Reviewer #1 (Public review):

Summary:

Pradhan et al investigated the potential gustatory mechanisms that allow flies to detect cholesterol. They found that flies are indifferent to low cholesterol and avoid high cholesterol. They further showed that the ionotropic receptors Ir7g, Ir51b, and Ir56d are important for the cholesterol sensitivity in bitter neurons. The figures are clear and the behavior result is interesting. However, I have several major comments, especially on the discrepancy of the expression of these Irs with other lab published results, and the confusing finding that the same receptors (Ir7g, Ir51b) have been implicated in the detection of various seemingly unrelated compounds.

Strengths:

The results are very well presented, the figures are clear and well-made, text is easy to follow.

Weaknesses:

(1) Regarding the expression of Ir56d. The reported Ir56d expression pattern contradicts multiple previous studies (Brown et al., 2021 eLife, Figure 6a-c; Sanchez-Alcaniz et al., 2017 Nature Communications, Figure 4e-h; Koh et al., 2014 Neuron, Figure 3b). These studies, using three different driver lines, consistently showed Ir56d expression in sweet-sensing neurons and taste peg neurons. Importantly, Sanchez-Alcaniz et al. demonstrated that Ir56d is not expressed in Gr66a-expressing (bitter) neurons. This discrepancy is critical since Ir56d is identified as the key subunit for cholesterol detection in bitter neurons, and misexpression of Ir7g and Ir51b together is insufficient to confer cholesterol sensitivity (Fig.4b,d). Which Ir56d-GAL4 (and Gr66a-I-GFP) line was used in this study? Is there additional evidence (scRNA sequencing, in-situ hybridization, or immunostaining) supporting Ir56d expression in bitter neurons?

(2) Ir51b has previously been implicated in detecting nitrogenous waste (Dhakal 2021), lactic acid (Pradhan 2024), and amino acids (Aryal 2022), all by the same lab. Additionally, both Ir7g and Ir51b have been implicated in detecting cantharidin, an insect-secreted compound that flies may or may not encounter in the wild, by the same lab. Is Ir51b proposed to be a specific receptor for these chemically distinct compounds or a general multimodal receptor for aversive stimuli? Unlike other multimodal bitter receptors, the expression level of Ir51b is rather low and it's unclear which subset of GRNs express this receptor. The chemical diversity among nitrogenous waste, amino acids, lactic acid, cantharidin, and cholesterol raises questions about the specificity of these receptors and warrants further investigation and at a minimum discussion in this paper. Given the wide and seemingly unrelated sensitivity of Ir51b and Ir7g to these compounds I'm leaning towards the hypothesis that at least some of these is non-specific and ecologically irrelevant without further supporting evidence from the authors.

(3) The Benton lab Ir7g-GAL4 reporter shows no expression in adults. Additionally, two independent labellar RNA sequencing studies (Dweck, 2021 eLife; Bontonou et al., 2024 Nature Communications) failed to detect Ir7g expression in the labellum. This contradicts the authors' previous RT-PCR results (Pradhan 2024 Fig. S4, Journal of Hazardous Materials) showing Ir7g expression in the labellum. Additionally the Benton and Carlson lab Ir51b-GAL4 reporters show no expression in adults as well. Please address these inconsistencies.

(4) The premise that high cholesterol intake is harmful to flies, which makes sensory mechanisms for cholesterol avoidance necessary, is interesting but underdeveloped. Animal sensory systems typically evolve to detect ecologically relevant stimuli with dynamic ranges matching environmental conditions. Given that Drosophila primarily consume fruits and plant matter (which contain minimal cholesterol) rather than animal-derived foods (which contain higher cholesterol), the ecological relevance of cholesterol detection requires more thorough discussion. Furthermore, at high concentrations, chemicals often activate multiple receptors beyond those specifically evolved for their detection. If the cholesterol concentrations used in this study substantially exceed those encountered in the fly's natural diet, the observed responses may represent an epiphenomenon rather than an ecologically and ethologically relevant sensory mechanism. What is the cholesterol content in flies' diet and how does that compare to the concentrations used in this paper?

Reviewer #1 (Public review):

The aim of this study is to test the overarching hypothesis that plasticity in BNST CRF neurons drives distinct behavioral responses to unpredictable threat in males and females. The manuscript provides solid evidence for a sex-specific role for CRF-expressing neurons in the BNST in unpredictable aversive conditioning and subsequent hypervigilance across sexes. As the authors note, this is an important question given the high prevalence of sex differences in stress-related disorders, like PTSD, and the role of hypervigilance and avoidance behaviors in these conditions. The study includes in vivo manipulation, bulk calcium imaging, and cellular resolution calcium imaging, which yield important insights into cell-type specific activity patterns. A major strength of this manuscript is the inclusion of both males and females and attention to possible behavioral and neurobiological differences between them throughout.

Reviewer #1 (Public review):

In this study, Osiurak and colleagues investigate the neurocognitive basis of technical reasoning. They use multiple tasks from two neuroimaging studies to show that the area PF is central to technical reasoning and plays an essential role in tool-use and non-tool-use physical problem-solving, as well as both conditions of mentalizing tasks. They also demonstrate the specificity of technical reasoning, finding that area PF is not involved in the fluid-cognition task or the mentalizing network (INT+PHYS vs. PHYS-only). This work enhances our understanding of the neurocognitive basis of technical reasoning that supports advanced technologies.

Strengths:

- The topic this study focuses on is intriguing and can help us understand the neurocognitive processes involved in technical reasoning and advanced technologies.<br /> - The researchers collected fMRI data from multiple tasks. The data is rich and encompasses the mechanical problem-solving task, psychotechnical task, fluid-cognition task, and mentalizing tasks.<br /> - The article is well written.

The authors have addressed many of the reviewers' concerns in their response. They utilized both correlation analysis and coordinate analysis to tackle alternative hypotheses, namely the same-region-but-different-function interpretation and the adjacency interpretation. Additionally, ROI analysis was conducted to validate the negative results. These additional analyses have enhanced the reliability of the findings. This study offers valuable insights into the neurocognitive mechanisms underlying technical reasoning.

Weaknesses:

While the authors attempted to address the limitations of overlap analysis by correlating activation across different tasks within subjects, this issue could not be entirely resolved due to the constraints of the current experimental design. The mechanical problem-solving task was not included since the sample of subjects differed from that of other tasks. Furthermore, the fluid-cognition task was not scanned in the same run as the psychotechnical and mentalizing tasks, which may have contributed to a lack of correlation between them, thereby affecting result interpretation. Moreover, the core cognitive focus of this study, technical reasoning, may be influenced by assumptions about motion-related information. While this issue has been discussed in the discussion section, further evidence is needed to substantiate this interpretation.

Reviewer #1 (Public review):

Hüppe and colleagues had already developed an apparatus and an analytical approach to capture swimming activity rhythms in krill. In a previous manuscript they explained the system, and here they employ it to show a circadian clock, supplemented by exogenous light, produces an activity pattern consistent with "twilight" diel vertical migration (DVM; a peak at sunset, a midnight sink, and a peak in the latter half of the night).

They used light:dark (LD) followed by dark:dark (DD) photoperiods at two times of the year to confirm the circadian clock, coupled with DD experiments at four times a year to show rhythmicity occurs throughout the year along with DVM in the wild population. The individual activity data show variability in the rhythmic response, which is expected. However, their results showed rhythmicity was sustained in DD throughout the year, although the amplitude decayed quickly. The interpretation of a weak clock is reasonable, and they provide a convincing justification for the adaptive nature of such a clock in a species that has a wide distributional range and experiences various photic environments. These data also show that exogenous light increases the activity response and can explain the morning activity bouts, with the circadian clock explaining the evening and late-night bouts. This acknowledgement that vertical migration can be driven by multiple proximate mechanisms is important.

The work is rigorously done, and the interpretations are sound. I see no major weaknesses in the manuscript. Because a considerable amount of processing is required to extract and interpret the rhythmic signals (see Methods and previous AMAZE paper), it is informative to have the individual activity plots of krill as a gut check on the group data.

The manuscript will be useful to the field as it provides an elegant example of looking for biological rhythms in a marine planktonic organism and disentangling the exogenous response from the endogenous one. Furthermore, as high-latitude environments change, understanding how important organisms like krill have the potential to respond will become increasingly important. This work provides a solid behavioral dataset to complement the earlier molecular data suggestive of a circadian clock in this species.

Reviewer #1 (Public review):

Summary:

This manuscript by Kaya et al. studies the effect of food consumption on hippocampal sharp wave ripples (SWRs) in mice. The authors use multiple foods and forms of food delivery to show that the frequency and power of SWRs increase following food intake, and that this effect depends on the caloric content of food. The authors also studied the effects of administration of various food-intake-related hormones on SWRs during sleep, demonstrating that ghrelin negatively affects SWR rate and power, but not GLP-1, insulin, or leptin. Finally, the authors use fiber photometry to show that GABAergic neurons in the lateral hypothalamus, increase activity during a SWR event.

Strengths:

The experiments in this study seem to be well performed, and the data are well presented, visually. The data support the main conclusions of the manuscript that food intake enhances hippocampal SWRs. Taken together, this study is likely to be impactful to the study of the impact of feeding on sleep behavior, as well as the phenomena of hippocampal SWRs in metabolism.

Weaknesses:

None

Reviewer #2 (Public review):

This manuscript addresses an important question which has not yet been solved in the field, what is the contribution of different gamma oscillatory inputs to the development of "theta sequences" in the hippocampal CA1 region. Theta sequences have received much attention due to their proposed roles in encoding short-term behavioral predictions, mediating synaptic plasticity, and guiding flexible decision-making. Gamma oscillations in CA1 offer a readout of different inputs to this region and have been proposed to synchronize neuronal assemblies and modulate spike timing and temporal coding. However, the interactions between these two important phenomena have not been sufficiently investigated. The authors conducted place cell and local field potential (LFP) recordings in the CA1 region of rats running on a circular track. They then analyzed the phase locking of place cell spikes to slow and fast gamma rhythms, the evolution of theta sequences during behavior and the interaction between these two phenomena. They found that place cell with the strongest modulation by fast gamma oscillations were the most important contributors to the early development of theta sequences and that they also displayed a faster form of phase precession within slow gamma cycles nested with theta.

Comments on revisions:

Several important shortcomings were noted in the original manuscript. These have been addressed in this revised version with the addition of multiple new analysis, controls and clarifications. The revised manuscript has been significantly improved and its conclusions are adequately supported by the results presented.

Reviewer #1 (Public review):

Summary:

This very interesting manuscript proposes a general mechanism for how activating signaling proteins respond to species specific signals arising from a variety of stresses. In brief, the authors propose that the activating signal alters the structure by a universal allosteric mechanism.

Strengths:

The unitary mechanism proposed is appealing and testable. The propose that the allosteric module consists of crossed alpha-helical linkers with similar architecture and that their attached regulatory domains connect to phosphatases or other molecules through coiled-coli domains, such that the signal is transduced via rigidifying the alpha helices, permitting downstream enzymatic activity. The authors present genetic and structural prediction data in favor of the model for the system they are studying, and stronger structural data in other systems.

Weaknesses:

I thank the authors for making significant revisions that addressed almost all of my concerns. I hope that the authors will consider addressing my last concern, which is that the title is inappropriate. However, I do not believe that this should hold up the publication of the ms.

"A General Mechanism for Initiating the General Stress Response in Bacteria" is misleading because it suggests a broadly applicable, universal mechanism across all bacterial species, whereas the study primarily focuses on Bacillus subtilis and its RsbU phosphatase activation. While the authors propose that the mechanism may extend to other bacteria, the evidence is largely based on structural modeling rather than direct experimental validation across multiple phyla. Additionally, the phrase "General Stress Response" might imply that the paper broadly explains stress response regulation, but it specifically examines the activation of RsbU by RsbT, which is just one really small part of the broader GSR network. The redundancy in "A General Mechanism for the General Stress Response" could also create an impression of an oversimplified, universal model when stress responses are often species- and context-specific. Furthermore, the study builds upon existing knowledge of partner-switching mechanisms rather than introducing an entirely new concept, making the claim of a general mechanism overstated and misleading for the field.

Title options could be "A Conserved Activation Mechanism for the General Stress Response Phosphatase in Bacteria", "Coiled-Coil Linker-Mediated Activation of a General Stress Response Phosphatase", all of which more accurately reflect the study's scope and findings.

Reviewer #1 (Public review):

Summary:

Kimura et al performed a saturation mutagenesis study of CDKN2A to assess functionality of all possible missense variants and compare them to previously identified pathogenic variants. They also compared their assay result with those from in silico predictors.

Strengths:

CDKN2A is an important gene that modulate cell cycle and apoptosis, therefore it is critical to accurately assess functionality of missense variants. Overall, the paper reads well and touches upon major discoveries in a logical manner.

Weaknesses:

The paper lacks proper details for experiments and basic data, leaving the results less convincing. Analyses are superficial and does not provide variant-level resolution.

Comments on revisions

The manuscript was improved during the revision process.

Reviewer #3 (Public review):

Summary:

The authors investigate the effect of high concentrations of the lipid aldehyde trans-2-hexadecenal (t-2-hex) in a yeast deletion strain lacking the detoxification enzyme. Transcriptomic analyses as global read out reveals that a large range of cellular functions across all compartments are affected (transcriptomic changes affect 1/3 of all genes). The authors provide additional analyses, which indicate that mitochondrial protein import is affected.

Strengths:

Global analyses (transcriptomic and functional genomics approach) to obtain an overview of changes upon yeast treatment with high doses of t-2-hex.

Weaknesses:

The use of high concentrations of t-2-hex in combination with a deletion of the detoxifying enzyme Hfd1 limits the possibility to identify physiological relevant changes. For the follow-up analysis, the authors focus on mitochondrial proteins and describe an impairment of mitochondrial protein biogenesis, but the underlying molecular modification resulting in the observed impairment is not yet known.

Reviewer #1 (Public review):

Summary:

The authors have developed self-amplifying RNAs (saRNAs) encoding additional genes to suppress dsRNA-related inflammatory responses and cytokine release. Their results demonstrate that saRNA constructs encoding anti-inflammatory genes effectively reduce cytotoxicity and cytokine production, enhancing the potential of saRNAs. This work is significant for advancing saRNA therapeutics by mitigating unintended immune activation.

Strengths:

This study successfully demonstrates the concept of enhancing saRNA applications by encoding immune-suppressive genes. A key challenge for saRNA-based therapeutics, particularly for non-vaccine applications, is the innate immune response triggered by dsRNA recognition. By leveraging viral protein properties to suppress immunity, the authors provide a novel strategy to overcome this limitation. The study presents a well-designed approach with potential implications for improving saRNA stability and minimizing inflammatory side effects.

Weaknesses:

(1) Impact on Cellular Translation:

The authors demonstrate that modified saRNAs with additional components enhance transgene expression by inhibiting dsRNA-sensing pathways. However, it is unclear whether these modifications influence global cellular translation beyond the expression of GFP and mScarlet-3 (which are encoded by the saRNA itself). Conducting a polysome profiling analysis or a puromycin labeling assay would clarify whether the modified saRNAs alter overall translation efficiency. This additional data would strengthen the conclusions regarding the specificity of dsRNA-sensing inhibition.

(2) Stability and Replication Efficiency of Long saRNA Constructs:

The saRNA constructs used in this study exceed 16 kb, making them more fragile and challenging to handle. Assessing their mRNA integrity and quality would be crucial to ensure their robustness.<br /> Furthermore, the replicative capacity of the designed saRNAs should be confirmed. Since Figure 4 shows lower inflammatory cytokine production when encoding srIkBα and srIkBα-Smad7-SOCS1, it is important to determine whether this effect is due to reduced immune activation or impaired replication. Providing data on replication efficiency and expression levels of the encoded anti-inflammatory proteins would help rule out the possibility that reduced cytokine production is a consequence of lower replication.

(3) Comparative Data with Native saRNA:

Including native saRNA controls in Figures 5-7 would allow for a clearer assessment of the impact of additional genes on cytokine production. This comparison would help distinguish the effect of the encoded suppressor proteins from other potential factors.

(4) In vivo Validation and Safety Considerations:

Have the authors considered evaluating the in vivo potential of these saRNA constructs? Conducting animal studies would provide stronger evidence for their therapeutic applicability. If in vivo experiments have not been performed, discussing potential challenges - such as saRNA persistence, biodistribution, and possible secondary effects-would be valuable.

(5) Immune Response to Viral Proteins:

Since the inhibitors of dsRNA-sensing proteins (E3, NSs, and L*) are viral proteins, they would be expected to induce an immune response. Analyzing these effects in vivo would add insight into the applicability of this approach.

(6) Streamlining the Discussion Section:

The discussion is quite lengthy. To improve readability, some content - such as the rationale for gene selection-could be moved to the Results section. Additionally, the descriptions of Figure 3 should be consolidated into a single section under a broader heading for improved coherence.

Reviewer #1 (Public review):

Summary:

The authors present a novel usage of fluorescence lifetime imaging microscopy (FLIM) to measure NAD(P)H autofluorescence in the Drosophila brain, as a proxy for cellular metabolic/redox states. This new method relies on the fact that both NADH and NADPH are autofluorescent, with a different excitation lifetime depending on whether they are free (indicating glycolysis) or protein-bound (indicating oxidative phosphorylation). The authors successfully use this method in Drosophila to measure changes in metabolic activity across different areas of the fly brain, with a particular focus on the main center for associative memory: the mushroom body.

Strengths:

The authors have made a commendable effort to explain the technical aspects of the method in accessible language. This clarity will benefit both non-experts seeking to understand the methodology and researchers interested in applying FLIM to Drosophila in other contexts.

Weaknesses:

(1) Despite being statistically significant, the learning-induced change in f-free in α/β Kenyon cells is minimal (a decrease from 0.76 to 0.73, with a high variability). The authors should provide justification for why they believe this small effect represents a meaningful shift in neuronal metabolic state.

(2) The lack of experiments examining the effects of long-term memory (after spaced or massed conditioning) seems like a missed opportunity. Such experiments could likely reveal more drastic changes in the metabolic profiles of KCs, as a consequence of memory consolidation processes.

(3) The discussion is mostly just a summary of the findings. It would be useful if the authors could discuss potential future applications of their method and new research questions that it could help address.

Joint Public Review:

The manuscript describes the role of mmp21, a metallopeptidase, in left-right patterning. MMP21 has been implicated in genetic studies of patients with heterotaxy and the authors add an additional case. However, a molecular mechanism for Htx/LR patterning defects is not clear although one previous study implicated Notch signaling. The authors find that mmp21 does indeed cause LR patterning defects in Xenopus consistent with work in mice and zebrafish without affecting cilia motility. Importantly, the authors extend this work to place mmp21 in the LR pathway between dand5 (in the nodal cascade) and the cilia-driven sensation of flow. With RNA overexpression studies, the authors show MMP21 can induce Nodal signaling bilaterally suggesting it is an activator of the pathway, potentially through regulation of dand5 asymmetry. The authors also show that the role of MMP21 is upstream of another matrix metalloprotease CIROP which is tethered to the plasma membrane and possibly the cilium. They propose that mmp21, which is secreted, may represent a morphogen that is asymmetrically distributed along the LR axis due to cilia-driven flow and sensed by sensory cilia in the LRO.

The authors attempt to address a highly controversial subject in the LR patterning field, that is, the debate between Nodal Vesicular Particles (NVP, ie morphogens) being driven by cilia to activate signaling on the left and the Two Cilia model which posits that mechanosensation of fluid flow and not morphogens drive asymmetric organogenesis.

The model they propose is that mmp21 is secreted in the center of the LRO. LRO cilia generate leftward flow driving mmp21 to the left where sensory cilia at the LRO margin detect the mmp21 via cirop and suppress dand5, leading to activation of Nodal and Pitx2 expression.

First and foremost, the authors need to consider alternative models in the discussion and acknowledge the strengths and weaknesses of their work. All three reviewers felt that their conclusion that mmp21 is a morphogen is premature and that other models could also fit their data which needs to be discussed. The authors need to soften the conclusion that other models have been excluded.

Reviewer #1 (Public review):

Summary:

The authors demonstrate that two human preproprotein human mutations in the BMP4 gene cause a defect in proprotein cleavage and BMP4 mature ligand formation, leading to hypomorphic phenotypes in mouse knock-in alleles and in Xenopus embryo assays.

Strengths:

They provide compelling biochemical and in vivo analyses supporting their conclusions, showing the reduced processing of the proprotein and concomitant reduced mature BMP4 ligand protein from impressively mouse embryonic lysates. They perform excellent analysis of the embryo and post-natal phenotypes demonstrating the hypomorphic nature of these alleles. Interesting phenotypic differences between the S91C and E93G mutants are shown with excellent hypotheses for the differences. Their results support that BMP4 heterodimers act predominantly throughout embryogenesis whereas BMP4 homodimers play essential roles at later developmental stages.

Weaknesses:

In the revision the authors have appropriately addressed the previous minor weaknesses.

Reviewer #2 (Public review):

Summary:

In this paper, the authors first examined lens phenotypes in mice with Le-Cre-mediated knockdown (KD) of all the four FGFR (FGFR1-4), and found that pERK signals, Jag1 and foxe3 expression are absent or drastically reduced, indicating that FGF signaling is essential for lens induction. Next, the authors examined lens phenotypes of FGFR1/2-KD mice and found that lens fiber differentiation is compromised, and that proliferative activity and cell survival are also compromised in lens epithelium. Interestingly, Kras activation rescues defects in lens growth and lens fiber differentiation in FGFR1/2-KD mice, indicating that Ras activation is a key step for lens development, downstream of FGF signaling. Next, the authors examined the role of Frs2, Shp2 and Grb2 in FGF signaling for lens development. They confirmed that lens fiber differentiation is compromised in FGFR1/3-KD mice combined with Frs2-dysfunctional FGFR2 mutants, which is similar to lens phenotypes of Grb2-KD mice. However, lens defects are milder in mice with Shp2YF/YF and Shp2CS mutant alleles, indicating that involvement of Shp2 is limited for the Grb2 recruitment for lens fiber differentiation. Lastly, the authors showed new evidence on the possibility that another adapter protein, Shc1, promotes Grb2 recruitment independent of Frs2/Shp2-mediated Grb2 recruitment.

Strengths:

Overall, the manuscript provides valuable data on how FGFR activation leads to Ras activation through the adapter platform of Frs2/Shp2/Grb2, which advances our understanding on complex modification of FGF signaling pathway. The authors applied a genetic approach using mice, whose methods and results are valid to support the conclusion. The discussion also well summarizes the significance of their findings.

Weaknesses:

The authors found that the new adaptor protein Shc1 is involved in Grb2 recruitment in response to FGF receptor activation. However, the main data on Shc1 are only histological sections and statistical evaluation of lens size. Cellular-level evidence on Shc1 makes the authors' conclusion more convincing.

Comments on latest version:

In the 2nd revised version of the manuscript, the authors responded to my recommendation to show the number of biological replicates for Prox1 and αA-crystallin (Fig. 1F) and conductedstatistical analysis for pmTOR, and pS6 (Supplementary figure 1B).

The authors also explained why the animals are no longer available for the additional experiments that I requested. I may understand the situation, but hope that the authors will investigate the cellular-level evidence on Shc1 in more detail and report it maybe as another paper in future.

Reviewer #1 (Public review):

Summary:

Chang and colleagues use tetrode recordings in behaving rats to study how learning an audiovisual discrimination task shapes multisensory interactions in auditory cortex. They find that a significant fraction of neurons in auditory cortex responded to visual (crossmodal) and audiovisual stimuli. Both auditory-responsive and visually-responsive neurons preferentially responded to the cue signaling the contralateral choice in the two-alternative forced choice task. Importantly, multisensory interactions were similarly specific for the congruent audiovisual pairing for the contralateral side.

Strengths:

The experiments are conducted in a rigorous manner. Particularly thorough are the comparisons across cohorts of rats trained in a control task, in a unisensory auditory discrimination task and the multisensory task, while also varying the recording hemisphere and behavioral state (engaged vs. anesthesia). The resulting contrasts strengthen the authors' findings and rule out important alternative explanations regarding the effect of experience. Through the comparisons, they show that the enhancements of activity in multisensory trials in auditory cortex are specific to the paired audiovisual stimulus and specific to contralateral choices in correct trials and thus dependent on learned associations in a task engaged state.

Weaknesses:

The main result that multisensory interactions are specific for contralateral paired audiovisual stimuli is consistent across experiments and interpretable as a learned task-dependent effect. However, the alternative interpretation of behavioral signals is crucial to rule out, which would also be specific to contralateral, correct trials in trained animals. Although the authors focus on the first 150 ms after cue onset, some of the temporal profiles of activity suggest that choice-related activity could confound some of the results.

The main concern (noted by all reviewers) is the interpretation of the evoked activity in visual trials. In the revised manuscript, the authors have not provided much data to disentangle movement related activity from sensory related activity. The only new data is on the visual response dynamics in supplementary figure 2, which is unconvincing both in terms of visual response latency and response dynamics. Therefore, the response of the authors has been insufficient to prove the visual nature of the evoked responses.

In this supplemental figure 2 the same example neuron as in the original manuscript is shown again as well as the average z-scored visual response. First, the visual response latency is inconsistent with literature. The first evoked activity in mouse V1 (!) is routinely reported around 50 ms (for example, 45 ms in Niell Stryker 2008, 52 ms, Schnabel et al. 2018, 54 ms in Oude Lohuis et al. 2024). According to the authors the potential route of crossmodal modulation of AC can occur through either corticocortical connections (which will impose further polysynaptic delays - monosynaptic projection from dLGN or V1 incredibly sparse), or through pulvinar (but pulvinar visual responses are much later (they find 170 vs 80 ms in dLGN, Roth et al. 2019) as expected from a higher order thalamic nucleus). One can also critique the estimation of the response latency which depends on the signal strength (visual response is smaller) and thus choice of threshold. With a different arbitrary threshold one would come to different conclusions.

Second, the temporal response dynamics to visual input are the same as the auditory response. It can be observed that if the data were normalized by the max response the dynamics are very similar, with the response back to near baseline levels at 100 ms post stimulus. I am not aware of publications that have observed response dynamics that are similar between A and V stimuli, nor such short-lasting visual response. In the visual system, mean activity typically drops again around 150-200ms.<br /> With the nature of the observed activity unclear, careful interpretation is warranted about audiovisual interactions in auditory cortex.

Reviewer #2 (Public review):

Summary:

In this work, the authors manage to optimize a simple and rapid protocol using SEC followed by DGCU to isolate sEVs with adequate purity and yield from small volumes of plasma. Isolated fractions containing sEVs using SEC, DGCU, SEC-DGCU and DGCU-SEC are compared in terms of their yield, purity surface protein profile and RNA content. Although the combined use of these methodologies has already been evaluated in previous works, the authors manage to adapt them for the use of small volumes of plasma, which allows working in 1.5 mL tubes and reducing the centrifugation time to 2 hours.<br /> The authors finally find that although both the SEC-DGCU and DGCU-SEC combinations achieve isolates with high purity, the SEC-DGCU combination results in higher yields.<br /> This work provides an interesting tool for the rapid obtention of sEVs with sufficient yield and purity for detailed characterization which could be very useful in research and clinical therapy.

Strengths:

The work is well written and organized.<br /> The authors clearly state the problem they want to address, that is, optimizing a method that allows sEV to be isolated from small volumes of plasma.<br /> Although these methodologies have been tested in previous works, the authors manage to isolate sEVs of high purity and good performance through a simple and fast methodology.<br /> The characteristics of all isolated fractions are exhaustively analyzed through various state-of-the-art methodologies.<br /> They present a good interpretation of the results obtained through the methodologies used.

Weaknesses:

Although this work focuses on comparing different techniques and their combinations to find an optimal option, the authors could strengthen their analysis by using statistical methods that reliably show the differences between the explored techniques.

Comments on revisions:

Although superiority of the proposed method was demonstrated by other techniques, it is always advisable to calculate the differences between different methodologies through different statistical methods, whenever possible, to strengthen the obtained results.

Reviewer #1 (Public review):

Summary:

In this manuscript entitled "Molecular dynamics of the matrisome across sea anemone life history", Bergheim and colleagues report the prediction, using an established sequence analysis pipeline, of the "matrisome" - that is, the compendium of genes encoding constituents of the extracellular matrix - of the starlet sea anemone Nematostella vectensis. Re-analysis of an existing scRNA-Seq dataset allowed the authors to identify the cell types expressing matrisome components and different developmental stages. Last, the authors apply time-resolved proteomics to provide experimental evidence of the presence of the extracellular matrix proteins at three different stages of the life cycle of the sea anemone (larva, primary polyp, adult) and show that different subsets of matrisome components are present in the ECM at different life stages with, for example, basement membrane components accompanying the transition from larva to primary polyp and elastic fiber components and matricellular proteins accompanying the transition from primary polyp to the adult stage.

Strengths:

The ECM is a structure that has evolved to support the emergence of multicellularity and different transitions that have accompanied the complexification of multicellular organisms. Understanding the molecular makeup of structures that are conserved throughout evolution is thus of paramount importance.

The in-silico predicted matrisome of the sea anemone has the potential to become an essential resource for the scientific community to support big data annotation efforts and understand better the evolution of the matrisome and of ECM proteins, an important endeavor to better understand structure/function relationships. This study is also an excellent example of how integrating datasets generated using different -omic modalities can shed light on various aspects of ECM metabolism, from identifying the cell types of origins of matrisome components using scRNA-Seq to studying ECM dynamics using proteomics.

Weaknesses:

My concerns pertain to the three following areas of the manuscript:

(1) In-silico definition of the anemone matrisome using sequence analysis:

a) While a similar computational pipeline has been applied to predict the matrisome of several model organisms, the authors fail to provide a comprehensive definition of the anemone matrisome: In the text, the authors state the anemone matrisome is composed of "551 proteins, constituting approximately 3% of its proteome (see page 6, line 14), but Figure 1 lists 829 entries as part of the "curated" matrisome, Supplementary Table S1 lists the same 829 entries and the authors state that "Here, we identified 829 ECM proteins that comprise the matrisome of the sea anemone Nematostella vectensis" (see page 17, line 10). Is the sea anemone matrisome composed of 551 or 829 genes? If we refer to the text, the additional 278 entries should not be considered as part of the matrisome, but what is confusing is that some are listed as glycoproteins and the "new_manual_annotation" proposed by the authors and that refer to the protein domains found in these additional proteins suggest that in fact, some could or should be classified as matrisome proteins. For example, shouldn't the two lectins encoded by NV2.3951 and NV2.3157 be classified as matrisome-affiliated proteins? Based on what has been done for other model organisms, receptors have typically been excluded from the "matrisome" but included as part of the "adhesome" for consistency with previously published matrisome; the reviewer is left wondering whether the components classified as "Other" / "Receptor" should not be excluded from the matrisome and moved to a separate "adhesome" list.

In addition to receptors, the authors identify nearly 70 glycoproteins classified as "Other". Here, does other mean "non-matrisome" or "another matrisome division" that is not core or associated? If the latter, could the authors try to propose a unifying term for these proteins? Unfortunately, since the authors do not provide the reasons for excluding these entries from the bona fide matrisome (list of excluding domains present, localization data), the reader is left wondering how to treat these entries.

Overall, the study would gain in strength if the authors could be more definitive and, if needed, even propose novel additional matrisome annotations to include the components for now listed as "Other" (as was done, for example, for the Drosophila or C. elegans matrisomes).

b) It is surprising that the authors are not providing the full currently accepted protein names to the entries listed in Supplementary Table S1 and have used instead "new_manual_annotation" that resembles formal protein names. This liberty is misleading. In fact, the "new_manual_annotation" seems biased toward describing the reason the proteins were positively screened for through sequence analysis, but many are misleading because there is, in fact, more known about them, including evidence that they are not ECM proteins. The authors should at least provide the current protein names in addition to their "new_manual_annotations".

c) To truly serve as a resource, the Table should provide links to each gene entry in the Stowers Institute for Medical Research genome database used and some sort of versioning (this could be added to columns A, B, or D). Such enhancements would facilitate the assessment of the rigor of the list beyond the manual QC of just a few entries.

d) Since UniProt is the reference protein knowledge database, providing the UniProt IDs associated with the predicted matrisome entries would also be helpful, giving easy access to information on protein domains, protein structures, orthology information, etc.

e) In conclusion, at present, the study only provides a preliminary draft that should be more rigorously curated and enriched with more comprehensive and authoritative annotations if the authors aspire the list to become the reference anemone matrisome and serve the community.

(2) Proteomic analysis of the composition of the mesoglea during the sea anemone life cycle:

a) The product of 287 of the 829 genes proposed to encode matrisome components was detected by proteomics. What about the other ~550 matrisome genes? When and where are they expressed? The wording employed by the authors (see line 11, page 13) implies that only these 287 components are "validated" matrisome components. Is that to say that the other ~550 predicted genes do not encode components of the ECM? This should be discussed.

b) Can the authors comment on how they have treated zero TMT values or proteins for which a TMT ratio could not be calculated because unique to one life stage, for example?

c) Could the authors provide a plot showing the distribution of protein abundances for each matrisome category in the main figure 4? In mammals, the bulk of the ECM is composed of collagens, followed by fibrillar ECM glycoproteins, the other matrisome components being more minor. Is a similar distribution observed in the sea anemone mesoglea?

d) Prior proteomic studies on the ECM of vertebrate organisms have shown the importance of allowing certain post-translational modifications during database search to ensure maximizing peptide-to-spectrum matching. Such PTMs include the hydroxylation of lysines and prolines that are collagen-specific PTMs. Multiple reports have shown that omitting these PTMs while analyzing LC-MS/MS data would lead to underestimating the abundance of collagens and the misidentification of certain collagens. The authors may want to re-analyze their dataset and include these PTMs as part of their search criteria to ensure capturing all collagen-derived peptides.

e) The authors should ensure that reviewers are provided with access to the private PRIDE repository so the data deposited can also be evaluated. They should also ensure that sufficient meta-data is provided using the SRDF format to allow the re-use of their LC-MS/MS datasets.

(3) Supplementary tables:

The supplementary tables are very difficult to navigate. They would become more accessible to readers and non-specialists if they were accompanied by brief legends or "README" tabs and if the headers were more detailed (see, for example, Table S2, what does "ctrl.ratio_Larvae_rep2" exactly refer to? Or Table S6 whose column headers using extensive abbreviations are quite obscure). Similarly, what do columns K to BX in Supplementary Table S1 correspond to? Without more substantial explanations, readers have no way of assessing these data points.

Reviewer #1 (Public review):

Summary:

The authors aimed to assess the variability in the expression of surface protein multigene families between amastigote and trypomastigote Trypanosoma cruzi, as well as between individuals within each population. The analysis presented shows higher expression of multigene family transcripts in trypomastigotes compared to amastigotes and that there is variation in which copies are expressed between individual parasites. Notably, they find no clear subpopulations expressing previously characterised trans-sialidase groups. The mapping accuracy to these multicopy genes requires demonstration to confirm this, and the analysis could be extended further to probe the features of the top expressed genes and the other multigene families also identified as variable.

Strengths:

The authors successfully process methanol-fixed parasites with the 10x Genomics platform. This approach is valuable for other studies where using live parasites for these methods is logistically challenging.

Weaknesses:

The authors describe a single experiment, which lacks controls or complementation with other approaches and the investigation is limited to the trans-sialidase transcripts.

It would be more convincing to show either bioinformatically or by carrying out a controlled experiment, that the sequencing generated has been mapped accurately to different members of multigene families to distinguish their expression. If mapping to the multigene families is inaccurate, this will impact the transcript counts and downstream analysis.

Reviewer #1 (Public review):

Liu et al., present glmSMA, a network-regularized linear model that integrates single-cell RNA-seq data with spatial transcriptomics, enabling high-resolution mapping of cellular locations across diverse datasets. Its dual regularization framework (L1 for sparsity and generalized L2 via a graph Laplacian for spatial smoothness) demonstrates robust performance of their model and offers novel tools for spatial biology, despite some gaps in fully addressing spatial communication.

Overall, the manuscript is commendable for its comprehensive benchmarking across different spatial omics platforms and its novel application of regularized linear models for cell mapping. I think this manuscript can be improved by addressing method assumptions, expanding the discussion on feature dependence and cell type-specific biases, and clarifying the mechanism of spatial communication.

The conclusions of this paper are mostly well supported by data, but some aspects of model development and performance evaluation need to be clarified and extended.

(1) What were the assumptions made behind the model? One of them could be the linear relationship between cellular gene expression and spatial location. In complex biological tissues, non-linear relationships could be present, and this would also vary across organ systems and species. Similarly, with regularization parameters, they can be tuned to balance sparsity and smoothness adequately but may not hold uniformly across different tissue types or data quality levels. The model also seems to assume independent errors with normal distribution and linear additive effects - a simplification that may overlook overdispersion or heteroscedasticity commonly observed in RNA-seq data.

(2) The performance of glmSMA is likely sensitive to the number and quality of features used. With too few features, the model may struggle to anchor cells correctly due to insufficient discriminatory power, whereas too many features could lead to overfitting unless appropriately regularized. The manuscript briefly acknowledges this issue, but further systematic evaluation of how varying feature numbers affect mapping accuracy would strengthen the claims, particularly in settings where marker gene availability is limited. A simple way to show some of this would be testing on multiple spatial omics (imaging-based) platforms with varying panel sizes and organ systems. Related to this, based on the figures, it also seems like the performance varies by cell type. What are the factors that contribute to this? Variability in expression levels, RNA quantity/quality? Biases in the panel? Personally, I am also curious how this model can be used similarly/differently if we have a FISH-based, high-plex reference atlas. Additional explanation around these points would be helpful for the readers.

(3) Application 3 (spatial communication) in the graphical abstract appears relatively underdeveloped. While it is clear that the model infers spatial proximities, further explanation of how these mappings translate into insights into cell-cell communication networks would enhance the biological relevance of the findings.

(4) What is the final resolution of the model outputs? I am assuming this is dictated by the granularity of the reference atlas and the imposed sparsity via the L1 norm, but if there are clear examples that would be good. In figures (or maybe in practice too), cells seem to be assigned to small, contiguous patches rather than pinpoint single-cell locations, which is a pragmatic compromise given the inherent limitations of current spatial transcriptomics technologies. Clarification on the precise spatial scale (e.g., pixel or micrometer resolution) and any post-mapping refinement steps would be beneficial for the users to make informed decisions on the right bioinformatic tools to use.

Reviewer #1 (Public review):

Summary:

Kwon et al present a very well-conducted and well-written sieve analysis of rotavirus infections in a passive surveillance network in the US, considering how relative vaccine efficacy changes with genetic distance from the vaccine strains including the whole genome. The results are compelling, supported by a number of sensitivity analyses, and the manuscript is generally easy to follow.

Strengths:

(1) The underlying study base, a surveillance network across multiple sites in the US.

(2) The use of a test-negative design, which is well established for rotavirus, to estimate vaccine efficacy.

(3) The use of genetic distance to measure differences between infecting and vaccine strains, and the innovative use of k-means clustering to make results more interpretable.

(4) The secondary and sensitivity analyses that provide additional context and support for the primary findings.

Weaknesses:

(1) As identified by the authors, there is a limited sample size for the analysis of RV1 (monovalent rotavirus vaccine).

(2) Sieve analyses were originally designed for randomized trials, in which setting their key assumptions are more likely to be met. There is little discussion in this paper of how those assumptions might be violated and what effect that might have on the results. The authors have access to some important confounders, but I believe some more discussion on potential biases in this observational study is warranted.

Reviewer #1 (Public review):

Summary:

This study presents findings on dual TCR regulatory T cells (Tregs) using previously published single-cell RNA and TCR sequencing datasets. The authors aimed to quantify dual TCR Tregs in different tissues and analyze their characteristics. Rather than perform the difficult experiments needed to ascertain the functional role of dual receptors, this study relies entirely on scRNA-VDJ-seq data published by two other groups. The findings primarily confirm prior work rather than provide new insights, and the methodology has significant weaknesses that limit the study's impact. We have concerns about the scientific integrity of this work.

Strengths:

(1) The use of single-cell RNA and TCR sequencing is appropriate for addressing potential relationships between gene expression and dual TCR.

(2) The data confirm the presence of dual TCR Tregs in various tissues, with proportions ranging from 10.1% to 21.4%, aligning with earlier observations in αβ T cells.

(3) Tissue-specific patterns of TCR gene usage are reported, which could be of interest to researchers studying T cell adaptation, although these were more rigorously analyzed in the original works.

Weaknesses

(1) Lack of Novelty: The primary findings do not substantially advance our understanding of dual TCR expression, as similar results have been reported previously in other contexts.

(2) Incomplete Evidence: The claims about tissue-specific differences lack sufficient controls (e.g., comparison with conventional T cells) and functional validation (e.g., cell surface expression of dual TCRs).

(3) Methodological Weaknesses: The diversity analysis does not account for sample size differences, and the clonal analysis conflates counts and clonotypes, leading to potential misinterpretation.

(4) Insufficient Transparency: The sequence analysis pipeline is inadequately described, and the study lacks reproducibility features such as shared code and data.

(5) Weak Gene Expression Analysis: No statistical validation is provided for differential gene expression, and the UMAP plots fail to reveal meaningful clustering patterns.

(6) A quick online search reveals that the same authors have repeated their approach of reanalysing other scientists' publicly available scRNA-VDJ-seq data in six other publications:

(1) Peng, Q., Xu, Y. & Yao, X. scRNA+ TCR-seq revealed dual TCR T cells antitumor response in the TME of NSCLC. J Immunother Cancer 12 (2024). https://doi.org:10.1136/jitc-2024-009376

(2) Wang, H., Li, J., Xu, Y. & Yao, X. scRNA + BCR-seq identifies proportions and characteristics of dual BCR B cells in the peritoneal cavity of mice and peripheral blood of healthy human donors across different ages. Immun Ageing 21, 90 (2024). https://doi.org:10.1186/s12979-024-00493-6

(3) Xu, Y. et al. scRNA+TCR-seq reveals the pivotal role of dual receptor T lymphocytes in the pathogenesis of Kawasaki disease and during IVIG treatment. Front Immunol 15, 1457687 (2024). https://doi.org:10.3389/fimmu.2024.1457687

(4) Yuanyuanxu, Qipeng, Qingqingma & Yao, X. scRNA + TCR-seq revealed the dual TCR pTh17 and Treg T cells involvement in autoimmune response in ankylosing spondylitis. Int Immunopharmacol 135, 112279 (2024). https://doi.org:10.1016/j.intimp.2024.112279

(5) Zhu, L. et al. scRNA-seq revealed the special TCR beta & alpha V(D)J allelic inclusion rearrangement and the high proportion dual (or more) TCR-expressing cells. Cell Death Dis 14, 487 (2023). https://doi.org:10.1038/s41419-023-06004-7

(6) Zhu, L., Peng, Q., Wu, Y. & Yao, X. scBCR-seq revealed a special and novel IG H&L V(D)J allelic inclusion rearrangement and the high proportion dual BCR expressing B cells. Cell Mol Life Sci 80, 319 (2023). https://doi.org:10.1007/s00018-023-04973-8

In other words, the approach used here seems to be focused on quick re-analyses of publicly available data without further validation and/or exploration

Appraisal of the Study's Aims and Conclusions:

The authors set out to analyze dual TCR Tregs across tissues, but the lack of robust controls, incomplete analyses, and insufficient novelty limit the study's ability to achieve its aims. The results confirm prior findings but do not provide compelling evidence to support the broader claims about the characteristics or significance of dual TCR Tregs.

Impact and Utility:

While the study provides a descriptive analysis of dual TCR Tregs, its limited novelty and methodological weaknesses reduce its likely impact on the field. The methods and data could have utility for researchers interested in tissue-specific TCR gene usage, but additional rigor is required to make the findings broadly applicable.

Reviewer #1 (Public review):

Summary:

The authors report four cryoEM structures (2.99 to 3.65 Å resolution) of the 180 kDa, full-length, glycosylated, soluble Angiotensin-I converting enzyme (sACE) dimer, with two homologous catalytic domains at the N- and C-terminal ends (ACE-N and ACE-C). ACE is a protease capable of effectively degrading Aβ. The four structures are C2 pseudo-symmetric homodimers and provide insight into sACE dimerization. These structures were obtained using discrete classification in cryoSPARC and show different combinations of open, intermediate, and closed states of the catalytic domains, resulting in varying degrees of solvent accessibility to the active sites.

To deepen the understanding of the gradient of heterogeneity (from closed to open states) observed with discrete classification, the authors performed all-atom MD simulations and continuous conformational analysis of cryo-EM data using cryoSPARC 3DVA, cryoDRGN, and RECOVAR. cryoDRGN and cryoSPARC 3DVA revealed coordinated open-closed transitions across four catalytic domains, whereas RECOVAR revealed independent motion of two ACE-N domains, also observed with cryoSPARC-focused classification. The authors suggest that the discrepancy in the results of the different methods for continuous conformational analysis in cryo-EM could result from different approaches used for dimensionality reduction and trajectory generation in these methods.

Strengths:

This is an important study that shows, for the first time, the structure and the snapshots of the dynamics of the full-length sACE dimer. Moreover, the study highlights the importance of combining insights from different cryo-EM methods that address questions difficult or impossible to tackle experimentally while lacking ground truth for validation.

Weaknesses:

The open, closed, and intermediate states of ACE-N and ACE-C in the four cryo-EM structures from discrete classification were designated quantitatively (based on measured atomic distances on the models fitted into cryo-EM maps, Figure 2D). Unfortunately, atomic models were not fitted into cryo-EM maps obtained with cryoSPARC 3DVA, cryoDRGN, and RECOVAR, and the open/closed states in these cases were designated based on qualitative analysis. As the authors clearly pointed out, there are many other methods for continuous conformational heterogeneity analysis in cryo-EM. Among these methods, some allow analyzing particle images in terms of atomic models, like MDSPACE (Vuillemot et al., J. Mol. Biol. 2023, 435:167951), which result in one atomic model per particle image and can help in analyzing cooperativity of domain motions through measuring atomic distances or angular differences between different domains (Valimehr et al., Int. J. Mol. Sci. 2024, 25: 3371). This could be discussed in the article.

Reviewer #1 (Public review):

Summary:

In their manuscript, Andriani et al. show intracellular zinc is exported from sperm during capacitation and suppresses the alkalinization-induced hyperpolarization in sperm. Intracellular zinc inhibits Slo3 current, which is enhanced by the co-expression of gamma subunit Lrrc52. Computational studies reveal that the Zn binding site on mSlo3 is located near E169 and E205, which are involved in the sustained zinc inhibition of mSlo3 current. The authors propose that intracellular zinc plays a key role in sperm capacitation by inhibiting the Slo3 channel.

Strengths:

Overall, the work appears well-designed (e.g., oocyte patch-clamp experiments), and clearly presented. Three-dimensional structural modeling and flooding simulations are executed.

Weaknesses:

The simple mutagenesis analysis of E169 and E205 showed partial abolishment, but the molecular mechanism by which zinc inhibits Slo3 current is not yet fully shown. The authors should consider performing more extensive experiments, such as creating double mutants or combination mutants involving other residues. Additionally, could other mechanisms explain the role of zinc in regulating the Slo3 current?

While elucidating the mechanism of Slo3 is interesting, there is substantial literature indicating how zinc regulates channel functions at a molecular level. Given this, the manuscript should provide a deeper understanding by clearly elucidating the molecular mechanism of the regulation of Slo3 current by zinc.<br /> The manuscript includes no experimental data on the mechanism of intracellular zinc export during sperm capacitation, despite being crucial for the regulation of sperm function.

Reviewer #1 (Public review):

Summary:

The manuscript "Lifestyles shape genome size and gene content in fungal pathogens" by Fijarczyk et al. presents a comprehensive analysis of a large dataset of fungal genomes to investigate what genomic features correlate with pathogenicity and insect associations. The authors focus on a single class of fungi, due to the diversity of lifestyles and availability of genomes. They analyze a set of 12 genomic features for correlations with either pathogenicity or insect association and find that, contrary to previous assertions, repeat content does not associate with pathogenicity. They discover that the number of protein-coding genes, including the total size of non-repetitive DNA does correlate with pathogenicity. However, unique features are associated with insect associations. This work represents an important contribution to the attempts to understand what features of genomic architecture impact the evolution of pathogenicity in fungi.

Strengths:

The statistical methods appear to be properly employed and analyses thoroughly conducted. The manuscript is well written and the information, while dense, is generally presented in a clear manner.

Weaknesses:

My main concerns all involve the genomic data, how they were annotated, and the biases this could impart to the downstream analyses. The three main features I'm concerned with are sequencing technology, gene annotation, and repeat annotation.

The collection of genomes is diverse and includes assemblies generated from multiple sequencing technologies including both short- and long-read technologies. Not only has the impact of the sequencing method not been evaluated, but the technology is not even listed in Table S1. From the number of scaffolds it is clear that the quality of the assemblies varies dramatically. This is going to impact many of the values important for this study, including genome size, repeat content, and gene number. Additionally, since some filtering was employed for small contigs, this could also bias the results.

I have considerable worries that the gene annotation methods could impart biases that significantly affect the main conclusions. Only 5 reference training sets were used for the Sordariomycetes and these are unequally distributed across the phylogeny. Augusts obviously performed less than ideally, as the authors reported that it under-annotated the genomes by 10%. I suspect it will have performed worse with increasing phylogenetic distance from the reference genomes. None of the species used for training were insect-associated, except for those generated by the authors for this study. As this feature was used to split the data it could impact the results. Some major results rely explicitly on having good gene annotations, like exon length, adding to these concerns. Looking manually at Table S1 at Ophiostoma, it does seem to be a general trend that the genomes annotated with Magnaporthe grisea have shorter exons than those annotated with H294. I also wonder if many of the trends evident in Figure 5 are also the result of these biases. Clades H1 and G each contain a species used in the training and have an increase in genes for example.

Unfortunately, the genomes available from NCBI will vary greatly in the quality of their repeat masking. While some will have been masked using custom libraries generated with software like Repeatmodeler, others will probably have been masked with public databases like repbase. As public databases are again biased towards certain species (Fusarium is well represented in repbase for example), this could have significant impacts on estimating repeat content. Additionally, even custom libraries can be problematic as some software (like RepeatModeler) will include multicopy host genes leading to bona fide genes being masked if proper filtering is not employed. A more consistent repeat masking pipeline would add to the robustness of the conclusions.

To a lesser degree, I wonder what impact the use of representative genomes for a species has on the analyses. Some species vary greatly in genome size, repeat content, and architecture among strains. I understand that it is difficult to address in this type of analysis, but it could be discussed.

Reviewer #1 (Public review):

IBEX Knowledge Database

Here, Anidi and colleagues present the IBEX knowledge base. A community tool developed to centralize knowledge and help its adoption by more users. The authors have done a fantastic job, and there is careful consideration of the many aspects of data management and FAIR principles. The manuscript needs no further work, as it is very well written and has detailed descriptions for data contribution as well as describing the KB itself. Overall, it is a great initiative, especially the aim to inform about negative data and non-recommended reagents, which will positively affect the user community and scientific reproducibility.

As such amount of work has been put into developing this community tool, it would be worth thinking about how it could serve other multiplex-immunofluorescence methods (such as immunoSABER, 4i, etc). Adding an extra tab where the particular method that uses those reagents is mentioned. This would also help as IBEX itself and related methods evolve in the future.

It has a rather minimal description of the software. In particular, there is software that has not been developed for IBEX specifically but that could be used for IBEX datasets (ASHLAR, WSIReg, VALIS, WARPY, and QuPath, etc). It would be nice if there was mention of those.

There is a concern about how the negative data information will be added, as no publication or peer-review process can back it up. Perhaps the particular conditions of the experiment should be very well described to allow future users to assess the validity. The proposed scheme where a reagent can be validated or recommended against by up to 4 different labs should be good. It may be good to make sure that researchers who validate belong to different labs and are not only different ORCID that belong to the same group. Similar to making a case of recommendations against a reagent.

It is very interesting to keep track of the protocol versions used. Perhaps users should be able to validate independent versions and it will be important to know how information is kept.

The final point I would make is that the need to form a GitHub repository may deter some people from submitting data. For sporadic contributions, authors could think that users could either reach out to main developers and/or provide a submission form that can help less experienced users of command-line and GitHub programming, but still promote the contribution from the community.

I am keen to see how the KB evolves and how it helps disseminate the use of this and other great techniques.

Reviewer #1 (Public review):

Summary:

In this study, Le et al.. aimed to explore whether AAV-mediated overexpression of Oct4 could induce neurogenic competence in adult murine Müller glia, a cell type that, unlike its counterparts in cold-blooded vertebrates, lacks regenerative potential in mammals. The primary goal was to determine whether Oct4 alone, or in combination with Notch signaling inhibition, could drive Müller glia to transdifferentiate into bipolar neurons, offering a potential strategy for retinal regeneration.

The authors demonstrated that Oct4 overexpression alone resulted in the conversion of 5.1% of Müller glia into Otx2+ bipolar-like neurons by five weeks post-injury, compared to 1.1% at two weeks. To further enhance the efficiency of this conversion, they investigated the synergistic effect of Notch signaling inhibition by genetically disrupting Rbpj, a key Notch effector. Under these conditions, the percentage of Müller glia-derived bipolar cells increased significantly to 24.3%, compared to 4.5% in Rbpj-deficient controls without Oct4 overexpression. Similarly, in Notch1/2 double-knockout Müller glia, Oct4 overexpression increased the proportion of GFP+ bipolar cells from 6.6% to 15.8%.

To elucidate the molecular mechanisms driving this reprogramming, the authors performed single-cell RNA sequencing (scRNA-seq) and ATAC-seq, revealing that Oct4 overexpression significantly altered gene regulatory networks. They identified Rfx4, Sox2, and Klf4 as potential mediators of Oct4-induced neurogenic competence, suggesting that Oct4 cooperates with endogenously expressed neurogenic factors to reshape Müller glia identity.

Overall, this study aimed to establish Oct4 overexpression as a novel and efficient strategy to reprogram mammalian Müller glia into retinal neurons, demonstrating both its independent and synergistic effects with Notch pathway inhibition. The findings have important implications for regenerative therapies as they suggest that manipulating pluripotency factors in vivo could unlock the neurogenic potential of Müller glia for treating retinal degenerative diseases.

Strengths:

(1) Novelty: The study provides compelling evidence that Oct4 overexpression alone can induce Müller glia-to-bipolar neuron conversion, challenging the conventional view that mammalian Müller glia lacks neurogenic potential.

(2) Technological Advances: The combination of Muller glia-specific labeling and modifying mouse line, AAV-GFAP promoter-mediated gene expression, single-cell RNA-seq, and ATAC-seq provides a comprehensive mechanistic dissection of glial reprogramming.

(3) Synergistic Effects: The finding that Oct4 overexpression enhances neurogenesis in the absence of Notch signaling introduces a new avenue for retinal repair strategies.

Weaknesses:

(1) In this study, the authors did not perform a comprehensive functional assessment of the bipolar cells derived from Müller glia to confirm their neuronal identity and functionality.

(2) Demonstrating visual recovery in a bipolar cell-deficiency disease model would significantly enhance the translational impact of this work and further validate its therapeutic potential.

Reviewer #1 (Public review):

The paper by Fournier et al. investigates the sensitivity of neural circuits to changes in intrinsic and synaptic conductances. The authors use models of the stomatogastric ganglion (STG) to compare how perturbations to intrinsic and synaptic parameters impact network robustness. Their main finding is that changes to intrinsic conductances tend to have a larger impact on network function than changes to synaptic conductances, suggesting that intrinsic parameters are more critical for maintaining circuit function.

The paper is well-written, and the results are compelling. The authors addressed most of the minor comments I had and improved the manuscript.

However, it remains unclear how general the results are and what the underlying mechanism is. Regarding generality, the authors changed the title and added a sentence in the discussion. At this point, they do not claim generality beyond the specific function they explore in the STG circuit. While this is acceptable, I still believe the paper would be much more insightful if it provided a more general statement and investigated the mechanism behind why, in their hands, synaptic parameters appear more resilient to changes than intrinsic parameters.

Reviewer #1 (Public review):

Summary:

This study takes a detailed approach to understand the effect of menopausal hormone therapy (MHT) in brain aging of females. Neuroimaging data from the UK Biobank is used to explore brain aging and shows an unexpected effect of current MHT use and poorer brain health outcomes relative to never users. There is considerable debate about the benefits of MHT and estrogens in particular for brain health, and this analysis illustrates thta the effects are certainly not straight forward and require greater considerations.

Strengths:

(1) The detailed approach to obtain important information about MHT use from primary care records. Prior studies have suggested that factors such as estrogen/progestin type, route of administration, duration, and timing of use relative to menopause onset can contribute to whether MHT benefits brain health.<br /> (2) Consideration of type of menopause (spontaneous, or surgical) in the analysis, as well as sensitivity diagnoses to rule out the effect being driven by those with clinical conditions<br /> (3) The incorporation of the brain age estimate along with hippocampal volume to address brain health<br /> (4) The complex data are also well explained and interpretations are reasonable.<br /> (5) Limitations of the UKbiobank data are acknowledged

Weaknesses:

These have since been addressed by the authors in the revision.

Reviewer #1 (Public review):

Summary:

The author studied metabolic networks for central metabolism, focusing on how system trajectories returned to their steady state. To quantify the response, systematic perturbation was performed in simulation and the maximal destabilization away from steady state (compared with initial perturbation distance) was characterized. The author analyzed the perturbation response and found that sparse network and networks with more cofactors are more "stable", in the sense that the perturbed trajectories have smaller deviation along the path back to the steady state.

Strengths and major contributions:

The author compared three metabolic models and performed systematic perturbation analysis in simulation. This is the first work characterized how perturbed trajectories deviate from equilibrium in large biochemical systems and illustrated interesting findings about the difference between sparse biological systems and randomly simulated reaction networks.

Discussion and impact for the field:

Metabolic perturbation is an important topic in cell biology and has important clinical implication in pharmacodynamics. The computational analysis in this study provides an initiative for future quantitative analysis on metabolism and homeostasis.

Comments on latest version:

In the latest version of this work, the author included NADH, NADPH into the analysis, and perform some comparison about sensitivity analysis. I think this paper is ready to be finalized, and many open questions inspired from this work can be studied in future.

Reviewer #1 (Public review):

Summary:

The authors examine the role of the medial prefrontal cortex (mPFC) in cognitive control, i.e. the ability to use task-relevant information and ignore irrelevant information, in the rat. According to the central-computation hypothesis, cognitive control in the brain is centralized in the mPFC and according to the local hypothesis, cognitive control is performed in task-related local neural circuits. Using the place avoidance task which involves cognitive control, it is predicted that if mPFC lesions affect learning, this would support the central computation hypothesis whereas no effect of lesions would rather support the local hypothesis. The authors thus examine the effect of mPFC lesions in learning and retention of the place avoidance task. They also look at functional interconnectivity within a large network of areas that could be activated during the task by using cytochrome oxydase, a metabolic marker. In addition, electrophysiological unit recordings of CA1 hippocampal cells are made in a subset of (mPFC-lesioned or intact) animals to evaluate overdispersion, a firing property that reflects cognitive control in the hippocampus. The results indicate that mPFC lesions disrupted correlations of activity between functionally-related regions. Behaviorally, lesions did not impair place avoidance learning and retention (though flexibility was altered during conflict training). In addition, hippocampal place cell overdispersion was decreased in lesioned rats only in the absence of cognitive control challenge (pretraining). Cognitive control seen in hippocampal place cell activity (alternation of frame-specific firing) was not affected by the lesion. Overall, the absence of effects of mPFC lesions on cognitive control in the task or in hippocampal place cells firing support the local hypothesis.

Strengths:

Straightforward hypothesis: clarification of the involvement of the mPFC in the brain is expected and achieved. Appropriate use of fully mastered methods (active place avoidance task, electrophysiological unit recordings, measure of metabolic marker cytochrome oxidase) and rigorous analysis of the data. The conclusion is strongly supported by the data.

Weaknesses:

No notable weaknesses in the conception, making of the study and data analysis.

Comments on revisions:

The authors have satisfactorily addressed all my comments in the revised version.

Reviewer #1 (Public review):

Summary:

In this manuscript by Obray et al., the authors show that adolescent ethanol exposure increases mechanical allodynia in adulthood. Additionally, the show that BLA mediated inhibition of prelimbic cortex is reduced, resulting in increased excitability in neurons that then project to vlPAG. This effect was mediated by BLA inputs onto PV interneurons. The primary finding of the manuscript is that these AIE induced changes further impact acute pain processing in the BLA-PrL-vlPAG circuit, albeit behavioral readouts after inducing acute pain were not different between AIE rats and controls. These results provide novel insights into how AIE can have long lasting effects on pain-related behaviors and neurophysiology.In this manuscript by Obray et al., the authors show that adolescent ethanol exposure increases mechanical allodynia in adulthood. Additionally, the show that BLA mediated inhibition of prelimbic cortex is reduced, resulting in increased excitability in neurons that then project to vlPAG. This effect was mediated by BLA inputs onto PV interneurons. The primary finding of the manuscript is that these AIE induced changes further impact acute pain processing in the BLA-PrL-vlPAG circuit, albeit behavioral readouts after inducing acute pain were not different between AIE rats and controls. These results provide novel insights into how AIE can have long lasting effects on pain-related behaviors and neurophysiology.

The manuscript was very well written and the experiments were rigorously conducted. The inclusion of both behavioral and neurophysiological circuit recordings was appropriate and compelling. The authors analyzed their data extensively, and consider how many different factors may influence physiological activity and downstream behavior. The attention to SABV and appropriate controls was well thought out. The Discussion provided novel ideas for how to think about AIE and chronic pain, and proposed several interesting mechanisms. This was a very well executed set of experiments.

Comments on revisions:

The authors have addressed the concerns raised by the reviewers. Excellent work!

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Reviewer #1 (Public review):

Summary:

This is a convincing description of approximately ten years of funding from the NIH BRAIN initiative. It is of particular value at this moment in history, given the cataclysmic changes in the US government structure and function occurring in early 2025.

Strengths:

The paper contains a fair bit of documentation so that the curious reader can actually parse what this BRAIN program funded.

Weaknesses:

There are too many acronyms, and the manuscript reads as if it were an internal NIH document, where the audience knows all of the NIH nomenclature and program details. It is not particularly friendly to the outside, lay reader.

Reviewer #1 (Public review):

Summary:

In this useful narrative, the authors attempt to capture their experience of the success of team projects for the scientific community.

Strengths:

The authors are able to draw on a wealth of real-life experience reviewing, funding, and administering large team projects, and assessing how well they achieve their goals.

Weaknesses:

The utility of the RCR as a measure is questionable. I am not sure if this really makes the case for the success of these projects. The conclusions do not depend on Figure 1.

Reviewer #1 (Public review):

This computational study builds on a previous study (Liu et al) from the Marder lab from 1998, where a model was proposed that demonstrated activity-dependent homeostatic recovery of activity in individual bursting neurons, based on three "sensors" of intrinsic calcium concentration. The original model modified levels of ion channel conductances. The current model builds on that and adds activity-dependent modifications of the voltage-dependence of these ionic currents, implemented to happen concurrently with maximum conductance levels, but at a different timescale. The faster timescale change in voltage dependence is justified by the assumption that such changes can occur by neuromodulatory chemicals or similar second messenger-based mechanisms that presumably act at a faster rate than the regulation of channel densities. The main finding is that the difference in timescales between the two homeostatic mechanisms (channel density vs. voltage dependence) could result in distinct subsets of parameters, depending on how fast the second messenger mechanisms operate.

This study is an interesting and noteworthy extension of the theoretical ideas proposed by the classic study of Liu et al, 1998. It addresses a very important question: How do two known mechanisms of modifications of neuronal activity that occur at different timescales interact within an activity-dependent homeostatic framework? However, the study and its presentation have some major shortcomings that should be addressed to strengthen the claim.

Major comments:

(1) The main issue that I have with this study is the lack of exploration of "why" the model produces the results it does. Considering this is a model, it should be possible to find out why the three timescales of half-act/inact parameter modifications lead to different sets of results. Without this, it is simply an exploratory exercise. (The model does this, but we do not know the mechanism.) Perhaps this is enough as an interesting finding, but it remains unconvincing and (clearly) does not have the impact of describing a potential mechanism that could be potentially explored experimentally.

(2) A related issue is the use of bootstrapping to do statistics for a family of models, especially when the question is in fact the width of the distribution of output attributes. I don't buy this. One can run enough models to find say N number of models within a tight range (say 2% cycle period) and the same N number within a loose range (say 20%) and compare the statistics within the two groups with the same N.

(3) The third issue is that many of the results that are presented (but not the main one) are completely expected. If one starts with gmax values that would never work (say all of them 0), then it doesn't matter how much one moves the act/inact curves one probably won't get the desired activity. Alternately, if one starts with gmax values that are known to work and randomizes the act/inact midpoints, then the expectation would be that it converges to something that works. This is Figure 1 B and C, no surprise. But it should work the other way around too. If one starts with random act/inact curves that would never work and fixes those, then why would one expect any set of gmax values would produce the desired response? I can easily imagine setting the half-act/inact values to values that never produce any activity with any gmax.

(4) A potential response to my previous criticism would be that you put reasonable constraints on gmax's or half-act/inact values or tie the half-act to half-inact. But that is simply arbitrary ad hoc decisions made to make the model work, much like the L8-norm used to amplify some errors. There is absolutely no reason to believe this is tied to the biology of the system.

(5) The discussion of this manuscript is at once too long and not adequate. It goes into excruciating detail about things that are simply not explored in this study, such as phosphorylation mechanisms, justification of model assumptions of how these alterations occur, or even the biological relevance. (The whole model is an oversimplification - lack of anatomical structure, three calcium sensors, arbitrary assumptions, and how parameter bounds are implemented.) Lengthy justifications for why channel density & half-act/inact of all currents are obeying the same time constant are answering a question that no one asked. It is a simplified model to make an important point. The authors should make these parts concise and to the point. More importantly, the authors should discuss the mechanism through which these differences may arise. Even if it is not clear, they should speculate.

(6) There should be some justification or discussion of the arbitrary assumptions made in the model/methods. I understand some of this is to resolve issues that had come up in previous iterations of this approach and in fact the Alonso et al, 2023 paper was mainly to deal with these issues. However, some level of explanation is needed, especially when assumptions are made simply because of the intuition of the modeler rather than the existence of a biological constraint or any other objective measure.

Reviewer #1 (Public review):

Summary:

Inhibitory hM4Di and excitatory hM3Dq DREADDs are currently the most commonly utilized chemogenetic tools in the field of nonhuman primate research, but there is a lack of available information regarding the temporal aspects of virally-mediated DREADD expression and function. Nagai et al. investigated the longitudinal expression and efficacy of DREADDs to modulate neuronal activity in the macaque model. The authors demonstrate that both hM4Di and hM3Dq DREADDs reach peak expression levels after approximately 60 days and are stably expressed for a period of at least 1.5 years in the macaque brain. During this period, DREADDs effectively modulated neuronal activity, as evidenced by a variety of measures, including behavioural testing, functional imaging, and/or electrophysiological recording. Notably, some of the data suggest that DREADD expression may decline after two years. This is a novel finding and has important implications for the utilization of this technology for long-term studies, as well as its potential therapeutic applications. Lastly, the authors highlight that peak DREADD expression may be significantly influenced by the choice of viral titer and the expressed protein tag, emphasizing the importance of careful design and selection of viral constructs for neuroscientific research. This study represents a critical step in the field of chemogenetics, setting the scene for future development and optimization of this technology.

Strengths:

The longitudinal approach of this study provides important preliminary insights into the long-term utility of chemogenetics, which has not yet been thoroughly explored.

The data presented are novel and inclusive, relying on well-established in vivo imaging methods, as well as behavioral and immunohistochemical techniques. The conclusions made by the authors are generally supported by a combination of these techniques. In particular, the utilization of in vivo imaging as a non-invasive method is translationally relevant and likely to make an impact in the field of chemogenetics, such that other researchers may adopt this method of longitudinal assessment in their own experiments. Rigorous standards have been applied to the datasets, and the appropriate controls have been included where possible.

The number of macaque subjects (20) from which data was available is also notable. Behavioral testing was performed in 11 subjects, FDG-PET in 5, electrophysiology in 1, and [11C]DCZ-PET in 15. This is an impressive accumulation of work that will surely be appreciated by the growing community of researchers using chemogenetics in nonhuman primates.

The implication that chemogenetic effects can be maintained for up to 1.5-2 years, followed by a gradual decline beyond this period, is an important development in knowledge. The limited duration of DREADD expression may present an obstacle in the translation of chemogenetic technology as a potential therapeutic tool, and it will be of interest for researchers to explore whether this limitation can be overcome. This study therefore represents a key starting point upon which future research can build.

Weaknesses:

Overall, the conclusions of the paper are mostly supported by the data but may be overstated in some cases, and some details are also missing or not easily recognizable within the figures. The provision of additional information and analyses would be valuable to the reader and may even benefit the authors' interpretation of the data.

The conclusion that DREADD expression gradually decreases after 1.5-2 years is only based on a select few of the subjects assessed; in Figure 2, it appears that only 3 hM4Di cases and 2 hM3Dq cases are assessed after the 2-year timepoint. The observed decline appears consistent within the hM4Di cases, but not for the hM3Dq cases (see Figure 2C: the AAV2.1-hSyn-hM3Dq-IRES-AcGFP line is increasing after 2 years.)

Given that individual differences may affect expression levels, it would be helpful to see additional labels on the graphs (or in the legends) indicating which subject and which region are being represented for each line and/or data point in Figure 1C, 2B, 2C, 5A, and 5B. Alternatively, for Figures 5A and B, an accompanying table listing this information would be sufficient.

While the authors comment on several factors that may influence peak expression levels, including serotype, promoter, titer, tag, and DREADD type, they do not comment on the volume of injection. The range in volume used per region in this study is between 2 and 54 microliters, with larger volumes typically (but not always) being used for cortical regions like the OFC and dlPFC, and smaller volumes for subcortical regions like the amygdala and putamen. This may weaken the claim that there is no significant relationship between peak expression level and brain region, as volume may be considered a confounding variable. Additionally, because of the possibility that larger volumes of viral vectors may be more likely to induce an immune response, which the authors suggest as a potential influence on transgene expression, not including volume as a factor of interest seems to be an oversight.

The authors conclude that vectors encoding co-expressed protein tags (such as HA) led to reduced peak expression levels, relative to vectors with an IRES-GFP sequence or with no such element at all. While interesting, this finding does not necessarily seem relevant for the efficacy of long-term expression and function, given that the authors show in Figures 1 and 2 that peak expression (as indicated by a change in binding potential relative to non-displaced radioligand, or ΔBPND) appears to taper off in all or most of the constructs assessed. The authors should take care to point out that the decline in peak expression should not be confused with the decline in longitudinal expression, as this is not clear in the discussion; i.e. the subheading, "Factors influencing DREADD expression," might be better written as, "Factors influencing peak DREADD expression," and subsequent wording in this section should specify that these particular data concern peak expression only.

Reviewer #1 (Public review):

Summary:

The manuscript from Kaletsky et al is a response to a paper recently published by Craig Hunter's group (Gainey et al 2024). The Murphy lab has previously shown that learned avoidance of C. elegans to PA14 can be transmitted through four generations. In a series of detailed studies, they defined the mechanism of this transgenerational epigenetic inheritance (TEI), identifying both PA14 and C. elegans factors required for this effect (Moore et al., 2019, Kaletsky et al., 2020; Moore et al., 2021). PA14 produces a small RNA, P11, that is necessary and sufficient for transgenerational epigenetic inheritance of avoidance behaviour in C. elegans. In the worm, P11 decreases maco-1 expression, which in turn regulates daf-7.

In the study by Gainey et al (eLife 2024), the authors report their attempt at replicating the original findings of the Murphy lab using a modified experimental setup. The Gainey study observed avoidance of PA14 and upregulation of daf-7::GFP in the F1 progeny of trained parents, but not in subsequent generations. Importantly, although they examined a number of different deviations of the protocol, they did not repeat the original experiment using the exact protocol outlined in the Moore or Kaletsky papers. Nevertheless, the authors concluded that "this example of TEI is insufficiently robust for experimental investigations".

The manuscript by Kaletsky et al. attempts to provide an explanation as to why Gainey et al., were unable to observe transgenerational avoidance of PA14. They identify two discrepancies in the methodology used between the two studies and examine the possible impacts of these.

One of the primary differences in protocols between the two papers is how avoidance is measured. The Murphy group uses the traditional method of adding azide to bacterial spots on the choice plates to trap worms once they have come close to the food spot. The animals are on the plate for 1 hour but most have likely been immobilized before this time point. Gainey et al. omit the azide and instead shift animals to 4C after 30-60 minutes of exposure to immobilize the worms for counting. Kaletsky et al show that the choice of assay has a significant impact on measuring attraction and avoidance.

While Gainey et al., assert that the addition of azide had no discernable effect on the choice assay results, these data are not shown in their paper. Kaletsky et al. test these conditions head-to-head with the same 1 hour exposure time, showing that with azide, the initial response to PA14 in untrained worms is attraction. By contrast, in the absence of azide, when cold temperature is used to immobilize the worms , the response recorded is aversion to PA14. The choice assay generated by Kaletsky et al without azide is consistent with the choice assays in untrained worms shown in the Gainey paper, demonstrating that this is likely one factor that contributed to the different outcomes reported in the Gainey paper.

Kaletsky et al. propose that learned aversion to PA14 may be occurring within the 1-hour exposure time when worms are not trapped in their initial decision with the use of azide. This is consistent with previous findings from another group (Ooi and Prahlad 2017), showing that 45 minutes of exposure is sufficient to overcome the attraction to PA14 and shift to avoidance of PA14. Importantly, the Gainey paper notes exposure times between 30 and 60 minutes before shifting worms to 4C to count, this window may have generated additional variability between assays.

The second possibility explored by Kaletsky et al. is that the expression of P11 differed between the studies. Because P11 is required for TEI, differences in P11 expression is a reasonable explanation for different observations between studies. Unfortunately, in the Gainey study, P11 levels were not measured; it is therefore not possible to know whether low or absent levels of P11 explain the inability to observe TEI. Nevertheless, Kaletsky et al. test the potential for changes in one growth condition, temperature, to influence the production P11. Indeed, the expression of P11 differs in PA14 grown at different growth temperatures, providing an additional explanation for the discrepancies.

While it is possible that temperature is the culprit, it may be another culture condition or media component suppressing P11 expression. Nevertheless, the fact that expression of P11 can so easily be modified demonstrates that P11 expression is not immune to differences in culture conditions. Given its role in nitrogen fixation, I would be surprised if it was not regulated by environmental conditions. Differences in iron content between media batches are notorious for altering bacteria phenotypes. Although outside the scope of this study, with the connection to biofilm formation, I would be curious if iron levels had an impact on P11 expression. All in all, the data highlight the fact that P11 levels should be measured if TEI is not seen.

Strengths:

Overall, this is an excellent study that has provided additional understanding of the difference between naïve preference and TEI and provides guidance for investigators in replicating TEI experiments. The manuscript is very well written and provides additional understanding regarding the replication of TEI in response to P. aeruginosa.

The manuscript provides an important discussion about differences in methodology and how they might reflect specific biology. Many examples of experimental deviations that have large impacts have simple biological explanations. I believe the authors have done an excellent job making this point.

Weaknesses:

None noted.

Reviewer #1 (Public review):

Summary:

This study presents a system for delivering precisely controlled cutaneous stimuli to freely moving mice by coupling markerless real-time tracking to transdermal optogenetic stimulation, using the tracking signal to direct a laser via galvanometer mirrors. The principal claims are that the system achieves sub-mm targeting accuracy with a latency of <100 ms. The nature of mouse gait enables accurate targeting of forepaws even when mice are moving.

Strengths:

The study is of high quality and the evidence for the claims is convincing. There is increasing focus in neurobiology in studying neural function in freely moving animals, engaged in natural behaviour. However, a substantial challenge is how to deliver controlled stimuli to sense organs under such conditions. The system presented here constitutes notable progress towards such experiments in the somatosensory system and is, in my view, a highly significant development that will be of interest to a broad readership.

Weaknesses:

(1) "laser spot size was set to 2.00 } 0.08 mm2 diameter (coefficient of variation = 3.85)" is unclear. Is the 0.08 SD or SEM? (not stated). Also, is this systematic variation across the arena (or something else)? Readers will want to know how much the spot size varies across the arena - ie SD. CV=4 implies that SD~7 mm. ie non-trivial variation in spot size, implying substantial differences in power delivery (and hence stimulus intensity) when the mouse is in different locations. If I misunderstood, perhaps this helps the authors to clarify. Similarly, it would be informative to have mean & SD (or mean & CV) for power and power density. In future refinements of the system, would it be possible/useful to vary laser power according to arena location?

(2) "The video resolution (1920 x 1200) required a processing time higher than the frame interval (33.33 ms), resulting in real-time pose estimation on a sub-sample of all frames recorded". Given this, how was it possible to achieve 84 ms latency? An important issue for closed-loop research will relate to such delays. Therefore please explain in more depth and (in Discussion) comment on how the latency of the current system might be improved/generalised. For example, although the current system works well for paws it would seem to be less suited to body parts such as the snout that do not naturally have a stationary period during the gait cycle.

Reviewer #1 (Public review):

Summary:

Fluorescence imaging has become an increasingly popular technique for monitoring neuronal activity and neurotransmitter concentrations in the living brain. However, factors such as brain motion and changes in blood flow and oxygenation can introduce significant artifacts, particularly when activity-dependent signals are small. Yogesh et al. quantified these effects using GFP, an activity-independent marker, under two-photon and wide-field imaging conditions in awake behaving mice. They report significant GFP responses across various brain regions, layers, and behavioral contexts, with magnitudes comparable to those of commonly used activity sensors. These data highlight the need for robust control strategies and careful interpretation of fluorescence functional imaging data.

Strengths:

The effect of hemodynamic occlusion in two-photon imaging has been previously demonstrated in sparsely labeled neurons in V1 of anesthetized animals (see Shen and Kara et al., Nature Methods, 2012). The present study builds on these findings by imaging a substantially larger population of neurons in awake, behaving mice across multiple cortical regions, layers, and stimulus conditions. The experiments are extensive, the statistical analyses are rigorous, and the results convincingly demonstrate significant GFP responses that must be accounted for in functional imaging experiments.

In the revised version, the authors have provided further methodological details that were lacking in the previous version, expanded discussions regarding alternative explanations of these GFP responses as well as potential mitigation strategies. They also added a quantification of brain motion (Fig. S5) and the fraction of responsive neurons when conducting the same experiment using GCaMP6f (Fig. 3D-3F), among other additional information.

Weaknesses:

(1) The authors have now included a detailed methodology for blood vessel area quantification, where they detect blood vessels as dark holes in GFP images and measure vessel area by counting pixels below a given intensity threshold (line 437-443). However, this approach has a critical caveat: any unspecific decrease in image fluorescence will increase the number of pixels below the threshold, leading to an apparent increase in blood vessel area, even when the actual vessel size remains unchanged. As a result, this method inherently introduces a positive correlation between fluorescence decrease and vessel dilation, regardless of whether such a relationship truly exists.

To address this issue, I recommend labelling blood vessels with an independent marker, such as a red fluorescence dye injected into the bloodstream. This approach would allow vessel dilation to be assessed independently of GFP fluorescence -- dilation would cause opposite fluorescence changes in the green and red channels (i.e., a decrease in green due to hemodynamic occlusion and an increase in red due to the expanding vessel area). In my opinion, only when such ani-correlation is observed can one reliably infer a relationship between GFP signal changes and blood vessel dynamics.

Because this relationship is central to the author's conclusion regarding the nature of the observed GFP signals, including this experiment would greatly strengthen the paper's conclusion.

(2) Regarding mitigation strategy, the authors advocate repeating key functional imaging experiments using GFP, and state that their aim here is to provide a control for their 2012 study (Keller et al., Neuron). Given this goal, I find it important to discuss how these new findings impact the interpretation of their 2012 results, particularly given the large GFP responses observed.

For example, Keller et al. (2012) concluded that visuomotor mismatch strongly drives V1 activity (Fig. 3A in that study). However, in the present study, mismatch fails to produce any hemodynamic/GFP response (Fig. 3A, 3B, rightmost bar), and the corresponding calcium response is also the weakest among the three tested conditions (Fig. 3D). How do these findings affect their 2012 conclusions?

Similarly, the present study shows that GFP reveals twice as many responsive neurons as GCaMP during locomotion (Fig. 3A vs. Fig. 3D, "running"). Does this mean that their 2012 conclusions regarding locomotion-induced calcium activity need reconsideration? Given that more neurons responded with GFP than with GCaMP, the authors should clarify whether they still consider GCaMP a reliable tool for measuring brain activity during locomotion.

(3) More generally, the author should discuss how functional imaging data should be interpreted going forward, given the large GFP responses reported here. Even when key experiments are repeated using GFP, it is not entirely clear how one could reliably estimate underlying neuronal activity from the observed GFP and GCaMP responses.

For example, consider the results in Fig. 3A vs. 3D: how should one assess the relative strength of neuronal activity elicited by running, grating, or visuomotor mismatch? Does mismatch produce the strongest neuronal activity, since it is least affected by the hemodynamic/GFP confounds (Fig. 3A)? Or does mismatch actually produce the weakest neuronal activity, given that both its hemodynamic and calcium responses are the smallest?

In my opinion, such uncertainty makes it difficult to robustly interpret functional imaging results. Simply repeating experiments with GFP does not fully resolve this issue, as it does not provide a clear framework for quantifying the underlying neuronal activity. Does this suggest a need for a better mitigation strategy? What could these strategies be?

In my opinion, addressing these questions is critical not only for the authors' own work but also for the broader field to ensure a robust and reliable interpretation of functional imaging data.

(4) The authors now discuss various alternative sources of the observed GFP signals. However, I feel that they often appear to dismiss these possibilities too quickly, rather than appreciating their true potential impacts (see below).

For example, the authors argue that brain movement cannot explain their data, as movement should only result in a decrease in observed fluorescence. However, while this might hold for x-y motion, movement in the axial (z) direction can easily lead to both fluorescence increase and decrease. Neurons are not always precisely located at the focal plane -- some are slightly above or below. Axial movement in a given direction will bring some cells into focus while moving others out of focus, leading to fluorescence changes in both directions, exactly as observed in the data (see Fig. S2).

Furthermore, the authors state that they discard data with 'visible' z-motion. However, subtle axial movements that escape visual detection could still cause fluorescence fluctuations on the order of a few percent, comparable to the reported signal amplitudes.

Finally, the authors state that "brain movement kinematics are different in shape than the GFP responses we observe". However, this appears to contradict what they show in Fig. 2A. Specifically, the first example neuron exhibits fast GFP transients locked to running onset, with rapid kinematics closely matching the movement speed signals in Fig. S5A. These fast transients are incompatible with slower blood vessel area signals (Fig. 4), suggesting that alternative sources could contribute significantly.

In sum, the possibility that alternative signal sources could significantly contribute should be taken seriously and more thoroughly discussed.

(5) The authors added a quantification of brain movement (Fig. S5) and claim that they "only find detectable brain motion during locomotion onsets and not the other stimuli." However, Fig. S5 presents brain 'velocity' rather than 'displacement'. A constant (non-zero) velocity in Fig. S5 B-D indicates that the brain continues to move over time, potentially leading to significant displacement from its initial position across all conditions. While displacement in the x-y plane are corrected, similar displacement in the z direction likely occurs concurrently and cannot be easily accounted for. To assess this possibility, the authors should present absolute displacement relative to pre-stimulus frames, as displacement -- not velocity -- determines the size of movement-related fluorescence changes.

(6) In line 132-133, the authors draw an analogy between the effect of hemodynamic occlusion and liquid crystal display (LCD) function. However, there are fundamental differences between the two. LCDs modulate light transmission by rotating the polarization of light, which then passes through a crossed polarizer. In contrast, hemodynamic occlusion alters light transmission by changing the number and absorbance properties of hemoglobin. Additionally, LCDs do not involve 'emission' light - back-illumination travels through the liquid crystal layer only once, whereas hemodynamic occlusion affects both incoming excitation light and the emitted fluorescence. Given these fundamental differences, the LCD analogy may not be entirely appropriate.

Reviewer #1 (Public review):

Summary:

The authors performed experimental evolution of MreB mutants that have a slow growing round phenotype and studied the subsequent evolutionary trajectory using analysis tool from molecular biology. It was remarkable and interesting that they found that the original phenotype was not restored (most common in these studies) but that the round phenotype was maintained.

Strengths:

The finding that the round phenotype was maintained during evolution rather than that the original phenotype, rod shape cells, was recovered is interesting. The paper extensively investigates what happens during adaptation with various different techniques. Also the extensive discussion of the findings at the end of the paper is well thought through and insightful.

Reviewer #1 (Public review):

Summary:

Evading predation is of utmost importance for most animals and camouflage is one of the predominant mechanisms. Wu et al. set out to test the hypothesis of a unique camouflage system in leafhoppers. These animals coat themselves with brochosomes, which are spherical nanostructures that are produced in the Malpighian tubules and are distributed on the cuticle after eclosion. Based on previous findings on reflectivity properties of brochosomes, the authors provide convincing evidence that these nanostructures indeed reduce reflectivity of the animals thereby reducing predation by jumping spiders. Further, they identify four proteins, which are essential for proper development and function of brochosomes: In RNAi experiments, the regular brochosome structure is lost, the reflectivity reduced and the respective animals are prone to increased predation. Finally, the authors provide phylogenetic sequence analyses and speculate about the evolution of these genes.

Strengths:

The study is very comprehensive including careful optical measurements, EM and TM analysis of the nanoparticles and their production line in the malphigian tubules, in vivo predation tests and knock-down experiments to identify essential proteins. Indeed, the results are very convincingly in line with the starting hypothesis such that the study robustly assigns a new biological function to the brochosome coating system.

A key strength of the study is that the biological relevance of the brochosome coating is convincingly shown by an in vivo predation test using a known predator from the same habitat.

Another major step forward is an RNAi screen, which identified four proteins, which are essential for the brochosome structure (BSMs). After respective RNAi knock-downs, the brochosomes show curious malformations that are interesting in terms of the self-assembly of these nanostructures. The optical and in vivo predation tests provide excellent support for the model that the RNAi knock-down leads to a change of brochosomes structure, which reduces reflectivity, which in turn leads to a decrease of the antipredatory effect.

Conclusion:

The authors successfully tested their hypothesis in a multidisciplinary approach and convincingly assigned a new biological function to the brochosomes system. The results fully support their claims on the involvement of the four BSM genes in brochosome structure, the relevance of brochosomes for predation avoidance and they provide evidence for the evolution of these genes.

The work is a very interesting study case of the evolutionary emergence of a new system to evade predators. Based on this study, the function of the BSM genes could now be studied in other species to provide insights into putative ancestral functions. Further, studying the self-assembly of such highly regular complex nano-structures will be strongly fostered by the identification of the four key structural genes.

Reviewer #1 (Public review):

The article provides a timely and well-written examination of how group identification influences collective behaviors and performance using fNIRs and behavioral data.

Comments on revisions:

Most Reviewer concerns have been addressed in the revised manuscript, but some limitations persist with respect to core aspects of study design (e.g., long block durations and lack of counter-balancing) and analysis (i.e., the potential circularity of some analyses, the insufficiency of a mediation model to demonstrate causality, and a lack of clarity concerning the model us to map task activation).

Editor's note: Although the Reviewers found the reviews generally responsive, some fundamental concerns remain which will not be changed by further revision.

Reviewer #1 (Public review):

The goal of this study was to identify the phenotype of olfactory ensheathing cells (OECs) that have been associated with neural tissue repair, and investigate the properties of these cells that can be used to identify them. OECs modify inhibitory glial scar formation, enabling axon regeneration past the scar border and into the lesion center. Single-cell RNA sequencing revealed diverse subtypes of OECs expressing novel marker genes associated with progenitor, axonal regeneration, repair, and microglia-like functions, suggesting their potential roles in wound healing, injury repair, and axonal regeneration. Additionally, the study identified secreted molecules such as Reelin and Connective tissue growth factor, which are important for neural repair and axonal outgrowth, further supporting the multifunctional nature of OECs in facilitating spinal cord injury recovery. This is an extremely well written and impactful series of experiments from a renowned leader in the field. The experimental questions are timely, with similar therapeutic approaches being prepared for clinical trial. The results address a gap that has persisted in the field for several decades, and one that has asked by many scientists long before technology existed to find answers. This highlights the importance of these experiments and the results reported here. The authors have also included a thoughtful discussion that highlights the importance of their data in the context of prior research. They have carefully interpreted their results and also indicate where additional studies in future work will continue to expand our knowledge of these important cells and their potential use for neural repair.

Reviewer #1 (Public review):

Summary:

This study provides new insights on the phenomenon of pre-saccadic foveal prediction previously reported by the same authors. In particular, this study examines to what extent this phenomenon varies based on the visibility of the saccade target. Visibility is defined as the contrast level of the target with respect to the noise background, and it is related to the signal-to-noise ratio of the target. A more visible target facilitates the oculomotor behavior planning and execution, however, as speculated by the authors, it can also benefit foveal prediction even if the foveal stimulus visibility is maintained constant. Remarkably, the authors show that presenting a highly visible saccade target is beneficial for foveal vision as detection of stimuli with an orientation similar to that of the saccade target is improved, the lower is the saccade target visibility, the less prominent is this effect. The results are convincing and the research methodology is technically sound.

Comments on revisions:

The authors addressed all the concerns raised in the previous rounds of reviews.

Reviewer #1 (Public review):

Summary:

The manuscript by Velichko et al. argues that the ability of nucleolar protein Treacles to form phase-separated condensates is necessary for its function in nucleolar organization, rRNA transcription, and rDNA repair. These findings may be of interest to the communities studying biomolecular condensates, nucleolar organization, and ribosome biogenesis. The authors propose that Treacle's ability to undergo liquid-liquid phase separation is the key to its role as a scaffold for the FC of the nucleolus. The experiments in this study were designed and performed well, particularly the overexpression studies, done in the absence of endogenous protein and accounted for the protein expression levels.

Comments on revisions:

I am satisfied with the authors' revisions; my earlier concerns have been addressed thoroughly, and the manuscript is considerably improved. This study is important for our understanding of the role of Treacle in nucleolar organization and function, as well as general principles of cellular compartmentalization that involve biomolecular condensates.

Reviewer #1 (Public review):

Summary:

In this meticulously conducted study, the authors show that Drosophila epidermal cells can modulate escape responses to noxious mechanical stimuli. First, they show that activation of epidermal cells evokes many types of behaviors including escape responses. Subsequently, they demonstrate that most somatosensory neurons are activated by activation of epidermal cells, and that this activation has a prolonged effect on escape behavior. In vivo analyses indicate that epidermal cells are mechanosensitive and require stored-operated calcium channel Orai. Altogether, the authors conclude that epidermal cells are essential for nociceptive sensitivity and sensitization, serving as primary sensory noxious stimuli.

Strengths:

The manuscript is clearly written. The experiments are logical and complementary. They support the authors' main claim that epidermal cells are mechanosensitive and that epidermal mechanically evoked calcium responses require the stored-operated calcium channel Orai. Epidermal cells activate nociceptive sensory neurons as well as other somatosensory neurons in Drosophila larvae, and thereby prolong escape rolling evoked by mechanical noxious stimulation.

Weaknesses:

In several places the text is unclear. For example, core details are missing in the protocols, including the level of LED intensity used, which are necessary for other researchers to reproduce the experiments. Secondly, the rationales are missing for some experiments (for experiments X, Y, and Z). It would be helpful to clarify for your readers why the experiments (for example Figure 3S2) were performed. Finally, for most experiments, the epidermal cells are activated for 60 s, which is long when considering that nocifensive rolling occurs on a timescale of milliseconds. It would be informative to know the shortest duration of epidermal cell activation that is sufficient for observing the behavioral phenotype (prolongation of escape behavior) and activation of sensory neurons.

Reviewer #1 (Public review):

Summary:

The authors show certain memory deficits in a mouse knock-in model of Alzheimer's Disease (AD). They show that the observed memory deficits can be explained by a computational model, the latent cause model of associative memory. The memory tasks used include the fear memory task (CFC) and the 'reverse' Barnes maze. Research on AD is important given its known huge societal burden. Likewise, better characterization of the behavioral phenotypes of genetic mouse models of AD is also imperative to advance our understanding of the disease using these models. In this light, I applaud the authors' efforts.

Strengths:

(1) Combining computational modelling with animal behavior in genetic knock-in mouse lines is a promising approach, which will be beneficial to the field and potentially explain any discrepancies in results across studies as well as provide new predictions for future work.

(2) The authors' usage of multiple tasks and multiple ages is also important to ensure generalization across memory tasks and 'modelling' of the progression of the disease.

Weaknesses:

(1) I have some concerns regarding the interpretation of the behavioral results. Since the computational model then rests on the authors' interpretation of the behavioral results, it, in turn, makes judging the model's explanatory power difficult as well. For the CFC data, why do knock-in mice have stronger memory in test 1 (Figure 2C)? Does this mean the knock-in mice have better memory at this time point? Is this explained by the latent cause model? Are there some compensatory changes in these mice leading to better memory? The authors use a discrimination index across tests to infer a deficit in re-instatement, but this indicates a relative deficit in re-instatement from memory strength in test 1. The interpretation of these differential DIs is not straightforward. This is evident when test 1 is compared with test 2, i.e., the time point after extinction, which also shows a significant difference across groups, Figure 2F, in the same direction as the re-instatement. A clarification of all these points will help strengthen the authors' case

(2) I have some concerns regarding the interpretation of the Barnes maze data as well, where there already seems to be a deficit in the memory at probe test 1 (Figure 6C). Given that there is already a deficit in memory, would not a more parsimonious explanation of the data be that general memory function in this task is impacted in these mice, rather than the authors' preferred interpretation? How does this memory weakening fit with the CFC data showing stronger memories at test 1? While I applaud the authors for using multiple memory tasks, I am left wondering if the authors tried fitting the latent cause model to the Barnes maze data as well.

(3) Since the authors use the behavioral data for each animal to fit the model, it is important to validate that the fits for the control vs. experimental groups are similar to the model (i.e., no significant differences in residuals). If that is the case, one can compare the differences in model results across groups (Figures 4 and 5). Some further estimates of the performance of the model across groups would help.

(4) Is there an alternative model the authors considered, which was outweighed in terms of prediction by this model? One concern here is also parameter overfitting. Did the authors try leaving out some data (trials/mice) and predicting their responses based on the fit derived from the training data?

Reviewer #1 (Public review):

Summary:

In the current study, Huang et al. examined ACC response during a novel discrimination-avoid task. The authors concluded that ACC neurons primarily encode post-action variables over extended periods, reflecting the animal's preceding actions rather than the outcomes or values of those actions. Specifically, they identified two subgroups of ACC neurons that responded to different aspects of the actions. This work represents admirable efforts to investigate the role of ACC in task-performing mice. However, in my opinion, alternative explanations of the data were not sufficiently explored, and some key findings were not well supported.

Strengths:

The development of the new discrimination-avoid task is applauded. Single-unit electrophysiology in task-performing animals represents admirable efforts and the datasets are valuable. The identification of different groups of encoding neurons in ACC can be potentially important.

Weaknesses:

One major conclusion is that ACC primarily encodes the so-called post-action variables (specifically shuttle crossing). However, only a single example session was included in Figure 2, while in Supplementary Figure 2 a considerable fraction of ACC neurons appears to respond to either the onset of movement or ramp up their activity prior to movement onset. How did the authors reach the conclusion that ACC preferentially respond to shuttle crossing?

In Figure 4, it was concluded that ACC neurons respond to action independent of outcome. Since these neurons are active on both correct and incorrect shuttle but not stay trials, they seem to primarily respond to overt movement. If so, the rationale for linking ACC activity and adaptive behavior/associative learning is not very clear to me. Further analyses are needed to test whether their firing rates correlated with locomotion speed or acceleration/deceleration. On a similar note, to what extent are the action state neurons actually responding to locomotion-related signals? And can ACC activity actually differentiate correct vs. incorrect stays?

Given that a considerable amount of ACC neurons encode 'action content', it is not surprising that by including all neurons the model is able to make accurate predictions in Figure 6. How would the model performance change by removing the content neurons?

Moving on to Figure 7. Since Figure 4 showed that ACC neurons respond to movement regardless of outcome, it is somewhat puzzling how ACC activity can be linked to future performance.

Two mice contributed about 50% of all the recorded cells. How robust are the results when analyzing mouse by mouse?

Lastly, the development of the new discrimination-avoid task is applauded. However, a major missing piece here is to show the importance of ACC in this task and what aspects of this behavior require ACC.

Reviewer #1 (Public review):

Summary:

The authors tackled the public concern about E-cigarettes among young adults by examining the lung immune environment in mice using single-cell RNA sequencing, discovering a subset of Ly6G- neutrophils with reduced IL-1 activity and increased CD8 T cells following exposure to tobacco-flavored e-cigarettes. Preliminary serum cotinine (nicotine metabolite) measurements validated the effective exposure to fruit, menthol, and tobacco-flavored e-cigarettes with air and PG:VG serving as control groups. They also highlighted the significance of metal leaching, which fluctuated over different exposure durations to flavored e-cigarettes, underscoring the inherent risks posed by these products. The scRNAseq analysis of e-cig exposure to flavors and tobacco demonstrated the most notable differences in the myeloid and lymphoid immune cell populations. Differentially expressed genes (DEGs) were identified for each group and compared against the air control. Further sub-clustering revealed a flavor-specific rise in Ly6G- neutrophils and heightened activation of cytotoxic T cells in response to tobacco-flavored e-cigarettes. These effects varied by sex, indicating that immune changes linked to e-cig use are dependent on gender. By analyzing the expression of various genes and employing gene ontology and gene enrichment analysis, they identified key pathways involved in this immune dysregulation resulting from flavor exposure. Overall, this study affirmed that e-cigarette exposure can suppress the neutrophil-mediated immune response, subsequently enhancing T cell toxicity in the lung tissue of mice.

Strengths:

This study used single-cell RNA sequencing to comprehensively analyze the impact of e-cigarettes on the lung. The study pinpointed alterations in immune cell populations and identified differentially expressed genes and pathways that are disrupted following e-cigarette exposure. The manuscript is well written, the hypothesis is clear, the experiments are logically designed with proper control groups, and the data is thoroughly analyzed and presented in an easily interpretable manner. Overall, this study suggested novel mechanisms by which e-cigs impact lung immunity and created a dataset that could benefit the lung immunity field.

Weaknesses:

(1) The authors included a valuable control group - the PG:VG group, since PG:VG is the foundation of the e-liquid formulation. However, most of the comparative analyses use the air group as the control. Further analysis comparing the air group to the PG:VG group, and the PG:VG group to the individual flavored e-cig groups will provide more clear insights into the true source of irritation. This is done for a few analyses but not consistently throughout the paper. Flavor-specific effects should be discussed in greater detail. For example, Figure 1E shows that the Fruit flavor group exhibits more severe histological pathology but similar effects were not corroborated by the single-cell data.

(2) The characterization of Ly6g+ vs Ly6g- neutrophils is interesting and potentially very impactful. Key results like this from scRNAseq analyses should be validated by qPCR and flow cytometry.

Also, a recent study by Ruscitti et al reported Ly6g+ macrophages in the lung which can potentially confound the cell type analysis. A more detailed marker gene and sub-population analysis of the myeloid clusters could rule out this potential confounding factor.

Reviewer #1 (Public review):

Summary:

Praegel et al. explore the differences in learning an auditory discrimination task between adolescent and adult mice. Using freely moving (Educage) and head-fixed paradigms, they compare behavioral performance and neuronal responses over the course of learning. The mice were initially trained for seven days on an easy pure frequency tone Go/No-go task (frequency difference of one octave), followed by seven days of a harder version (frequency difference of 0.25 octave). While adolescents and adults showed similar performances on the easy task, adults performed significantly better on the harder task. Quantifying the lick bias of both groups, the authors then argue that the difference in performance is not due to a difference in perception, but rather to a difference in cognitive control. The authors then used neuropixel recordings across 4 auditory cortical regions to quantify the neuronal activity related to the behavior. At the single-cell level, the data shows earlier stimulus-related discrimination for adults compared to adolescents in both the easy and hard tasks. At the neuronal population level, adults displayed a higher decoding accuracy and lower onset latency in the hard task as compared to adolescents. Such differences were not only due to learning, but also to age as concluded from recordings in novice mice. After learning, neuronal tuning properties had changed in adults but not in adolescents. Overall, the differences between adolescent and adult neuronal data correlate with the behavior results in showing that learning a difficult task is more challenging for younger mice.

Strengths:

(1) The behavioral task is well designed, with the comparison of easy and difficult tasks allowing for a refined conclusion regarding learning across ages. The experiments with optogenetics and novice mice complete the research question in a convincing way.

(2) The analysis, including the systematic comparison of task performance across the two age groups, is most interesting and reveals differences in learning (or learning strategies?) that are compelling.

(3) Neuronal recording during both behavioral training and passive sound exposure is particularly powerful and allows interesting conclusions.

Weaknesses:

(1) The presentation of the paper must be strengthened. Inconsistencies, mislabeling, duplicated text, typos, and inappropriate color code should be changed.

(2) Some claims are not supported by the data. For example, the sentence that says that "adolescent mice showed lower discrimination performance than adults (l.22) should be rewritten, as the data does not show that for the easy task (Figure 1F and Figure 1H).

(3) The recording electrodes cover regions in the primary and secondary cortices. It is well known that these two regions process sounds quite differently (for example, one has tonotopy, the other does not), and separating recordings from both regions is important to conclude anything about sound representations. The authors show that the conclusions are the same across regions for Figure 4, but is it also the case for the subsequent analysis? In Figure 7 for example, are the quantified properties not distinct across primary and secondary areas? If this is not the case, how is it compatible with the published literature?

(4) Some analysis interpretations should be more cautious. For example, I do not understand how the lick bias, defined -according to the method- as the inverse normal distribution of the z-score (hit rate) +z-scored (false alarm rate; Figure 1j?, l.749-750), should reflect a cognitive difficulty (l. 161-162, l.171). A lower lick rate in general could reflect a weaker ability to withhold licking- as indicated on l.164, but also so many other things, like a lower frustration threshold, lower satiation, more energy, etc).

Reviewer #1 (Public review):

Summary:

In this manuscript, the authors demonstrate for the first time that opioid signaling has opposing effects on the same target neuron depending on the source of the input. Further, the authors provide evidence to support the role of potassium channels in regulating a brake on glutamatergic and cholinergic signaling, with the latter finding being developmentally regulated and responsive to opioid treatment. This evidence solves a conundrum regarding cholinergic signaling in the interpeduncular nucleus that evaded elucidation for many years.

Strengths:

This manuscript provides 3 novel and important findings that significantly advance our understanding of the medial habenula-interpeduncular circuitry:

(1) Mu opioid receptor activation (mOR) reduces postsynaptic glutamatergic currents elicited from substance P neurons while simultaneously enhancing postsynaptic glutamatergic currents from cholinergic neurons, with the latter being developmentally regulated.

(2) Substance P neurons from the Mhb provide functional input to the rostral nucleus of the IPN, in addition to the previously characterized lateral nuclei.

(3) Potassium channels (Kv1.2) provide a break in neurotransmission in the IPN.

Weaknesses:

Overall I find the data presented compelling, but I feel that the number of observations is quite low (typically n=3-7 neurons, typically one per animal). While I understand that only a few slices can be obtained for the IPN from each animal, the strength of the novel findings would be more convincing with more frequent observations (larger n, more than one per animal). The findings here suggest that the authors have identified a novel mechanism for the normal function of neurotransmission in the IPN, so it would be expected to be observable in almost any animal. Thus it is not clear to me why the authors investigated so few neurons per slice and chose to combine different treatments into one group (e.g. Figure 2f), even if the treatments have the same expected effect.

There are also significant sex differences in nAChR expression in the IPN that might not be functionally apparent using the low n presented here. It would be helpful to know which of the recorded neurons came from each sex, rather than presenting only the pooled data.

There are also some particularly novel observations that are presented but not followed up on, and this creates a somewhat disjointed story. For example, in Figure 2, the authors identify neurons in which no response is elicited by light stimulation of ChAT-neurons, but the application of DAMGO (mOR agonist) un-silences these neurons. Are there baseline differences in the electrophysiological or morphological properties of these "silent" neurons compared to the responsive neurons?

Reviewer #1 (Public review):

Summary:

The authors were attempting to describe whether trained innate immunity would modulate antibody-dependent cellular phagocytosis (ADCP) and/or efferocytosis.

Strengths:

The use of primary murine macrophages, and not a cell line, is considered a strength.

The trained immunity-mediated changes to phagocytosis affected both melanoma and breast cancer cells. The broad effect is consistent with trained immunity.

Weaknesses:

The most significant weakness, also noted by the authors in the discussion, is the lack of in vivo data. Without these data, it is not possible to put the in vitro data in context. It is unknown if the described effects on efferocytosis will be relevant to the in vivo progression of cancer.

Reviewer #1 (Public review):

Summary:

Integrating large-field stimulation with a retinotopic atlas, this study introduces an fMRI-based method for measuring contrast sensitivity across the visual field. Retinotopy was assessed using pRF mapping and a calibrated Benson atlas. The authors validate their method by replicating known patterns of contrast sensitivity across eccentricities and visual field quadrants in healthy subjects and demonstrate its potential clinical utility through case studies of both simulated and real visual field loss.

Strengths:

The new method is promising, with potential clinical utility in assessing visual field loss.

Weaknesses:

The current claims should be better supported by more evidence.

In the first experiment, have the statistics undergone multiple comparison corrections (e.g., Line 441-442)? Given the small sample size, incorporating additional statistical tests (such as the Bayes Factor) could strengthen the analysis.

The authors claim that "structure-based atlases can replace the need for pRF mapping in cases where it might otherwise be difficult or impossible to collect pRF data." This claim needs further scrutiny. Currently, only one simulated condition of visual field loss was examined in one subject. Also, in Figure 7, contrast sensitivity in the periphery differs between pRF mapping and the Benson atlas. How do the authors explain this discrepancy?

Overall, the writing could be significantly improved.

Reviewer #1 (Public review):

Summary:

The Szczupak lab published a very interesting paper in 2012 (Rodriquez et al. J Neurophysiol 107:1917-1924) on the effects of the segmentally-distributed non-spiking (NS) cell on crawl-related motoneurons. As far as I can tell, the working model presented in 2012, for how the non-spiking (NS) cell impacts the crawling motor pattern, is the same functional model presented in this new paper. Unfortunately, the Discussion does not address any of the findings in the previous paper or cite them in the context of NS alterations of fictive crawling. Aside from different-looking figures and some new analyses, the results and conclusions are the same.

Strengths:

The figures are well illustrated.

Weaknesses:

The paper is a mix of what appears to be two different studies and abruptly switches gears to examine how closely the crawl patterning is in the intact animal as compared to the fictive crawl patterning in the intact animal. Unfortunately, previous studies in other labs are not cited even though identical results have been obtained and similar conclusions were made. Thus, the novelty of the results is missing for those who are familiar with the leech preparation. The lack of appropriate citations and discussion of previous studies also deprives the scientific community of fully comprehending the impact of the data presented and the science it was built upon.

(1) Results, Lines 167-170: "While multiple extracellular recordings have been performed previously (Eisenhart et al., 2000), these results present the first quantitative analysis of motor units activated throughout the crawling cycle. The In-Phase units are expected to control the contraction stage by exciting or inhibiting the longitudinal or circular muscles, respectively, and the Anti-Phase units to control the elongation stage by exciting or inhibiting the circular or longitudinal muscles, respectively."

The first line above is misleading. The study by Puhl and Mesce (2008, J. Neurosci, 28:4192- 420) contains a comprehensive analysis of the motoneurons active during fictive crawling with the aim of characterizing their roles and phase relationships and solidifying the idea that the oscillator for crawling resides in a single ganglion. Intracellular recordings from a number of key crawl-related motoneurons were made in combination with extracellular recordings of motoneuron DE-3, a key monitor of crawling. In their paper, it was shown that motoneurons AE, VE-4, DI-1, VI-2, and CV were all correlated with crawl activity, and fired repeatedly either in phase or out-of-phase with DE-3. They were shown to be either excitatory or inhibitory.

At a minimum, the above paper should be cited. The submitted paper would be strengthened if some of these previously identified motoneurons were again recorded with intracellular electrodes and concomitant NS cell stimulation. The power of the leech preparation is that cells can be identified as individuals with dual somatic (intracellular) and axonal recordings (extracellular). The shortfall of this aspect of the study (Figure 5) is that the extracellular units have not been identified here. In fact, these units might not even be motoneurons. They could represent activity from the centrally located sensory neurons, dopamine-modulated afferent neurons or peripherally projecting modulatory neurons. Essentially, they may not have much to do with the crawl motor pattern at all.

(2) Results Lines 206-210: "with the elongation and contraction stages of in vivo behavior. However the isometric stages displayed in vivo have no obvious counterpart in the electrophysiological recordings. It is important to consider that the rhythmic movement of successive segments along the antero-posterior axis of the animal requires a delay signal that allows the appropriate propagation of the metachronal wave, and this signal is probably absent in the isolated ganglion."

The so-called isometric stages, indeed, have an electrophysiological counterpart due in part to the overlapping activities across segments. This submitted paper would be considerably strengthened if it referred to the body of work that has examined how the individual crawl oscillators operate in a fully intact nerve cord, excised from the body but with all the ganglia (and cephalic ganglion) attached. Puhl and Mesce 2010 (J. Neurosci 30: 2373-2383) and Puhl et al. 2012 (J. Neurosci, 32:17646 -17657) have shown that "appropriate propagation of the metachronal wave" requires the brain, especially cell R3b-1. They also show that the long-distance projecting cell R3b-1 synapses with the CV motoneuron, providing rhythmic excitatory input to it.

For this and other reasons, the paper would be much more informative and exciting if the impacts of the NS cell were studied in a fully intact nerve cord. Those studies have never been done, and it would be exciting to see how and if the effects of NS cell manipulation deviated from those in the single ganglion.

(3) Discussion Lines 322-324. "The absence of descending brain signals and/or peripheral signals are assumed as important factors in determining the cycle period and the sequence at which the different behavioral stages take place."

The authors could strengthen their paper by including a more complete picture of what is known about the control of crawling. For example, Puhl et al. 2012 (J Neurosci, 32:17646-17657) demonstrated that the descending brain neuron R3b-1 plays a major role in establishing the crawl-cycle frequency. With increased R3b-1 cell stimulation, DE-3 periods substantially shortened throughout the entire nerve cord. Thus, the importance of descending brain inputs should not be merely assumed; empirical evidence exists.

(4) Discussion Lines 325-327: "the sequence of events, and the proportion of the active cycle dedicated to elongation and contraction were remarkably similar in both experimental settings. This suggests that the network activated in the isolated ganglion is the one underlying the motor behavior."

The results and conclusions drawn in the current manuscript mirror those previously reported by Puhl and Mesce (2008, J. Neurosci, 28:4192- 420) who first demonstrated that the essential pattern-generating elements for leech crawling were contained in each of the segmental ganglia comprising the nerve cord. Furthermore, the authors showed that the duty cycle of DE-3, in a single ganglion treated with dopamine, was statistically indistinguishable from the DE-3 duty cycle measured in an intact nerve cord showing spontaneous fictive crawling, in an intact nerve cord induced to crawl via dopamine, and in the intact behaving animal. What was statistically significant, however, was that the DE-3 burst period was greatly reduced in the intact animal (i.e., a higher crawl frequency), which was replicated in the submitted paper.

In my opinion, the novelty of the results reported in the submitted manuscript is diminished in the light of previously published studies. At a minimum, the previous studies should be cited, and the authors should provide additional rationale for conducting their studies. They need to explain in the discussion how their approach provided additional insights into what has already been reported.

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Reviewer #1 (Public Review):

The work of Umetani et al. monitors the death of about 100,000 cells caused by lethal antibiotic treatments in a microfluidic device. They observe that the surviving bacteria are either in a dormant or in a non-dormant state prior to the antibiotic treatment. They then study the relative abundances of these different persister cells when varying the physiological state of the culture. In agreement with previous observations, they observe that late stationary phase cultures harbor a high number of dormant persister cells and that this number goes down as the culture is more exponential but remains non-zero, suggesting that cultures at the exponential phase contain different types of persister bacteria. These results were qualitatively similar in a rich and poor medium. Further characterization of the growing persister bacteria shows that they often form L-forms, have low RpoS-mcherry expression levels and grow only slightly more slowly than the non-persister bacteria. Taken together, these results draw a detailed view of persister bacteria and the way they may survive extensive antibiotic treatments. However, in order to represent a substantial advance on previous knowledge, a deeper analysis of the persister bacteria should be done.

Reviewer #1 (Public review):

Weiler, Teichert, and Margrie systematically analyzed long-range cortical connectivity, using a retrograde viral tracing strategy to identify layer and region-specific cortical projections onto the primary visual, primary somatosensory, and primary motor cortices. Their analysis revealed several hundred thousand inputs into each region, with inputs originating from almost all cortical regions but dominated in number by connections within cortical sub-networks (e.g. anatomical modules). Generally, the relative areal distribution of contralateral inputs followed the distribution of corresponding ipsilateral inputs. The largest proportion of inputs originated from layer 6a cells, and this layer 6 dominance was more pronounced for contralateral than ipsilateral inputs, which suggests that these connections provide predominantly feedback inputs. The hierarchical organization of input regions was similar between ipsi- and contralateral regions, except for within-module connections, where ipsilateral connections were much more feed-forward than contralateral. These results contrast earlier studies which suggested that contralateral inputs only come from the same region (e.g. V1 to V1) and from L2/3 neurons. The conclusions of this paper are well-supported by the data and analysis, and useful follow-up analyses and discussions are present in the supplemental figures. Taken together, these results provide valuable data supporting a view of interhemispheric connectivity in which layer 6 neurons play an important role in providing modulatory feedback.

Reviewer #1 (Public review):

Summary:

This study aims to identify the proteins that compose the electrical synapse, which are much less understood than those of the chemical synapse. Identifying these proteins is important to understand how synaptogenesis and conductance are regulated in these synapses. The authors identified more than 50 new proteins and used immunoprecipitation and immunostaining to validate their interaction of localization. One new protein, a scaffolding protein, shows particularly strong evidence of being an integral component of the electrical synapse. However, many key experimental details are missing (e.g. mass spectrometry), making it difficult to assess the strength of the evidence.

Strengths:

One newly identified protein, SIPA1L3, has been validated both by immunoprecipitation and immunohistochemistry. The localization at the electrical synapse is very striking.<br /> A large number of candidate interacting proteins were validated with immunostaining in vivo or in vitro.

Weaknesses:

There is no systematic comparison between the zebrafish and mouse proteome. The claim that there is "a high degree of evolutionary conservation" was not substantiated.

No description of how mass spectrometry was done and what type of validation was done.

The threshold for enrichment seems arbitrary.

Inconsistent nomenclature and punctuation usage.

The description of figures is very sparse and error-prone (e.g. Figure 6).

In Figure 1B, there is very broad non-specific labeling by avidin in zebrafish (In contrast to the more specific avidin binding in mice, Figure 2B). How are the authors certain that the enrichment is specific at the electrical synapse?

In Figure 1E, there is very little colocalization between Cx35 and Cx34.7. More quantification is needed to show that it is indeed "frequently associated."

Expression of GFP in HCs would potentially be an issue, since GFP is fused to Cx36 (regardless of whether HC expresses Cx36 endogenously) and V5-TurboID-dGBP can bind to GFP and biotinylate any adjacent protein.

Figure 7: the description does not match up with the figure regarding ZO-1 and ZO-2.

Reviewer #1 (Public review):

Summary:

The Authors explore associations between plasma metabolites and glaucoma, a primary cause of irreversible vision loss worldwide. The study relies on measurements of 168 plasma metabolites in 4,658 glaucoma patients and 113,040 controls from the UK Biobank. The Authors show that metabolites improve the prediction of glaucoma risk based on polygenic risk score (PRS) alone, albeit weakly. The Authors also report a "metabolomic signature" that is associated with a reduced risk (or "resilience") for developing glaucoma among individuals in the highest PRS decile (reduction of risk by an estimated 29%). The Authors highlight the protective effect of pyruvate, a product of glycolysis, for glaucoma development and show that this molecule mitigates elevated intraocular pressure and optic nerve damage in a mouse model of this disease.

Strengths:

This work provides additional evidence that glycolysis may play a role in the pathophysiology of glaucoma. Previous studies have demonstrated the existence of an inverse relationship between intraocular pressure and retinal pyruvate levels in animal models (Hader et al. 2020, PNAS 117(52)) and pyruvate supplementation is currently being explored for neuro-enhancement in patients with glaucoma (De Moraes et al. 2022, JAMA Ophthalmology 140(1)). The study design is rigorous and relies on validated standard methods. Additional insights gained from a mouse model are valuable.

Weaknesses:

Caution is warranted when examining and interpreting the results of this study. Among all participants (cases and controls) glaucoma status was self-reported, determined on the basis of ICD codes or previous glaucoma laser/surgical therapy. This is problematic as it is not uncommon for individuals in the highest PRS decile to have undiagnosed glaucoma (as shown in previous work by some of the authors of this article). The Authors acknowledge a "relatively low glaucoma prevalence in the highest decile group" but do not explore how undiagnosed glaucoma may affect their results. This also applies to all controls selected for this study. The Authors state that "50 to 70% of people affected [with glaucoma] remain undiagnosed". Therefore, the absence of self-reported glaucoma does not necessarily indicate that the disease is not present. Validation of the findings from this study in humans is, therefore, critical. This should ideally be performed in a well-characterized glaucoma cohort, in which case and control status has been assessed by qualified clinicians.

The authors indicate that within the top decile of PRS participants with glaucoma are more likely to be of white ethnicity, while they are more likely to be of Black and Asian ethnicity if they are in the bottom half of PRS. Have the Authors explored how sensitive their predictions are to ethnicity? Since their cohort is predominantly of European ancestry (85.8%), would it make sense to exclude other ethnicities to increase the homogeneity of the cohort and reduce the risk for confounders that may not be explicitly accounted for?

The authors discuss the importance of pyruvate, and lactate for retinal ganglion cell survival along with that of several lipoproteins for neuroprotection. However, there is a distinction to be made between locally produced/available glycolysis end products and lipoproteins and those circulating in the blood. It may be useful to discuss this in the manuscript, and for the Authors to explore if plasma metabolites may be linked to metabolism that takes place past the blood-retinal barrier.

Comments on revisions:

The Authors have addressed all of my concerns.

Reviewer #1 (Public review):

Summary:

By way of background, the Jiang lab has previously shown that loss of the type II BMP receptor Punt (Put) from intestinal progenitors (ISCs and EBs) caused them to differentiate into EBs, with a concomitant loss of ISCs (Tian and Jiang, eLife 2014). The mechanism by which this occurs was activation of Notch in Put-deficient progenitors. How Notch was upregulated in Put-deficient ISCs was not established in this prior work. In the current study, the authors test whether a very low level of Dl was responsible. But co-depletion of Dl and Put led to a similar phenotype as depletion of Put alone. This result suggested that Dl was not the mechanism. They next investigate genetic interactions between BMP signaling and Numb, an inhibitor of Notch signaling. Prior work from Bardin, Schweisguth and other labs has shown that Numb is not required for ISC self-renewal. But the authors wanted to know whether loss of both the BMP signal transducer Mad and Numb would cause ISC loss. This result was observed for RNAi depletion from progenitors and for mad, numb double mutant clones. Of note, ISC loss was observed in 40% of mad, numb double mutant clones, whereas 60% of these clones had an ISC. They then employed a two-color tracing system called RGT to look at the outcome of ISC divisions (asymmetric (ISC/EB) or symmetric (ISC/ISC or EB/EB)). Control clones had 69%, 15% and 16%, respectively, whereas mad, numb double mutant clones had much lower ISC/ISC (11%) and much higher EB/EB (37%). They conclude that loss of Numb in moderate BMP loss of function mutants increased symmetric differentiation which lead caused ISC loss. They also reported that numb15 and numb4 clones had a moderate but significant increase in ISC-lacking clones compared to control clones, supporting the model that Numb plays a role in ISC maintenance. Finally, they investigated the relevance of these observation during regeneration. After bleomycin treatment, there was a significant increase in ISC-lacking clones and a significant decrease in clone size in numb4 and numb15 clones compared to control clones. Because bleomycin treatment has been shown to cause variation in BMP ligand production, the authors interpret the numb clone under bleomycin results as demonstrating an essential role of Numb in ISC maintenance during regeneration.

Strengths

i. Data are quantified with statistical analysis<br /> ii. Experiments have appropriate controls and large numbers of samples<br /> iii. Results demonstrate an important role of Numb in maintaining ISC number during regeneration and a genetic interaction between Mad and Numb during homeostasis.

Weaknesses

None noted in the revised manuscript.

Reviewer #1 (Public review):

The authors investigated the response of worms to the odorant 1-octanol (1-oct) using a combination of microfluidics-based behavioral analysis and whole-network calcium imaging. They hypothesized that 1-oct may be encoded through two simultaneous, opposing afferent pathways: a repulsive pathway driven by ASH, and an attractive pathway driven by AWC. And the ultimate chemotactic outcome is likely determined by the balance between these two pathways.

It is not surprising that 1-octanol is encoded as attractive at low concentrations and repulsive at higher concentrations. However, the novel aspect of this study is the discovery of the combinatorial coding of 1-oct in the periphery, where it serves as both an attractant and a repellent. Furthermore, the study uses this dual encoding as a model to explore the neural basis of sensory-driven behaviors at a whole-network scale in this organism. The basic conclusions of this study are well supported by the behavioral and imaging experiments, though there are certain aspects of the manuscript that would benefit from further clarification.

A key issue is that several previous studies have demonstrated a combinatorial and concentration-dependent coding of odorant sensing in the nematode peripheral nervous system. Specifically, ASH and AWC are the primary receptors for repellent and attractive responses, respectively. However, other neurons such as AWB, AWA, and ADL are also involved in the coding process. These neurons likely communicate with different interneurons to contribute to 1-oct-induced outputs. The authors' conclusion that loss of tax-4 reduces attractive responses and that osm-9 mutants reduce repulsive responses is not entirely convincing. TAX-4 is required for both AWC (an attractive neuron) and AWB (a repulsive neuron), and osm-9 is essential for ASH, ADL, and AWA (attraction-associated). Therefore, the observed effects on the attractive and repulsive responses could be more complex. Additionally, the interpretation of results involving the use of IAA to reduce the contribution of AWC at lower concentrations lacks clarity. A more effective approach might involve using transgenically expressed miniSOG or histamine (HisCl1) to specifically inhibit AWC neurons.

The authors did not observe any increased correlation between motor command interneurons and sensory neurons, which is consistent with the absence of a consistent relationship between state transitions and 1-oct application. Furthermore, they did not observe significant entrainment of AIB activity with the 2.2 mM 1-oct application. This might be due to the animals being anesthetized with 1 mM tetramisole hydrochloride, which could affect neural activity and/or feedback from locomotion. It is unclear whether subtracting AVA activity from AIB activity provides a valid measure. Similarly, it is unclear how the behavioral data from freely moving worms compares to the whole-network calcium imaging results obtained from immobilized worms.

Reviewer #2 (Public review):

Summary:

The manuscript by Xie and colleagues presents transcriptomic experiments that measure gene expression in eight different tissues taken from adult female and male mice from four species. These data are used to make inferences regarding the evolution of sex-biased gene expression across these taxa.

Strengths:

The experimental methods and data analysis appear appropriate. The authors promote their study as unprecedented in its size and technical precision.

Weaknesses:

The manuscript does not present a clear set of novel evolutionary conclusions. The major findings recapitulate many previous comparative transcriptomics studies - gene expression variation is prevalent between individuals, sexes, and species; and genes with sex-biased expression evolve more rapidly than genes with unbiased expression - but it is not clear how the study extends our understanding of gene expression or its evolution.

Many gene expression differences between individual animals are selectively neutral, because these differences in mRNA concentration are buffered at the level of translation, or differences in protein abundance have no effect on cellular or organismal function. The hypothesis that sex-biased genes are enriched for selectively neutral expression differences is supported by the excess of inter-individual expression variance and inter-specific expression differences in sex-biased genes. A higher rate of adaptive coding evolution is inferred among sex-biased genes as a group, but it is not clear whether this signal is driven by many sex-biased genes experiencing a little positive selection, or a few sex-biased genes experiencing a lot of positive selection, so the relationship between expression and protein-coding evolution remains unclear. It is likely that only a subset of the gene expression differences detected here will have phenotypic effects relevant for fitness or medicine, but without some idea of how many or which genes comprise this subset, it is difficult to interpret the results in this context.

Throughout the paper the concepts of sexual selection and sexually antagonistic selection are conflated; while both modes of selection can drive the evolution of sexually dimorphic gene expression, the conditions promoting and consequence of both kinds of selection are different, and the manuscript is not clear about the significance of the results for either mode of selection.

The manuscript's conclusion that "most of the genetic underpinnings of sex-differences show no long-term evolutionary stability" is not supported by the data, which measured gene expression phenotypes but did not investigate the underlying genetic variation causing these differences between individuals, sexes, or species. Furthermore, most of the gene expression differences are observed between sex-specific organs such as testes and ovaries, which are downstream of the sex-determination pathway that is conserved in these four mouse species, so these conclusions are limited to gene expression phenotypes in somatic organs shared by the sexes.

The differences between sex-biased expression in mice and humans are attributed to differences in the two species effective population sizes; but the human samples have significantly more environmental variation than the mouse samples taken from age-matched animals reared in controlled conditions, which could also explain the observed pattern.

The smoothed density plots in Figure 5 are confusing and misleading. Examining the individual SBI values in Table S9 reveals that all of the female and male SBI values for each species and organ are non-overlapping, with the exception of the heart in domesticus and mammary gland in musculus, where one male and one female individual fall within the range of the other sex. The smoothed plots therefore exaggerate the overlap between the sexes; in particular, the extreme variation shown in the SBI in the mammary glands in spretus females and spicilegus males is hard to understand given the normalized values in Table S3. The R code used to generate the smoothed plots is not included in the Github repository, so it is not possible to independently recreate those plots from the underlying data.

The correlations provided in Table S9 are confusing - most of the reported correlations are 1.0, which are not recovered when using the SBI values in Table S9, and which does not support the manuscript's assertion that sex-biased gene expression can vary between organs within an individual. Indeed, using the SBI values in Table S9, many correlations across organs are negative, which is expected given the description of the result in the text.

Reviewer #2 (Public review):

Summary:

Makarova et al. provide the first complete cellular-level reconstruction of an insect eye. They use the extremely miniaturized parasitoid wasp, Megaphragma viggiani and apply improved and optimized volumetric EM methods they can describe, the size, volume and position of every single cell in the insect compound eye.

This data has previously only been inferred from TEM cross-sections taken in different parts of the eye, but in this study and in the associated 3d datasets video and stacks, one can observe the exact position and orientation in 3D space.<br /> The authors have made a very rigorous effort to describe and assess the variation in each cell type and have also compared two different classes of dorsal rim and non-dorsal rim ommatidia and the associated visual apparatus for each, confirming previous known findings about the distribution and internal structure that assists in polarization detection in these insects.

Strengths:

The paper is well written and strives to compare the data with previous literature wherever possible and goes beyond cell morphology, calculating the optical properties of the different ommatidia and estimating light sensitivity and spatial resolution limits using rhabdom diameter, focal length and showing how this varies across the eye.

Finally, the authors provide very informative and illustrative videos showing how the cones, lenses, photoreceptors, pigment cells, and even the mitochondria are arranged in 3D space, comparing the structure of the dorsal rim and non-dorsal rim ommatidia. They also describe three 'ectopic' photoreceptors in more anatomical detail providing images and videos of them.

Comments on revisions:

The updates improve the manuscript.

Reviewer #1 (Public review):

Summary:

This interesting manuscript first shows that human, murine, and feline sperm penetrate the zona pellucida (ZP) of bovine oocytes recovered directly from the ovary, although first cleavage rates are reduced. Similarly, bovine sperm can penetrate superovulated murine oocytes recovered directly from the ovary. However, bovine oocytes incubated with oviduct fluid (30 min) are generally impenetrable by human sperm.

Thereafter, the cytoplasm was aspirated from murine oocytes - obtained from the ovary or oviduct. Binding and penetration by bovine and human sperm was reduced in both groups relative to homologous (murine) sperm. However, heterologous (bovine and human) sperm penetration was further reduced in oviduct vs. ovary derived empty ZP. These data show that outer (ZP) not inner (cytoplasmic) oocyte alterations reduce heterologous sperm penetration as well as homologous sperm binding.

This was repeated using empty bovine ZP incubated, or not, with bovine oviduct fluid. Prior oviduct fluid exposure reduced non-homologous (human and murine) empty ZP penetration, polyspermy, and sperm binding. This demonstrates that species-specific oviduct fluid factors regulate ZP penetrability.

To test the hypothesis that OVGP1 is responsible, the authors obtained histidiine-tagged bovine and murine OVGP1 and DDK-tagged human OVGP1 proteins. Tagging was to enable purification following over-expression in BHK-21 or HEK293T cells. The authors confirm these recombinant OVGP1 proteins bound to both murine and bovine oocytes. Moreover, previous data using oviduct fluid was mirrored using bovine oocytes supplemented with homologous (bovine) recombinant OVGP1, or not. This confirms the hypothesis, at least in cattle.

Next, the authors exposed bovine and murine empty ZP to bovine, murine, and human recombinant OVGP1, in addition to bovine, murine, or human sperm. Interestingly, both species-specific ZP and OVGP1 seem to be required for optimal sperm binding and penetration.

Lastly, empty bovine and murine ZP were treated with neuraminidase, or not, with or without pre-treatment with homologous OVGP1. In each case, neuraminidase reduced sperm binding and penetration. This further demonstrates that both ZP and OVGP1 are required for optimal sperm binding and penetration.

In summary, the authors demonstrate that two mechanisms seem to underpin mammalian sperm recognition and penetration, the first being specific (ZP-mediated) and the second non-specific (OVGP1 mediated).

Reviewer #1 (Public review):

Summary:

This important article reveals that the Nora virus can colonize the intestinal cells of Drosophila melanogaster, where it persists with minimal immediate impact on its host. However, upon aging, infection, or exposure to toxicants, stem cell activation induces Nora virus proliferation, enabling it to colonize enterocytes. This colonization disrupts enterocyte function, leading to increased gut permeability and a significant reduction in lifespan. Results are convincing with an important impact on the Drosophila community.

Strengths:

(1) Building on previous studies by Habayeb et al. (2009) and Hanson et al. (2023), this study highlights cryptic Nora virus infection as a crucial factor in aging and gut homeostasis in Drosophila melanogaster.

(2) Consistent with the oral route of Nora virus transmission, the study demonstrates that the virus resides in intestinal stem cells, with its replication directly linked to stem cell proliferation. This process facilitates the colonization of enterocytes, ultimately disrupting intestinal function.

(3) The study establishes a clear connection between stem cell proliferation and virus replication, suggesting that various factors - such as microbiota, aging, diet, and injury - can influence Nora virus dynamics and associated pathology.

(4) The experimental design is robust, comparing infected flies with virus-cured controls to validate findings.

Weaknesses:

(1) The study does not explore or discuss how oral ingestion of Nora virus leads to the colonization of stem cells, which are located basally in the gut. This mechanism should be discussed.

(2) The authors fail to detect Dicer-GFP fusion protein expression in stem cells, a finding that could explain why the virus persists in these cells. Further investigation is needed to determine whether RNAi functions are effective in stem cells compared to enterocytes. For clarification, the authors could cross esg-Gal4 UAS-GFP and Myo-Gal4 UAS-GFP with UAS GFP-RNAi and/or express a Dicer-GFP construct under a stem cell-specific driver.

(3) The presentation of experimental parameters (e.g., pathogen type, temperature, time points) should be improved in the results section and at the top of the figures to enhance clarity. Additionally, details regarding the mode of oral infection (continuous exposure vs. single feeding on a filter) should be specified. Given that fly stock flipping frequency influences microbiota load (as noted in Broderick et al.), this should be reported, especially for lifespan studies.

(4) To confirm that enterocyte colonization requires stem cell proliferation and differentiation, the authors should analyze Nora virus localization in JAK-STAT-deficient flies infected with bacteria or toxicants. This would help determine whether the virus can infect enterocytes in the absence of enterocyte differentiation, but stimulation of stem cells.

(5) The study does not discuss the spatial distribution of Nora virus infection along the gut. Specifically, it remains unclear whether viral colonization is higher in gut regions R2 and R3, which contain proliferative stem cells. Addressing this could provide valuable insights into the virus's infection dynamics.

Reviewer #1 (Public review):

Summary:

This work investigated how the sense of control influences perceptions of stress. In a novel "Wheel Stopping" task, the authors used task variations in difficulty and controllability to measure and manipulate perceived control in two large cohorts of online participants. The authors first show that their behavioral task has good internal consistency and external validity, showing that perceived control during the task was linked to relevant measures of anxiety, depression, and locus of control. Most importantly, manipulating controllability in the task led to reduced subjective stress, showing a direct impact of control on stress perception. However, this work has minor limitations due to the design of the stressor manipulations/measurements and the necessary logistics associated with online versus in-person stress studies.

Nevertheless, this research adds to our understanding of when and how control can influence the effects of stress and is particularly relevant to mental health interventions.

Strengths:

The primary strength of this research is the development of a unique and clever task design that can reliably and validly elicit variations in beliefs about control. Impressively, higher subjective control in the task was associated with decreased psychopathology measures such an anxiety and depression in a non-clinical sample of participants. In addition, the authors found that lower control and higher difficulty in the task led to higher perceived stress, suggesting that the task can reliably manipulate perceptions of stress. Prior tasks have not included both controllability and difficulty in this manner and have not directly tested the direct influence of these factors on incidental stress, making this work both novel and important for the field.

Weaknesses:

One minor weakness of this research is the validity of the online stress measurements and manipulations. In this study, the authors measure subjective stress via self-report both during the task and also after either a Trier Social Stress Test (high-stress condition) or a memory test (low-stress condition). One concern is that these stress manipulations were really "threats" of stress, where participants never had to complete the stress tasks (i.e., recording a speech for judgment). While this is not unusual for an in-lab study and can reliably elicit substantial stress/anxiety, in an online study, there is a possibility for communication between participants (via online forums dedicated to such communication), which could weaken the stress effects. That said, the authors did find sensible increases and decreases of perceived stress between relevant time points, but future work could improve upon this design by including more complete stress manipulations and measuring implicit physiological signs of stress.

Reviewer #1 (Public review):

Summary:

Busch and Hansel present a morphological and histological comparison between mouse and human Purkinje cells (PCs) in the cerebellum. The study reveals species-specific differences that have not previoulsy been reported despite numerous observations in these species. While mouse PCs show morphological heterogeneity and occasional multi-innervation by climbing fibers (CFs), human PCs exhibit a widespread, multi-dendritic structure that exceeds expectations based on allometric scaling. Specifically, human PCs are significantly larger, exhibit increased spine density, with a unique cluster-like morphology not found in mice.

Strengths:

The manuscript provides an exceptionally detailed analysis of PC morphology across species, surpassing any prior publication. Major strengths include a systematic and thorough methodology, rigorous data analysis, and clear presentation of results. This work is likely to become the go-to resource for quantitation in this field. The authors have largely achieved their aims, with the results effectively supporting their conclusions.

Weaknesses:

There are a few concerns that need to be addressed, specifically related to details of the methodolology as well as data interpretation based on the limits of some experimental approaches. Overall, these weaknesses are minor.

Comments on revisions:

The authors addressed my concerns in the revised manuscript. One bit of clarification, the defraction limit calculation involves the wavelength of light used for excitation not emission ("...for the minimum resolvable distance (R) given the fluorophore emission wavelength [l; 570nm for the Cy3 probe] and numerical aperture of the objective (NA) as follows:"). This is why a 2p system has less resolving power than a confocal system as it uses much longer wavelengths for excitation.

Reviewer #1 (Public review):

Summary:

In this study from Belato, Knight and co-workers, the authors investigated the Rec domain of a thermophilic Cas9 from Geobacillus stearothermophilus (GeoCas9). The authors investigated three constructs, two individual subdomains of Rec (Rec1 and Rec2) and the full Rec domain. This domain is involved in binding to the guide RNA of Cas9, as well as the RNA-DNA duplex that is formed upon target binding. The authors performed RNA binding and relaxation experiments using NMR for the wild-type domain as well as two-point mutants. They observed differences in RNA binding activities as well as the flexibility of the domain. The authors also performed molecular dynamics and functional experiments on full-length GeoCas9 to determine whether these biophysical differences affect the RNA binding or cleavage activity. Although the authors observed some changes in the thermal stability of the mutant GeoCas9-gRNA complex, they did not observe substantial differences in the guide RNA binding or cleavage activities of the mutant GeoCas9 variants.

Overall, this manuscript provides a detailed biophysical analysis of the GeoCas9 Rec domain. The NMR assignments for this construct should prove very useful, and can serve as the basis for future similar studies of GeoCas9 Rec domain mutants. While the two mutants tested in the study did not produce significant differences from wild-type GeoCas9, the study rules out the possibility that analogous mutations can be translated between type II-A and II-C Cas9 orthologs. Together, these findings may provide the grounds for future engineering of higher fidelity variants of GeoCas9

Reviewer #1 (Public review):

Summary:

Using lineage tracing and single-cell RNA sequencing, Li et al. reported brain ECs can differentiate into pericytes after stroke. This finding is novel and important to the field.

Strengths:

Detailed characterization of each time point and genetic manipulation of genes for study role of ECs and E-pericyte.

Weaknesses:

Genetic evidence for lineage tracing of ECs and E-pericytes requires more convincing data that includse staining, FACS, and scRNA-seq analysis.

Reviewer #1 (Public review):

Summary:

This manuscript by Toledo and colleagues describes the generation and characterization of Y220C mice (Y217C in the mouse allele). The authors make notable findings: Y217C mice that have been backcrossed to C57Bl/6 for five generations show decreased female pup births due to exencephaly, a known defect in p53 -/- mice, and they show a correlation with decreased Xist expression, as well as increased female neonatal death. They also noted similar tumor formation in Y217C/+ and p53 +/- mice, suggesting that Y217C may not function as a dominant negative. Notably, the authors find that homozygous Y217C mice die faster than p53 -/- mice, and that the lymphomas in the Y217C mice were more aggressive and invasive. The authors then perform RNA seq on thymi of Y217C homozygotes compared to p53 -/-, and they suggest that these differentially expressed genes may explain the increased tumorigenesis in Y217C mice.

Strengths:

Overall, the study is well controlled and quite well done and will be of interest to a broad audience, particularly given the high frequency of the Y220C mutation in cancer (1% of all cancers, 4% of ovarian cancer).

Weaknesses:

None noted

Comments on revisions:

The authors have done a superb job on this very interesting work.

Reviewer #1 (Public review):

Summary:

In this manuscript, Paturi et.al. presents a detailed structural and mechanistic study of the DRB7.2:DRB4 complex in plants, focusing on its role in sequestering endogenous inverted-repeat dsRNA precursors and inhibiting Dicer-like protein 3 (DCL3) activity. By truncating the two proteins, they systematically identify the domains involved in direct interaction between DRB7.2 and DRB4 and study the interactions between the two using biophysical techniques (ITC and NMR). They show using NMR that the interacting domains between the two proteins are likely partially unfolded or aggregated in the absence of the binding partner and determining the NMR structure of the individual interacting domains in the presence of the isotopically unlabelled partner using sparse restrain data combined with Rosetta. They also determine the complex structure of the interacting DRB7.2 dsRBD domain and the DRB4 D3 domain using X-ray crystallography.

Strengths:

Overall, the manuscript is well written, provides molecular details at high resolution between the interaction of DRB7.2 and DRB4 and the data in the manuscript strongly supports the proposed model where DRB7.2:DRB4 complex sequesters the DCL3 substrates inhibiting its function of producing epigenetically activated siRNAs.

Weaknesses:

Major comments:

(1) The manuscript unfortunately completely lacks functional validation of the determined DRB7.2:DRB4 complex structure which is required for the rigorous validation of the proposed model. For functional validation of the determined structures, the author should at least present the mutational analysis (impact on complex formation, RNA affinity) of the point mutants derived from the structure of the DRB7.2:DRB4 complex.

(2) The proposed model shows the DRB7.2M and DRB4D3 as partially folded/aggregated proteins in the absence of the complex, understandably from the presented NMR data of the individual domains. However, in the cellular context, when the RNAs are present, especially DRB7.2M might be properly folded/not aggregated. Could the authors support or negate this by showing the 15N HSQC spectrum of DRB7.2M in complex with the 13 bp dsRNA?

(3) It remains unclear from the manuscript if DRB7.1 will have a similar or different mechanism of interaction with DRB4. Based on the sequence comparisons of the two proteins, the authors should comment on this in the discussion section.

Minor comments:

(1) There are no errors for the N, dH and dS values of the ITC measurements in Table 1. Also, it seems that the measurements are done only once. Values derived from at least triplicates should be presented. This would be helpful to increase confidence in the values derived from ITC especially for the titration between DRB7.2, DRB4C, and DRB4D3 as the N value there is substantially lower than 1 which does not agree with the other data.

Reviewer #1 (Public review):

Summary:

The study shows, perhaps surprisingly, that human fecal homogenates enhance the invasiveness of Salmonella typhimurium into cells of a swine colonic explant. This effect is only seen with chemotactic cells that express the chemoreceptor Tsr. However, two molecules sensed by Tsr that are present at significant concentrations in the fecal homogenates, the repellent indole and the attractant serine, do not, either by themselves or together at the concentrations in which they are present in the fecal homogenates, show this same effect. The authors then go on to study the conflicting repellent response to indole and attractant response to serine in a number of different in vitro assays.

Strengths:

The demonstration that homogenates of human feces enhance the invasiveness of chemotactic Salmonella Typhimurium in a colonic explant is unexpected and interesting. The authors then go on to document the conflicting responses to the repellent indole and the attractant serine, both sensed by the Tsr chemoreceptor, as a function of their relative concentration and the spatial distribution of gradients.

Weaknesses:

The authors do not identify what is the critical compound or combination of compounds in the fecal homogenate that gives the reported response of increased invasiveness. They show it is not indole alone, serine alone, or both in combination that have this effect, although both are sensed by Tsr and both are present in the fecal homogenates. Some of the responses to conflicting stimuli by indole and serine in the in vitro experiments yield interesting results, but they do little to explain the initial interesting observation that fecal homogenates enhance invasiveness.

Reviewer #1 (Public review):

Summary:

Mazer & Yovel 2025 dissect the inverse problem of how echolocators in groups manage to navigate their surroundings despite intense jamming using computational simulations.

The authors show that despite the 'noisy' sensory environments that echolocating groups present, agents can still access some amount of echo-related information and use it to navigate their local environment. It is known that echolocating bats have strong small and large-scale spatial memory that plays an important role for individuals. The results from this paper also point to the potential importance of an even lower-level, short-term role of memory in the form of echo 'integration' across multiple calls, despite the unpredictability of echo detection in groups. The paper generates a useful basis to think about the mechanisms in echolocating groups for experimental investigations too.

Strengths:

(1) The paper builds on biologically well-motivated and parametrised 2D acoustics and sensory simulation setup to investigate the various key parameters of interest

(2) The 'null-model' of echolocators not being able to tell apart objects & conspecifics while echolocating still shows agents successfully emerge from groups - even though the probability of emergence drops severely in comparison to cognitively more 'capable' agents. This is nonetheless an important result showing the direction-of-arrival of a sound itself is the 'minimum' set of ingredients needed for echolocators navigating their environment.

(3) The results generate an important basis in unraveling how agents may navigate in sensorially noisy environments with a lot of irrelevant and very few relevant cues.

(4) The 2D simulation framework is simple and computationally tractable enough to perform multiple runs to investigate many variables - while also remaining true to the aim of the investigation.

Weaknesses:

There are a few places in the paper that can be misunderstood or don't provide complete details. Here is a selection:

(1) Line 61: '... studies have focused on movement algorithms while overlooking the sensory challenges involved' : This statement does not match the recent state of the literature. While the previous models may have had the assumption that all neighbours can be detected, there are models that specifically study the role of limited interaction arising from a potential inability to track all neighbours due to occlusion, and the effect of responding to only one/few neighbours at a time e.g. Bode et al. 2011 R. Soc. Interface, Rosenthal et al. 2015 PNAS, Jhawar et al. 2020 Nature Physics.

(2) The word 'interference' is used loosely places (Line 89: '...took all interference signals...', Line 319: 'spatial interference') - this is confusing as it is not clear whether the authors refer to interference in the physics/acoustics sense, or broadly speaking as a synonym for reflections and/or jamming.

(3) The paper discusses original results without reference to how they were obtained or what was done. The lack of detail here must be considered while interpreting the Discussion e.g. Line 302 ('our model suggests...increasing the call-rate..' - no clear mention of how/where call-rate was varied) & Line 323 '..no benefit beyond a certain level..' - also no clear mention of how/where call-level was manipulated in the simulations.

Reviewer #1 (Public review):

Summary:

The authors revisit the specific domains/signals required for the redirection of an inner nuclear membrane protein, emerin, to the secretory pathway. They find that epitope tagging influences protein fate, serving as a cautionary tale for how different visualisation methods are used. Multiple tags and lines of evidence are used, providing solid evidence for the altered fate of different constructs.

Strengths:

This is a thorough dissection of domains and properties that confer INM retention vs secretion to the PM/lysosome, and will serve the community well as a caution regarding the placement of tags and how this influences protein fate.

Weaknesses:

Biogenesis pathways are not explored experimentally: it would be interesting to know if the lysosomal pool arrives there via the secretory pathway (eg by engineering a glycosylation site into the lumenal domain) or by autophagy, where failed insertion products may accumulate in the cytoplasm and be degraded directly from cytoplasmic inclusions.

It would be helpful if the topology of constructs could be directly demonstrated by pulse-labelling and protease protection. It's possible that there are mixed pools of both topologies that might complicate interpretation.

Reviewer #1 (Public review):

Summary:

García-Vázquez et al. identify GTSE1 as a novel target of the cyclin D1-CDK4/6 kinases. The authors show that GTSE1 is phosphorylated at four distinct serine residues and that this phosphorylation stabilizes GTSE1 protein levels to promote proliferation. This regulatory link appears to be particularly important in pathological conditions such as cancer, where cyclin D levels are elevated.

Strengths:

The authors support their findings with several previously published results, including databases. In addition, the authors perform a wide range of experiments to support their findings.

Impact:

The authors reveal a mechanism by which elevated levels of cyclin D1-CDK4 can stabilize GTSE1 throughout the cell cycle via phosphorylation. This provides insight into the role of cyclin D1-CDK4 in regulating the cell cycle and promoting cancer growth.

Comments on revisions:

The authors have addressed all my concerns, and I would like to thank them for their efforts on this great study.

Reviewer #1 (Public review):

Summary:

In this paper, the authors have leveraged Single-cell RNA sequencing of the various stages of evolution of lung adenocarcinoma to identify the population of macrophages that contribute to tumor progression. They show that S100a4+ alveolar macrophages, active in fatty acid metabolic activity, such as palmitic acid metabolism, seem to drive atypical adenomatous hyperplasia (AAH) stage. These macrophages also seem to induce angiogenesis promoting tumor growth. Similar types of macrophage infiltration were demonstrated in the progression of the human lung adenocarcinomas.

Comments on revised version:

The authors have satisfactorily addressed my main concerns.

The only weakness is that infusion of S100a4+ macrophages seem not to affect tumor growth when introduced to the intratracheal route. This negative result somewhat diminishes the significance of the study.

Overall, the revised manuscript is significantly improved.

Reviewer #1 (Public review):

Summary:

The study combines predictions from MD simulations with sophisticated experimental approaches including native mass spectrometry (nMS), cryo-EM, and thermal protein stability assays to investigate the molecular determinants of cardiolipin (CDL) binding and binding-induced protein stability/function of an engineered model protein (ROCKET), as well as of the native E. coli intramembrane rhomboid protease, GlpG.

Strengths:

State-of-the-art approaches and sharply focused experimental investigation lend credence to the conclusions drawn. Stable CDL binding is accommodated by a largely degenerate protein fold that combines interactions from distant basic residues with greater intercalation of the lipid within the protein structure. Surprisingly, there appears to be no direct correlation between binding affinity/occupancy and protein stability.

Overall, using both model and native protein systems, this study convincingly underscores the molecular and structural requirements for CDL binding and binding-induced membrane protein stability. This work provides much-needed insight into the poorly understood nature of protein-CDL interactions.

Reviewer #1 (Public review):

Summary:

Fernandez et al. investigate the influence of maternal behavior on bat pup vocal development in Saccopteryx bilineata, a species known to exhibit vocal production learning. The authors performed detailed longitudinal observations of wild mother-pup interactions to ask whether non-vocal maternal displays during juvenile vocal practice, or 'babbling', affect vocal production. Specifically, the study examines the durations of pup babbling events and the developmental babbling phase, in relation to female display rates, as well as pup age and the number of nearby singing adult males. Furthermore, the authors examine pup vocal repertoire size and maturation in relation to maternal display rates encountered during babbling. Statistical models identify female display behavior as a predictor of i) babbling bout duration, ii) the length of the babbling phase, iii) song composition and iv) syllable maturation. Notably, these outcomes were not influenced by the number of nearby adult males (the pups' source of song models) and were largely independent of general maturation (pup age). These findings highlight the impact of non-vocal aspects of social interactions in guiding mammalian vocal development.

Strengths:

Historically, work on developmental vocal learning has focused on how juvenile vocalizations are influenced by the sounds produced by nearby adults (often males). In contrast, this study takes the novel approach of examining juvenile vocal ontogeny in relation to non-vocal maternal behavior, in one of the few mammals known to exhibit vocal production learning. The authors collected an impressive dataset from multiple wild bat colonies in two Central American countries. This includes longitudinal acoustic recordings and behavioral monitoring of individual mother-pup pairs, across development.

The identified relationships between maternal behavior and bat pup vocalizations have intriguing implications for understanding the mechanisms that enable vocal production learning in mammals, including human speech acquisition. As such, these findings are likely be relevant to a broad audience interested in the evolution and development of social behavior as well as sensory-motor learning.

Weaknesses:

The authors qualitatively describe specific patterns of female displays during pup babbling, however, subsequent quantitative analyses are based on aggregate measures of female behavior that pool across display types. Consequently, it remains unclear how certain maternal behaviors might differentially influence pup vocalizations (e.g. through specific feedback contingencies or more general modulation of pup behavioral states).

Comments on revisions:

(1) More detailed analyses of female behavior may be beyond the scope of this study, given the nature of the dataset/recordings. I look forward to the authors' future work on this aspect.

By addressing the important distinction between display number vs. display rate, the authors have provided more direct support for the claim that babbling behavior is related to female displays.

(2) The additional information regarding exposure to adult male song is appreciated.

(3) Added discussion of pup sex differences provides useful context and intriguing speculation about the role of female pup babbling.

(4) The authors' additions have significantly improved the clarity of their acoustic terminology and syllable analyses.

Reviewer #1 (Public review):

Du et al. address the cell cycle-dependent clearance of misfolded protein aggregates mediated by the endoplasmic reticulum (ER) associated Hsp70 chaperone family and ER reorganisation. The observations are interesting and impactful to the field.

Strength:

The manuscript addresses the connection between the clearance of misfolded protein aggregates and the cell cycle using a proteostasis reporter targeted to ER in multiple cell lines. Through imaging and some biochemical assays, they establish the role of BiP, an Hsp70 family chaperone, and Cdk1 inactivation in aggregate clearance upon mitotic exit. Furthermore, the authors present an initial analysis of the role of ER reorganisation in this clearance. These are important correlations and could have implications for ageing-associated pathologies. Overall, the results are convincing and impactful to the field.

Weakness:

The manuscript still lacks a mechanistic understanding of aggregate clearance. Even though the authors have provided the role of different cellular components, such as BiP, Cdk1 and ATL2/3 through specific inhibitors, at least an outline establishing the sequence of events leading to clearance is missing. Moreover, the authors show that the levels of ER-FlucDM-eGFP do not change significantly throughout the cell cycle, indicating that protein degradation is not in play. Therefore, addressing/elaborating on the mechanism of disassembly can add value to the work. Also, the physiological relevance of aggregate clearance upon mitotic exit has not been tested, nor have the cellular targets of this mode of clearance been identified or discussed.

Reviewer #1 (Public review):

Summary:

The authors investigate the neuroprotective effect of reserpine in a retinitis pigmentosa (P23H-1) model, characterized by a mutation in the rhodopsin gene. Their results reveal that female rats show better preservation of both rod and cone photoreceptors following reserpine treatment compared to males.

Strengths:

This study effectively highlights the neuroprotective potential of reserpine and underscores the value of drug repositioning as a strategy for accelerating the development of effective treatments. The findings are significant for their clinical implications, particularly in demonstrating sex-specific differences in therapeutic response.

Weaknesses:

The main limitation is the lack of precise identification of the specific pathway through which reserpine prevents photoreceptor death.

Comments on revisions:

Thank you for your thorough revisions. I appreciate the effort you have put into addressing all the concerns I previously raised. Upon reviewing your responses and the updated manuscript, I find that you have adequately clarified the issues and incorporated the necessary modifications. Your revisions have strengthened the paper, and I have no further concerns at this stage.

Reviewer #3 (Public review):

Summary:

Golamalamdari, van Schaik, Wang, Kumar Zhang, Zhang and colleagues study interactions between the speckle, nucleolus and lamina in multiple cell types (K562, H1, HCT116 and HFF). Their datasets define how interactions between the genome and the different nuclear landmarks relate to each other and change across cell types. They also identify how these relationships change in K562 cells in which LBR and LMNA are knocked out.

Strengths:

Overall, there are a number of datasets that are provided, and several "integrative" analyses performed. This is a major strength of the paper, and I imagine the datasets will be of use to the community to further probed and the relationships elucidated here further studied. An especially interesting result was that specific genomic regions (relative to their association with the speckle, lamina, and other molecular characteristics) segregate relative to the equatorial plane of the cell.

Weaknesses:

The experiments are primarily descriptive, and the cause-and-effect relationships are limited (though the authors do study the role of LMNA/LBR knockdown with their technologies).

Comments on revisions:

I have no additional comments. I appreciate the authors responding to my previous comments. I anticipate the datasets and concepts raised will be helpful to many investigators in the field.

Reviewer #1 (Public review):

Gray and colleagues describe the identification of Integrator complex subunit 12 (INTS12) as a contributor to HIV latency in two different cell lines and in cells isolated from the blood of people living with HIV. The authors employed a high-throughput CRISPR screening strategy to knock down genes and assess their relevance in maintaining HIV latency. They had used a similar approach in two previous studies, finding genes required for latency reactivation or genes preventing it and whose knockdown could enhance the latency-reactivating effect of the NFκB activator AZD5582. This work builds on the latter approach by testing the ability of gene knockdowns to complement the latency-reactivating effects of AZD5582 in combination with the BET inhibitor I-BET151. This drug combination was selected because it has been previously shown to display synergistic effects on latency reactivation.

The finding that INTS12 may play a role in HIV latency is novel, and the effect of its knock down in inducing HIV transcription in primary cells, albeit in only a subset of donors, is intriguing.

In this revised version, the authors have included new data and clarifications which help strengthen their conclusions.

Reviewer #1 (Public review):

Summary:

The study identifies two types of activation: one that is cue-triggered and non-specific to motion directions, and another that is specific to the exposed motion directions but occurs in a reversed manner. The finding that activity in the medial temporal lobe (MTL) preceded that in the visual cortex suggests that the visual cortex may serve as a platform for the manifestation of replay events, which potentially enhance visual sequence learning.

Evaluations:

Identifying the two types of activation after exposure to a sequence of motion directions is very interesting. The experimental design, procedures and analyses are solid. The findings are interesting and novel.

In the original submission, it was not immediately clear to me why the second type of activation was suggested to occur spontaneously. The procedural differences in the analyses that distinguished between the two types of activation need to be a little better clarified. However, this concern has been satisfactorily addressed in the revision.

Reviewer #1 (Public review):

Overall I found the approach taken by the authors to be clear and convincing. It is striking that the conclusions are similar to those obtained in a recent study using a different computational approach (finite state controllers), and lends confidence to the conclusions about the existence of an optimal memory duration. There are a few questions that could be expanded on in future studies:

(1) Spatial encoding requirements

The manuscript contrasts the approach taken here (reinforcement learning in a gridworld) with strategies that involve a "spatial map" such as infotaxis. However, the gridworld navigation algorithm has an implicit allocentric representation, since movement can be in one of four allocentric directions (up, down, left, right), and wind direction is defined in these coordinates. Future studies might ask if an agent can learn the strategy without a known wind direction if it can only go left/right/forward/back/turn (in egocentric coordinates). In discussing possible algorithms, and the features of this one, it might be helpful to distinguish (1) those that rely only on egocentric computations (run and tumble), (2) those that rely on a single direction cue such as wind direction, (3) those that rely on allocentric representations of direction, and (4) those that rely on a full spatial map of the environment.

(2) Recovery strategy on losing the plume

The authors explore several recovery strategies upon losing the plume, including backtracking, circling, and learned strategies, finding that a learned strategy is optimal. As insects show a variety of recovery strategies that can depend on the model of locomotion, it would be interesting in the future to explore under which conditions various recovery strategies are optimal and whether they can predict the strategies of real animals in different environments.

(3) Is there a minimal representation of odor for efficient navigation?

The authors suggest that the number of olfactory states could potentially be reduced to reduce computational cost. They show that reducing the number of olfactory states to 1 dramatically reduces performance. In the future it would be interesting to identify optimal internal representations of odor for navigation and to compare these to those found in real olfactory systems. Does the optimal number of odor and void states depend on the spatial structure of the turbulence as explored in Figure 5?

Reviewer #1 (Public review):

Summary:

In this elegant and thorough study, Sánchez-León et al. investigate the effects of tDCS on the firing of single cerebellar neurons in awake and anesthetized mice. They find heterogeneous responses depending on the orientation of the recorded Purkinje cell.

Strengths:

The paper is important in that it may well explain part of the controversial and ambiguous outcomes of various clinical trials. It is a well-written paper on a deeply analyzed dataset.

Weaknesses:

The sample size could be increased for some of the experiments.

Comments on revised version: They have not been able to increase the size of some of the critical experiments, but they have done additional statistics, which make me feel confident that the main conclusions are correct.

Reviewer #1 (Public review):

This study provides significant insights into the dynamics of attentional re-orienting within visual working memory, demonstrating how expected and unexpected memory tests influence attention focus and re-focus. The evidence supporting these conclusions is convincing, with the use of appropriate and validated methodologies, including behavioral measures, EEG, and eye tracking, that are in line with current state-of-the-art practices. This work will be of particular interest to cognitive neuroscientists studying attention and memory processes.

Thank you for the detailed revisions. I am pleased to see that the manuscript now effectively addresses every point I raised. The clarification between microsaccades and saccades greatly enhances transparency regarding the eye movement data. The inclusion of time-frequency plots and topographic maps for the working-memory test phase further improves the comprehensiveness of the alpha lateralization results, despite the relative lack of alpha effects at that stage. Moreover, the implementation of the Fractional Area Latency analysis successfully rules out amplitude-related confounds in the saccade bias latency measurements. Finally, the clear reporting of the statistical analyses for significant saccade bias further strengthens the reliability of the findings.

Overall, I appreciate the thorough and thoughtful response, and I believe that all my concerns have been successfully addressed.

Reviewer #1 (Public review):

The manuscript by Li et al., investigates metabolism independent role of nuclear IDH1 in chromatin state reprogramming during erythropoiesis. The authors describe accumulation and redistribution of histone H3K79me3, and downregulation of SIRT1, as a cause for dyserythropoiesis observed due to IDH1 deficiency. The authors studied the consequences of IDH1 knockdown, and targeted knockout of nuclear IDH1, in normal human erythroid cells derived from hematopoietic stem and progenitor cells and HUDEP2 cells respectively. They further correlate some of the observations such as nuclear localization of IDH1 and aberrant localization of histone modifications in MDS and AML patient samples harboring IDH1 mutations. These observations are overall intriguing from a mechanistic perspective and hold therapeutic significance. The authors have addressed the previous concerns sufficiently in the revised manuscript.

Reviewer #1 (Public review):

The manuscript investigates the role of the membrane-deforming cytoskeletal regulator protein Abba in cortical development and its potential implications for microcephaly. It is a valuable contribution to the understanding of Abba's role in cortical development. The strengths and weaknesses identified in the manuscript are outlined below:

Clinical Relevance:

The authors identified a patient with microcephaly and intellectual disability patient harboring a mutation in the Abba variant (R671W), adding a clinically relevant dimension to the study.

Mechanistic Insights:

The study offers valuable mechanistic insights into the development of microcephaly by elucidating the role of Abba in radial glial cell proliferation, radial fiber organization, and the migration of neuronal progenitors. The identification of Abba's involvement in the cleavage furrow during cell division, along with its interaction with Nedd9 and positive influence on RhoA activity, adds depth to our understanding of the molecular processes governing cortical development.

In Vivo Validation:

The overexpression of mutant Abba protein (R671W), which results in phenotypic similarities to Abba knockdown effects, supports the significance of Abba in cortical development.

Weaknesses:

The findings in the study suggest that heterozygous expression of the R671W variant may exert a dominant-negative effect on ABBA's role, disrupting normal brain development and leading to microcephaly and cognitive delay. However, evidence also points to a possible gain-of-function effect, as the mutation does not decrease RhoA activity or PH3 expression in vivo. Additionally, the impact of ABBA depletion on cell fate is not fully addressed. While abnormal progenitor accumulation in the ventricular and subventricular zones is observed, the transition of progenitors to neuroblasts and their ability to support neuroblast migration remains unclear. Impaired cleavage furrow ingression and disrupted Nedd9 and RhoA signaling could lead to structural abnormalities in radial glial progenitors, affecting their scaffold function and neuroblast progression. The manuscript lacks an exploration of the loss or decrease in interaction between Abba and NEDD9 in the case of the pathogenic patient-derived mutation in Abba. Furthermore, addressing the changes in localization and ineraction in for NEDD9 following over-expression of the mutant are important to further mehcanistically characterizxe this interaction in future studies. These gaps suggest the need for further exploration of ABBA's role in progenitor cell fate and neuroblast migration to clarify its mechanistic contributions to cortical development.

Reviewer #1 (Public review):

Summary:

This work by the Meng lab investigates the role of the proteins MARK2 and CAMSAP2 in the Golgi reorientation during cell polarisation and migration. They identified that both proteins interact together and that MARK2 phosphorylates CAMSAP2 on the residue S835. They show that the phosphorylation affects the localisation of CAMSAP2 at the Golgi apparatus and in turn influences the Golgi structure itself. Using the TurboID experimental approach, the author identified the USO1 protein as a protein that binds differentially to CAMSAP2 when it is itself phosphorylated at residue 835. Dissecting the molecular mechanisms controlling Golgi polarisation during cell migration is a highly complex but fundamental issue in cell biology and the author may have identified one important key step in this process.

Comments on latest version:

I thank the authors for the numerous revisions they have made to this manuscript, which have strengthened its clarity and overall quality. However, I must reiterate my initial concerns from the first review regarding the rigor of the data analysis, as certain methodological choices may lead to potential overinterpretation of the results.<br /> For instance, the low number of cells analyzed in the new Figure 1B (N = 3; 0 h: n = 28; 0.5 h: n = 23; 2 h: n = 20) indicates that fewer than 10 fixed cells have been quantified per replicate. Given the variability of the CAMSAP2 signal observed in Supplementary Figure 2, this sample size does not appear optimal for accurately capturing the complexity of CAMSAP2 localization within the cell population. Additionally, the Pearson's coefficients calculated between CAMSAP2 and GM130 in Figure 1B (approximately 0.4) do not align with those in Figure 3C, where the control condition shows values above 0.6. This discrepancy highlights the high variability of CAMSAP2 Golgi localization in the HT1080 cell population, which may not be adequately represented by the quantification of such a limited number of cells. If the population distribution were narrow, averaging only a few cells might be sufficient to achieve high statistical power; however, this does not appear to be the case, and a larger sample size is necessary.

Furthermore, to ensure a more robust analysis, SuperPlots displaying each biological replicate should be provided for all quantifications, and statistical analysis should be conducted using a t-test or ANOVA on the means of the three independent experiments rather than on the total number of cells, as the latter approach may influence statistical significance (for reference: jcb.202001064). This recommendation is relevant for Figures 1E, 3B, 3C, 4E, 4F, 6F, Sup1D, Sup3D, Sup3E, Sup3I, and Sup3G and should be implemented whenever possible.

For instance, in the new Figure 6F, the statistical difference (1 star) between Pearson's coefficients for HT1080 and siUSO1-2 conditions, both approaching 90, raises questions about whether this difference is truly substantial enough to support the claim that USO1 knockdown negatively impacts CAMSAP2 localization.

Publishing in journals such as eLife requires high standards in data analysis to ensure rigorous and reproducible scientific conclusions. In its present form, this manuscript does not yet meet those standards.

Additional comments:

Supplementary figure 2<br /> A) The video microscopy conditions are not described in the Materials and Methods section. It is unclear what type of microscope was used-was it a bright-field or confocal microscope? The images contain a significant amount of out-of-focus signal, making it difficult to accurately assess the extent of Golgi apparatus dispersion as described by the authors. If a confocal microscope was used, a Z-stack projection would be beneficial for quantifying this process.

Reviewer #1 (Public review):

Summary

In this manuscript, De La Forest Divonne et al. build a repertory of hemocytes from adult Pacific oysters combining scRNAseq data with cytologic and biochemical analyses. Three categories of hemocytes were described previously in this species (i.e. blast, hyalinocyte and granulocytes). Based on scRNAseq data, the authors identified 7 hemocyte clusters presenting distinct transcriptional signatures. Using Kegg pathway enrichment and RBGOA, the authors determined the main molecular features of the clusters. In parallel, using cytologic markers, the authors classified 7 populations of hemocytes (i.e. ML, H, BBL, ABL, SGC, BGC, and VC) presenting distinct sizes, nucleus sizes, acidophilic/basophilic, presence of pseudopods, cytoplasm/nucleus ratio and presence of granules. Then, the authors compared the phenotypic features with potential transcriptional signatures seen in the scRNAseq. The hemocytes were separated in a density gradient to enrich for specific subpopulations. The cell composition of each cell fraction was determined using cytologic markers and the cell fractions were analysed by quantitative PCR targeting major cluster markers (two per cluster). With this approach, the authors could assign cluster 7 to VC, cluster 2 to H, and cluster 3 to SGC. The other clusters did not show a clear association with this experimental approach. Using phagocytic assays, ROS, and copper monitoring, the authors showed that ML and SGC are phagocytic, ML produces ROS, and SGC and BGC accumulate copper. Then with the density gradient/qPCR approach, the authors identified the populations expressing anti-microbial peptides (ABL, BBL, and H). At last, the authors used Monocle to predict differentiation trajectories for each subgroup of hemocytes using cluster 4 as the progenitor subpopulation.

The manuscript provides a comprehensive characterisation of the diversity of circulating immune cells found in Pacific oysters.

Strengths

The combination of scRNAseq, cytologic markers and gradient based hemocyte sorting offers an integrative view of the immune cell diversity.<br /> Hemocytes represent a very plastic cell population that has key roles in homeostatic and challenged conditions. Grasping the molecular features of these cells at the single-cell level will help understand their biology.<br /> This type of study may help elucidate the diversification of immune cells in comparative studies and evolutionary immunology.

Weaknesses

Several figures show inconsistency leading to erroneous conclusions and some conclusions are poorly supported. Moreover, the manuscript remains highly descriptive with limited comparison with the available literature.

Reviewer #1 (Public review):

Summary:

There has been intense controversy over the generality of Hamilton's inclusive fitness rule for how evolution works on social behaviors. All generally agree that relatedness can be a game changer, for example allowing for otherwise unselectable altruistic behaviors when c < rb, where c is the fitness cost to the altruism, b is the fitness benefit to another, and r their relatedness. Many complications have been successfully incorporated into the theory, including different reproductive values and viscous population structures.

The controversy has centered on another dimension; Hamilton's original model was for additive fitness, but how does his result hold when fitnesses are non-additive? One approach has been not to worry about a general result but just find results for particular cases. A consistent finding is that the results depend on the frequency of the social allele - non-additivity causes frequency dependence that was absent in Hamilton's approach. Two other approaches derive from Queller via the Price equation. Queller 1 is to find forms like Hamilton's rule, but with additional terms that deal with non-additive interaction, each with an r-like population structure variable multiplied by a b-like fitness effect (Queller 1985). Queller 2 redefines the fitness effects c and b as partial regressions of the actor's and recipient's genes on fitness. This leaves Hamilton's rule intact, just with new definitions of c and b that depend on frequency.

Queller 2 is the version that has been most adopted by the inclusive fitness community along with assertions that Hamilton's rule in completely general. In this paper, van Veelen argues that Queller 1 is the correct approach. He derives a general form that Queller only hinted at. He does so within a more rigorous framework that puts both Price's equation and Hamilton's rule on firmer statistical ground. Within that framework, the Queller 2 approach is seen to be a statistical misspecification - it employs a model without interaction in cases that actually do have interaction. If we accept that this is a fatal flaw, the original version of Hamilton's rule is limited to linear fitness models, which might not be common.

Strengths:

While the approach is not entirely new, this paper provides a more rigorous approach and a more general result. It shows that both Queller 1 and Queller 2 are identities and give accurate results, because both are derived from the Price equation, which is an identity. So why prefer Queller 1? It identifies the misspecification issue with the Queller 2 approach and points out its consequences. For example, it will not give the minimum squared differences between the model and data. It does not separate the behavioral effects of the individuals from the population state (b and c become dependent on r and the population frequency).

The paper also shows how the same problems can apply to non-social traits. Epistasis is the non-additivity of effects of two genes within the individual. (So one wonders why have we not had a similarly fierce controversy over how we should treat epistasis?)

The paper is clearly written. Though somewhat repetitive, particularly in the long supplement, most of that repetition has the purpose of underscoring how the same points apply equally to a variety of different models.<br /> Finally, this may be a big step towards reconciliation in the inclusive fitness wars. Van Veelen has been one of the harshest critics of inclusive fitness, and now he is proposing a version of it.

Weaknesses:

van Veelen argues that the field essentially abandoned the Queller 1 approach after its publication. I think this is putting it too strongly - there have been a number of theoretical studies that incorporate extra terms with higher-order relatednesses. It is probably accurate to say that there has been relative neglect. But perhaps this is partly due to a perception that this approach is difficult to apply.

The model in this paper is quite elegant and helps clarify conceptual issues, but I wonder how practical it will turn out to be. In terms of modeling complicated cases, I suspect most practitioners will continue doing what they have been doing, for example using population genetics or adaptive dynamics, without worrying about neatly separating out a series of terms multiplying fitness coefficients and population structure coefficients.

For empirical studies, it is going to be hard to even try to estimate all those additional parameters. In reality, even the standard Hamilton's rule is rarely tested by trying to estimate all its parameters. Instead, it is commonly tested more indirectly, for example by comparative tests of the importance of relatedness. That of course would not distinguish between additive and non-additive models that both depend on relatedness, but it does test the core idea of kin selection. It will be interesting to see if van Veelen's approach stimulates new ways of exploring the real world.

Reviewer #2 (Public review):

In my previous review, I considered the contributions of the authors to be substantial because they have nearly doubled the number of genome sequences for chitons, and their newly sequenced genomes apparently are very well annotated. I would even extend these strengths now that I have had a chance to better review recent literature on marine animal genomes. Their contribution has helped make the chitons one of the best available marine taxa for comparative genomic studies. However, I still am unconvinced by the authors' claims to have demonstrated an unusually high rate of large-scale genome rearrangements across chitons. Their best argument seems to be comparisons drawn within a couple of similarly ancient bivalve lineages that were used to identify the conserved genomic regions in the first place, specifically the 20 molluscan linkage groups (MLGs). Perhaps it is safest to conclude that these MLGs are mostly conserved in conchiferans. Their main comparison with other molluscan classes is presented in tables 4 and 5 in the supplement, where they report a somewhat higher mean translocation rate for chitons (45.48) than for bivalves (41.10) or gastropods (41.87) but does this justify the implications of the title or the claims made in the Summary? I am not sure, partly because these summary tables are not made in a way that separates the gastropod or bivalve species listed into subtaxa separated by LCAs with estimated age, so the mean value across each class is not especially helpful. I still feel that the authors were not convincing in their arguments that chiton chromosomes have been subject to an unexpected history of rearrangement when contrasting quite ancient chitons lineages. This does not include impressive rearrangements documented for the likely geologically recent rearrangements seen within the genus, Acanthochitona, and separately within the subfamily Acanthopleurinae. These are quite impressive events that occurred recently within lineages of shallow-water chiton taxa, not deep still waters.

By the authors' estimates, some sequenced chiton genomes represent lineages that share a last common ancestor (LCA) as much as over 300 million years before present. This is like comparing a frog genome with a human genome. I suspect that the authors would agree that the pace of chiton genome rearrangements is not nearly as great as that observed for younger taxa such as mammals or particular insect orders known to have a history of genome shuffling. For example, according to Damas et al. (2022; https://www.pnas.org/doi/full/10.1073/pnas.2209139119) for comparisons within mammals, "94 inversions, 16 fissions, and 14 fusions that occurred over 53 My differentiated the therian from the descendent eutherian ancestor."

It is more interesting to me how the chiton genome rearrangements compare with other molluscan classes or for comparisons of other marine taxa genomes that share a similarly ancient LCA, but this is difficult to dig out of the authors' presentation. As far as I am aware, there are relatively few such comparisons of genome rearrangements available for marine animals. Attempting to do my own search for any comparison I could make, I noticed in that in a recent compilation of "high quality"* genomes (Martínez-Redondo 2024; https://doi.org/10.1093/gbe/evae235), this included genomes for 84 (mostly insect) arthropods, 67 vertebrates, 31 mollusks, 15 annelids, 12 nematodes, and 6 cnidarians, but the numbers drop off to 1-4 for many phyla, e.g., echinoderms. If there are really so few marine taxa available for comparison to the last 300 My of chiton genome rearrangements and fusions, then I would like to see a better presentation of the contrasts of the 20 molluscan linkage groups (MLGs) across molluscan classes. I found it very difficult to evaluate beyond the assertion that these are relatively conserved in two bivalve taxa. I remain unconvinced whether the amount of genome rearrangement observed by the authors for chitons is either especially rapid or slow. Certainly the genome browsers I have seen do not make it easy to compare, for example, marine gastropod or bivalve genomes (e.g., https://www.ncbi.nlm.nih.gov/cgv/9606 or https://genome.ucsc.edu/cgi-bin/hgGateway).

An unrelated topic that I also brought up in my earlier review is the ancestral reconstruction of molluscan chromosome numbers. The authors' explanation does nothing to justify how they ended up with an optimization of 20 for the ancestor of Mollusca. The outgroups included two annelids, Owenia [12 chromosomes] and Paraescarpia [14], plus the very distant chordate, Branchiostoma [19] (but the tunicate, Oikopleura has 6). Do the authors not understand that outgroups are critical for the optimization of character states at an ancestral node, with the most proximal outgroups being most important? How did they end up with an ancestral reconstruction of the chiton LCA with 16 chromosomes when there is no chiton with more than 13? Given the number of chromosomes in annelids, which is clearly the most proximal outgroups included with chromosome numbers available, it is more parsimonious to postulate that there was an increase in chromosome number for the conchiferan lineage. Related, they should have rooted that tree figure (Fig. 2) with the deuterostome, Branchiostoma, not a monophyletic grouping of all outgroups.

A recent study by Lewin et al. (2024; https://doi.org/10.1093/molbev/msae172) comparing annelid genomic rearrangements suggests to me that annelids probably have a more striking history of rearrangements than for chitons, but I found it difficult to evaluate. I do tend to agree with the overall conclusion of Lewin et al: "All animals with bilateral symmetry inherited a genome structure from their last common ancestor that has been highly conserved in some taxa but seemingly unconstrained in others." That is also my impression so far but the authors have done little to summarize what is known. One study that implies that at least deuterostomes have conserved elements of an ancestral chromosomal arrangement is provided by Lin et al. (2024; https://doi.org/10.1371/journal.pbio.3002661), who sequenced two genomes representing crown group hemichordates (LCA about 504 My).

Even if my general impression is wrong that the history of chiton genome rearrangement is not especially remarkable, or at least we still do not have a great idea of how rapid it is, I still think the authors could have done a better job of demonstrating their claims. This is important if they are going to make big claims about the pace of chiton chromosomal rearrangements. There is very little discussion of other similarly ancient marine animal taxa. I do not especially have a problem with excluding better known terrestrial mammalian or insect genomes as perhaps not a very relevant contrast, but am I supposed to be impressed with the comparisons made with bivalves and gastropods in Tables 4 and 5 of the Supplement? Where do the authors present a detailed comparison of how these estimates compare to conchiferans? Is this amount of genome rearrangement observed for chitons surprising for an extant taxon that has diversified for over 300 My? This is claimed in the title and summary of the manuscript as the take-home for the contribution, but I am left with the impression that there is too little attempt to justify that the pace across Polyplacophora (Neoloricata) is in any way remarkable. Apparently, there are few other lineages of marine taxa within which there are sequenced and well annotated genomes that can be compared, and this confounds the extent of conclusions that can be made.

* "high quality" genomes defined as follows by Martínez-Redondo (2024): "...we lowered the threshold used to consider a data set as high quality to 70% C + F (complete plus fragmented) BUSCO score (Manni et al. 2021), as the original 85% threshold was too restrictive when prioritizing a wide taxonomic sampling and the inclusion of biologically interesting species that are not widely studied."

Reviewer #1 (Public review):

Summary:

The study investigates protein-protein interactions (PPIs) within the nuage, a germline-specific organelle essential for piRNA biogenesis in Drosophila melanogaster, using AlphaFold2 to predict interactions among 20 nuage-localizing proteins. The authors identify five novel interaction candidates and experimentally validate three of them, including Spindle-E and Squash, through co-immunoprecipitation assays. They confirm the functional significance of these interactions by disrupting salt bridges at the Spn-E_Squ interface. The study further expands its scope to analyze approximately 430 oogenesis-related proteins, validating three additional interaction pairs. A comprehensive screen of around 12,000 Drosophila proteins for interactions with the key piRNA pathway player, Piwi, identifies 164 potential binding partners. Overall, the research demonstrates that in silico approaches using AlphaFold2 can link bioinformatics predictions with experimental validation, streamlining the identification of novel protein interactions and reducing the reliance on extensive experimental efforts.

Reviewer #1 (Public review):

Summary:

This manuscript investigates the role of the neck linker in coordinating the stepping cycles of the two heads of a kinesin-1 motor. Previous studies in the field showed that kinesin walks by alternating stepping of its heads, referred to as hand-over-hand. In this stepping mechanism, the front head of a kinesin dimer must remain bound until the rear head dissociates from the microtubule, moves forward, and rebinds to the tubulin on the plus-end side of the front head. There is a large body of work done to address this question. These studies all point to the central role of the 14 amino acid extension, a neck-linker, which connects the two heads to a common stalk, in coordination of kinesin motility. In a two-head-bound state, the motor domains (heads) are oriented parallel to the microtubule, but the neck linkers are orienting toward each other, thereby, breaking the symmetry in a homodimeric motor. In addition, the neck linkers are quite short, almost stretching to their near contour length to accommodate the microtubule binding of both heads. Previous studies pointed out that either the opposing orientation or the intramolecular tension of the neck linkers coordinate the stepping cycle.

However, we still do not know which step(s) in the chemo-mechanical cycle is controlled by the neck-linker to keep the two heads out of phase. The front head gating model postulates that ATP binding to the front head is gated until the rear head detaches from the microtubule. The rear head gating model proposes that the neck linker accelerates the detachment of the rear head from the microtubule. In this study, the authors use pre-steady state kinetics and smFRET to address this question. They measured ATP binding and microtubule detachment kinetics of kinesin's catalytic domain with neck linker constraints 1) imposed by disulfide crosslinking of the neck linker in monomeric kinesin in backward (rear head-like) and forward (front head-like) orientations, and 2) using the E236A-WT heterodimer to create a two-head microtubule-bound state with the mutant and WT heads occupying the rear and front positions respectively. They found that neck-linker conformation of the rear head reduces the ATP dissociation rate but has little effect on microtubule affinity. In comparison, the neck-linker conformation of the front head does not change ATP binding to the front head, but it reduces ATP-induced detachment of the front head, suggesting that a step after ATP binding (i.e. ATP hydrolysis or Pi release) is gated in the front head.

Significance:

I believe that this work will make an important contribution to the large body of literature focused on the mechanism of kinesin, which serves as an excellent model system to understand the kinetics and mechanics of a molecular motor. The mechanism proposed by the authors modifies the front-head gating model and is in agreement with recent structural work done on a kinesin dimer bound to a microtubule. Overall, the work is well performed, and the conclusions are well supported by the experimental data.

Reviewer #1 (Public review):

Summary:

Cell metabolism exhibits a well-known behavior in fast-growing cells, which employ seemingly wasteful fermentation to generate energy even in the presence of sufficient environmental oxygen. This phenomenon is known as Overflow Metabolism or the Warburg effect in cancer. It is present in a wide range of organisms, from bacteria and fungi to mammalian cells.

In this work, starting with a metabolic network for Escherichia coli based on sets of carbon sources, and using a corresponding coarse-grained model, the author applies some well-based approximations from the literature and algebraic manipulations. These are used to successfully explain the origins of Overflow Metabolism, both qualitatively and quantitatively, by comparing the results with E. coli experimental data.

By modeling the proteome energy efficiencies for respiration and fermentation, the study shows that these parameters are dependent on the carbon source quality constants K_i (p.115 and 116). It is demonstrated that as the environment becomes richer, the optimal solution for proteome energy efficiency shifts from respiration to fermentation. This shift occurs at a critical parameter value K_A(C).<br /> This counterintuitive result qualitatively explains Overflow Metabolism.

Quantitative agreement is achieved through the analysis of the heterogeneity of the metabolic status within a cell population. By introducing heterogeneity, the critical growth rate is assumed to follow a Gaussian distribution over the cell population, resulting in accordance with experimental data for E. coli. Overflow metabolism is explained by considering optimal protein allocation and cell heterogeneity.

The obtained model is extensively tested through perturbations: 1) Introduction of overexpression of useless proteins; 2) Studying energy dissipation; 3) Analysis of the impact of translation inhibition with different sub-lethal doses of chloramphenicol on Escherichia coli; 4) Alteration of nutrient categories of carbon sources using pyruvate. All model perturbations results are corroborated by E. coli experimental results.

Strengths:

In this work, the author effectively uses modeling techniques typical of Physics to address complex problems in Biology, demonstrating the potential of interdisciplinary approaches to yield novel insights. The use of Escherichia coli as a model organism ensures that the assumptions and approximations are well-supported in existing literature. The model is convincingly constructed and aligns well with experimental data, lending credibility to the findings. In this version, the extension of results from bacteria to yeast and cancer is substantiated by a literature base, suggesting that these findings may have broad implications for understanding diverse biological systems.

Weaknesses:

The author explores the generalization of their results from bacteria to cancer cells and yeast, adapting the metabolic network and coarse-grained model accordingly. In the previous version this generalization was not completely supported by references and data from the literature. This drawback, however, has been treated in this current version, where the authors discuss in much more detail and give references supporting this generalization.

Comments on revisions:

I have no specific comments for the authors. My previous comments were all addressed, discussed and explained.

Reviewer #1 (Public review):

Summary:

This paper presents a method for reconstructing videos from mouse visual cortex neuronal activity using a state-of-the-art dynamic neural encoding model. The authors achieve high-quality reconstructions of 10-second movies at 30 Hz from two-photon calcium imaging data, reporting a 2-fold increase in pixel-by-pixel correlation compared to previous methods. They identify key factors for successful reconstruction including the number of recorded neurons and model ensembling techniques.

Strengths:

(1) A comprehensive technical approach combining state-of-the-art neural encoding models with gradient-based optimization for video reconstruction.

(2) Thorough evaluation of reconstruction quality across different spatial and temporal frequencies using both natural videos and synthetic stimuli.

(3) Detailed analysis of factors affecting reconstruction quality, including population size and model ensembling effects.

(4) Clear methodology presentation with well-documented algorithms and reproducible code.

(5) Potential applications for investigating visual processing phenomena like predictive coding and perceptual learning.

Weaknesses:

The main metric of success (pixel correlation) may not be the most meaningful measure of reconstruction quality:

High correlation may not capture perceptually relevant features.

Different stimuli producing similar neural responses could have low pixel correlations The paper doesn't fully justify why high pixel correlation is a valuable goal

Comparison to previous work (Yoshida et al.) has methodological concerns: Direct comparison of correlation values across different datasets may be misleading; Large differences in the number of recorded neurons (10x more in the current study); Different stimulus types (dynamic vs static) make comparison difficult; No implementation of previous methods on the current dataset or vice versa.

Limited exploration of how the reconstruction method could provide insights into neural coding principles beyond demonstrating technical capability.

The claim that "stimulus reconstruction promises a more generalizable approach" (line 180) is not well supported with concrete examples or evidence.

The paper would benefit from addressing how the method handles cases where different stimuli produce similar neural responses, particularly for high-speed moving stimuli where phase differences might be lost in calcium imaging temporal resolution.

Reviewer #1 (Public review):

Summary:

This study is built on the emerging knowledge of trained immunity, where innate immune cells exhibit enhanced inflammatory responses upon being challenged by a prior insult. Trained immunity is now a very fast-evolving field and has been explored in diverse disease conditions and immune cell types. Earhart and the team approached the topic from a novel angle and were the first to explore a potential link to the complement system.

The study focused on the central complement protein C3 and investigated how its signalling may modulate immune training in alveolar macrophages. The authors first performed in vivo experiments in C57BL mouse models to observe the presence of enhanced inflammation and C3a in BAL fluid following immune training. These changes were then compared with those from C3-deficient mice, which confirmed the involvement of C3a. This trained immunity was further validated in ex vivo experiments using primary alveolar macrophage, which was blunted in C3-deficiency, and, intriguingly, rescued by adding exogenous C3 protein, but not C3a. The genetic-based findings were supported by pharmacological experiments using the C3aR antagonist SB290157. Mechanistically, transcriptomic analyses suggested the involvement of metabolism-linked, particularly glycolytic, genes, which was in agreement with an upregulation of glycolytic flux in WT but not C3-deficient macrophages.

Collectively, these data suggest that C3, possibly through engaging with C3aR, contributes to trained immunity in alveolar macrophages.

Strengths:

The conclusions reached were well supported by in vivo and ex vivo experiments, encompassing both genetic-knockout animal models and pharmacological tools.

The transcriptomic and cell metabolism studies provided valuable mechanistic insights.

Weaknesses:

For the in vivo experiments, the histopathological and other inflammatory markers (Figure 1) were not directly linked to alveolar macrophages by experimental evidence. Other innate immune cells (eg. dendritic cells, neutrophils) and endothelial cells could also be involved in immune training and contribute to the pathological outcomes. These cells were not examined or mentioned in the study.

For the ex vivo experiments assessing immune training in alveolar macrophages, only the release of selected inflammatory factors were measured. Macrophage activities constitute multiple aspects (e.g. phagocytosis, ROS production, microbe killing), which should also be considered to better depict the effect of trained immunity.

The proposed mechanism of C3 getting cleaved intracellularly and then binding to lysosomal C3aR needs to be further supported by experimental evidence.

There was an absence of any validation in human-based models.

Reviewer #1 (Public review):

Summary:

The authors aimed to characterize neurocomputational signals underlying interpersonal guilt and responsibility. Across two studies, one behavioral and one fMRI, participants made risky economic decisions for themselves or for themselves and a partner; they also experienced a condition in which the partners made decisions for themselves and the participant. The authors also assessed momentary happiness intermittently between choices in the task. Briefly, results demonstrated that participants' self-reported happiness decreased after disadvantageous outcomes for themselves and when both they and their partner were affected; this effect was exacerbated when participants were responsible for their partner's low outcome, rather than the opposite, reflecting experienced guilt. Consistent with previous work, BOLD signals in the insula correlated with experienced guilt, and insula-right IFG connectivity was enhanced when participants made risky choices for themselves and safe choices for themselves and a partner.

Strengths:

This study implements an interesting approach to investigating guilt and responsibility; the paradigm in particular is well-suited to approach this question, offering participants the chance to make risky v. safe choices that affect both themselves and others. I appreciate the assessment of happiness as a metric for assessing guilt across the different task/outcome conditions, as well as the implementation of both computational models and fMRI.

Weaknesses:

In spite of the overall strengths of the study, I think there are a few areas in which the paper fell a bit short and could be improved.

(1) While the framing and goal of this study was to investigate guilt and felt responsibility, the task implemented - a risky choice task with social conditions - has been conducted in similar ways in past research that were not addressed here. The novelty of this study would appear to be the additional happiness assessments, but it would be helpful to consider the changes noted in risk-taking behavior in the context of additional studies that have investigated changes in risky economic choice in social contexts (e.g., Arioli et al., 2023 Cerebral Cortex; Fareri et al., 2022 Scientific Reports).

(2) The authors note they assessed changes in risk preferences between social and solo conditions in two ways - by calculating a 'risk premium' and then by estimating rho from an expected utility model. I am curious why the authors took both approaches (this did not seem clearly justified, though I apologize if I missed it). Relatedly, in the expected utility approach, the authors report that since 'the number of these types of trials varied across participants', they 'only obtained reliable estimates for [gain and loss] trials in some participants' - in study 1, 22 participants had unreliable estimates and in study 2, 28 participants had unreliable estimates. Because of this, and because the task itself only had 20 gains, 20 losses, and 20 mixed gambles per condition, I wonder if the authors can comment on how interpretable these findings are in the Discussion. Other work investigating loss aversion has implemented larger numbers of trials to mitigate the potential for unreliable estimates (e.g., Sokol-Hessner et al., 2009).

(3) One thing seemingly not addressed in the Discussion is the fact that the behavioral effect did not replicate significantly in study 2.

(4) Regarding the computational models, the authors suggest that the Reponsibility and Responsibility Redux models provided the best fit, but they are claiming this based on separate metrics (e.g., in study 1, the redux model had the lowest AIC, but the responsibility only model had the highest R^2; additionally, the basic model had the lowest BIC). I am wondering if the authors considered conducting a direct model comparison to statistically compare model fits.

(5) In the reporting of imaging results, the authors report in a univariate analysis that a small cluster in the left anterior insula showed a stronger response to low outcomes for the partner as a result of participant choice rather than from partner choice. It then seems as though the authors performed small volume correction on this cluster to see whether it survived. If that is accurate, then I would suggest that this result be removed because it is not recommended to perform SVC where the volume is defined based on a result from the same whole-brain analysis (i.e., it should be done a priori).

Reviewer #1 (Public review):

Summary:

In this article, the authors set out to understand how people's food decisions change when they are hungry vs. sated. To do so, they used an eye-tracking experiment where participants chose between two food options, each presented as a picture of the food plus its "Nutri-Score". In both conditions, participants fasted overnight, but in the sated condition, participants received a protein shake before making their decisions. The authors find that participants in the hungry condition were more likely to choose the tastier option. Using variants of the attentional drift-diffusion model, they further find that the best-fitting model has different attentional discounts on the taste and health attributes and that the attentional discount on the health information was larger for the hungry participants.

Strengths:

The article has many strengths. It uses a food-choice paradigm that is established in neuroeconomics. The experiment uses real foods, with accurate nutrition information, and incentivized choices. The experimental manipulation is elegant in its simplicity - administering a high-calorie protein shake. It is also commendable that the study was within-participant. The experiment also includes hunger and mood ratings to confirm the effectiveness of the manipulation. The modeling work is impressive in its rigor - the authors test 9 different variants of the DDM, including recent models like the mtDDM and maaDDM, as well as some completely new variants (maaDDM2phi and 2phisp). The model fits decisively favor the maaDDM2phi.

Weaknesses:

First, in examining some of the model fits in the supplements, e.g. Figures S9, S10, S12, S13, it looks like the "taste weight" parameter is being constrained below 1. Theoretically, I understand why the authors imposed this constraint, but it might be unfairly penalizing these models. In theory, the taste weight could go above 1 if participants had a negative weight on health. This might occur if there is a negative correlation between attractiveness and health and the taste ratings do not completely account for attractiveness. I would recommend eliminating this constraint on the taste weight.

Second, I'm not sure about the mediation model. Why should hunger change the dwell time on the chosen item? Shouldn't this model instead focus on the dwell time on the tasty option?

Third, while I do appreciate the within-participant design, it does raise a small concern about potential demand effects. I think the authors' results would be more compelling if they replicated when only analyzing the first session from each participant. Along similar lines, it would be useful to know whether there was any effect of order.

Fourth, the authors report that tasty choices are faster. Is this a systematic effect, or simply due to the fact that tasty options were generally more attractive? To put this in the context of the DDM, was there a constant in the drift rate, and did this constant favor the tasty option?

Fifth, I wonder about the mtDDM. What are the units on the "starting time" parameters? Seconds? These seem like minuscule effects. Do they align with the eye-tracking data? In other words, which attributes did participants look at first? Was there a correlation between the first fixations and the relative starting times? If not, does that cast doubt on the mtDDM fits? Did the authors do any parameter recovery exercises on the mtDDM?

Reviewer #1 (Public review):

Summary:

Mancl et al. present cryo-EM structures of the Insulin Degrading Enzyme (IDE) dimer and characterize its conformational dynamics by integrating structures with SEC-SAXS, enzymatic activity assays, and all-atom molecular dynamics (MD) simulations. They present five cryo-EM structures of the IDE dimer at 3.0-4.1 Å resolution, obtained with one of its substrates, insulin, added to IDE in a 1:2 ratio. The study identified R668 as a key residue mediating the open-close transition of IDE, a finding supported by simulations and experimental data. The work offers a refined model for how IDE recognizes and degrades amyloid peptides, incorporating the roles of IDE-N rotation and charge-swapping events at the IDE-N/C interface.

Strengths:

The study by Mancl et al. uses a combination of experimental (cryoEM, SEC-SAXS, enzymatic assays) and computational (MD simulations, multibody analysis, 3DVA) techniques to provide a comprehensive characterization of IDE dynamics. The identification of R668 as a key residue mediating the open-to-close transition of IDE is a novel finding, supported by both simulations and experimental data presented in the manuscript. The work offers a refined model for how IDE recognizes and degrades amyloid peptides, incorporating the roles of IDE-N rotation and charge-swapping events at the IDE-N/C interface. The study identifies the structural basis and key residues for IDE dynamics that were not revealed by static structures.

Weaknesses:

Based on MD simulations and enzymatic assays of IDE, the authors claim that the R668A mutation in IDE affects the conformational dynamics governing the open-closed transition, which leads to altered substrate binding and catalysis. The functional importance of R668 would be substantiated by enzymatic assays that included some of the other known substrates of IDE than insulin such as amylin and glucagon.

It is unclear to what extent the force field (FF) employed in the MD simulations favors secondary structures and if the lack of any observed structural changes within the IDE domains in the simulations - which is taken to suggest that the domains behave as rigid bodies - stems from bias by the FF.

Reviewer #1 (Public review):

This work employs both in vitro and in vivo/transplant methods to investigate the contribution of BDNF/TrkB signaling to enhancing differentiation and dentin-repair capabilities of dental pulp stem cells in the context of exposure to a variety of inflammatory cytokines. A particular emphasis of the approach is the employment of dental pulp stem cells in which BDNF expression has been enhanced using CRISPR technology. Transplantation of such cells is said to improve dentin regeneration in a mouse model of tooth decay.

The study provides several interesting findings, including demonstrating that exposure to several cytokines/inflammatory agents increases the quantity of (activated) phospho-Trk B in dental pulp stem cells.

However, a variety of technical issues weaken support for the major conclusions offered by the authors. These technical issues include the following:

(1) It remains unclear exactly how the cytokines tested affect BDNF/TrkB signaling. For example, in Figure 1C, TNF-alpha increases TrkB and phospho-TrkB immunoreactivity to the same degree, suggesting that the cytokine promotes TrkB abundance without stimulating pathways that activate TrkB, whereas in Figure 2D, TNF-alpha has little effect on the abundance of TrkB, while increasing phospho-TrkB, suggesting that it affects TrkB activation and not TrkB abundance.

(2) I find the histological images in Figure 3 to be difficult to interpret. I would have imagined that DAPI nuclear stains would reveal the odontoblast layer, but this is not apparent. An adjacent section labeled with conventional histological stains would be helpful here. Others have described Stro-1 as a stem cell marker that is expressed on a minority of cells associated with vasculature in the dental pulp, but in the images in Figure 3, Stro-l label is essentially co-distributed with DAPI, in both control and injured teeth, indicating that it is expressed in nearly all cells. Although the authors state that the Stro-1-positive cells are associated with vasculature, but I see no evidence that is true.

(3) The data presented convincingly demonstrate that they have elevated BDNF expression in their dental pulp stem cells using a CRISPR-based approach I have a number of questions about these findings. Firstly, nowhere in the paper do they describe the nature of the CRISPR plasmid they are transiently transfecting. Some published methods delete segments of the BDNF 3'-UTR while others use an inactivated Cas9 to position an active transactivator to sequences in the BDNF promoter. If it is the latter approach, transient transfection will yield transient increases in BDNF expression. Also, as BDNF employs multiple promoters, it would be helpful to know which promoter sequence is targeted, and finally, knowing the identity of the guide RNAs would allow assessment for the potential of off-target effects I am guessing that the investigators employ a commercially obtained system from Santa Cruz, but nowhere is this mentioned. Please provide this information.

(4) Another question left unresolved is whether their approach elevated BDNF, proBDNF, or both. Their 28 kDa western blot band apparently represents proBDNF exclusively, with no mature BDNF apparent, yet only mature BDNF effectively activates TrkB receptors. On the other hand, proBDNF preferentially activates p75NTR receptors. The present paper never mentions p75NTR, which is a significant omission, since other investigators have demonstrated that p75NTR controls odontoblast differentiation.

(5) In any case, no evidence is presented to support the conclusion that the artificially elevated BDNF expression has any effect on the capability of the dental pulp stem cells to promote dentin regeneration. The results shown in Figures 4 and 5 compare dentin regeneration with BDNF-over-expressing stem cells with results lacking any stem cell transplantation. A suitable control is required to allow any conclusion about the benefit of over-expressing BDNF.

(6) Whether increased BDNF expression is beneficial or not, the evidence that the BDNF-overexpressing dental pulp stem cells promote dentin regeneration is somewhat weak. The data presented indicate that the cells increase dentin density by only 6%. The text and figure legend disagree on whether the p-value for this effect is 0.05 or 0.01. In either case, nowhere is the value of N for this statistic mentioned, leaving uncertainty about whether the effect is real.

(7) The final set of experiments applies transcriptomic analysis to address the mechanisms mediating function differences in dental pulp stem cell behavior. Unfortunately, while the Abstract indicates " we conducted transcriptomic profiling of TNFα-treated DPSCs, both with and without TrkB antagonist CTX-B" that does not describe the experiment described, which compared the transcriptome of control cells with cells simultaneously exposed to TNF-alpha and CTX-B. Since CTX-B blocks the functional response of cells to TNF-alpha, I don't understand how any useful interpretation can be attached to the data without controls for the effect of TNF alone and CTX-B alone.

Reviewer #1 (Public review):

Summary:

In this study, authors utilized in situ cryo-electron tomography (cryo-ET) to uncover the native thylakoid architecture of spinach chloroplasts and mapped the molecular organization of these thylakoids with single-molecule resolution. The obtained images show the detailed ultrastructural features of grana membranes and highlight interactions between thylakoids and plastoglobules. Interestingly, despite the distinct three-dimensional architecture of vascular plant thylakoids, their molecular organization closely resembles that of green algae. The pronounced lateral segregation of PSII and PSI was observed at the interface between appressed and non-appressed thylakoid regions, without evidence of a specialized grana margin zone where these complexes might intermix. Furthermore, unlike isolated thylakoid membranes, photosystem II (PSII) did not form a semi-crystalline array and distributed uniformly within the membrane plane and across stacked grana membranes in intact chloroplasts. Based on the above observations, the authors propose a simplified two-domain model for the molecular organization of thylakoid membranes that can apply to both green algae and vascular plants. This study suggests that the general understanding of the functional separation of thylakoid membranes in vascular plants should be reconsidered.

Strengths:

By employing and refining AI-driven computational tools for the automated segmentation of membranes and identification of membrane proteins, this study successfully quantifies the spatial organization of photosynthetic complexes both within individual thylakoid membranes and across neighboring stacked membranes.

Weaknesses:

This study's weakness is that it requires the use of chloroplasts isolated from leaves and the need to freeze them on a grid for observation, so it is unclear to what extent the observations reflect physiological conditions. In particular, the mode of existence of the thylakoid membrane complexes seems to be strongly influenced by the physicochemical environment surrounding the membranes, as indicated by the different distribution of PSII between intact chloroplasts and those with ruptured envelope membranes.

Reviewer #1 (Public review):

Summary:

This paper proposes a new set of local synaptic plasticity rules that differs from classic rules in two regards: First, working under the assumption that signals coming into synapses change smoothly over time and thus have temporal correlations such that immediate activity is positively correlated with subsequent activity, it proposes both fast plasticity that immediately corrects errors as well as slower plasticity. Second, it derives these rules from optimal, Bayesian control theory principles that, even without the fast component of plasticity, are shown to provide more accurate performance than classic, non-Bayesian plasticity rules. As a proof of principle, it applies these to a simple cerebellar learning example that demonstrates how the proposed rules lead to learning performance that exceeds that achieved with classic cerebellar learning rules. The work also provides a potential normative explanation for post-climbing fiber spike pauses in Purkinje cell firing and proposes testable predictions for cerebellar experiments. Overall, I found the idea to be compelling and potentially broadly applicable across many systems. Further, I thought the work was a rare, very beautiful display of the application of optimal control theory to fundamental problems in neuroscience. My comments are all relatively minor and more expressions of interest than criticism.

Comments:

(1) The algorithm assumes, reasonably, that inputs are relatively smooth. However, I was wondering if this could make additional experimental predictions for the system being exceptionally noisy or otherwise behaving in signature ways if one were able to train a real biological network to match a rapidly changing or non-smooth function that does not align with the underlying assumptions of the model.

(2) The algorithm assumes that one can, to a good approximation, replace individual input rates by their across-synapse average. How sensitive is the learning to this assumption, as one might imagine scenarios where a neuron is sensitive to different inputs for different tasks or contexts so that a grand average might not be correct? Or, the functional number of inputs driving the output might be relatively low or otherwise highly fluctuating and less easily averaged over.

(3) On the cerebellar example, it is nice that the Bayesian example provides a narrower PF-CF interval for plasticity than the classical rules, but the window is not nearly as narrow as the Suvrathan et al. 2016 paper cited by the authors. Maybe this is something special about that system having well-defined, delayed feedback, but (optional) further comments or insights would be welcome if available.

(4) In the discussion, I appreciated the comparison with the Deneve work which has fast and slow feedback components. I was curious whether, although non-local, there were also conceptual similarities with FORCE learning in which there is also an immediate correction of activity through fast changing of synaptic weights, which then aids the slow long-term learning of synaptic weights.

Reviewer #1 (Public review):

The ventral nerve cord (VNC) of organisms like Drosophila is an invaluable model for studying neural development and organisation in more complex organisms. Its well-defined structure allows researchers to investigate how neurons develop, differentiate, and organise into functional circuits. As a critical central nervous system component, the VNC plays a key role in controlling motor functions, reflexes, and sensory integration.

Particularly relevant to this work, the VNC provides a unique opportunity to explore neuronal hemilineages - groups of neurons that share molecular, genetic, and functional identities. Understanding these hemilineages is crucial for elucidating how neurons cooperate to form specialized circuits, essential for comprehending normal brain function and dysfunction.

A significant challenge in the field has been the lack of developmentally stable, hemilineage-specific driver lines that enable precise tracking and measurement of individual VNC hemilineages. The authors address this need by generating and validating a comprehensive, lineage-specific split-GAL4 driver library.

Strengths and weaknesses

The authors select new marker genes for hemilineages from previously published single-cell data of the VNC. They generate and validate specific and temporally stable lines for almost all the hemilineages in the VNC. They successfully achieved their aims, and their results support their conclusions. This will be a valuable resource for investigating neural circuit formation and function.

Reviewer #1 (Public review):

Summary:

The authors introduce ImPaqT, a modular toolkit for zebrafish transgenesis, utilizing the Golden Gate cloning approach with the rare-cutting enzyme PaqCI. The toolkit is designed to streamline the construction of transgenes with broad applications, particularly for immunological studies. By providing a versatile platform, the study aims to address limitations in generating plasmids for zebrafish transgenesis.

Strengths:

The ImPaqT toolkit offers a modular method for constructing transgenes tailored to specific research needs. By employing Golden Gate cloning, the system simplifies the assembly process, allowing seamless integration of multiple genetic elements while maintaining scalability for complex designs. The toolkit's utility is evident from its inclusion of a diverse range of promoters, genetic tools, and fluorescent markers, which cater to both immunological and general zebrafish research needs. Furthermore, the modular design ensures expandability, enabling researchers to customize constructs for diverse experimental designs. The validation provided in the manuscript is solid, demonstrating the successful generation of several functional transgenic lines. These examples highlight the toolkit's efficacy, particularly for immune-focused applications.

Weaknesses:

While the toolkit's technical capabilities are well-demonstrated, there are several areas where additional validation and examples could enhance its impact. One limitation is the lack of data showing whether the toolkit can be directly used for rapid cloning and testing of enhancers or promoters, particularly cloning them directly from PCR using PaqCI overhangs without needing an entry vector. Similarly, the feasibility of cloning genes directly from PCR products into the system is not demonstrated, which would significantly increase the utility for researchers working with genomic elements.

The authors discuss potential applications such as using the toolkit for tissue-specific knockout applications by assembling CRISPR/Cas9 gRNA constructs. However, they do not demonstrate the cloning of short fragments, such as gRNA sequences downstream of a U6 promoter, which would be an important proof-of-concept to validate these applications. Furthermore, while the manuscript focuses on macrophage-specific promoters, the widely used mpeg1.1 promoter is not included or tested, which limits the toolkit's appeal for researchers studying macrophages and microglia.

Another potential limitation is the handling of sequences containing PaqCI recognition sites. Although the authors discuss domestication to remove these sites, a demonstration of cloning strategies for such cases or alternative methods to address these challenges would provide practical guidance for users.