior in these animals varies depending on context, previous experience, and internal metabolic state. The authors use this variability to explore the neuronal mechanisms that control these influences. In an abstraction step, they compare the different mating durations to concepts of neuronal interval timing.

The behavioral functions of the neuropeptide SIFamide have been thoroughly characterized in several studies, particularly in the contexts of circadian rhythm and sleep, courtship behavior, and food uptake. This study adds new data, demonstrating that SIFamide is essential for the proper control of mating behavior, highlighting the interconnection of various state- and motivation-dependent behaviors at the neuronal level. However, the hypothesis that mating behavior is related to interval timing is not convincingly supported.

Experimentally, the authors show that RNAi-mediated downregulation of SIFamide affects mating duration in male flies. They use combinations of RNAi lines under the control of various Gal4 lines to identify additional neurotransmitters, neuropeptides, and receptors involved in this process. This approach is complemented by neuroanatomical staining and single-cell RNA sequencing.*

* Overall, the study advances our knowledge about the behavioral roles of SIFamide, which is certainly important, interesting, and worthy of being reported. However, the manuscript also raises several serious caveats and includes points that remain speculative, are less convincing, or are simply incorrect.*

• Answer: We would like to thank the reviewer for their thoughtful and constructive comments regarding our study. We appreciate the recognition of our investigation into the behavioral roles of the neuropeptide SIFamide in male Drosophila melanogaster*, particularly how we explored the variability in mating duration influenced by context, previous experience, and internal metabolic state. We are grateful for the acknowledgment that our study adds valuable data demonstrating the essential role of SIFamide in regulating mating behavior, highlighting the interconnectedness of various state- and motivation-dependent behaviors at the neuronal level.

  We also appreciate the reviewer's recognition of our experimental approach, which includes RNAi-mediated downregulation of SIFamide, the use of various Gal4 lines to identify additional neurotransmitters, neuropeptides, and receptors involved in this process, as well as our incorporation of neuroanatomical staining and single-cell RNA sequencing.

  In response to the reviewer’s concerns regarding the hypothesis that mating behavior is related to interval timing, we acknowledge that this aspect requires further clarification and support. We have revisited this hypothesis in our manuscript to strengthen its foundation and address any speculative elements. We aim to provide more robust evidence and clearer connections between mating behavior and neuronal interval timing.

  Furthermore, we have taken care to address any points that may have been perceived as less convincing or incorrect. We are committed to refining our manuscript to ensure that all claims are well-supported by our data. Thank you once again for your valuable feedback. We believe that these revisions will enhance the clarity and impact of our study while addressing the concerns raised.

Major concerns:

Comment 1. The authors conclude from their mating experiments that SIFamide controls interval timing. This conclusion is not supported by the data, which only indicate that SIFamide is required for normal mating duration and modulates the motivation-dependent component of this behavior. There is no clear evidence linking this to interval timing.

__ Answer: __We appreciate the reviewer’s insightful comments regarding our conclusion linking SIFamide to interval timing in mating behavior. We acknowledge that our data primarily demonstrate that SIFamide is required for normal mating duration and modulates the motivation-dependent aspects of this behavior, and we recognize the need for clearer evidence connecting these observations to interval timing. Current research by Crickmore et al. has shed light on how mating duration in Drosophila serves as a powerful model for exploring changes in motivation over time as behavioral goals are achieved. For instance, at approximately six minutes into mating, sperm transfer occurs, leading to a significant shift in the male's nervous system: he no longer prioritizes sustaining the mating at the expense of his own survival. This change is driven by the output of four male-specific neurons that produce the neuropeptide Corazonin (Crz). When these Crz neurons are inhibited, sperm transfer does not occur, and the male fails to downregulate his motivation, resulting in matings that can last for hours instead of the typical ~23 minutes [10].

   Recent research by Crickmore et al. has received NIH R01 funding (Mechanisms of Interval Timing, 1R01GM134222-01) to explore mating duration in *Drosophila* as a genetic model for interval timing. Their work highlights how changes in motivation over time can influence mating behavior, particularly noting that significant behavioral shifts occur during mating, such as the transfer of sperm at approximately six minutes, which correlates with a decrease in the male's motivation to continue mating [10]. These findings suggest that mating duration is not only a behavioral endpoint but may also reflect underlying mechanisms related to interval timing.

   We believe that by leveraging the robustness and experimental tractability of these findings, along with our own work on SIFamide's role in mating behavior, we can gain deeper insights into the molecular and circuit mechanisms underlying interval timing. We will revise our manuscript to clarify this relationship and emphasize how SIFamide may interact with other neuropeptides and neuronal circuits involved in motivation and timing.

   In addition to the efforts of Crickmore's group to connect mating duration with a straightforward genetic model for interval timing, we have previously published several papers demonstrating that LMD and SMD can serve as effective genetic models for interval timing within the fly research community. For instance, we have successfully connected SMD to an interval timing model in a recently published paper [6], as detailed below:

"We hypothesize that SMD can serve as a straightforward genetic model system through which we can investigate "interval timing," the capacity of animals to distinguish between periods ranging from minutes to hours in duration.....

In summary, we report a novel sensory pathway that controls mating investment related to sexual experiences in Drosophila. Since both LMD and SMD behaviors are involved in controlling male investment by varying the interval of mating, these two behavioral paradigms will provide a new avenue to study how the brain computes the ‘interval timing’ that allows an animal to subjectively experience the passage of physical time [11–16]."

   Lee, S. G., Sun, D., Miao, H., Wu, Z., Kang, C., Saad, B., ... & Kim, W. J. (2023). Taste and pheromonal inputs govern the regulation of time investment for mating by sexual experience in male Drosophila melanogaster. *PLoS Genetics*, *19*(5), e1010753.

   We have also successfully linked LMD behavior to an interval timing model and have published several papers on this topic recently [4,5,7].

   Sun, Y., Zhang, X., Wu, Z., Li, W., & Kim, W. J. (2024). Genetic Screening Reveals Cone Cell-Specific Factors as Common Genetic Targets Modulating Rival-Induced Prolonged Mating in male Drosophila melanogaster. *G3: Genes, Genomes, Genetics*, jkae255.

   Zhang, T., Zhang, X., Sun, D., & Kim, W. J. (2024). Exploring the Asymmetric Body’s Influence on Interval Timing Behaviors of Drosophila melanogaster. *Behavior Genetics*, *54*(5), 416-425.

   Huang, Y., Kwan, A., & Kim, W. J. (2024). Y chromosome genes interplay with interval timing in regulating mating duration of male Drosophila melanogaster. *Gene Reports*, *36*, 101999.

   Finally, in this context, we have outlined in our INTRODUCTION section below how our LMD and SMD models are related to interval timing, aiming to persuade readers of their relevance. We hope that the reviewer and readers are convinced that mating duration and its associated motivational changes such as LMD and SMD provide a compelling model for studying the genetic basis of interval timing in *Drosophila*.

"The mating duration of male fruit flies is a suitable model for studying interval timing and it could change based on internal states and environmental context. Previous studies by our group[27–30] and others[31,32] have established several frameworks for investigating the mating duration using sophisticated genetic techniques that can analyze and uncover the neural circuits’ principles governing interval timing. In particular, males exhibit LMD behavior when they are exposed to an environment with rivals, which means they prolong their mating duration. Conversely, they display SMD behavior when they are in a sexually saturated condition, meaning they reduce their mating duration[33,34]."

Comment 2. On line 160, the authors state, "The connection between the dendrites and axons of the SIFamide neuronal processes is unknown." This is not entirely correct. State-of-the-art connectome analyses can determine synaptic connectivities between SIFamidergic neurons and pre-/postsynaptic neurons. The authors also overlook the thorough connectivity analysis by Martelli et al. (2017), which includes functional analyses and detailed anatomical descriptions that the current study confirms.

__ Answer:__ We appreciate the reviewer for acknowledging the efforts of Martelli et al. in elucidating the neuronal architecture of SIFa neurons. We recognize that it was an oversight on our part to state that "the connection between the dendrites and axons of SIFa neurons is unknown." This error arose because our manuscript has been in preparation for over ten years, predating the publication of Martelli et al.'s work. That statement likely reflects an outdated section of the manuscript.

We fully acknowledge the findings from previous publications and have removed that sentence entirely from our manuscript. In its place, we have added the following statement:

"The established connections and architecture of SIFa neurons has been described by Martelli et al., which enhances our understanding of their functional roles within the neuronal circuitry [51]. To identify the dendritic and axonal components of SIFa-neuronal processes, we employed a similar approach to that reported by Martelli [51]."

Thank you for your valuable feedback, which has helped us improve the clarity and accuracy of our manuscript.

Comment 3. The mating experiments are overall okay, with sufficiently high sample sizes and appropriate statistical tests. However, many experiments lack genetic controls for the heterozygous parental strains, such as Gal4-ines AND UAS-lines. This is of course of importance and common standard.

__ Answer: __While we have previously addressed this type of reviewer feedback in our published manuscript [2–7] as well as this manuscript by Reviewer #1, we appreciate the reviewer’s suggestion to include traditional genetic control experiments. In response, we conducted all feasible combinations of genetic control experiments for LMD/SMD during the revision period. The results are presented in the supplementary figures and are described in the main text.

Comment 4. *Using a battery of RNAi lines, the authors aim to uncover which neurotransmitters might be co-released from SIFamide neurons to influence mating behavior. However, a behavioral effect of an RNAi construct expressed in SIFamidergic neurons does not demonstrate that the respective transmitter is actually released from these neurons. Alternative methods are needed to show whether glutamate, dopamine, serotonin, octopamine, etc., are present and released from SIFamide neurons. It is particularly challenging to prove that a certain substance acts as a transmitter released by a specific neuron. For example, anti-Tdc2 staining does not actually cover SIFamide neurons, and dopamine has not been described as present in SIFamide neurons. *

__ Answer:__ We appreciate the reviewer’s constructive comments regarding the need to demonstrate the presence of the responsible neurotransmitters in SIFa neurons. While many studies utilize neurotransmitter-synthesizing enzymes such as TH, VGlut, Gad1, and Trhn to assess neurotransmitter effects, we recognize the importance of conclusively establishing that glutamate and dopamine play significant roles in modulating energy balance within SIFa neurons.

   First, the enrichment of tyramine (TA), octopamine (OA), and dopamine (DA) in SIFa neurons was suggested in the study by Croset et al. (2018) [17]. Although we tested Tdc2-RNAi and observed interesting phenotypes, we chose not to publish these findings, as our data on glutamate and dopamine provide a more compelling explanation for how SIFa cotransmission with these neurotransmitters can independently influence various behaviors, including sleep and mating duration.

   To confirm the expression of DA in SIFa neurons, we employed a well-established genetic toolkit for dissecting dopamine circuit function in *Drosophila* [18]. Our findings indicate that TH-C-GAL4 specifically labels SIFa neurons, which have been confirmed as dopaminergic (S4M Fig). Our genetic intersection data, along with Xie et al.'s findings from 2018, confirm that a subset of SIFa neurons is indeed dopaminergic. We have described these new results in the main text as follows:

To further verify the presence of DA neurons within the SIFa neuron population, we utilized a well-established genetic toolkit for dissecting DA circuits and confirmed part of SIFa neurons are dopaminergic (S4M Fig) [58].

    To confirm the glutamatergic characteristics of SIFa neurons, we conducted several experiments that established glutamate as the most critical neurotransmitter for generating interval timing in both SIFa and SIFaR neurons. First, to demonstrate the presence of glutamatergic synaptic vesicles in SIFa neurons, we utilized a conditional glutamatergic synaptic vesicle marker for *Drosophila*, developed by Certel et al. [19]. Our results confirmed that SIFa neurons exhibit strong expression of glutamatergic synaptic vesicles (Fig. 2P and Fig. S4N as a genetic control). We have described these new results in the main text as follows:

“To further verify the presence of DA neurons within the SIFa neuron population, we utilized a well-established genetic toolkit for dissecting DA circuits and confirmed part of SIFa neurons are dopaminergic (S4M Fig) [58]. We also employed a conditional glutamatergic synaptic vesicle marker to confirm the presence of glutamatergic SIFa neurons (Fig 2P and Fig S4N) [59].”

   To further confirm that glutamate release from SIFa neurons influences the function of SIFaR neurons, we tested several RNAi strains targeting glutamate receptors. Our results showed that the knockdown of glutamate receptors in SIFaR-expressing neurons produced phenotypes similar to those observed with VGlut-RNAi knockdown in SIFa neurons (Fig. G-L). We believe that this series of experiments demonstrates that glutamate and dopamine work in conjunction with SIFa to modulate interval timing and other behaviors related to energy balance. We have described these new results in the main text as follows:

"To further substantiate the role of glutamate in SIFa-mediated behaviors. we targeted knockdown of VGlut receptors in SIFaR-expressing neurons. Strikingly, the knockdown of VGlut receptors in these neurons also disrupted SMD behavior, mirroring the phenotype observed upon direct suppression of glutamatergic signaling in SIFa neurons (S4G to S4L Fig). This suggests that glutamate is an essential neurotransmitter for modulating interval timing in SIFa neurons.”

Comment 5. Single-cell RNA sequencing data alone is insufficient to claim multiple transmitter co-release from SIFamide neurons. Figures illustrating single-cell RNA sequencing, such as Figure 3P-R, are not intuitively understandable, and the figure legends lack sufficient information to clarify these panels. As a side note, Tdc2 is not only present in octopaminergic neurons, but also in tyraminergic neurons.

__ Answer:__ We agree with the reviewer that scRNA-seq data alone is insufficient to support claims of multiple transmitter co-release in SIFa neurons. We also appreciate the reviewer for highlighting the potential for confusion among readers regarding the visualization methods used in our figures, particularly the tSNE plots of the scRNA-seq data. As noted in our previous response to Reviewer #1, we have removed most of the tSNE plots related to co-expression data involving SIFa and NPRs, which we believe will help clarify the interpretation for readers. However, we have retained a few tSNE plots, specifically Figures 2N-O, to illustrate the potential co-expression of the ple and Vglut genes in SIFa cells.

   We understand the reviewer’s concerns regarding the clarity of the presented data and the need for more detailed information about the extent of co-expression and the identification of SIFa-expressing cells. To address these concerns, we have provided a comprehensive description of our methods in the __MATERIALS AND METHODS__ section below.

"Single-nucleus RNA-sequencing analyses

The snRNAseq dataset analyzed in this paper is published in [20]and available at the Nextflow pipelines (VSN, https://github.com/vib-singlecell-nf), the availability of raw and processed datasets for users to explore, and the development of a crowd-annotation platform with voting, comments, and references through SCope (https://flycellatlas.org/scope), linked to an online analysis platform in ASAP (https://asap.epfl.ch/fca). For the generation of the tSNE plots, we utilized the Fly SCope website (https://scope.aertslab.org/#/FlyCellAtlas/*/welcome). Within the session interface, we selected the appropriate tissues and configured the parameters as follows: 'Log transform' enabled, 'CPM normalize' enabled, 'Expression-based plotting' enabled, 'Show labels' enabled, 'Dissociate viewers' enabled, and both 'Point size' and 'Point alpha level' set to maximum. For all tissues, we referred to the individual tissue sessions within the '10X Cross-tissue' RNAseq dataset. Each tSNE visualization depicts the coexpression patterns of genes, with each color corresponding to the genes listed on the left, right, and bottom of the plot. The tissue name, as referenced on the Fly SCope website is indicated in the upper left corner of the tSNE plot. Dashed lines denote the significant overlap of cell populations annotated by the respective genes. Coexpression between genes or annotated tissues is visually represented by differentially colored cell populations. For instance, yellow cells indicate the coexpression of a gene (or annotated tissue) with red color and another gene (or annotated tissue) with green color. Cyan cells signify coexpression between green and blue, purple cells for red and blue, and white cells for the coexpression of all three colors (red, green, and blue). Consistency in the tSNE plot visualization is preserved across all figures.

Single-cell RNA sequencing (scRNA-seq) data from the Drosophila melanogaster were obtained from the Fly Cell Atlas website (https://doi.org/10.1126/science.abk2432). Oenocytes gene expression analysis employed UMI (Unique Molecular Identifier) data extracted from the 10x VSN oenocyte (Stringent) loom and h5ad file, encompassing a total of 506,660 cells. The Seurat (v4.2.2) package (https://doi.org/10.1016/j.cell.2021.04.048) was utilized for data analysis. Violin plots were generated using the “Vlnplot” function, the cell types are split by FCA."

   We have also included detailed descriptions in the figure legends for the initial tSNE plot presented below to help readers clearly understand the significance of this visualization.

"Each tSNE visualization depicts the coexpression patterns of genes, with each color corresponding to the genes listed on the left, right, and/or bottom of the plot. The tissue name, as referenced on the Fly SCope website is indicated in the upper left corner of the tSNE plot. Consistency in the tSNE plot visualization is preserved across all figures."

   We appreciate the reviewer for acknowledging that Tdc2 is present in both TA and OA neurons. As we mentioned earlier, we have completely removed the Tdc2-related results from this manuscript, as we believe that more detailed experiments are necessary to confirm the roles of TA and OA in SIFa neurons.

Comment 6. The same argument applies to the expression of sNPF receptors in SIFamide neurons. The rather small anatomical stainings shown in figure 4M do not convincingly and unambiguously show that actually sNPF receptors are located on SIFamide neurons.

__ Answer:__ We appreciate the reviewer for pointing out that the co-expression of sNPF-R and SIFa needs further verification, and we agree with this assessment. To confirm the co-expression of SIFa with sNPF-R, we conducted a mini-screen of various sNPF-R driver lines and found that the chemoconnectome (CCT) sNPF-R2A driver which represent the physiological expression patterns of sNPF-R, consistently labels SIFa neurons [21].

   To further establish the functional connection between the SIFa and sNPF systems, we performed GCaMP experiments using SIFa-driven GCaMP in conjunction with sNPF-R neurons expressing P2X2, which can be activated by ATP treatment. As shown in Figures 3N-P, we demonstrated that activation of sNPF-R neurons by ATP significantly increases calcium levels in SIFa neurons. Our results strongly suggest that the sNPF-sNPF-R/SIFa system is functionally present and plays a role in modulating interval timing behaviors.

Comment 7. The authors use the GRASP technique (figure 4N) to determine whether synaptic connections are subject to modulation as a result from the animals' individual experience. The overall extremely bright fluorescence at the dorsal areas of both brain hemispheres (figure 4 N, middle panel) raises doubts whether this signal is actually a specific GRASP fluorescence between two small populations of neurons.

Answer: We appreciate the reviewer for critically highlighting the inadequacies in our presentation of the GRASP data. We agree that one of our previous panels contained excessive background noise, making it difficult for reviewers and readers to discern the different neuronal connections. To address this issue, we have replaced it with a more representative image that clearly illustrates the strengthening of synaptic connections from SIF to sNPF-R in several neurons, including SIFa cells (Fig. S5J). We hope that this updated image will help convince both the reviewer and readers of the validity of our GRASP data.

Comment 8. The authors cite Martelli et al. (2017) with the hypothesis that sNPF-releasing neurons provide input signals to SIFamide neurons to modulate feeding behavior. However, the cited manuscript does not contain such a hypothesis. The authors should review the reference in more detail.

__ Answer:__ We appreciate reviewer to correctly point our misunderstanding of references. We agree with reviewer that Martelli et al.'s paper didn't mention about sNPF signaling transmits hunger and satiety information to SIFa neurons. We removed this sentence and replaced it as below correctly mentioning that sNPF signaling is related to feeding behavior however it's connection to SIFa neurons are not known. We greatly appreciate the reviewer for acknowledging our efforts to accurately cite previous articles that support our rationale and ideas.

" Short neuropeptide F (sNPF) signaling plays a crucial role in regulating feeding behavior in Drosophila melanogaster, influencing food intake and body size [60,66,67]. However, there is currently no direct evidence reported linking sNPF signaling to SIFa neurons."

Comment ____9. In lines 281 ff., the authors state that SIFamide neurons receive inputs from peptidergic neurons but simultaneously claim that "this speculation is based on morphological observations." This is incorrect. The functional co-activation/imaging analyses provided in Martelli et al. (2017) should not be ignored.

* Answer: We fully agree with the reviewer that we misinterpreted Martelli et al.'s analysis. We have removed "this speculation is based on morphological observations." from* the following sentence and finalize as below:

"The SIFa neurons receive inputs from many peptidergic pathways including Crz, dilp2, Dsk, sNPF, MIP, and hugin"

Comment 10. Figure 6: A transcriptional calcium sensor (TRIC) was used to quantify the accumulation GFP induced by calcium influx in SIFamide neurons. However, I could not find any description of the method in the materials and methods section, nor any explanation how the data were acquired or analyzed. What is the RFP expression good for? How exactly are thresholds determined, and why are areas rather than fluorescence intensities quantified? Overall, this part of the manuscript is rather confusing and needs more explanation.

__ Answer: Thank you for your continued engagement with our manuscript and for highlighting the need for further clarification on our methods. Your attention to the details of our immunohistochemistry experiments is commendable, and we agree that providing a clear explanation of our thresholding and normalization procedures is essential for the transparency and reproducibility of our results. We primarily adhered to the established methods outlined by Kayser et al. [8]. To address your first point, we have now included a more detailed description of our thresholding and normalization procedures in the __MATERIALS AND METHODS section as below.

"Quantitative analysis of fluorescence intensity

To ascertain calcium levels and synaptic intensity from microscopic images, we dissected and imaged five-day-old flies of various social conditions and genotypes under uniform conditions. The GFP signal in the brains and VNCs was amplified through immunostaining with chicken anti-GFP, rabbit anti-DsRed, and mouse anti-nc82 primary antibodies. Image analysis was conducted using ImageJ software. For the quantification of fluorescence intensities, an investigator, blinded to the fly's genotype, thresholded the sum of all pixel intensities within a sub-stack to optimize the signal-to-noise ratio, following established methods [100]. The total fluorescent area or region of interest (ROI) was then quantified using ImageJ, as previously reported. For CaLexA or TRIC signal quantification, we adhered to protocols detailed by Kayser et al. [101], which involve measuring the ROI's GFP-labeled area by summing pixel values across the image stack. This method assumes that changes in the GFP-labeled area and intensity are indicative of alterations in the CaLexA and TRIC signal, reflecting synaptic activity. ROI intensities were background-corrected by measuring and subtracting the fluorescent intensity from a non-specific adjacent area, as per Kayser et al. [101]. For normalization, nc82 fluorescence is utilized for CaLexA, while RFP signal is employed for TRIC experiments, as the RFP signal from the TRIC reporter is independent of calcium signaling [72] . For the analysis of GRASP or tGRASP signals, a sub-stack encompassing all synaptic puncta was thresholded by a genotype-blinded investigator to achieve the optimal signal-to-noise ratio. The fluorescence area or ROI for each region was quantified using ImageJ, employing a similar approach to that used for CaLexA or TRIC quantification [100]. 'Norm. GFP Int.' refers to the normalized GFP intensity relative to the RFP signal.

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__Comment 11. __Similarly, it remains unclear how exactly syteGFP fluorescence and DenMark fluorescence were quantified. Why are areas indicated and not fluorescence intensity values? In fact, it appears worrisome that isolation of males should lead to a drastic decline in synaptic terminals (as measure through a vesicle-associated protein) by ~ 30%, or, conversely, keeping animals in groups lead to an respective increase (figure 7D). The technical information how exactly this was quantified is not sufficient.

__ Answer: __Thank you for your ongoing engagement with our manuscript and for emphasizing the need for clarification on our methods. We appreciate your attention to the details of our immunohistochemistry experiments and agree that a clear explanation of our thresholding and normalization procedures is vital for transparency and reproducibility. We acknowledge that signal intensity correlates with area measurements, which is an important consideration. In response to your valuable suggestion, we have revised our approach to present data based on intensity measurements and updated the Y-axis labeling to "Norm. GFP Int." (normalized GFP intensity) for clarity. We primarily followed the established methods from Kayser et al. (2014) [8]. Additionally, we have included a more detailed description of our thresholding and normalization procedures in the "Quantitative analysis of fluorescence intensity" in __MATERIALS AND METHODS __section as we quoted above.

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Minor concerns:

Comment 1. Reference 29 and reference 33 are the same.

   __Answer:__ We removed reference 29.

Comment 2. In figure legends, abbreviations should be explained when used first (e.g., figure 1 A "MD", is explained below for panel C-F), or "CS males". __ __

__Answer: __We have ensured that abbreviations are explained only when they are first used in the figure legends.

Comment 3. Indications for statistical significance must be shown in all figure legends at the end of each figure legend, not only in figure 1. __ __

__ Answer:__ We appreciate the reviewer’s advice. However, we have published all our other manuscripts using the same format for mating duration, stating, "The same notations for statistical significance are used in other figures," in the first figure where we describe our statistical significances. We intend to continue with this approach initially and will then adhere to the journal's policy.

Comment 4. The figures appear overloaded. For example why do you need two different axis designations (mating duration and differences between means)? __ __

__ Answer: __We appreciate the reviewer's suggestion to refine our figures, and we have indeed reformatted them to provide clearer presentation and improved readability. Our decision is based on the fact that our analysis encompasses not only traditional t-tests but also incorporates estimation statistics, which have been demonstrated to be effective for biological data analysis [22]. The inclusion of DBMs is essential for the accurate interpretation of these estimation statistics, ensuring a comprehensive representation of our findings. This is the primary area where we present two different axis designations.

Comment 5. Line: 1154: Typo: gluttaminergic should be glutamatergic.

   __Answer:__ We fixed all.

Comment 6. The authors frequently write "system" when referring to transmitter types, e.g., "glutaminergic system", "octopaminergic system", etc. It I not clear what the term "system" actually refers to. If the authors claim that SIFamide neurons release these transmitters in addition to SIFamide, they should state that precisely and then add experiments to show that this is the case.

   __Answer:__ We agree with reviewer and removed the word 'system' after the name of neurotransmitter's name.

Comment 7. Figure S6: It is not explained in the figure legend what fly strain "UAS-ctrl" actually is. Does "ctrl" mean control? And what genotype is hat control? __ __

__Answer: __It was wild-type strain. We fixed it as "+".

Comment 8. Figure legend S6, line 1371: The authors indicate experiments using UAS-OrkDeltaC. I could not find these data in the figure. __ __

__Answer: __It's now in Fig.S6U-W.

Comment 9. Line 470: "...reduced branching of SIFa axons at the postsynaptic level" should perhaps be "presynaptic level"?

Answer: Reviewer is correct. We fixed it.

Conclusive Comments:* Overall, the study advances our knowledge about the behavioral roles of SIFamide, which is certainly important, interesting, and worthy of being reported. However, the manuscript also raises several serious caveats and includes points that remain speculative and are less convincing.

Overall, the neuronal basis of action selection based on motivational factors (metabolic state, mating experience, sleep/wake status, etc.) is not well understood. The analysis of SIFamide function in insects might provide a way to address the question how different motivational signals are integrated to orchestrate behavior.*

• *Answer: Thank you for your thoughtful review and for recognizing the significance of our study in advancing knowledge about the behavioral roles of SIFamide. We appreciate your acknowledgment that our work is important, interesting, and worthy of publication.

We understand your concerns regarding the caveats and speculative points raised in the manuscript. We agree that the neuronal basis of action selection influenced by motivational factors—such as metabolic state, mating experience, and sleep/wake status—remains poorly understood. We believe that our analysis of SIFamide function in insects offers valuable insights into how various motivational signals are integrated to orchestrate behavior.

In response to your comments, we have made revisions to clarify our findings and address the concerns raised. We aim to strengthen the arguments presented in the manuscript and provide a more robust discussion of the implications of our results. Thank you once again for your constructive feedback, which has been instrumental in improving the clarity and impact of our work.

• *

* *

Reviewer #3

General Comments:* The Manuscript Peptidergic neurons with extensive branching orchestrate the internal states and energy balance of male Drosophila melanogaster by Yuton Song and colleagues addresses the question how SIFamidergic neurons coordinate behavioral responses in a context-dependent manner. In this context the authors investigate how SIFa neurons receive information about the physiological state of the animal and integrate this information into the processing of external stimuli. The authors show that SIFamidergic neurons and sNPPF expressing neurons form a feedback loop in the ventral nerve cord that modulate long mating (LMD) and shorter mating duration (SMD).

The manuscript is well written and very detailed and provides an enormous amount of data corroborating the claims of the authors. However, before publication the authors may want to address some points of concern that warrant some deeper explanation.*

• *__Answer: __Thank you for your positive feedback on our manuscript. We appreciate your recognition of the importance of our study in investigating how SIFa neurons integrate information about the physiological state of the animal with external stimuli, as well as your acknowledgment of the substantial data we provide to support our claims. We understand your concerns regarding certain points that require deeper explanation, and we are committed to addressing these issues to enhance the clarity and robustness of our findings. Your insights into the neuronal basis of action selection influenced by motivational factors are invaluable, and we believe that our exploration of SIFamide function in insects contributes significantly to understanding how various motivational signals orchestrate behavior. Thank you once again for your constructive comments, which will help us improve our manuscript before publication.

Major concerns:

Comment 1. On page 6 line 110 the authors describe that knocking-down SIFamide in glia cell does not change LMD or SMD and say that SIFa expression in glia does not contribute to interval timing behavior. However, the authors do not provide any information why they investigate the role of SIFa expression in glia. Is there any SIFa-expression in glia? The authors should somehow demonstrate using antibody labelling against SIFamide whether any glia specific expression of this peptide is to be expected. If they cannot provide this data - the take home message of the experiment cannot be that glia knockdown of SIFamide does not affect the behavior because you cannot knockdown anything that is not there.

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• In the latter case the experiment could be considered as a nice negative control for the elav-Gal4 pan-neuronal knockdown of SIFamide. The authors provide some Figure supplement where they use repo-Gal80 to partially answer this question. However, the authors should keep in mind that Gal4-drivers are not always complete in the expression pattern. Accordingly, the result should be corroborated with immune-labelling against SIFamide directly.*

__ Answer: __We appreciate the reviewer's constructive and critical comments regarding the use of our glial cell drivers. As the reviewer rightly pointed out, we believe that glial control is not essential for our manuscript, given that the expression of SIFa is well established in only four neurons. Therefore, we have removed the data related to glial drivers from this manuscript.

Comment 2. At this point I would like to directly comment on the figure quality. The figures are so crowded that the described anatomical details are hardly visible. In my opinion the manuscript would profit from less data in the main part and more stringent description of the core of the biological problem the authors want to address. The authors may want to reduce data from the main text and provide additional data that are not directly related to the main story as supplementary information.

__ Answer: __We agree with the reviewer. As another reviewer also suggested that we streamline our figures and data, we have completely restructured our figures and their presentation. In response, we have significantly reduced the density of the main figures and decreased the size of the graphs to enhance clarity. Additionally, we have increased the spacing between panels to ensure that each component is more easily distinguishable. Further details will be provided in our responses to each comment below.

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Comment 3. On page 8 starting with line 140 the authors describe the architecture of SIFamidergic neurons using several anatomical markers e.g., Denmark and further state that they have discovered that the dendrites of SIFa neurons span just the central brain area. Seeing that these data have been published in Martelli et al., 2017 the authors should tune down the claim that this was discovered in their work but rather corroborated earlier results.

__ Answer: __We acknowledge this error, as another reviewer also raised this issue. We have corrected our manuscript as follows:

"The established connections and architecture of SIFa neurons has been described by Martelli et al., which enhances our understanding of their functional roles within the neuronal circuitry [51]. To identify the dendritic and axonal components of SIFa-neuronal processes, we employed a similar approach to that reported by Martelli [51]."

Comment 4. In the next chapter, the authors aim at identifying the presynaptic inputs from SIFa positive neurons that may influence interval timing behavior and make a broad RNAi knock-down screen targeting a majority of neuromodulators. The authors claim that glutaminergic and dopaminergic signaling is necessary for interval timing behavior. I guess the authors mean "glutamatergic" instead of "glutaminergic" as glutamine is the precursor but not the neurotransmitter.

__ Answer: __The reviewer is correct. We have corrected this error and changed all instances to "glutamatergic."

Comment 5____. Furthermore, the authors show that the knock down of Tdc2 with RNAi has comparable effects on SMD than Glutamate and dopamine but appear to not further discuss this in the main text. To me it is not clear why the authors exclude Tdc2 from their resume. The authors should explain this in detail.

   __Answer:__ We appreciate the reviewer’s constructive comments regarding the need for a more detailed demonstration of the role of Tdc2 data. While we did test Tdc2-RNAi and observed interesting phenotypes, we decided not to include these findings in our publication, as our data on glutamate and dopamine offer a more compelling explanation for how SIFa cotransmission with these neurotransmitters can independently influence various behaviors, such as sleep and mating duration. Consequently, we have removed all data related to Tdc2. We believe that further evaluation is necessary to better understand the roles of the tyramine and octopamine systems in SIFa neurons.

Comment 6. The authors base their assumptions that the tested neurotransmitters are expressed in SIFamidergic neurons on Scope database analysis. But a transcript does not necessarily mean that it will be translated too. To my knowledge there is no available data in the literature showing that tyrosine hydroxylase is expressed in SIFamidergic neurons (see e.g., Mao and Davis, 2010). To show that ple or Tdc2 are indeed expressed and translated into functional enzymes in SIFamidergic neurons the authors should provide the according antibody labelling corroborating the result from the transcriptome analysis.

__ Answer:__ We appreciate the reviewer’s constructive comments regarding the role of neurotransmitters in conjunction with SIFa in modulating interval timing behaviors. To confirm the expression of dopamine (DA) in SIFa neurons, we utilized a well-established genetic toolkit for dissecting dopamine circuit function in Drosophila [18]. Our findings demonstrate that TH-C-GAL4 specifically labels SIFa neurons, which have been confirmed to be dopaminergic (Fig. S4M). This aligns with the genetic intersection data and the findings from Xie et al. (2018), confirming that a subset of SIFa neurons is indeed dopaminergic. We have included these new results in the main text as follows:

" To further verify the presence of DA neurons within the SIFa neuron population, we utilized a well-established genetic toolkit for dissecting DA circuits and confirmed part of SIFa neurons are dopaminergic (S4M Fig) [58]."

   To confirm the glutamatergic characteristics of SIFa neurons, we conducted several experiments that established glutamate as the most critical neurotransmitter for generating interval timing in both SIFa and SIFaR neurons. First, to demonstrate the presence of glutamatergic synaptic vesicles in SIFa neurons, we utilized a conditional glutamatergic synaptic vesicle marker for *Drosophila*, developed by Certel et al. [19]. Our results confirmed that SIFa neurons exhibit strong expression of glutamatergic synaptic vesicles (Fig. 2P and Fig. S4N as a genetic control). We have described these new results in the main text as follows:

"To further substantiate the role of glutamate in SIFa-mediated behaviors. we targeted the expression of VGlut receptor in neurons that carry the SIFaR. Strikingly, the knockdown of VGlut receptor in these neurons also disrupted SMD behavior, mirroring the phenotype observed upon direct suppression of glutamatergic signaling in SIFa neurons (S4O-L Fig)."

   To further confirm that glutamate release from SIFa neurons influences the function of SIFaR neurons, we tested several RNAi strains targeting glutamate receptors. Our results showed that the knockdown of glutamate receptors in SIFaR-expressing neurons produced phenotypes similar to those observed with VGlut-RNAi knockdown in SIFa neurons (Fig. S4I-N). We believe that this series of experiments demonstrates that glutamate and dopamine work in conjunction with SIFa to modulate interval timing and other behaviors related to energy balance. We have described these new results in the main text as follows:

"We also further verified that the knockdown of glutamate receptors in SIFaR-expressing neurons produces phenotypes similar to those resulting from VGlut knockdown in SIFa neurons (S4G to S4L Fig). This suggests that glutamate is an essential neurotransmitter for modulating interval timing in SIFa neurons."

Comment 7. The authors compare the LMD and SMD behavior of the animals with reduced expression with "heterozygous control animals" the authors should describe in detail what these are - are these controls the driver lines or the effector lines or a mix of both? The authors should provide the data for heterozygous driver line controls as well as heterozygous effector line controls to exclude any genetic background influence on the measured behavior. Accordingly, the authors should provide the data for the same controls for the sleep experiment in figure 3O and all the other behavioral experiments in the following parts of the manuscript.

__ Answer: __We sincerely thank the reviewer for insightful comments regarding the absence of traditional genetic controls in our study of LMD and SMD behaviors. We acknowledge the importance of such controls and wish to clarify our rationale for not including them in the current investigation. The primary reason for not incorporating all genetic control lines is that we have previously assessed the LMD and SMD behaviors of GAL4/+ and UAS/+ strains in our earlier studies. Our past experiences have consistently shown that 100% of the genetic control flies for both GAL4 and UAS exhibit normal LMD and SMD behaviors. Given these findings, we deemed the inclusion of additional genetic controls to be non-essential for the present study, particularly in the context of extensive screening efforts. We understand the value of providing a clear rationale for our methodology choices. To this end, we have added a detailed explanation in the "MATERIALS AND METHODS" section and the figure legends of Figure 1. This clarification aims to assist readers in understanding our decision to omit traditional controls, as outlined below.

"Mating Duration Assays for Successful Copulation

The mating duration assay in this study has been reported [33,73,93]. To enhance the efficiency of the mating duration assay, we utilized the Df (1) Exel6234 (DF here after) genetic modified fly line in this study, which harbors a deletion of a specific genomic region that includes the sex peptide receptor (SPR)[94,95]. Previous studies have demonstrated that virgin females of this line exhibit increased receptivity to males [95]. We conducted a comparative analysis between the virgin females of this line and the CS virgin females and found that both groups induced SMD. Consequently, we have elected to employ virgin females from this modified line in all subsequent studies. For naïve males, 40 males from the same strain were placed into a vial with food for 5 days. For single reared males, males of the same strain were collected individually and placed into vials with food for 5 days. For experienced males, 40 males from the same strain were placed into a vial with food for 4 days then 80 DF virgin females were introduced into vials for last 1 day before assay. 40 DF virgin females were collected from bottles and placed into a vial for 5 days. These females provide both sexually experienced partners and mating partners for mating duration assays. At the fifth day after eclosion, males of the appropriate strain and DF virgin females were mildly anaesthetized by CO2. After placing a single female in to the mating chamber, we inserted a transparent film then placed a single male to the other side of the film in each chamber. After allowing for 1 h of recovery in the mating chamber in 25℃ incubators, we removed the transparent film and recorded the mating activities. Only those males that succeeded to mate within 1 h were included for analyses. Initiation and completion of copulation were recorded with an accuracy of 10 sec, and total mating duration was calculated for each couple. All assays were performed from noon to 4pm. Genetic controls with GAL4/+ or UAS/+ lines were omitted from supplementary figures, as prior data confirm their consistent exhibition of normal LMD and SMD behaviors [33,73,93,96,97]. Hence, genetic controls for LMD and SMD behaviors were incorporated exclusively when assessing novel fly strains that had not previously been examined. In essence, internal controls were predominantly employed in the experiments, as LMD and SMD behaviors exhibit enhanced statistical significance when internally controlled. Within the LMD assay, both group and single conditions function reciprocally as internal controls. A significant distinction between the naïve and single conditions implies that the experimental manipulation does not affect LMD. Conversely, the lack of a significant discrepancy suggests that the manipulation does influence LMD. In the context of SMD experiments, the naïve condition (equivalent to the group condition in the LMD assay) and sexually experienced males act as mutual internal controls for one another. A statistically significant divergence between naïve and experienced males indicates that the experimental procedure does not alter SMD. Conversely, the absence of a statistically significant difference suggests that the manipulation does impact SMD. Hence, we incorporated supplementary genetic control experiments solely if they deemed indispensable for testing. All assays were performed from noon to 4 PM. We conducted blinded studies for every test[98,99] .

   While we have previously addressed this type of reviewer feedback in our published manuscript [2–7], we appreciate the reviewer’s suggestion to include traditional genetic control experiments. In response, we conducted all feasible combinations of genetic control experiments for LMD/SMD during the revision period. The results are presented in the supplementary figures and are described in the main text.

__Comment 8. __On page 11 line 231 to page 12 line 233 the authors claim that "sNPF signaling transmits hunger and satiety information to SIFa neurons in order to control food search and feeding" and cite Martelli et al., 2017. Could the authors explain more in detail how the Martelli paper somehow proposes this idea? I do not find the link between sNPF signaling hunger and SIFamide in this precise paper.

__ Answer:__ We appreciate the reviewer for accurately pointing out our misunderstanding of the references. We agree that Martelli et al.'s paper does not mention that sNPF signaling transmits hunger and satiety information to SIFa neurons. Consequently, we have removed the relevant sentence and replaced it with a statement correctly indicating that while sNPF signaling is related to feeding behavior, its connection to SIFa neurons remains unknown. We are grateful to the reviewer for acknowledging our efforts to accurately cite previous articles that support our rationale and ideas.

" Short neuropeptide F (sNPF) signaling plays a crucial role in regulating feeding behavior in Drosophila melanogaster, influencing food intake and body size [60,66,67] . However, there is currently no direct evidence reported linking sNPF signaling to SIFa neurons."

Comment 9. On page 15 line 302 - 303 the authors write that "except for PK2-R2, all other genes coexpress with SIFa in SCope data, indicating that hugin inputs to SIFa may not be transmitted through peptidergic signaling" - if SIFamidergic neurons do not express hugin-receptors how do the authors explain the inverted effect of PK2-R2-RNAi on single housed male courtship index when compared to heterozygous SIFaPT Gal4 control that show a reduction under comparable conditions.

__ Answer:__ We appreciate the reviewer’s constructive comments. In line with another reviewer’s suggestion, we have completely removed results of other neuropeptidergic inputs, focusing instead on how sNPF inputs modulate SIFa-mediated behavioral modulation using more advanced techniques such as GCaMP (Fig 3N). Consequently, the phenotypes resulting from various knockdowns of neuropeptide receptors are currently under investigation for a separate manuscript that we are preparing. We hope to successfully address how different neuropeptidergic inputs regulate SIFa neuron activity through various strategies.

Comment 10. On page 17 line 350 - 351 the authors write that "Stimulation of SIFa neurons resulted in an elevation in food consumption. Further, the authors write that "deactivation of SIFa neurons leads to a decrease in food consumption in male flies". From the way this is formulated it is not visible that the role of SIFamide in feeding control was published by Martelli and colleagues before. As the authors do not discuss the finding further in their discussion but cite the concerned paper in other aspects it appears as the authors intentionally want to omit this information to the reader. The authors may add a note that this has been shown before for female flies by Martelli and colleagues.

__ Answer:__ We appreciate reviewer's concern for properly mention previous Martelli et al.'s results about female feeding behavior modulated by SIFa neurons' activity. We agree with reviewer and added sentence as below in main text.

"Nevertheless, the temporary deactivation of SIFa neurons leads to a decrease in food consumption in male flies (Fig 4N and S6F to S6H) as previously described by Martelli et al.'s report in female flies [43]."

Comment 11. SIFamide receptor and GnIHR are discussed as descendants from a common ancestor and the authors nicely demonstrate that SIFamide does not only control homeostatic behavior as shown by Martelli and colleagues but also controls reproductive behavior. The evolution of such behavior control mechanisms may be integrated in the discussion too.

Answer: We appreciate the reviewer’s constructive comments, which enhance the evolutionary significance of our study. We agree with the reviewer and have added the following paragraph to the DISCUSSION section:

"The relationship between SIFamide receptors (SIFaR) and gonadotropin inhibitory hormone receptors (GnIHR) [89] highlights an intriguing evolutionary connection, as both are believed to have descended from a common ancestor [90,91]. This study expands on previous findings by Martelli et al., demonstrating that SIFamide not only regulates homeostatic behaviors but also plays a significant role in reproductive behavior [43]. GnIHR regulates food intake and reproductive behavior in opposing directions, thereby prioritizing feeding behavior over other behavioral tasks during times of metabolic need [92]. The evolution of these behavioral control mechanisms suggests a complex interplay between neuropeptides that modulate both physiological states and reproductive strategies. As SIFamide influences various behaviors, including feeding and sexual activity, it may be integral to understanding how organisms adapt their reproductive strategies in response to environmental and internal cues. This integration of behavioral modulation underscores the evolutionary significance of SIFamide signaling in coordinating essential life functions in Drosophila melanogaster and potentially other species, revealing pathways through which neuropeptides can shape behavior across different contexts."

Conclusive Comments: The manuscript by Song and colleagues is very interesting and may attract a broad readership. However, the authors miss to make clear what was already known and published on the role of SIFamide in homeostatic behavior control before their own study. Seen that the receptors for SIFamide and GnRHI derive from a common ancestor and apparently both GnRHI and SIFamide share similar roles in behavioral control this might indeed suggests that the basic function of this SIFaR/GnIHR-signaling pathway is conserved. This more broad evolutionary aspect is missing in the discussion of the manuscript.

• *Answer: We wholeheartedly agree with the reviewer regarding the evolutionary significance of SIFaR's function in relation to GnIHR, and we have expanded the DISCUSSION section to emphasize this important aspect.

"The relationship between SIFamide receptors (SIFaR) and gonadotropin inhibitory hormone receptors (GnIHR) [89] highlights an intriguing evolutionary connection, as both are believed to have descended from a common ancestor [90,91]. This study expands on previous findings by Martelli et al., demonstrating that SIFamide not only regulates homeostatic behaviors but also plays a significant role in reproductive behavior [43]. GnIHR regulates food intake and reproductive behavior in opposing directions, thereby prioritizing feeding behavior over other behavioral tasks during times of metabolic need [92]. The evolution of these behavioral control mechanisms suggests a complex interplay between neuropeptides that modulate both physiological states and reproductive strategies. As SIFamide influences various behaviors, including feeding and sexual activity, it may be integral to understanding how organisms adapt their reproductive strategies in response to environmental and internal cues. This integration of behavioral modulation underscores the evolutionary significance of SIFamide signaling in coordinating essential life functions in Drosophila melanogaster and potentially other species, revealing pathways through which neuropeptides can shape behavior across different contexts."

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