Reviewer #2 (Public review):

Summary:

Stephens et al. present a comprehensive study of TMEM16-members via coarse-grained MD simulations (CGMD). They particularly focus on the scramblase ability of these proteins and aim to characterize the "energetics of scrambling". Through their simulations, the authors interestingly relate protein conformational states to the membrane's thickness and link those to the scrambling ability of TMEM members, measured as the trespassing tendency of lipids across leaflets. They validate their simulation with a direct qualitative comparison with Cryo-EM maps.

Strengths:

The study demonstrates an efficient use of CGMD simulations to explore lipid scrambling across various TMEM16 family members. By leveraging this approach, the authors are able to bypass some of the sampling limitations inherent in all-atom simulations, providing a more comprehensive and high-throughput analysis of lipid scrambling. Their comparison of different protein conformations, including open and closed groove states, presents a detailed exploration of how structural features influence scrambling activity, adding significant value to the field. A key contribution of this study is the finding that groove dilation plays a central role in lipid scrambling. The authors observe that for scrambling-competent TMEM16 structures, there is substantial membrane thinning and groove widening. The open Ca2+-bound nhTMEM16 structure (PDB ID 4WIS) was identified as the fastest scrambler in their simulations, with scrambling rates as high as 24.4 {plus minus} 5.2 events per μs. This structure also shows significant membrane thinning (up to 18 Å), which supports the hypothesis that groove dilation lowers the energetic barrier for lipid translocation, facilitating scrambling.

The study also establishes a correlation between structural features and scrambling competence, though analyses often lack statistical robustness and quantitative comparisons. The simulations differentiate between open and closed conformations of TMEM16 structures, with open-groove structures exhibiting increased scrambling activity, while closed-groove structures do not. This finding aligns with previous research suggesting that the structural dynamics of the groove are critical for scrambling. Furthermore, the authors explore how the physical dimensions of the groove qualitatively correlate with observed scrambling rates. For example, TMEM16K induces increased membrane thinning in its open form, suggesting that membrane properties, along with structural features, play a role in modulating scrambling activity.

Another significant finding is the concept of "out-of-the-groove" scrambling, where lipid translocation occurs outside the protein's groove. This observation introduces the possibility of alternate scrambling mechanisms that do not follow the traditional "credit-card model" of groove-mediated lipid scrambling. In their simulations, the authors note that these out-of-the-groove events predominantly occur at the dimer interface between TM3 and TM10, especially in mammalian TMEM16 structures. While these events were not observed in fungal TMEM16s, they may provide insight into Ca2+-independent scrambling mechanisms, as they do not require groove opening.

Weaknesses:

A significant challenge of the study is the discrepancy between the scrambling rates observed in CGMD simulations and those reported experimentally. Despite the authors' claim that the rates are in line experimentally, the observed differences can mean large energetic discrepancies in describing scrambling (larger than 1kT barrier in reality). For instance, the authors report scrambling rates of 10.7 events per μs for TMEM16F and 24.4 events per μs for nhTMEM16, which are several orders of magnitude faster than experimental rates. While the authors suggest that this discrepancy could be due to the Martini 3 force field's faster diffusion dynamics, this explanation does not fully account for the large difference in rates. A more thorough discussion on how the choice of force field and simulation parameters influence the results, and how these discrepancies can be reconciled with experimental data, would strengthen the conclusions. Likewise, rate calculations in the study are based on 10 μs simulations, while experimental scrambling rates occur over seconds. This timescale discrepancy limits the study's accuracy, as the simulations may not capture rare or slow scrambling events that are observed experimentally and therefore might underestimate the kinetics of scrambling. It's however important to recognize that it's hard (borderline unachievable) to pinpoint reasonable kinetics for systems like this using the currently available computational power and force field accuracy. The faster diffusion in simulations may lead to overestimated scrambling rates, making the simulation results less comparable to real-world observations. Thus, I would therefore read the findings qualitatively rather than quantitatively. An interesting observation is the asymmetry observed in the scrambling rates of the two monomers. Since MARTINI is known to be limited in correctly sampling protein dynamics, the authors - in order to preserve the fold - have applied a strong (500 kJ mol-1 nm-2) elastic network. However, I am wondering how the ENM applies across the dimer and if any asymmetry can be noticed in the application of restraints for each monomer and at the dimer interface. How can this have potentially biased the asymmetry in the scrambling rates observed between the monomers? Is this artificially obtained from restraining the initial structure, or is the asymmetry somehow gatekeeping the scrambling mechanism to occur majorly across a single monomer? Answering this question would have far-reaching implications to better describe the mechanism of scrambling.

Notably, the manuscript does not explore the impact of membrane composition on scrambling rates. While the authors use a specific lipid composition (DOPC) in their simulations, they acknowledge that membrane composition can influence scrambling activity. However, the study does not explore how different lipids or membrane environments or varying membrane curvature and tension, could alter scrambling behaviour. I appreciate that this might have been beyond the scope of this particular paper and the authors plan to further chase these questions, as this work sets a strong protocol for this study. Contextualizing scrambling in the context of membrane composition is particularly relevant since the authors note that TMEM16K's scrambling rate increases tenfold in thinner membranes, suggesting that lipid-specific or membrane-thickness-dependent effects could play a role.

Reviewer #2 (Public review):

Summary:

Building upon the group's previous work, this study used a 3-day threat acquisition, extinction, recall, reextinction, and reacquisition paradigm with 7T imaging to probe the mechanism by which the cerebellum contributes to fear extinction learning. The authors hypothesise this may be via its connection to the VTA, a known modulator of fear extinction due to its role in reward processing. Using complementary analysis methods, the authors demonstrate that activity with the cerebellum, DNC, and VTA is modulated by predictions about the occurrence of the US, which shows regional specificity. They show trend-level evidence that there is increased functional connectivity between the cerebellum and VTA during all phases of the paradigm with unexpected omissions. They also present a DCM which indicates that the cerebellum could positively modulate VTA activity during extinction learning. This study adds to a growing literature supporting the role of the historically overlooked cerebellum in the control of emotions and suggests that an interaction between the cerebellum and VTA should be considered in the existing model of the fear extinction network.

Strengths:

The authors address their research question using a number of complementary methods, including parametric modulation by model-derived expectation parameters, PPI, and DCM, in a logical and easily understood way. I feel the authors provide a balanced interpretation of their findings, presenting numerous interpretations and offering insight with regard to reward vs attention or unsigned prediction errors and the directionality of the interaction they identify. The manuscript is a timely addition to growing literature highlighting the role of the cerebellum in fear conditioning, and emotion generation and regulation more generally.

Weaknesses:

Subjective and skin conductance responses do not completely support the success of the learning paradigm. For example, CS+/CS- differentiation in both domains persisted after extinction training. I do not feel that this negates the findings of this manuscript, though it raises questions about the parametric modulators used, and the interpretation of the neural mechanisms proposed if they do not strongly relate to updated subjective appraisals (the goal of extinction therapy). My interpretation of the manuscript suggests there are some key results based upon contrasts that have as few as three events; I am a little unsure about the power and reliability of these effects, though I await author clarification on this matter. There are a number of unaddressed deviations from the pre-registered protocol that I have asked the authors to elaborate upon.

Reviewer #2 (Public review):

Summary:

The authors use a genetically encoded fluorescent sensor, GRABNE, to measure NE dynamics in the dorsal hippocampus of mice in response to multiple behavioral manipulations. A non-linear model and regression were used to quantitatively assess the contribution of multiple behavioral covariates to changes in NE signaling, with the result that NE signal dynamics were best predicted by time from event transitions, with the signal exponentially decaying over a period of seconds to minutes after transitions. Event transitions were implemented as a transfer from a home cage to a novel arena, a transfer to a familiar linear track, and the introduction of novel objects. Additional experiments showed that spatial context transitions dominate NE signaling over novel object presentations, and experience accelerates the decay of the NE signal after spatial context transitions. Correspondingly, the hippocampal CA1 spatial code takes minutes to stabilize after context transition in both novel and familiar spaces.

Strengths:

A strength of the study is the use of the NE sensor with sub-second resolution, non-linear modeling, and regression to identify the prominent variable of interest as time from event transition, and multiple behavioral controls. The use of multiple behavioral designs to investigate the effect of familiarity, experience, and interaction of spatial context transitions and novel object introduction is a strength. Relating the dynamics of NE signal decay to the rate of CA1 spatial code changes is also a strength.

Weaknesses:

A minor weakness is that the concept of an event boundary needs to be more broadly discussed. The manuscript uses event transitions such as spatial context changes and novel object introduction to implement an event boundary. However, especially in episodic memory studies in humans, event structure and boundaries have also been shown to occur through the automatic segmentation of experiences into discrete events (Baldassano et al., Neuron, 2017; Radvansky and Zacks, Curr. Opi. Behav. Sci, 2017). The rodent experiments in the current manuscript explicitly introduce event boundaries through changes in context or objects, which can potentially be conflated with novelty. A discussion of these differences, and whether NE can also have a role in event boundary transitions based on automatic segmentation of experiences, will add to the impact of the manuscript.

Reviewer #2 (Public review):

Summary:

In this work, the authors examined how neural activity related to temporal information is distributed and coordinated throughout the hippocampus, dorsal striatum, and orbitofrontal cortex. Rats were forced to run for fixed time intervals on a treadmill and make a decision based on whether the interval was long (10s) or short (5s). Under these conditions time cells were observed across all examined brain regions. The primary finding of the authors is that synchronized activity between time cells across brain regions is entrained into the theta cycle. This observation is used to support the central claim that the sharing of temporal information is mediated by the theta oscillation.

Strengths:

By simultaneously recording several brain regions in an interval discrimination task, the authors provide a valuable dataset for understanding how temporal information is processed and distributed throughout relevant networks.

Weaknesses:

Several methodological concerns should be addressed and a more focused analysis should be performed to strengthen the central claims of this work.

Major Concerns

(1) The restriction to only use time cells to understand temporal information processing. Other mechanisms of encoding time, like population clocks and ramping, have been characterized in the striatum and frontal cortex, and these dynamics might contain more temporal information than the subset of cells that meet the statistical criteria for being a time cell. Furthermore, time cells in the OFC, and DS in particular, appear to be heavily biased towards the beginning of treadmill running. This raises the question of whether temporal information can be encoded by neurons other than time cells in these two regions.

(2) The results of the Bayesian decoding analysis should be expanded on. In particular, the performance of each decoder above the chance level is not quantified. Comparing the performance of decoders trained on all cells to the performance of decoders trained on time cells alone would partially address the question of whether or not time cells are the only cells that can encode temporal information in the DS and OFC.

(3) The decoding results for the test trials appear different from the results in the authors' previous publication (Shimbo et. al., 2021). There, differences in decoded time between the selected-long and selected-short trials emerged after 5s, the duration of the short trials. This was to be expected given the following two reasons. First, from the task design, it is unclear that the animal can distinguish trial types (long, short, or test) until after the first 5 seconds of treadmill running, making it logical for differences in decoded time to emerge only after this point. Second, time cell activity was identical in the first 5s of the long and short trials as shown in Figure 2A. Here, however, the differences in decoded time during the selected-long and selected-short test trials emerge within the first 2s of treadmill running. Could the authors explain this discrepancy?

Furthermore, in Figure 6B, at 3 seconds of running time, the decoded time for selected-long and selected-short trials shows a difference of nearly 2 seconds, with no further increase as running time progresses. In contrast, at 2 seconds of running time, there is no significant difference in decoded time for DS and OFC, while CA1 shows a slight increase in the decoded time for selected-long trials. This pattern suggests a sudden jump in the encoded time for selected-long trials between 2 and 3 seconds. However, without explicitly showing the raw data, it is difficult to interpret this result and other results from the decoding analysis.

Minor Concerns

(1) It is not clear how the Bayes decoder was trained. Does the training data come entirely from the long trials?

(2) For Figure 5D, even if only one of two neurons in a pair has its spike rate modulated by theta, wouldn't the expectation be that synchronous spike events between these two neurons would be modulated by theta as well? This analysis might benefit from shuffling methods to determine if the mean resultant length of synchronous spike events is larger than the chance level.

(3) In Figure 5A, the authors suggest that 'the synchronization of time cells was modulated by theta oscillation.' However, it is unclear whether the population exhibits a preferred theta phase or the phase preference only occurs at the individual cell level. If there is no preference on the population level, how would the authors interpret this result?

Reviewer #2 (Public review):

Summary:

Blood pressure variability has been identified as an important risk factor for dementia. However, there are no established animal models to study the molecular mechanisms of increased blood pressure variability. In this manuscript, the authors present a novel mouse model of elevated BPV produced by pulsatile infusions of high-dose angiotensin II (3.1ug/hour) in middle-aged male mice. Using elegant methodology, including direct blood pressure measurement by telemetry, programmable infusion pumps, in vivo two-photon microscopy, and neurobehavioral tests, the authors show that this BPV model resulted in a blunted bradycardic response and cognitive deficits, enhanced myogenic response in parenchymal arterioles, and a loss of the pressure-evoked increase in functional hyperemia to whisker stimulation.

Strengths:

As the presentation of the first model of increased blood pressure variability, this manuscript establishes a method for assessing molecular mechanisms. The state-of-the-art methodology and robust data analysis provide convincing evidence that increased blood pressure variability impacts brain health.

Weaknesses:

One major drawback is that there is no comparison with another pressor agent (such as phenylephrine); therefore, it is not possible to conclude whether the observed effects are a result of increased blood pressure variability or caused by direct actions of Ang II. Ang II is known to have direct actions on cerebrovascular reactivity, neuronal function, and learning and memory. Given that Ang II is increased in only 15% of human hypertensive patients (and an even lower percentage of non-hypertensive), the clinical relevance is diminished. Nonetheless, this is an important study establishing the first mouse model of increased BPV.

Reviewer #2 (Public review):

Summary:

Communication between sensory and motor cortices is likely to be important for many aspects of behavior, and in this study, the authors carefully analyse neuronal spiking activity in S1 and M1 evoked by peripheral paw stimulation finding clear evidence for sensory responses in both cortical regions

Strengths:

The experiments and data analyses appear to have been carefully carried out and clearly represented.

Weaknesses:

(1) Some studies have found evidence for excitatory projection neurons expressing PV and in particular some excitatory pyramidal cells can be labelled in PV-Cre mice. The authors might want to check if this is the case in their study, and if so, whether that might impact any conclusions.

(2) I think the analysis shown in Figure S1 apparently reporting the absence of movements evoked by the forepaw stimulation could be strengthened. It is unclear what is shown in the various panels. I would imagine that an average of many stimulus repetitions would be needed to indicate whether there is an evoked movement or not. This could also be state-dependent and perhaps more likely to happen early in a recording session. Videography could also be helpful.

(3) Some similar aspects of the evoked responses, including triphasic dynamics, have been reported in whisker S1 and M1, and the authors might want to cite Sreenivasan et al., 2016.

Reviewer #2 (Public review):

As noted in the original review, the study by Sebastian-Perez addresses an important research question using a tractable model system to examine the earliest drivers of heterochromatin formation during embryogenesis. Moreover, the proteomic analyses provide a valuable resource to the research community to understand changes in the chromatin-bound proteome during the 2C-to-ESC transition. From there, they carry out more detailed analyses of TOPBP1, which shows substantive changes in chromatin association in 2C-like cells, and a potential interacting protein SMARCAD1, which shows only modest changes in chromatin association. While I appreciate that the authors have revised the manuscript to some extent to address the minor points raised, the major over-arching issue of how TOPBP1 and SMARCAD1 function in the 2C-like state is still a concern.

Reviewer #2 (Public review):

Summary:

This work by Zhao et al. demonstrates the role of the Edwardsiella tarda type 3 secretion system translocon in activating human macrophage inflammation and pyroptosis. The authors show the requirement of both the bacterial translocon proteins and particular host inflammasome components for E. tarda-induced pyroptosis. In addition, the authors show that the C-terminal region of the translocon protein, EseB, is both necessary and sufficient to induce pyroptosis when present in the cytoplasm. The most terminal region of EseB was determined to be highly conserved among other T3SS-encoding pathogenic bacteria and a subset of these exhibited functionally similar effects on inflammasome activation. Overall, the data support the conclusions and interpretations and provide valuable insights into interactions between bacterial T3SS components and the host immune system., thereby expanding our understanding of E. tarda pathogenesis.

Strengths:

The authors use established and reliable molecular biology and bacterial genetics strategies to characterize the roles of the bacterial T3SS translocon and host inflammasome pathways to E. tarda-induced pyroptosis in human macrophages. These observations are naturally expanded upon by demonstrating the specific regions of EseB that are required for inflammasome activation and the conservation of this sequence and function among other pathogenic bacteria.

Reviewer #2 (Public review):

Satouh et al report the presence of spherical structures composed of endosomes, lysosomes and autophagosomes within immature mouse oocytes. These endolysosomal compartments have been named as Endosomal-LYSosomal organellar Assembly (ELYSA). ELYSAs increase in size as the oocytes undergo maturation. ELYSAs are distributed throughout the oocyte cytoplasm of GV stage immature oocytes but these structures become mostly cortical in the mature oocytes. Interestingly, they tend to avoid the region which contain metaphase II spindle and chromosomes. They show that the endolysosomal compartments in oocytes are less acidic and therefore non-degradative but their pH decreases and become degradative as the ELYSAs begin to disassemble in the embryos post fertilization. This manuscript shows that lysosomal switching does not happen during oocyte development, and the formation of ELYSAs prevent lysosomes from being activated. Structures similar to these ELYSAs have been previously described in mouse oocytes (Zaffagnini et al, 2024) and these vesicular assemblies are important for sequestering protein aggregates in the oocytes but facilitate proteolysis after fertilization. The current manuscript, however, provides further details of endolysosomal disassembly post fertilization. Specifically, the V1-subunit of V-ATPase targeting to the ELYSAs increases the acidity of lysosomal compartments in the embryos. This is a well-conducted study and their model is supported by experimental evidence and data analyses.

Comments on revisions:

This revised version of the manuscript has addressed most of my concerns.

Reviewer #3 (Public review):

Summary:

Kondrychyn and colleagues describe the contribution of two Aquaporins Aqp1a.1 and Aqp8a.1 towards angiogenic sprouting in the zebrafish embryo. By whole-mount in situ hybridization, RNAscope and scRNA-seq, they show that both genes are expressed in endothelial cells in partly overlapping spatiotemporal patterns. Pharmacological inhibition experiments indicate a requirement for VEGR2 signaling (but not Notch) in transcriptional activation.

To assess the role of both genes during vascular development the authors generate genetic mutations. While homozygous single mutants appear normal, aqp1a.1;aqp8a.1 double mutants exhibit defects in EC sprouting and ISV formation.

At the cellular level, the aquaporin mutants display a reduction of filopodia in number and length. Furthermore, a reduction in cell volume is observed indicating a defect in water uptake.

The authors conclude, that polarized water uptake mediated by aquaporins is required for the initiation of endothelial sprouting and (tip) cell migration during ISV formation. They further propose that water influx increases hydrostatic pressure within the cells which may facilitate actin polymerization and formation membrane protrusions.

In the revised version of the manuscript the authors have added data which show that inhibition of swell-induced chloride channels mimics aqp mutant phenotypes, giving credence to the model that water influx via aquaporins is driven by an osmotic gradient.

Strengths:

The authors provide a detailed analysis of Aqp1a.1 and Aqp8a.1 during blood vessel formation in vivo, using zebrafish intersomitic vessels as a model. State-of-the-art imaging demonstrates an essential role aquaporins in different aspects of endothelial cell activation and migration during angiogenesis.

Weaknesses:

With respect to the connection between Aqp1/8 and actin polymerization/filopodia formation, the evidence appears preliminary and the authors' interpretation is guided by evidence from other experimental systems.

After revision, the authors have addressed all other concerns

Reviewer #2 (Public review):

Summary:

The authors perform a remarkably comprehensive, rigorous, and extensive investigation into the spatiotemporal dynamics between ribosomal accumulation, nucleoid segregation, and cell division. Using detailed experimental characterization and rigorous physical models, they offer a compelling argument that nucleoid segregation rates are determined at least in part by the accumulation of ribosomes in the center of the cell, exerting a steric force to drive nucleoid segregation prior to cell division. This evolutionarily ingenious mechanism means cells can rely on ribosomal biogenesis as the sole determinant for the growth rate and cell division rate, avoiding the need for two separate 'sensors,' which would require careful coupling.

Strengths:

In terms of strengths; the paper is very well written, the data are of extremely high quality, and the work is of fundamental importance to the field of cell growth and division. This is an important and innovative discovery enabled through a combination of rigorous experimental work and innovative conceptual, statistical, and physical modeling.

Weaknesses:

In terms of weaknesses, I have three specific thoughts.

Firstly, my biggest question (and this may or may not be a bona fide weakness) is how unambiguously the authors can be sure their ribosomal labeling is reporting on polysomes, specifically. My reading of the work is that the loss of spatial density upon rifampicin treatment is used to infer that spatial density corresponds to polysomes, yet this feels like a relatively indirect way to get at this question, given rifampicin targets RNA polymerase and not translation. It would be good if a more direct way to confirm polysome dependence were possible.

Second, the authors invoke a phase separation model to explain the data, yet it is unclear whether there is any particular evidence supporting such a model, whether they can exclude simpler models of entanglement/local diffusion (and/or perhaps this is what is meant by phase separation?) and it's not clear if claiming phase separation offers any additional insight/predictive power/utility. I am OK with this being proposed as a hypothesis/idea/working model, and I agree the model is consistent with the data, BUT I also feel other models are consistent with the data. I also very much do not think that this specific aspect of the paper has any bearing on the paper's impact and importance.

Finally, the writing and the figures are of extremely high quality, but the sheer volume of data here is potentially overwhelming. I wonder if there is any way for the authors to consider stripping down the text/figures to streamline things a bit? I also think it would be useful to include visually consistent schematics of the question/hypothesis/idea each of the figures is addressing to help keep readers on the same page as to what is going on in each figure. Again, there was no figure or section I felt was particularly unclear, but the sheer volume of text/data made reading this quite the mental endurance sport! I am completely guilty of this myself, so I don't think I have any super strong suggestions for how to fix this, but just something to consider.

Reviewer #2 (Public review):

Summary:

Shimin Wang et al. investigated the role of Sertoli cells in mediating spermatogenesis disorders in non-obstructive azoospermia (NOA) through stage-specific communications. The authors utilized scRNA-seq and scATAC-seq to analyze the molecular and epigenetic profiles of germ cells and Sertoli cells at different stages of spermatogenesis.

Strengths:

By understanding the gene expression patterns and chromatin accessibility changes in Sertoli cells, the authors sought to uncover key regulatory mechanisms underlying male infertility and identify potential targets for therapeutic interventions. They emphasized that the absence of the SC3 subtype would be a major factor contributing to NOA.

Comments on revisions:

The authors have addressed my concerns. I have no further comments.

Reviewer #2 (Public review):

Summary:

Disruption of the nicotinamide adenine dinucleotide (NAD) de novo Synthesis Pathway, by which L-tryptophan is converted to NAD results in multi-organ malformations which collectively has been termed Congenital NAD Deficiency Disorder (CNDD).

While NAD de novo synthesis is primarily active in the liver postnatally, the site of activity prior to and during organogenesis is unknown. However, mouse embryos are susceptible to CNDD between E7.5-E12.5, before the embryo has developed a functional liver. Therefore, NAD de novo synthesis is likely active in another cell or tissue during this time window of susceptibility.

The body of work presented in this paper continues the corresponding author's labs investigation of the cause and effects of NAD Deficiency and the primary goal was to determine the cell or tissue responsible for NAD de novo synthesis during early embryogenesis.

The authors conclude that visceral yolk sac endoderm is the source of NAD de novo synthesis, which is essential for mouse embryonic development, and furthermore that the dynamics of NAD synthesis are conserved in human equivalent cells and tissues, the perturbation of which results in CNDD.

Strengths:

Overall, the primary findings regarding the source of NAD synthesis, the temporal requirement and conservation between rodent and human species is quite novel and important for our understanding of NAD synthesis and function and role in CNDD.

The authors used UHPLC-MS/MS to quantify NAD+ and NAD-related metabolites and showed convincingly that the NAD salvage pathway can compensate for the loss of NAD synthesis in Halo-/- embryos, then determined that Haao activity was present in the yolk sac prior to hepatic development identifying this organ as the site of de novo NAD synthesis. Dietary modulation between E7.5-10.5 was sufficient to induce CNDD phenotypes, narrowing the window of susceptibility, and then re-analysis of RNA-seq datasets suggested the endoderm was the cell source of NAD synthesis.

Weaknesses:

Page 4 and Table S4. The descriptors for malformations of organs such as the kidney and vertebrae are quite vague and uninformative. More specific details are required to convey the type and range of anomalies observed as a consequence of NAD deficiency.

Can the authors define whether the role for the NAD pathway in a couple of tissue or organ systems is the same. By this I mean is the molecular or cellular effect of NAD deficiency the same in the vertebrae and organs such as the kidney. What unifies the effects on these specific tissues and organs and are all tissues and organs affected. If some are not, can the authors explain why they escape the need for the NAD pathway.

Page 5 and Figure 6C. The expectation and conclusion for whether specific genes are expressed in particular cell types in scRNA-seq datasets depends on number of cells sequenced, the technology (methodology) used, the depth of sequencing and also the resolution of the analysis. It is therefore essential to perform secondary validation of the analysis of scRNA-seq data. At a minimum, the authors should perform in situ hybridization or immunostaining for Tdo2, Amid, Kmo, Kanu, Haas, Qprt and Nadsyn1 or some combination thereof at multiple time points during early mouse embryogenesis to truly understand the spatiotemporal dynamics of expression and NAD synthesis.

Absolute functional proof of the yolk sac endoderm as being essential and required for NAD synthesis in the context of CNDD might require conditional deletion of Haoo in the yolk sac versus embryo using appropriate Cre driver lines or in the absence of a conditional allele, could be performed by tetraploid embryo-ES cell complementation approaches. But temporal dietary intervention can also approximate the same thing by perturbing NAD synthesis then the yolk sac is the primary source versus when the liver becomes the primary source in the embryo.

In further revisions, the authors have added data to Supp Table 4 and Supplemental Figures 1 and 2

Although the authors did not perform in situ hybridization for some of the genes requested to define the critical cell type of expression, available scRNA-sequencing suggests the endoderm and yolk sac are the only likely source of NAD synthesis prior to its synthesis in the liver. Absolute functional proof of the yolk sac endoderm as being essential and required for NAD synthesis in the context of CNDD still requires validation but nonetheless it seems likely given the absence of the liver in some embryos. The authors provided some additional data pertaining to the type of kidney and vertebral anomalies observed which makes this data more complete.

Reviewer #2 (Public review):

Summary:

The manuscript reports the computational study of the dynamics of PROTAC-induced degradation complexes. The research investigates how different linkers within PROTACs affect the formation and stability of ternary complexes between the target protein BRD4BD1 and Cereblon E3 ligase, and the degradation machinery. Using computational modeling, docking, and molecular dynamics simulations, the study demonstrates that although all PROTACs form ternary complexes, the linkers significantly influence the dynamics and efficacy of protein degradation. The findings highlight that the flexibility and positioning of Lys residues are crucial for successful ubiquitination. The results also discussed the correlated motions between the PROTAC linker and the complex.

Strengths:

The field of PROTAC discovery and design, characterized by its limited research, distinguishes itself from traditional binary ligand-protein interactions by forming a ternary complex involving two proteins. The current understanding of how the structure of PROTAC influences its degradation efficacy remains insufficient. This study investigated the atomic-level dynamics of the degradation complex, offering potentially valuable insights for future research into PROTAC degradability.

Comments on revisions:

All my questions have been addressed.

Reviewer #3 (Public review):

Summary:

Simoes et al enhanced dynamic glucose-enhanced (DGE) deuterium spectroscopy with Deuterium Metabolic Imaging (DMI) to characterize the kinetics of glucose conversion in two murine models of glioblastoma (GBM). The authors combined spectroscopic imaging and noise attenuation with histological analysis and showcased the efficacy of metabolic markers determined from DGE DMI to correlate with histological features of the tumors. This approach is also potent to differentiate the two models from GL261 and CT2A.

Strengths:

The primary strength of this study is to highlight the significance of DGE DMI to interrogate the metabolic flux from glucose. The authors focused on glutamine/glutamate and lactate. They attempted to correlate the imaging findings with in-depth histological analysis to depict the link between metabolic features and pathological characteristics such as cell density, infiltration, and distant migration.

Reviewer #2 (Public review):

Using a combination of in vivo studies with testosterone-inhibited and aged mice with lower testosterone levels as well as isolated mouse and human seminal vesicle epithelial cells the authors show that testosterone induces an increase in glucose uptake. They find that testosterone induces a difference in gene expression with a focus on metabolic enzymes. Specifically, they identify increased expression of enzymes regulating cholesterol and fatty acid synthesis, leading to increased production of 18:1 oleic acid. The revised version strengthens the role of ACLY as the main regulator of seminal vesicle epithelial cell metabolic programming. 18:1 oleic acid is secreted by seminal vesicle epithelial cells and taken up by sperm, inducing an increase in mitochondrial respiration. The difference in sperm motility and in vivo fertilization in the presence of 18:1 oleic acid and the absence of testosterone, however, is small. Additional experiments should be included to further support that oleic acid positively affects sperm function.

Reviewer #2 (Public review):

Summary:

This manuscript aims to follow up on a previously published paper (Busch and Hansel 2023) which proposed that the morphological variation of dendritic bifurcation in Purkinje cells in mice and humans is indicative of the number of climbing fiber inputs, with dendritic bifurcation at the level of the soma resulting in a proportion of these neurons being multi-innervated. The functional and anatomical climbing fiber data was obtained solely from mice since all human tissue was embalmed and fixed, and the extension of these findings to human Purkinje cells was indirect. The current comparative anatomy study aims to resolve this question in human tissue more directly and to further analyse in detail the properties of adult human Purkinje cell dendritic morphology.

Strengths:

The authors have carried out a meticulous anatomical quantification of human Purkinje cell dendrites, in tissue preparations with a better signal-to-noise ratio than their previous study, comparing them with those from mice. Importantly, they now present immunolabelling results that trace climbing fiber axons innervating human PCs. As well as providing detailed analyses of spine properties and interesting new findings of human PC dendritic length and spine types, the work confirms that human PCs that have two clearly distinct dendritic branches have an approximately x% chance of receiving more than one CF input, segregated across the two branches. Albeit entirely observational, the data will be of widespread interest to the cerebellar field, in particular, those building computational models of Purkinje cells.

Weaknesses:

The work is, by necessity, purely anatomical. It remains to be seen whether there are any functional differences in ion channel expression or functional mapping of granule inputs to human PCs compared with the mouse that might mitigate the major differences in electronic properties suggested.

Reviewer #2 (Public review):

Summary:

The authors have made microfluidic arrays of pores and obstacles with a complex shape and studied the swimming of multicellular magnetotactic bacteria through this system. They provide a comprehensive discussion of the relevant parameters of this system and identify one dimensionless parameter, which they call the scattering number and which depends on the swimming speed and magnetic moment of the bacteria as well as the magnetic field and the size of the pores, as the most relevant. They measure the effective speed through the array of pores and obstacles as a function of that parameter, both in their microfluidic experiments and in simulations, and find an optimal scattering number, which they estimate to reflect the parameters of the studied multicellular bacteria in their natural environment. They finally use this knowledge to compare different species to test the generality of this idea.

Strengths:

This is a beautiful experimental approach and the observation of an optimal scattering number (likely reflecting an optimal magnetic moment) is very convincing. The results here improve on similar previous work in two respects: On the one hand, the tracking of bacteria does not have the limitations of previous work, and on the other hand, the effective motility is quantified. Both features are enabled by choices of the experimental system: the use the multicellular bacteria which are larger than the usual single-celled magnetotactic bacteria and the design of the obstacle array which allows the quantification of transition rates due to the regular organization as well as the controlled release of bacteria into this array through a clever mechanism.

Weaknesses:

Some of the reported results are not as new as the authors suggest, specifically trapping by obstacles and the detrimental effect of a strong magnetic field have been reported before as has the hypothesis that the magnetic moment may be optimized for swimming in a sediment environment where there is a competition of directed swimming and trapping. Other than that, some of the key experimental choices on which the strength of the approach is based also come at a price and impose some limitations, namely the use of a non-culturable organism and the regular, somewhat unrealistic artificial obstacle array.

Reviewer #2 (Public review):

Summary:

This paper seeks to characterize the portability of methylation clocks across groups. Methylation clocks are trained to predict biological aging from DNA methylation but have largely been developed in datasets of individuals with primarily European ancestries. Given that genetic variation can influence DNA methylation, the authors hypothesize that methylation clocks might have reduced accuracy in non-European ancestries.

Strengths:

The authors evaluate five methylation clocks in 621 individuals from the MAGENTA study. This includes approximately 280 individuals sampled in Puerto Rico, Cuba, and Peru, as well as approximately 200 self-identified African American individuals sampled in the US. To understand how methylation clock accuracy varies with proportion of non-European ancestry, the authors inferred local ancestry for the Puerto Rican, Cuban, Peruvian, and African American cohorts. Overall, this paper presents solid evidence that methylation clocks have reduced accuracy in individuals with non-European ancestries, relative to individuals with primarily European ancestries. This should be of great interest to those researchers who seek to use methylation clocks as predictors of age-related, late-onset diseases and other health outcomes.

Weaknesses:

One clear strength of this paper is the ability to do more sophisticated analyses using the local ancestry calls for the MAGENTA study. It would be valuable to capitalize on this strength and assess portability across the genetic ancestry spectrum, as was recently advocated by Ding et al. in Nature (2023). For example, the authors could regress non-European local ancestry fraction on measures of prediction accuracy. This could paint a clearer picture of the relationship between genetic ancestry and clock accuracy, compared to looking at overall correlations within each cohort.

The authors present two possible reasons that methylation clocks might have reduced accuracy in individuals with non-European ancestries: genetic variants disrupting methylation sites (i.e. "disruptive variants"), and genetic variants influencing methylation sites (i.e. meQTLs). The authors conclude disruptive variants do not contribute to poor methylation clock portability, but the evidence in support of this conclusion is incomplete. The site frequency spectrum of disruptive variants in Figure 4 is estimated from all gnomAD individuals, and gnomAD is comprised of primarily European individuals. Thus, the observation that disruptive variants are generally rare in gnomAD does not rule them out as a source of poor clock portability in admixed individuals with non-European ancestries.

It is also unclear to what extent meQTLs impact methylation clock portability. The authors find that the frequency of meQTLs is higher in African ancestry populations, but this could reflect the fact that some of the analyzed meQTLs were ascertained in African Americans. The number of meQTL-affected methylation sites also varies widely between clocks, ranging from 6 to 271; thus, meQTLs likely impact the portability of different clocks in different ways. Overall, the paper would benefit from a more quantitative assessment of the extent to which meQTLs influence clock portability.

The paper implies that methylation clocks have an inferior ability to predict AD risk in admixed populations relative to white individuals, but the difference between white AD patients and controls is not significant when correcting for multiple testing. This nuance should be made more explicit.

Finally, this paper overlooks the possibility that environmental exposures co-vary with genetic ancestry and play a role in decreasing the accuracy of methylation clocks in genetically admixed individuals. Quantifying the impact of environmental factors is almost certainly outside of the scope of this paper. However, it is worth acknowledging the role of environmental factors to provide the field with a more comprehensive overview of factors influencing methylation clock portability. It is also essential to avoid the assumption that correlations with genetic ancestry necessarily arise from genetic causes.

Reviewer #2 (Public review):

Summary:

Chromosomal inversions have been predicted to play a role in adaptive evolution and speciation because of their ability to "lock" together adaptive alleles in genomic regions of low recombination. In this study, the authors use a combination of cutting-edge genomic methods, including BioNano and PacBio HiFi sequencing, to identify six large chromosomal inversions segregating in over 100 species of Lake Malawi cichlids, a classic example of adaptive radiation and rapid speciation. By examining the frequencies of these inversions present in species from six different linages, the authors show that there is an association between the presence of specific inversions with specific lineages/habitats. Using a combination of phylogenetic analyses and sequencing data, they demonstrate that three of the inversions have been introduced to one lineage via hybridization. Finally, genotyping of wild individuals as well as laboratory crosses suggests that three inversions are associated with XY sex determination systems in a subset of species. The data add to a growing number of systems in which inversions have been associated with adaptation to divergent environments. However, like most of the other recent studies in the field, this study does not go beyond describing the presence of the inversions to demonstrate that the inversions are under sexual or natural selection or that they contribute to adaptation or speciation in this system.

Strengths:

All analyses are very well done, and the conclusions about the presence of the six inversions in Lake Malawi cichlids, the frequencies of the inversions in different species, and the presence of three inversions in the benthic lineages due to hybridization are well-supported. Genotyping of 48 individuals resulting from laboratory crosses provides strong support that the chromosome 10 inversion is associated with a sex-determination locus.

Weaknesses:

The evidence supporting a role for the chromosome 11 inversion and the chromosome 9 inversion in sex determination is based on relatively few individuals and therefore remains suggestive. The authors are mostly cautious in their interpretations of the data. However, there are a few places where they state that the inversions are favored by selection, but they provide no evidence that this is the case and there is no consideration of alternative hypotheses (i.e. that the inversions might have been fixed via drift).

Reviewer #2 (Public review):

Summary:

Cilia are antenna-like extensions projecting from the surface of most vertebrate cells. Protein transport along the ciliary axoneme is enabled by motor protein complexes with multimeric so-called IFT-A and IFT-B complexes attached. While the components of these IFT complexes have been known for a while, precise interactions between different complex members, especially how IFT-A and IFT-B subcomplexes interact, are still not entirely clear. Likewise, the precise underlying molecular mechanism in human ciliopathies resulting from IFT dysfunction has remained elusive.

Here, the authors investigated the structure and putative function of the to-date poorly characterised C-terminus of IFT-B complex member IFT172 using alpha-fold predictions, crystallography and biochemical analyses including proteomics analyses followed by mass spectrometry, pull-down assays, and TGFbeta signalling analyses using chlamydomonas flagellae and RPE cells. The authors hereby provide novel insights into the crystal structure of IFT172 and identify novel interaction sites between IFT172 and the IFT-A complex members IFT140/IFT144. They suggest a U-box-like domain within the IFT172 C-terminus could play a role in IFT172 auto-ubiquitination as well as for TGFbeta signalling regulation.

As a number of disease-causing IFT72 sequence variants resulting in mammalian ciliopathy phenotypes in IFT172 have been previously identified in the IFT172 C-terminus, the authors also investigate the effects of such variants on auto-ubiquitination. This revealed no mutational effect on mono-ubiquitination which the authors suggest could be independent of the U-box-like domain but reduced overall IFT172 ubiquitination.

Strengths:

The manuscript is clear and well written and experimental data is of high quality. The findings provide novel insights into IFT172 function, IFT complex-A and B interactions, and they offer novel potential mechanisms that could contribute to the phenotypes associated with IFT172 C-terminal ciliopathy variants.

Weaknesses:

Some suggestions/questions are included in the comments to the authors below.

Reviewer #2 (Public review):

This work presents a 27-region DMR model for early diagnosis and prognostic prediction of colorectal cancer using plasma methylation markers. While this non-invasive diagnostic and prognostic tool could interest a broad readership, several critical issues require attention.

Major Concerns:

(1) Inconsistencies and clarity issues in data presentation

a) Sample size discrepancies<br /> - The abstract mentions screening 119 CRC tissue samples, while Figure 1 shows 136 tissues. Please clarify if this represents 119 CRC and 17 normal samples.<br /> - The plasma sample numbers vary across sections: the abstract cites 161 samples, Figure 1 shows 116 samples, and the Supplementary Methods mentions 77 samples (13 Normal, 15 NAA, 12 AA, 37 CRC).

b) Methodological inconsistencies<br /> - The Supplementary Material reports 477 hypermethylated sites from TCGA data analysis (Δβ>0.20, FDR<0.05), but Figure 1 indicates 499 sites.<br /> - The manuscript states that analyzing TCGA data across six cancer types identified 499 CRC-specific methylation sites, yet Figure 1 shows 477. Please also explain the rationale for selecting these specific cancer types from TCGA.<br /> - "404 CRC-specific DMRs" mentioned in the main text while "404 MCBs" in Figure 1, the authors need to clarify if these terms are interchangeable or how MCBs are defined.

(2) Methodological documentation

- The Results section requires a more detailed description of marker identification procedures and justification of methodological choices.<br /> - Figure 3 panels need reordering for sequential citation.

(3) Quality control and data transparency

- No quality control metrics are presented for the in-house sequencing data (e.g., sequencing quality, alignment rate, BS conversion rate, coverage, PCA plots for each cohort).<br /> - The analysis code should be publicly available through GitHub or Zenodo.<br /> - At a minimum, processed data should be made publicly accessible to ensure reproducibility.

Reviewer #2 (Public review):

Surgical resection remains the most effective treatment for retroperitoneal liposarcoma. However, postoperative recurrence is very common and is considered the main cause of disease-related death. Considering the importance and effectiveness of precision medicine, the identification of molecular characteristics is particularly important for the prognosis assessment and individualized treatment of RPLS. In this work, the authors described the gene expression map of RPLS and illustrated an innovative strategy of molecular classification. Through the pathway enrichment of differentially expressed genes, characteristic abnormal biological processes were identified, and RPLS patients were simply categorized based on the two major abnormal biological processes. Subsequently, the classification strategy was further simplified through nonnegative matrix factorization. The authors finally narrowed the classification indicators to two characteristic molecules LEP and PTTG1, and constructed novel molecular prognosis models that presented obviously a great area under the curve. A relatively interpretable logistic regression model was selected to obtain the risk scoring formula, and its clinical relevance and prognostic evaluation efficiency were verified by immunohistochemistry. Recently, prognostic model construction has been a hot topic in the field of oncology. The interesting point of this study is that it effectively screened characteristic molecules and practically simplified the typing strategy on the basis of ensuring high matching clinical relevance. Overall, the study is well-designed and will serve as a valuable resource for RPLS research.

Reviewer #2 (Public review):

Summary:

The manuscript by Flowers et al. aimed to enhance the accuracy of automated ligand model building by refining the qFit-ligand algorithm. Recognizing that ligands can exhibit conformational flexibility even when bound to receptors, the authors developed a bioinformatic pipeline to model alternate ligand conformations while improving fitting and more energetically favorable conformations.

Strengths:

The authors present a computational pipeline designed to automatically model and fit ligands into electron density maps, identifying potential alternative conformations within the structures.

Weaknesses:

Ligand modeling, particularly in cases of poorly defined electron density, remains a challenging task. The procedure presented in this manuscript exhibits clear limitations in low-resolution electron density maps (resolution > 2.0 Å) and low-occupancy scenarios, significantly restricting its applicability. Considering that the maps used to establish the operational bounds of qFit-ligand were synthetically generated, it's likely that the resolution cutoff will be even stricter when applied to real-world data.<br /> The reported changes in real-space correlation coefficients (RSCC) are not substantial, especially considering a cutoff of 0.1. Furthermore, the significance of improvements in the strain metric remains unclear. A comprehensive analysis of the distribution of this metric across the Protein Data Bank (PDB) would provide valuable insights.<br /> To mitigate the risk of introducing bias by avoiding real strained ligand conformations, the authors should demonstrate the effectiveness of the new procedure by testing it on known examples of strained ligand-substrate complexes.

In Grammar... change the form of (a word) to express a particular grammatical function or attribute, typically tense, mood, person, number, case, and gender.

2. vary the intonation or pitch of (the voice), especially to express mood or feeling.

Reviewer #2 (Public review):

Summary:

The authors investigate the mechanisms supporting learning to suppress distractors at predictable locations, focusing on proactive suppression mechanisms manifesting before the onset of a distractor. They used EEG and inverted encoding models (IEM). The experimental paradigm alternates between a visual search task and a spatial memory task, followed by a placeholder screen acting as a 'ping' stimulus -i.e., a stimulus to reveal how learned distractor suppression affects hidden priority maps. Behaviorally, their results align with the effects of statistical learning on distractor suppression. Contrary to the proactive suppression hypothesis, which predicts reduced memory-specific tuning of neural representations at the expected distractor location, their IEM results indicate increased tuning at the high-probability distractor location following the placeholder and prior to the onset of the search display.

Strengths:

Overall, the manuscript is well-written and clear, and the research question is relevant and timely, given the ongoing debate on the roles of proactive and reactive components in distractor processing. The use of a secondary task and EEG/IEM to provide a direct assessment of hidden priority maps in anticipation of a distractor is, in principle, a clever approach. The study also provides behavioral results supporting prior literature on distractor suppression at high-probability locations.

Weaknesses:

In response to my comments during the first review, the authors have clarified and further discussed several methodological aspects, limitations, and alternative interpretations, tempering some of their claims and, overall, improving the manuscript. These involved mostly broadening the introduction and discussion of the putative mechanisms in distractor suppression, evaluating alternative explanations due to the dual-task design, clarifying methodological details regarding the inverted encoding model, and discussing the possibility that proactive suppression might actually require enhanced tuning toward the expected feature. While, to some degree, the results may still remain open to alternative explanations, the study, in its current form, presents an interesting paradigm and promising findings that will undoubtedly be useful for future research. I therefore have no major remaining comments.

Reviewer #2 (Public review):

Summary:

In this work, the authors present a biologically plausible, efficient E-I spiking network model and study various aspects of the model and its relation to experimental observations. This includes a derivation of the network into two (E-I) populations, the study of single-neuron perturbations and lateral-inhibition, the study of the effects of adaptation and metabolic cost, and considerations of optimal parameters. From this, they conclude that their work puts forth a plausible implementation of efficient coding that matches several experimental findings, including feature-specific inhibition, tight instantaneous balance, a 4 to 1 ratio of excitatory to inhibitory neurons, and a 3 to 1 ratio of I-I to E-I connectivity strength.

Strengths:

While many network implementations of efficient coding have been developed, such normative models are often abstract and lacking sufficient detail to compare directly to experiments. The intention of this work to produce a more plausible and efficient spiking model and compare it with experimental data is important and necessary in order to test these models. In rigorously deriving the model with real physical units, this work maps efficient spiking networks onto other more classical biophysical spiking neuron models. It also attempts to compare the model to recent single-neuron perturbation experiments, as well as some long-standing puzzles about neural circuits, such as the presence of separate excitatory and inhibitory neurons, the ratio of excitatory to inhibitory neurons, and E/I balance. One of the primary goals of this paper, to determine if these are merely biological constraints or come from some normative efficient coding objective, is also important. Lastly, though several of the observations have been reported and studied before, this work arguably studies them in more depth, which could be useful for comparing more directly to experiments.

Weaknesses:

This work is the latest among a line of research papers studying the properties of efficient spiking networks. Many of the characteristics and findings here have been discussed before, thereby limiting the new insights that this work can provide. Thus, the conclusions of this work should be considered and understood in the context of those previous works, as the authors state. Furthermore, the number of assumptions and free parameters in the model, though necessary to bring the model closer to biophysical reality, make it more difficult to understand and to draw clear conclusions from. As the authors state, many of the optimality claims depend on these free parameters, such as the dimensionality of the input signal (M=3), the relative weighting of encoding error and metabolic cost, and several others. This raises the possibility that it is not the case that the set of biophysical properties measured in the brain are accounted for by efficient coding, but rather that theories of efficient coding are flexible enough to be consistent with this regime. With this in mind, some of the conclusions made in the text may be overstated and should be considered in this light.

Conclusions, Impact, and additional context:

Notions of optimality are important for normative theories, but they are often studied in simple models with as few free parameters as possible. Biophysically detailed and mechanistic models, on the other hand, will often have many free parameters by their very nature, thereby muddying the connection to optimality. This tradeoff is an important concern in neuroscientific models. Previous efficient spiking models have often been criticized for their lack of biophysically-plausible characteristics, such as large synaptic weights, dense connectivity, and instantaneous communication. This work is an important contribution in showing that such networks can be modified to be much closer to biophysical reality without losing their essential properties. Though the model presented does suffer from complexity issues which raise questions about its connections to "optimal" efficient coding, the extensive study of various parameter dependencies offers a good characterization of the model and puts its conclusions in context.

Reviewer #2 (Public review):

Hensel investigated the implications of SARS-CoV-2 RNA secondary structure in synonymous and nonsynonymous mutation frequency. The analysis integrated estimates of mutational fitness generated by Bloom and Neher (from publicly available patient sequences) and a population-averaged model of RNA base-pairing from Lan et al (from DMS mutational profiling with sequencing, DMS-MaPseq)

The results show that base-pairing limits the frequency of some synonymous substitutions (including the most common C→T), but not all: G→A and A→G substitutions seem unaffected by base-pairing.

The author then addressed nonsynonymous C→T substitutions at basepaired positions. While there is still a generally higher estimated mutational fitness at unpaired positions, they propose a coarse adjustment to disentangle base-pairing from inherent mutational fitness at a given position. This adjustment reveals that nonsynonymous substitutions at base-paired positions, which define major variants, have higher mutational fitness.

Overall, this manuscript highlights the importance of considering RNA secondary structure in viral evolution studies.

The conclusions of this work are generally well supported by the data presented. Particularly, the author acknowledges most limitations of the analyses and addresses them. Even though no new sequencing results were generated, the author used available data generated from the analysis of roughly seven million sequenced patient samples. Finally, the author discusses ways to improve the current available models.

There are a number of limitations of this work that should be highlighted, specifically in regard to the secondary structure data used in this paper. The Lan et al. dataset was generated using a multiplicity of infection (MOI) of 0.05, 24 hours post-infection (h.p.i.). At such a low MOI and late timepoint, viral replication is not synchronous and sequencing artifacts might be generated by cell debris and viral RNA degradation, therefore impacting the population-averaged results. In addition, the nonsynonymous base-paired positions in Figure 2 have relatively high population-averaged DMS reactivity, which suggests those positions are dynamic. Therefore, the proposed adjustment could result in an incorrect estimation of their inherent mutational fitness.

Additionally, like all such RNA probing experiments within cells, it remains difficult to deconvolve DMS/SHAPE low reactivity with RNA accessibility (e.g. from protein binding).

This work presents clear methods and an easy-to-access bioinformatic pipeline, which can be applied to other RNA viruses. Of note, it can be readily implemented in existing datasets. Finally, this study raises novel mechanistic questions on how mutational fitness is not correlated to secondary structure in the same way for every substitution.

Overall, this work highlights the importance of studying mutational fitness beyond an immune evasion perspective. On the other hand, it also adds to the viral intrinsic constraints to immune evasion.

Comments on revisions:

Following revision by the author, our concerns have been addressed. The additional analysis strengthens the conclusions & the revisions to the text have improved the manuscript for a general audience.

Reviewer #2 (Public review):

Excessive sucrose is a possible initial factor for the development of metabolic dysfunction-associated fatty liver disease (MAFLD). To investigate the possibility that intervention with JNK inhibitor could lead to the treatment of metabolic dysfunction caused by excessive sucrose intake, the authors performed multi-organ transcriptomics analysis (liver, visceral fat (vWAT), skeletal muscle, and brain) in a rat model of MAFLD induced by sucrose overtake (+ JNK inhibitor treatment).

The major strengths and weakness of this study are as follows.

Strengths:

・It has been previously reported that inhibition of JNK signalling can contribute to the prevention of hepatic steatosis (HS) and related metabolic syndrome in other models, but the role of JNK signalling in the metabolic disruption caused by excessive intake of sucrose, a possible initial factor for the development of MAFLD, has not been well understood, and the authors have addressed this point.<br /> ・This study is also important because pharmacological therapy for MAFLD has not yet been established.<br /> ・By obtaining transcriptomic data in multiple organs and comprehensively analyzing the data using gene co-expression network (GCN) analysis and genome-scale metabolic models (GEM), the authors showed the multi-organ interaction in not only in the pathology of MAFLD caused by excessive sucrose intake but also in the treatment effects by JNK-IN-5A.<br /> ・Since JNK signalling has diverse physiological functions in many organs, the authors effectively assessed possible side effects with a view to the clinical application of JNK-IN-5A.

Weaknesses:

・The metabolic process activities were evaluated using RNA-seq results in Figure 7, but direct data such as metabolite measurements are lacking.<br /> ・There is a lack of consistency in the data between JNK-IN-5A_D1 and _D2, and there is no sufficient data-based explanation for why the effects observed in D1 were inconsistent in the D2 samples.<br /> ・Although it is valuable that the authors were able to suggest the possibility of JNK inhibitor as a therapeutic strategy for MAFLD, the evaluation of the therapeutic effect was limited to evaluation of plasma TG, LDH, and gene expression changes. As there was no evaluation of liver tissue images, it is unclear what changes were brought about in the liver by the excessive sucrose intake and the treatment with JNK-IN-5A.

As mentioned in the Weakness section, biological data is insufficient, such as the lack of metabolite measurements and a histological evaluation of the liver. However, overall, the authors successfully provided the valuable insights that the JNK inhibitor has a cross-organ therapeutic effect on their MAFLD model induced by sucrose overtake. Their insist is supported by convincing data, comprehensively analysing the transcriptomic data obtained from multiple organs using GCN (gene co-expression network) analysis and GEM (genome-scale metabolic modelling).

Their comprehensive transcriptomic analysis in multiple organs, including the brain, has demonstrated that the effects of drugs are more widespread than just on specific tissues thought to be the main target, indicating the importance of focusing on tissue interactions when we assess the effects of drugs. Also, the data set in this study will be useful for comparative evaluation with transcriptomics data for other MALFD models.

Reviewer #2 (Public review):

Summary:

The authors set out to develop a tissue culture method in which to study the different regenerative abilities of the central and peripheral branch of sensory axons. Neurons developed a small and large branch, which have different regenerative abilities, different transport rates and different microtubule properties. The study provides convincing evidence that the two axonal branches differ in a way to corresponds to in vivo. The different regenerative abilities of the two branches are an important observation, because until now it has not been clear whether this difference is intrinsic to the neuron and axons or due to differences in the environment surrounding the axons. The authors have then looked for molecular explanations of the differences between the branches. They find different transport rates and different microtubule dynamics. The different microtubule dynamics are explained by differing levels of spastin, an enzyme that severs microtubules encouraging dynamics.

Strengths:

The differences between the two branches are clearly shown, together with differences in transport, microtubule dynamics and regeneration. The in vitro model is novel and could be widely used. The methods used are robust and generally accepted.

Weaknesses:

The revised version of the paper has addressed the weaknesses that were identified.

Reviewer #2 (Public Review):

The manuscript by Zhang et al. explores the effect of autophagy regulator ATG6 on NPR1-mediated immunity. The authors propose that ATG6 directly interacts with NPR1 in the nucleus to increase its stability and promote NPR1-dependent immune gene expression and pathogen resistance. This novel role of ATG6 is proposed to be independent of its role in autophagy in the cytoplasm. The authors demonstrate through biochemical analysis that ATG6 interacts with NPR1 in yeast and very weakly in vitro. They further demonstrate using overexpression transgenic plants that in the presence of ATG6-mcherry the stability of NPR1-GFP and its nuclear pool is increased.

Comments on latest version:

The initial apprehensions about statistical oversights and the use of an unclear nuclear marker were fixed. The implementation of the nls-mCherry for nuclear co-localization and additional statistical analyses was done well. However, the functional importance pertaining to cytoplasmic accumulation of the ARG6 protein should ideally be explored in more detail in future studies.

Updated sections:<br /> • Figure 1e: Added statistical analysis and updated with a nuclear marker.<br /> • Line Revisions: Terminology corrections for "infection" instead of "invasion".<br /> • NLS Analysis: Extended alignment and inclusion of conserved domains with predicted NLS (cut-off score: 2.6).

Reviewer #2 (Public review):

Summary:

Sphingosine-1-phosphate (S1P) metabolic and signaling genes are expressed highly in retinal Müller glia (MG) cells. This study tested how S1P signaling regulates glial phenotype, dedifferentiation of, reprogramming into proliferating MG-derived progenitor cells (MGPCs), and neuronal differentiation of the progeny of MGPCs using in vivo chick retina. Major techniques used are Sc-RNASeq and immunohistochemistry to determine the gene expression and proliferation of MG cells that co-label with signaling antibodies or mRNA FISH following treating the in vivo eyes with various S1P signaling antagonists, agonists, and signal modulators. The major conclusions drawn are supported by the results presented. However, the methodology they have used to modulate the S1P pathway using various chemical drugs raises questions about the outcomes and whether those are the real effects of S1P receptor modulation or S1P synthesis inhibition.

Strengths:

- Use of elaborated single-cell RNAseq expression data.<br /> - Use of FISH for S1P receptors and kinase as a good quality antibody is not available.<br /> - Use of EdU assay in combination with IHC<br /> - Comparison with human and Zebrafish Sc-RNA data

Weaknesses:

The methodology is not very clean. A number of drugs (inhibitors/ antagonists/agonists signal modulators) are used to modulate S1P expression or signaling in the retina without evidence that these drugs are reaching the target cells. No alternative evaluation if the drugs, in fact, are effective. The drug solubility in the vehicle and in the vitreous is not provided, and how did they decide on using a single dose of each drug to have the optimal expected effect on the S1P pathway?

In the revision, the authors provided justification for the use of single doses of the modulators and how they could pass the retinal barrier and affect the MG gene expression and receptor functioning.

Reviewer #2 (Public review):

Summary:

In this article Wen et. al., describe the development of a 'proof-of-concept' bi-functional vector based out of HSV-deltaICP-34.5's ability to purge latent HIV-1 and SIV genomes from cells. They show that co-infection of latent J-lat T-cell lines with a HSV-deltaICP-34.5 vector can reactivate HIV-1 from a latent state. Over- or stable expression of ICP 34.5 ORF in these cells can arrest latent HIV-1 genomes from transcription, even in the presence of latency reversal agents. ICP34.5 can co-IP with- and de-phosphorylate IKKa/b to block its interaction with NF-k/B transcription factor. Additionally, ICP34.5 can interact with HSF1 which was identified by mass-spec. Thus, the authors propose that the latency reversal effect of HSV-deltaICP-34.5 in co-infected JLat cells is due to modulatory effects on the IKKa/b-NF-kB and PP1-HSF-1 pathway.

Next the authors cleverly construct a bifunctional HSV based vector with deleted ICP34.5 and 47 ORFs to purge latency and avoid immunological refluxes, and additionally expand the application of this construct as a vaccine by introducing SIV genes. They use this 'vaccine' in mouse models and show the expected SIV-immune responses. Experiments in rhesus macaques (RM), further elicit potential for their approach to reactivate SIV genomes and at the same time block their replication by antibodies. What was interesting in the SIV experiments is that the dual-functional vector vaccine containing sPD1- and SIV Gag/Env ORFs effectively delayed SIV rebound in RMs and in some cases almost neutralized viral DNA copy detection in serum. Very promising indeed, however there are some questions I wish the authors explored to answer, detailed below.

Overall, this is an elegant and timely work demonstrating the feasibility of reducing virus rebound in animals, and potentially expand to clinical studies. The work was well written, and sections were clearly discussed.

Strengths:

The work is well designed, rationale explained and written very clearly for lay readers.<br /> Claims are adequately supported by evidence and well designed experiments including controls.

Weaknesses:

(1) It looks like ICP0 is also involved in latency reversal effects. More follow-up work will be required to test if this is in fact true.

(2) It is difficult to estimate the depletion of the latent viral reservoir. The authors have tried to address this issue. A more convincing argument to this reviewer will be data to demonstrate that after the bi-functional vaccine, the animals show overall reduction in the number of circulating latent cells. The feasibility to obtain such a result is not clearly demonstrated.

(3) The authors state that the reduced virus rebound detected following bi-functional vaccine delivery is due to latent genomes becoming activated and steady-state neutralization of these viruses by antibody response. This needs to be demonstrated. Perhaps cell-culture experiments from specimen taken from animals might help address this issue. In lab cultures one could create environments without antibody responses, under these conditions one would expect higher level of viral loads being released in response to the vaccine in question.

Reviewer #2 (Public review):

Summary:

The authors have tried to determine the regulatory role of Phosphoglycerate mutate (PGAM), an enzyme involved in converting 3-phosphoglycerate to 2-phosphoglycerate in glycolysis, in differentiation and suppressive function of regulatory CD4 T cells through de novo serine synthesis. This is done by contributing one carbon metabolism and eventually epigenetic regulation of Treg differentiation.

Strengths:

The authors have rigorously used inhibitors and antisense RNA to verify the contribution of these pathways in Treg differentiation in-vitro. This has also been verified in an in-vivo murine model of autoimmune colitis. This has further clinical implications in autoimmune disorders and cancer.

Weaknesses:

The authors have used inhibitors to study pathways involved in Treg differentiation. However, they have not studied the context of overexpression of PGAM, which was the actual reason to pursue this study.

Reviewer #2 (Public review):

Summary:

Troyer and colleagues have studied the in vivo localisation and mobility of the E.coli RNaseE (a protein key for mRNA degradation in all bacteria) as well as the impact of two key protein segments (MTS and CTD) on RNase E cellular localisation and mobility. Such sequences are important to study since there is significant sequence diversity within bacteria, as well as a lack of clarity about their functional effects. Using single-molecule tracking in living bacteria, the authors confirmed that >90% of RNaseE localised on the membrane, and measured its diffusion coefficient. Via a series of mutants, they also showed that MTS leads to stronger membrane association and slower diffusion compared to a transmembrane motif (despite the latter being more embedded in the membrane), and that the CTD weakens membrane binding. The study also rationalised how the interplay of MTS and CTD modulate mRNA metabolism (and hence gene expression) in different cellular contexts.

Strengths:

The study uses powerful single-molecule tracking in living cells along with solid quantitative analysis, and provides direct measurements for the mobility and localisation of E.coli RNaseE, adding to information from complementary studies and other bacteria. The exploration of different membrane-binding motifs (both MTS and CTD) has novelty and provides insight on how sequence and membrane interactions can control function of protein-associated membranes and complexes. The methods and membrane-protein standards used contribute to the toolbox for molecular analysis in live bacteria.

Weaknesses:

The Results sections can be structured better to present the main hypotheses to be tested. For example, since it is well known that RNase E is membrane-localised (via its MTS), one expects its mobility to be mainly controlled by the interaction with the membrane (rather than with other molecules, such as polysomes and the degradosome). The results indeed support this expectation - however, the manuscript in its current form does not lay down the dominant hypothesis early on (see second Results chapter), and instead considers the rifampicin-addition results as "surprising"; it will be best to outline the most likely hypotheses, and then discuss the results in that light.

Similarly, the authors should first discuss the different modes of interaction for a peripheral anchor vs a transmembrane anchor, outline the state of knowledge and possibilities, and then discuss their result; in its current version, the ms considers the LacY2 and LacY6 faster diffusion compared to MTS "remarkable", but considering the very different mode of interaction, there is no clear expectation prior to the experiment. In the same section, it would be good to see how the MD simulations capture the motion of LacY6 and LacY12, since this will provide a set of results consistent with the experimental set.

The work will benefit from further exploration of the membrane-RNase E interactions; e.g., the effect of membrane composition is explored by just using two different growth media (which on its own is not a well-controlled setting), and no attempts to change the MTS itself were made. The manuscript will benefit from considering experiments that explore the diversity of RNaseE interactions in different species; for example, the authors may want to consider the possibility of using the membrane-localisation signals of functional homologs of RNaseE in different bacteria (e.g., B. subtilis). It would be good to look at the effect of CTD deletions in a similar context (i.e., in addition to the MTS substitution by LacY2 and LacY6).

The manuscript will benefit from further discussion of the unstructured nature of the CTD, especially since the RNase CTD is well known to form condensates in Caulobacter crescentus; it is unclear how the authors excluded any roles for RNaseE phase separation in the mobility of RNaseE in E.coli cells.

Some statements in the Discussion require support with example calculations or toning down substantially. Specifically, it is not clear how the authors conclude that RNaseE interacts with its substrate for a short time (and what this time may actually be); further, the speculation about the MTS "not being an efficient membrane-binding motif for diffusion" lacks adequate support as it stands.

Reviewer #2 (Public review):

Summary:

This manuscript by Alexander et al describes a careful and rigorous application of multiomics to mouse primordial germ cells (PGCs) and their surrounding gonadal cells during the period of sex differentiation.

Strengths:

In thoughtfully designed figures, the authors identify both known and new candidate gene regulatory networks in differentiating XX and XY PGCs and sex-specific interactions of PGCs with supporting cells. In XY germ cells, novel findings include the predicted set of TFs regulating Bnc2, which is known to promote mitotic arrest, as well as the TFs POU6F1/2 and FOXK2 and their predicted targets that function in mitosis and signal transduction. In XX germ cells, the authors deconstruct the regulation of the premeiotic replication factor Stra8, which reveals TFs involved in meiosis, retinoic acid signaling, pluripotency and epigenetics among predictions; this finding, along with evidence supporting regulatory potential of retinoic acid receptors in meiotic gene expression is an important addition to the debate over the necessity of retinoic acid in XX meiotic initiation. In addition, a self-regulatory network of other TFs is hypothesized in XX differentiating PGCs, including TFAP2c, TCF5, ZFX, MGA and NR6A1, which is predicted to turn on meiotic and Wnt signaling targets. Finally, analysis of PGC-support cell interactions during sex differentiation reveals substantially more interactions in XX, via WNTs and BMPs, as well as some new signaling pathways that predominate in XY PGCs including ephrins, CADM1, Desert Hedgehog and matrix metalloproteases. This dataset will be an excellent resource for the community, motivating functional studies and serving as a discovery platform.

Weaknesses:

While the authors performed all of their comparisons between XX versus XY datasets at each timepoint, a more systematic analysis of expression and accessibility changes across time for each sex would be valuable. It remains possible that common mechanisms of differentiation to XX and XY could be missing from this analysis that focused on sex-specific differences.

Specific Questions:

(1) Line 461: "the population of E13.5 XX PGCs displaying the strongest Stra8 expression levels corresponded to the same population of XX PGCs with the highest module score of early meiotic prophase I genes (Fig. 3c; Supplementary Fig. 3a-b)" however the Stra8+ XX PGCs that do not robustly express meiotic genes should be examined to understand more about their differentiation potential. The authors are well-poised to identify the likely trajectories available to cell subsets in their dataset, and not doing so is a missed opportunity.

(2) The authors state that "we found that Stra8, Rec8, Rnf2, Sycp1, Sycp2, Ccnb3, and Zglp1 contain the RA receptor motifs in their regulatory sequences (Supplementary Figure 4g)." What is the strength of the RA->meiosis pathway compared to other mechanisms regulating meiosis? Perhaps the authors could take this analysis further with the following questions: (1) ask whether meiotic genes more enriched in RA motifs compared to other expressed genes or other motifs (2) compare the strength of peak-gene correlations for all peaks containing RA receptor motifs vs. those with peaks for Zglp1, Rnf2, etc binding. The strengths of these correlations could provide clues to how much gene expression varies in response to RA exposure vs. modulation of these other factors and thus tell us something about how much RA is playing a role.

(3) In figure 4, the shift from promoters in E11.5 XX PGCs to distal intergenic regions is fascinating. What can we learn about epigenetic reprogramming/methylation changes across gene bodies?

(4) The overlap between gene targets of TCFL5 with other highly expressed TFs differentially upregulated in E13.5 XX PGCs over XY suggests ambiguity regarding its role as a central or high-level regulator of differentiation; as in vivo validation has not been performed, I suggest softening this conclusion.

Reviewer #2 (Public review):

Initial Review:

This paper reports investigations of chromosome stiffness in oocytes and spermatocytes> the paper shows that prophase I spermatocytes and MI/MII oocytes yield high Young Modulus values in the assay the authors applied. Deficiency in each one of three meiosis-specific cohesins they claim did not affect this result and increased stiffness was seen in aged oocytes but not in oocytes treated with the DNA-damaging agent etoposide.

The paper reports some interesting observations which are in line with a report by the same authors of 2020 where increased stiffness of spermatocyte chromosomes was already shown. In that sense, it the current manuscript is an extension of that previous paper and thus novelty is somewhat limited. The paper is also largely descriptive as it does neither propose mechanism nor report factors that determine the chromosomal stiffness.

There are several points that need to be considered.

Limitations of the study and the conclusions are not discussed in "Discussion"; that's a significant gap. Even more so as the authors rely on just one experimental system for all their data - no independent verification - and that in vitro system may be prone to artefacts.

It is somewhat unfortunate that they jump between oocytes and spermatocytes to address the cohesin question. Prophase I (pachytene) spermatocytes chromosomes are not directly comparable to MI or MII oocyte chromosomes. In fact, the authors report Young Modulus values of 3700 for MI oocytes and only 2700 for spermatocyte prophase chromosomes, illustrating this difference. Why not using oocyte-specific cohesin deficiencies?

It remains unclear whether the treatment of oocytes with the detergent TritonX-100 affects the spindle and thus the chromosomes isolated directly from the Triton-lysed oocytes. In fact, it is rather likely that the detergent affects chromatin-associated proteins and thus structural features of the chromosomes.

Why did the authors use mouse strains of different genetic background, CD-1 and C57BL/6? That makes comparison difficult. Breeding of heterozygous cohesin mutants will yield the ideal controls, i.e. littermates.

How did the authors capture chromosome axes from STAG3-deficient spermatocytes which feature very little if any axes? How representative are those chromosomes that could be captured?

Line 135: that statement is not substantiated; better to show retraction data and full reversibility.

Line 144: the authors claim that the Young Modulus of MII oocytes is "slightly" higher than that of mitotic cells (MEFs). Well, "slightly" means it is rather similar and therefore the commonly used statement that MII is similar to mitosis is OK - contrary to the authors claim.

There are a lot of awkward sentences in this text. Some sentences lack words, are not sufficiently precise in wording and/or logic, and there are numerous typos. Some examples can be found in lines 89 (grammar), 94, 95 ("looked"), 98, 101 ("difference" - between what?), and some are commonplaces or superficial (lines 92/93, 120..., ). Occasionally the present and past tense are mixed (e.g. in M&M). Thus the manuscript is quite badly written.

Comments on revisions:

In their revised paper, Liu et al have addressed a number of my concerns and thus the paper is clearly improved in several details, e.g. in showing a control for a potential effect of the detergent (new supplies. fig. 5). Other points were not sufficiently addressed though.

I remain sceptical about using mice of a substantially different genetic background (CD1) as controls in the analysis of the cohesin mutants (C57BL/6). The argument that C57BL/6 yield smaller litter size is, frankly, ridiculous. Hundreds of labs worldwide extensively and successfully work with C57BL/6. Further, the paper Liu et al. cite to argue that there are no (or minor) differences in chromosome structure (Biggs et al., 2020, which is from the same lab) of the two mouse strains deals with spermatocyte chromosomes only. Nothing there on oocyte chromosomes. And there is no direct comparison within the same experimental setting since in Biggs et al only C57BL/6 is used (sic!). Thus, this is not a convincing argument. It would also be reassuring to see an independent reference directly comparing different genetic backgrounds (authors may have a look at older papers of Pat Hunt/Terry Hassold where they may find some data). In my experience, differences in genetic background do play a very clear role in meiosis, e.g. in the timing of juvenile spermatogenesis, in the onset of puberty, in the kinetics of oocyte maturation, in the success of PBE, and in biophysical properties as seen in the stability of oocytes during experimental handling. In fact, the authors themselves indicate differences in reproduction by stating the low litter size of C57BL/6. Thus, I strongly advise carrying out at least a few key experiments using C57BL/6 control mice (which can very easily and cheaply be obtained from vendors; the authors have used C57BL/6 wt before - see their 2020 paper).

The answer to my question #5 is not really satisfactory. I asked specifically how the authors isolated the very small chromosomes from Stag3-/- spermatocytes, where the axes are almost non-existing. The authors refer to suppl. fig. 3, but that shows isolation from Rec8-/- spermatocytes, which still have nicely visible, well-formed, shortened axes. Suppl. fig. 4 shows this for Rad21l-/-. Why not show this for the Stag3-/-, which in this respect is the most critical and difficult, and specifically answer my question?

The overall criticism of the lack of conceptual novelty of the basic message of the paper and of very little if any insights into the mechanisms and factors determining the changes in chromosome stiffness remains.

Reviewer #2 (Public review):

In An image-computable model of speeded decision-making, the authors introduce and fit a combined CCN-EAM (a 'VAM') to flanker-task-like data. They show that the VAM can fit mean RTs and accuracies as well as the congruency effect that is present in the data, and subsequently analyze the VAM in terms of where in the network congruency effects arise.

I have mixed feelings about this manuscript, as I appreciate the innovative efforts to combine CNNs with EAMs in a new class of cognitive models, while also having some reservations from an EAM perspective. The idea of combining these approaches has great potential, and I'm excited to see where this research will lead. However, I do have some concerns about the quality of fit between the behavioral data and the model. Specifically, the RT distributions, delta plots, and conditional accuracy function don't appear to be well-matched by the VAM. The conflict effects on behavioral data are well-established and typically considered crucial to understanding the underlying cognitive process. Unfortunately, it seems that these parts of the data don't fit well with the proposed model.

This disparity is not entirely surprising. The EAM literature suggests that LBA models might not be suitable for conflict tasks, and the presented results seem to confirm this concern. Conflict EAMs, including the DMC (e.g., Ulrich et al., 2015; Evans & Servant, 2022; Lee & Sewell 2024), propose dynamic drift rates with a fast automatic process that is gradually withdrawn from evidence accumulation over time. This approach results in congruency effects arising from temporal dynamics, not spatial representations.<br /> In contrast, the VAM imposes static drift rates in the LBA model, leading to an effect between drift rates that translates to changes in representations. However, this account does not adequately explain the behavioral data, and the proposed representational geometry explanation is therefore limited.

My concerns are addressed in the revised manuscript, but I struggle to understand why the authors distinguish between explaining mean effects across individuals and congruency effects within individuals. These concepts seem related, and issues at the individual level could propagate to the group mean. Furthermore, I find it challenging to accept that dynamics merely act 'in concert' with the orthogonalization mechanism, as it seems possible that an account that uses a time-varying EAM may not require any orthogonalization mechanism in the first place. The orthogonalization mechanism might have arisen because the model does not have the possibility to account for the conflict effect from temporal effects, instead of spatial effects. I could envision a CNN-DMC in which conflict effects arise only at the level of the choice model (e.g., as a time-varying filter that changes which information is read out from the visual system, rather than due to changes in the representations in the visual system itself). This possibility should be acknowledged in the paper, and it would be interesting to discuss how such an account would be tested.

While I appreciate the technological advancement presented in this paper, my concerns are not about implementation details but rather about the choice of models and their consequences. I believe that a more in-depth exploration of which conclusions can be drawn, and which model comparisons would be required to reach a final conclusion.

Reviewer #3 (Public review):

Summary:

In this study, the authors have started off using an immortalized human cell line and then gene edited it to decrease the levels of VEGF1 (in order to influence vascularization), and the levels of Runx2 (to decrease osteogenesis). They first transplanted these cells with a collagen scaffold. The modified cells showed a decrease in vascularization when VEGF1 was decreased, and suggested an increase in cartilage formation.

In another study, matrix generated by these cells subsequently remodeled into a bone marrow organ. When RUNX2 was decreased, the cells did not mineralize in vitro, and their matrices expressed types I and II collagen but not type X collagen in vitro, in comparison with unedited cells. In vivo, the author claims that remodeling of the matrices into bone was somewhat inhibited. Lastly, they utilized matrices generated by RUNX2-edited cells to regenerate chondro-osteal defects. They suggest that the edited cells regenerated cartilage in comparison with unedited cells.

Strengths:

- The notion that inducing changes in the ECM by genetically editing the cells is a novel one, as it has long been thought that ECM composition influences cell activity.<br /> - If successful, it may be possible to make off the shelf ECMS to carry out different types of tissue repair.

Weaknesses:

- The authors have not demonstrated robust cartilage formation (quantitation would be useful).<br /> - Measuring total GAG content does not prove the presence of cartilage<br /> - There are numerous overstatements about forming and implanting cartilage.<br /> - Although it is implied, RUNX2 deletion did not improve cartilage formation by the modified cells.<br /> - In the control line, MSOD-B there were variability in the amount of safranin O positive material in various histological panels in the figures.; more quantitation is needed.<br /> - In the in vivo articular defect experiments, an untreated injured joint is needed as a negative control.<br /> - Statements about bone generation are often not reflective of the microCT data presented.<br /> - The discussion over-interprets the results.

Reviewer #2 (Public review):

Summary:

Dong et al. present a thorough investigation into the potential of repurposing citalopram, an SSRI, for hepatocellular carcinoma (HCC) therapy. The study highlights the dual mechanisms by which citalopram exerts anti-tumor effects: reprogramming tumor-associated macrophages (TAMs) toward an anti-tumor phenotype via C5aR1 modulation and suppressing cancer cell metabolism through GLUT1 inhibition while enhancing CD8+ T cell activation. The findings emphasize the potential of drug repurposing strategies and position C5aR1 as a promising immunotherapeutic target. However, certain aspects of experimental design and clinical relevance could be further developed to strengthen the study's impact.

Strength:

It provides detailed evidence of citalopram's non-canonical action on C5aR1, demonstrating its ability to modulate macrophage behavior and enhance CD8+ T cell cytotoxicity. The use of DARTS assays, in silico docking, and gene signature network analyses offers robust validation of drug-target interactions. Additionally, the dual focus on immune cell reprogramming and metabolic suppression presents a thorough strategy for HCC therapy. By emphasizing the potential for existing drugs like citalopram to be repurposed, the study also underscores the feasibility of translational applications.

Major weaknesses/suggestions:

The dataset and signature database used for GSEA analyses are not clearly specified, limiting reproducibility. The manuscript does not fully explore the potential promiscuity of citalopram's interactions across GLUT1, C5aR1, and SERT1, which could provide a deeper understanding of binding selectivity. The absence of GLUT1 knockdown or knockout experiments in macrophages prevents a complete assessment of GLUT1's role in macrophage versus tumor cell metabolism. Furthermore, there is minimal discussion of clinical data on SSRI use in HCC patients. Incorporating survival outcomes based on SSRI treatment could strengthen the study's translational relevance.

By addressing these limitations, the manuscript could make an even stronger contribution to the fields of cancer immunotherapy and drug repurposing.

Reviewer #2 (Public review):

This manuscript asks an interesting and important question: what part of 'cerebellar' motor dysfunction is an acute control problem vs a compensatory strategy to the acute control issue? The authors use a cerebellar 'blockade' protocol, consisting of high-frequency stimuli applied to the cerebellar peduncle which is thought to interfere with outflow signals. This protocol was applied in monkeys performing center outreaching movements and has been published from this laboratory in several preceding studies. I found the take-home-message broadly convincing and clarifying - that cerebellar block reduces muscle activation acutely particularly in movements that involve multiple joints and therefore invoke interaction torques, and that movements progressively slow down to in effect 'compensate' for these acute tone deficits. The manuscript was generally well written, and the data was clear, convincing, and novel. My comments below highlight suggestions to improve clarity and sharpen some arguments.

Primary comments:

(1) Torque vs. tone: Is it known whether this type of cerebellar blockade is reducing muscle tone or inducing any type of acute co-contraction that could influence limb velocity through mechanisms different than 'atonia'? If so, the authors should discuss this information in the discussion section starting around line 336, and clarify that this motivates (if it does) the focus on 'torques' rather than muscle activation. Relatedly, besides the fact that there are joints involved, is there a reason there is so much emphasis on torque per se? If the muscle is deprived of sufficient drive, it would seem that it would be more straightforward to conceptualize the deficit as one of insufficient timed drive to a set of muscles than joint force. Some text better contextualizing the choices made here would be sufficient to address this concern. I found statements like those in the introduction "hand velocity was low initially, reflecting a primary muscle torque deficit" to be lacking in substance. Either that statement is self-evident or the alternative was not made clear. Finally, emphasize that it is a loss of self-generated torque at the shoulder that accounts for the velocity deficits. At times the phrasing makes it seem that there is a loss of some kind of passive torque.

(2) Please clarify some of the experimental metrics: Ln 94 RESULTS. The success rate is used as a primary behavioral readout, but what constitutes success is not clearly defined in the methods. In addition to providing a clear definition in the methods section, it would also be helpful for the authors to provide a brief list of criteria used to determine a 'successful' movement in the results section before the behavioral consequences of stimulation are described. In particular, the time and positional error requirements should be clear.

(3) Based on the polar plot in Figure 1c, it seemed odd to consider Targets 1-4 outward and 5-8 inward movements, when 1 and 5 are side-to-side. Is there a rationale for this grouping or might results be cleaner by cleanly segregating outward (targets 2-4) and inward (targets 6-8) movements? Indeed, by Figure 3 where interaction torques are measured, this grouping would seem to align with the hypothesis much more cleanly since it is with T2,T3,and T4 where clear coupling torques deficits are seen with cerebellar block.

4. I did not follow Figure 3d. Both the figure axis labels and the description in the main text were difficult to follow. Furthermore, the color code per animal made me question whether the linear regression across the entire dataset was valid, or would be better performed within animal, and the regressions summarized across animals. The authors should look again at this section and figure.

(5) Line 206+ The rationale for examining movement decomposition with a cerebellar block is presented as testing the role of the cerebellum in timing. Yet it is not spelled out what movement decomposition and trajectory variability have to do with motor timing per se.

Reviewer #2 (Public review):

Summary:

This is a short and straightforward paper describing BOLD fMRI and depth electrode measurements from two regions of the fusiform gyrus that show either higher or lower BOLD responses to faces vs. objects (which I will call face-positive and face-negative regions). In these regions, which were studied separately in two patients undergoing epilepsy surgery, spiking activity increased for faces relative to objects in the face-positive region and decreased for faces relative to objects in the face-negative region. Interestingly, about 30% of neurons in the face-negative region did not respond to objects and decreased their responses below baseline in response to faces (absolute suppression).

Strengths:

These patient data are valuable, with many recording sessions and neurons from human face-selective regions, and the methods used for comparing face and object responses in both fMRI and electrode recordings were robust and well-established. The finding of absolute suppression could clarify the nature of face selectivity in human fusiform gyrus since previous fMRI studies of the face-negative region could not distinguish whether face < object responses came from absolute suppression, or just relatively lower but still positive responses to faces vs. objects.

Weaknesses:

The authors claim that the results tell us about both 1) face-selectivity in the fusiform gyrus, and 2) the physiological basis of the BOLD signal. However, I would like to see more of the data that supports the first claim, and I am not sure the second claim is supported.

(1) The authors report that ~30% of neurons showed absolute suppression, but those data are not shown separately from the neurons that only show relative reductions. It is difficult to evaluate the absolute suppression claim from the short assertion in the text alone (lines 105-106), although this is a critical claim in the paper.<br /> (2) I am not sure how much light the results shed on the physiological basis of the BOLD signal. The authors write that the results reveal "that BOLD decreases can be due to relative, but also absolute, spike suppression in the human brain" (line 120). But I think to make this claim, you would need a region that exclusively had neurons showing absolute suppression, not a region with a mix of neurons, some showing absolute suppression and some showing relative suppression, as here. The responses of both groups of neurons contribute to the measured BOLD signal, so it seems impossible to tell from these data how absolute suppression per se drives the BOLD response.

Reviewer #2 (Public review):

Summary:

The authors aimed to investigate the effects of organic strip cropping on carabid richness and density as well as on crop yields. They find on average higher carabid richness and density in strip cropping and organic farming, but not in all cases.

Strengths:

Based on highly resolved species-level carabid data, the authors present estimates for many different crop types, some of them rarely studied, at the same time. The authors did a great job investigating different aspects of the assemblages (although some questions remain concerning the analyses) and they present their results in a visually pleasing and intuitive way.

Weaknesses:

The authors used data from four different strip cropping experiments and there is no real replication in space as all of these differed in many aspects (different crops, different areas between years, different combinations, design of the strip cropping (orientation and width), sampling effort and sample sizes of beetles (differing more than 35 fold between sites; L 100f); for more differences see L 237ff). The reader gets the impression that the authors stitched data from various places together that were not made to fit together. This may not be a problem per se but it surely limits the strength of the data as results for various crops may only be based on small samples from one or two sites (it is generally unclear how many samples were used for each crop/crop combination).

One of my major concerns is that it is completely unclear where carabids were collected. As some strips were 3m wide, some others were 6m and the monoculture plots large, it can be expected that carabids were collected at different distances from the plot edge. This alone, however, was conclusively shown to affect carabid assemblages dramatically and could easily outweigh the differences shown here if not accounted for in the models (see e.g. Boetzl et al. (2024) or Knapp et al. (2019) among many other studies on within field-distributions of carabids).

The authors hint at a related but somewhat different problem in L 137ff - carabid assemblages sampled in strips were sampled in closer proximity to each other than assemblages in monoculture fields which is very likely a problem. The authors did not check whether their results are spatially autocorrelated and this shortcoming is hard to account for as it would have required a much bigger, spatially replicated design in which distances are maintained from the beginning. This limitation needs to be stated more clearly in the manuscript.

Similarly, we know that carabid richness and density depend strongly on crop type (see e.g. Toivonen et al. (2022)) which could have biased results if the design is not balanced (this information is missing but it seems to be the case, see e.g. Celeriac in Almere in 2022).

A more basic problem is that the reader neither learns where traps were located, how missing traps were treated for analyses how many samples there were per crop or crop combination (in a simple way, not through Table S7 - there has to have been a logic in each of these field trials) or why there are differences in the number of samples from the same location and year (see Table S7). This information needs to be added to the methods section.

As carabid assemblages undergo rapid phenological changes across the year, assemblages that are collected at different phenological points within and across years cannot easily be compared. The authors would need to standardize for this and make sure that the assemblages they analyze are comparable prior to analyses. Otherwise, I see the possibility that the reported differences might simply be biased by phenology.

Surrounding landscape structure is known to affect carabid richness and density and could thus also bias observed differences between treatments at the same locations (lower overall richness => lower differences between treatments). Landscape structure has not been taken into account in any way.

In the statistical analyses, it is unclear whether the authors used estimated marginal means (as they should) - this needs to be clarified.

In addition, and as mentioned by Dr. Rasmann in the previous round (comment 1), the manuscript, in its current form, still suffers from simplified generalizations that 'oversell' the impact of the study and should be avoided. The authors restricted their analyses to ground beetles and based their conclusions on a design with many 'heterogeneities' - they should not draw conclusions for farmland biodiversity but stick to their system and report what they found. Although I understand the authors have previously stated that this is 'not practically feasible', the reason for this comment is simply to say that the authors should not oversell their findings.

Reviewer #2 (Public review):

Summary:

The reduction in a response to a specific stimulus after repeated exposures is called habituation. Alterations in habituation to noxious stimuli are associated with chronic pain in humans, however, the underlying molecular mechanisms involved are not clear. This study uses the nematode C. elegans to study genes and mechanisms that underlie habituation to a form of noxious stimuli based on heat, termed thermo-noxious stimuli. The authors previously showed that the Calcium/Calmodulin-dependent protein kinase (CMK-1) regulates thermo-nociceptive habituation in the nematode C. elegans. Although CMK-1 is a kinase with many known substrates, the downstream targets relevant for thermo-nociceptive habituation are not known. In this study, the authors use two different kinase screens to identify phosphorylation targets of CMK-1. One of the targets they identify is Calcineurin (TAX-6). The authors show that CMK-1 phosphorylates a regulatory domain of Calcineurin at a highly conserved site (S443). In a series of elegant experiments, the authors use genetic and pharmacological approaches to increase or decrease CMK-1 and Calcineurin signaling to study their effects on thermo-nociceptive habituation in C. elegans. They also combine these various approaches to study the interactions between these two signaling proteins. The authors use specific promoters to determine in which neurons CMK-1 and Calcineurin function to regulate thermo-nociceptive habituation. The authors propose a model based on their findings illustrating that CMK-1 and Calcineurin act mostly in different neurons to antagonistically regulate habituation to thermo-nociceptive stimuli in a complex manner.

Strengths:

(1) Given the conservation of habituation across phylogeny, identifying genes and mechanisms that underlie nociceptive habituation in C. elegans may be relevant for understanding chronic pain in humans.

(2) The identification of canonical CaM Kinase phosphorylation motifs in the substrates identified in the CMK-1 substrate screen validates the screen.

(3) The use of loss and gain of function approaches to study the effects of CMK-1 and Calcineurin on thermo-nociceptive responses and habituation is elegant.

(4) The ability to determine the cellular place of action of CMK-1 and Calcineurin using neuron-specific promoters in the nematode is a clear strength of the genetic model system.

Weaknesses:

(1) The manuscript begins by identifying Calcineurin as a direct substrate of CMK-1 but ends by showing that CMK-1 and Calcineurin mostly act in different neurons to regulate nociceptive habituation which disrupts the logical flow of the manuscript.

(2) The physiological relevance of CMK-1 phosphorylation of Calcineurin is not clear.

(3) It is not clear if Calcineurin is already a known substrate of CaM Kinases in other systems or if this finding is new.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors use genetic tools to ablate oligodendrocytes in the cerebellum during postnatal development. They show that the oligodendrocyte numbers return to normal post-weaning. Yet, the loss of oligodendrocytes during development seems to result in decreased synchrony of calcium transients in Purkinje neurons across the cerebellum. Further, there were deficits in social behaviors and motor coordination. Finally, they suppress activity in a subset of climbing fibers to show that it results in similar phenotypes in the calcium signaling and behavioral assays. They conclude that the behavioral deficits in the oligodendrocyte ablation experiments must result from loss of synchrony.

Strengths:

Use of genetic tools to induce perturbations in a spatiotemporally specific manner.

Weaknesses:

The main weakness in this manuscript is the lack of a cohesive causal connection between the experimental manipulation performed and the phenotypes observed. Though they have taken great care to induce oligodendrocyte loss specifically in the cerebellum and at specific time windows, the subsequent experiments do not address specific questions regarding the effect of this manipulation. Calcium transients in Purkinje neurons are caused to a large extent by climbing fibers, but there is evidence for simple spikes to also underlie the dF/F signatures (Ramirez and Stell, Cell Reports, 2016). Also, it is erroneous to categorize these calcium signals as signatures of "spontaneous activity" of Purkinje neurons as they can have dual origins. Further, the effect of developmental oligodendrocyte ablation on the cerebellum has been previously reported by Mathis et al., Development, 2003. They report very severe effects such as the loss of molecular layer interneurons, stunted Purkinje neuron dendritic arbors, abnormal foliations, etc. In this context, it is hardly surprising that one would observe a reduction of synchrony in Purkinje neurons (perhaps due to loss of synaptic contacts, not only from CFs but also from granule cells). The last experiment with the expression of Kir2.1 in the inferior olive is hardly convincing. In summary, while the authors used a specific tool to probe the role of developmental oligodendrocytes in cerebellar physiology and function, they failed to answer specific questions regarding this role, which they could have done with more fine-grained experimental analysis.

Reviewer #2 (Public review):

Summary:

This manuscript describes the role of the production of c-di-AMP on the chlamydial developmental cycle. Chlamydia are obligate intracellular bacterial pathogens that rely on eukaryotic host cells for growth. The chlamydial life cycle depends on a cell form developmental cycle that produces phenotypically distinct cell forms with specific roles during the infectious cycle. The RB cell form replicates amplifying chlamydia numbers while the EB cell form mediates entry into new host cells disseminating the infection to new hosts. Regulation of cell form development is a critical question in chlamydia biology and pathogenesis. Chlamydia must balance amplification (RB numbers) and dissemination (EB numbers) to maximize survival in its infection niche. The main findings In this manuscript show that overexpression of the dacA-ybbR operon results in increased production of c-di-AMP and early expression of the transitionary gene hctA and late gene omcB. The authors also knocked down the expression of the dacA-ybbR operon and reported a reduction in the expression of both hctA and omcB. The authors conclude with a model suggesting the amount of c-di-AMP determines the fate of the RB, continued replication, or EB conversion. Overall, this is a very intriguing study with important implications however the data is very preliminary and the model is very rudimentary and is not well supported by the data.

Describing the significance of the findings:

The findings are important and point to very exciting new avenues to explore the important questions in chlamydial cell form development. The authors present a model that is not quantified and does not match the data well.

Describing the strength of evidence:

The evidence presented is incomplete. The authors do a nice job of showing that overexpression of the dacA-ybbR operon increases c-di-AMP and that knockdown or overexpression of the catalytically dead DacA protein decreases the c-di-AMP levels. However, the effects on the developmental cycle and how they fit the proposed model are less well supported.

dacA-ybbR ectopic expression:

For the dacA-ybbR ectopic expression experiments they show that hctA is induced early but there is no significant change in OmcB gene expression. This is problematic as when RBs are treated with Pen (this paper) and (DOI 10.1128/MSYSTEMS.00689-20) hctA is expressed in the aberrant cell forms but these forms do not go on to express the late genes suggesting stress events can result in changes in the developmental expression kinetic profile. The RNA-seq data are a little reassuring as many of the EB/Late genes were shown to be upregulated by dacA-ybbR ectopic expression in this assay.

The authors also demonstrate that this ectopic expression reduces the overall growth rate but produces EBs earlier in the cycle but overall fewer EBs late in the cycle. This observation matches their model well as when RBs convert early there is less amplification of cell numbers.

dacA knockdown and dacA(mut)

The authors showed that dacA knockdown and ectopic expression of the dacA mutant both reduced the amount of c-di-AMP. The authors show that for both of these conditions, hctA and omcB expression is reduced at 24 hpi. This was also partially supported by the RNA-seq data for the dacA knockdown as many of the late genes were downregulated. However, a shift to an increase in RB-only genes was not readily evident. This is maybe not surprising as the chlamydial inclusion would just have an increase in RB forms and changes in cell form ratios would need more time points.

Interestingly, the overall growth rate appears to differ in these two conditions, growth is unaffected by dacA knockdown but is significantly affected by the expression of the mutant. In both cases, EB production is repressed. The overall model they present does not support this data well as if RBs were blocked from converting into EBs then the growth rate should increase as the RB cell form replicates while the EB cell form does not. This should shift the population to replicating cells.

Overall this is a very intriguing finding that will require more gene expression data, phenotypic characterization of cell forms, and better quantitative models to fully interpret these findings.

Reviewer #2 (Public review):

Summary:

The authors took a well-characterised (partly by them), important E3 ligase, in the anaphase-promoting complex, and decided to design peptide inhibitors for it based on one of the known interacting motifs (called D-box) from its substrates. They incorporate unnatural amino acids to better occupy the interaction site, improve the binding affinity, and lay foundations for future therapeutics - maybe combining their findings with additional target sites.

Strengths:

The paper is mostly strengths - a logical progression of experiments, very well explained and carried out to a high standard. The authors use a carefully chosen variety of techniques (including X-ray crystallography, multiple binding analyses, and ubiquitination assays) to verify their findings - and they impressively achieve their goals by honing in on tight-binders.

Weaknesses:

Some things are not explained fully and it would be useful to have some clarification. Why did the authors decide to model their inhibitors on the D-box motif and not the other two SLiMs that they describe? What exactly do they mean when they say their 'observation is consistent with the idea that high-affinity binding at degron binding sites on APC/C, such as in the case of the yeast 'pseudo-substrate' inhibitor Acm1, acts to impede polyubiquitination of the bound protein'? It's an interesting thing to think about, and probably the paper they cite explains it more but I would like to know without having to find that other paper.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors have explored the beneficial effect of autophagy upregulation in the context of HD pathology in a disease stage-specific manner. The authors have observed functional autophagy lysosomal pathway (ALP) and its machineries at the early stage in the HD mouse model, whereas impairment of ALP has been documented at the later stages of the disease progression. Eventually, the authors took advantage of the operational ALP pathway at the early stage of HD pathology, in order to upregulate ALP and autophagy flux by inhibiting mTORC1 in vivo, which ultimately reverted back to multiple ALP-related abnormalities and phenotypes. Therefore, this manuscript is a promising effort to shed light on the therapeutic interventions with which HD pathology can be treated at the patient level in the future.

Strengths:

The study has shown the alteration of ALP in the HD mouse model in a very detailed manner. Such stage-dependent in vivo study will be informative and has not been done before. Also, this research provides possible therapeutic interventions for patients in the future.

Weaknesses:

Some constructive comments and suggestions in order to reflect the key aspects and concepts better in the manuscript :

(1) The authors have observed lysosome number alteration in a temporally regulated disease stage-specific manner. In this scenario investigation of regulation, localization, and level of TFEB, the transcription factor required for lysosome biogenesis, would be interesting and informative.

(2) For the general scientific community better clarification of the short forms will be useful. For example, in line 97, page 4, AP full form would be useful. Also 'metabolized via autophagy' can be replaced by 'degraded via autophagy'.

(3) The nuclear vs cytosolic localization of HTT aggregates shown in Figure 2, are very interesting. The increase in cytosolic HTT aggregate formation at 10 months compared to 6 months probably suggests spatio-temporal regulation of aggregate formation. The authors could comment in a more elaborate manner, on the reason and impact of this kind of regulation of aggregate formation in the context of HD pathology.

(4) In this manuscript, the authors have convincingly shown that mTOR inhibition is inducing autophagy in the HD mouse model in vivo. On the other hand, mTOR inhibition would also reduce overall cellular protein translation. This aspect of mTOR inhibition can also potentially contribute to the alleviation of disease phenotype and disease symptoms by reducing protein overload in HD pathology. The authors' comments regarding this aspect would be appreciated.

(5) The authors have shown nuclear inclusion formation and aggregation of mHTT and also commented on its potential removal with the UPS system (proteasomal degradation) in vivo. As there is also a reciprocal relationship present between autophagy and proteasomal machineries, upon upregulation of autophagy machinery by mTOR inhibition proteasomal activity may decrease. How nuclear proteasomal activity increases to tackle nuclear mHTT IBs, would be interesting to understand in the context of HD pathology. Comments from the authors in this aspect would clarify the role of multiple degradation pathways in handling mutant HTT protein in HD pathology.

(6) For the treatment of neurodegenerative disorders taking the temporal regulation into consideration is extremely important, as that will determine the success rate of the treatments in patients. The authors in this manuscript have clearly discussed this scenario. However, for neurodegenerative disordered patients, in most cases, the symptom manifestation is a late onset scenario. In that case, it will be complicated to initiate an early treatment regime in HD patients. If the authors can comment on and discuss the practicality of the early treatment regime for therapeutic purposes that would be impactful.

Reviewer #2 (Public review):

Summary:

The paper 'The electrogenicity of the Na+/K+-ATPase poses challenges for computation in highly active spiking cells' by Weerdmeester, Schleimer, and Schreiber uses computational models to present the biological constraints under which electrocytes-specialized highly active cells that facilitate electro-sensing in weakly electric fish-may operate. The authors suggest potential solutions these cells could employ to circumvent these constraints.

Electrocytes are highly active or spiking (greater than 300Hz) for sustained periods (for minutes to hours), and such activity is possible due to an influx of sodium and efflux of potassium ions into these cells for each spike. This ion imbalance must be restored after each spike, which in electrocytes, as with many other biological cells, is facilitated by the Na-K pumps at the expense of biological energy, i.e., ATP molecules. For each ATP molecule the pump uses, three positively charged sodium ions from the intracellular space are exchanged for two positively charged potassium ions from the extracellular volume. This creates a net efflux of positive ions into the extracellular space, resulting in hyperpolarized potentials for the cell over time. This does not pose an issue in most cells since the firing rate is much slower, and other compensatory mechanisms and other pumps can effectively restore the ion imbalances. In electrocytes of weakly electric fish, however, that operate under very different circumstances, the firing rate is exceptionally high. On top of this, these cells are also involved in critical communication and survival behaviors, emphasizing their reliable functioning.

In a computation model, the authors test four increasingly complex solutions to the problem of counteracting the hyperpolarized states that occur due to continuous NaK pump action to sustain baseline activity. First, they propose a solution for a well-matched Na leak channel that operates in conjunction with the NaK pump, counteracting the hyperpolarizing states naturally. Additionally, their model shows that when such an orchestrated Na leak current is not included, quick changes in the firing rates could have unexpected side effects. Secondly, they study the implication of this cell in the context of chirps - a means of communication between individual fishes. Here, an upstream pacemaking neuron entrains the electrocyte to spike, which ceases to produce a so-called chirp - a brief pause in the sustained activity of the electrocytes. In their model, the authors show that it is necessary to include the extracellular potassium buffer to have a reliable chirp signal. Thirdly, they tested another means of communication in which there was a sudden increase in the firing rate of the electrocyte followed by a decay to the baseline. For reliable occurrence of this, they emphasize that a strong synaptic connection between the pacemaker neuron and the electrocyte is warranted. Finally, since these cells are energy-intensive, they hypothesize that electrocytes may have energy-efficient action potentials, for which their NaK pumps may be sensitive to the membrane voltages and perform course correction rapidly.

Strengths:

The authors extend an existing electrocyte model (Joos et al., 2018) based on the classical Hodgkin and Huxley conductance-based models of Na and K currents to include the dynamics of the NaK pump. The authors estimate the pump's properties based on reasonable assumptions related to the leak potential. Their proposed solutions are valid and may be employed by weakly electric fish. The authors explore theoretical solutions that compound and suggest that all these solutions must be simultaneously active for the survival and behavior of the fish. This work provides a good starting point for exploring and testing in in vivo experiments which of these proposed solutions the fish use and their relative importance.

Weaknesses:

The modeling work makes assumptions and simplifications that should be listed explicitly. For example, it assumes only potassium ions constitute the leak current, which may not be true as other ions (chloride and calcium) may also cross the cell membrane. This implies<br /> that the leak channels' reversal potential may differ from that of potassium. Additionally, the spikes are composed of sodium and potassium currents only and no other ion type (no calcium). Further, these ion channels are static and do not undergo any post-translational modifications. For instance, a sodium-dependent potassium pump could fine-tune the potassium leak currents and modulate the spike amplitude (Markham et al., 2013).

This model considers only NaK pumps. In many cell types, several other ion pumps/exchangers/symporters are simultaneously present and actively participate in restoring the ion gradients. It may be true that only NaK pumps are expressed in the weakly electric fish Eigenmannia virescens. This limits the generalizability of the results to other cell types. While this does not invalidate the results of the present study, biological processes may find many other solutions to address the non-electroneutral nature of the NaK pump. For example, each spike could include a small calcium ion influx that could be buffered or extracted via a sodium-calcium exchanger.

Finally, including testable hypotheses for these computational models would strengthen this work.

Reviewer #2 (Public review):

Using multimodal closed-loop behavior and activity monitoring in the neocortex, Solyga and Keller show that the auditory cortex computes the deviation of current sensory input from expectations. Interestingly, in addition, mismatch responses within the auditory stream are non-linearly influenced by concurrent sensorimotor error computations in the visual pathway. These results suggest that non-hierarchical interactions (lateral relational cross-talk) must be considered when analyzing cortical models based on predictive processing. In my opinion, this is a fundamental study that addresses the question of hierarchical vs. no-hierarchical interactions across neocortical areas. Overall, I find the experiments elegantly designed, and the results robust, providing compelling evidence for non-hierarchical interactions across neocortical areas, and more specifically of exchange of sensorimotor prediction error signals across modalities. The authors thoroughly addressed the concerns raised. In my opinion, this has substantially strengthened the manuscript, enabling much clearer interpretation of the results reported.

Reviewer #2 (Public review):

Summary:

This paper focuses on understanding the behavioral and neural basis of regime shift detection, a common yet hard problem that people encounter in an uncertain world. Using a regime-shift task, the authors examined cognitive factors influencing belief updates by manipulating signal diagnosticity and environmental volatility. Behaviorally, they have found that people demonstrate both over and under-reaction to changes given different combinations of task parameters, which can be explained by a unified system-neglect account. Neurally, the authors have found that the vmPFC-striatum network represents current belief as well as belief revision unique to the regime detection task. Meanwhile, the frontoparietal network represents cognitive factors influencing regime detection i.e., the strength of the evidence in support of the regime shift and the intertemporal belief probability. The authors further link behavioral signatures of system neglect with neural signals and have found dissociable patterns, with the frontoparietal network representing sensitivity to signal diagnosticity when the observation is consistent with regime shift and vmPFC representing environmental volatility, respectively. Together, these results shed light on the neural basis of regime shift detection especially the neural correlates of bias in belief update that can be observed behaviorally.

Strengths:

(1) The regime-shift detection task offers a solid ground to examine regime-shift detection without the potential confounding impact of learning and reward. Relatedly, the system-neglect modeling framework provides a unified account for both over or under-reacting to environmental changes, allowing researchers to extract a single parameter reflecting people's sensitivity to changes in decision variables and making it desirable for neuroimaging analysis to locate corresponding neural signals.

(2) The analysis for locating brain regions related to belief revision is solid. Within the current task, the authors look for brain regions whose activation covary with both current belief and belief change. Furthermore, the authors have ruled out the possibility of representing mere current belief or motor signal by comparing the current study results with two other studies. This set of analyses is very convincing.

(3) The section on using neuroimaging findings (i.e., the frontoparietal network is sensitive to evidence that signals regime shift) to reveal nuances in behavioral data (i.e., belief revision is more sensitive to evidence consistent with change) is very intriguing. I like how the authors structure the flow of the results, offering this as an extra piece of behavioral findings instead of ad-hoc implanting that into the computational modeling.

Weaknesses:

(1) The authors have presented two sets of neuroimaging results, and it is unclear to me how to reason between these two sets of results, especially for the frontoparietal network. On one hand, the frontoparietal network represents belief revision but not variables influencing belief revision (i.e., signal diagnosticity and environmental volatility). On the other hand, when it comes to understanding individual differences in regime detection, the frontoparietal network is associated with sensitivity to change and consistent evidence strength. I understand that belief revision correlates with sensitivity to signals, but it can probably benefit from formally discussing and connecting these two sets of results in discussion. Relatedly, the whole section on behavioral vs. neural slope results was not sufficiently discussed and connected to the existing literature in the discussion section. For example, the authors could provide more context to reason through the finding that striatum (but not vmPFC) is not sensitive to volatility.

(2) More details are needed for behavioral modeling under the system-neglect framework, particularly results on model comparison. I understand that this model has been validated in previous publications, but it is unclear to me whether it provides a superior model fit in the current dataset compared to other models (e.g., a model without \alpha or \beta). Relatedly, I wonder whether the final result section can be incorporated into modeling as well - i.e., the authors could test a variant of the model with two \betas depending on whether the observation is consistent with a regime shift and conduct model comparison.

Reviewer #3 (Public review):

Summary:

In this study, the authors have attempted to demonstrate a critical role for the cytoskeletal scaffold protein Ezrin, in the upstream regulation of EGFR/AKT/MTOR signaling. They show that in the absence of Ezrin, ligand-induced EGFR trafficking and activation at the endosomes is perturbed, with decreased endosomal recruitment of the TSC complex, and a corresponding decrease in AKT/MTOR signaling.

Strengths:

The authors have used a combination of novel imaging techniques, as well as conventional proteomic and biochemical assays to substantiate their findings. The findings expand our understanding of the upstream regulators of the EGFR/AKT MTOR signaling and lysosomal biogenesis, appear to be conserved in multiple species, and may have important implications for the pathogenesis and treatment of diseases involving endo-lysosomal function, such as diabetes and cancer, as well as neuro-degenerative diseases like macular degeneration. Furthermore, pharmacological targeting of Ezrin could potentially be utilized in diseases with defective TFEB/TFE3 functions like LSDs. While a majority of the findings appear to support the hypotheses, there are substantial gaps in the findings that could be better addressed. Since Ezrin appears to directly regulate MTOR activity, the effects of Ezrin KO on MTOR-regulated, TFEB/TFE3 -driven lysosomal function should be explored more thoroughly. Similarly, a more convincing analysis of autophagic flux should be carried out. Additionally, many immunoblots lack key controls (Control IgG in CO-Ips) and many others merit repetition to either improve upon the quality of the existing data, validate the findings using orthogonal approaches or to provide a more rigorous quantitative assessment of the findings, as highlighted in the recommendation for authors.

Comments on revisions:

The authors have satisfactorily addressed most of the concerns raised in the prior version, and have significantly improved upon the overall findings in the revised version.

Reviewer #2 (Public review):

This study investigates the cortical circuitry at the mesoscopic level of cortical columns in the human secondary visual cortex (V2) using high-resolution fMRI at ultra-high field strength (7T). The findings confirm the columnar organization of color-selective thin and disparity-selective thick stripes, a result previously demonstrated and replicated in human fMRI research. However, this study adds a novel layer of analysis by examining cortical depth, providing insights into feedforward and feedback connections to and from V2. Furthermore, examining texture selectivity in V2 showed no evidence of a columnar structure when compared to color- and disparity-selective activation clusters. Interestingly, texture selectivity in V2 was most pronounced in deeper cortical layers, with significant feedback connectivity from V4. The authors conclude that local columnar circuitry plays a crucial role in color and disparity processing within V2, while texture selectivity is driven by feedback modulation. This research underscores the potential of high-resolution human fMRI to explore the local circuitry of the cortex at the mesoscopic scale.

However, I still have a few comments that I would like to be addressed:

(1) In lines 401-403, the authors state that differential BOLD responses can significantly enhance the laminar specificity. Differential contrasts indeed have the potential to reduce macrovascular contributions that are unspecific to both experimental conditions, which was already discussed in the literature (e.g., Yacoub et al., 2008, High-field fMRI unveils orientation columns in humans). This might be especially true for the pial vasculature that drains a larger surface area of the cortex, e.g., multiple columns, which is probably the key factor that enables cortical column mapping using differential BOLD contrasts despite the relatively large spatial point spread function of the BOLD response. However, this may differ for laminar analyses, where neuronal and vascular responses from intracortical and pial veins might be harder to disentangle. It would, therefore, be advisable to tone down this statement somewhat since it could imply that laminar specificity can be readily achieved with GE-BOLD, while this remains an active area of research. This is not to say that the present results are incorrect, but the broader implications of this statement should be cautiously framed.

(2) Looking at Figure 3, one might also argue (excluding responses from V4) that statistically significant differences in selectivity are only observed where the cortical profiles generally show higher response levels. Could this be simply due to varying signal-to-noise ratios (SNR) achieved by different contrasts (color, disparity, texture)?

(3) In lines 480-484, the authors state that twenty blocks for each stimulus condition should be sufficient to investigate within-subject effects. It would be helpful if they could elaborate on the basis for this claim. High-resolution fMRI is typically limited by low temporal signal-to-noise ratio (tSNR), and extensive averaging is often required to achieve sufficient signal. Clarifying the rationale behind this assertion would strengthen the argument.

Reviewer #2 (Public review):

Summary:

Plectin is a cytolinker that associates with cytoskeletal and intercellular junction proteins and is essential for epithelial integrity and cell migration. Previous reports showed that PLEC regulates tumor growth and metastasis in different cancers. In this manuscript, the authors describe PLEC as a target in initiation and growth of HCC. They show that inhibiting PLEC reduced tumorigenesis in different in vitro and in vivo HCC models, including in a xenograft model, DEN model, oncogene-induced HCC model and a lung metastasis model. A drug PST had similar effects, a purported Plectin inhibitor, suggesting that PLEC inhibition could be a tumor prevention or treatment strategy. Mechanistically, the authors show that inhibiting PLEC results in a disorganized cytoskeleton, deficiency in cell migration, and changes in cancer-relevant signaling pathways. This study demonstrates the importance of understanding mechanobiology of HCC for the development of new treatment strategies.

Strengths:

(1) This study used a variety of in vivo models to explore the role of Plectin in HCC formation and metastasis, which extend beyond the cell line-based studies reported in prior research.<br /> (2) Blocking PLEC disrupts pathways that promote tumors and cell migration, thus preventing tumor progression.<br /> (3) Overall, the anti-cancer phenotype is promising, strengthening the important role of PLEC and related factors in tumor growth and metastasis.

Weaknesses:

(1) There is limited novel mechanistic insights as the effect of inhibiting PLEC on the cytoskeleton, cell migration and related signaling pathways have previously been reported.<br /> (2) The results associated with PST, should be interpretated with caution. Although it is reported as an inhibitor of PLECTIN, and the phenotypes and pathways affected are similar to the knock-out, additional research is needed to support whether it will be safe and specific in treating or preventing HCC.

Reviewer #3 (Public review):

Summary:

Tanaka and colleagues addressed the role of the C-C chemokine receptor 4 (CCR4) in early atherosclerotic plaque development using ApoE-deficient mice on a standard chow diet as a model. Because several CD4+ T cell subsets express CCR4, they examined whether CCR4-deficiency alters the immune response mediated by CD4+ T cells. By histological analysis of aortic lesions, they demonstrated that the absence of CCR4 promoted the development of early atherosclerosis, with heightened inflammation linked to increased macrophages and pro-inflammatory CD4+ T cells, along with reduced collagen content. Flow cytometry and mRNA expression analysis for identifying CD4+ T cell subsets showed that CCR4 deficiency promoted higher proliferation of pro-inflammatory effector CD4+ T cells in peripheral lymphoid tissues and accumulation of Th1 cells in the atherosclerotic lesions. Interestingly, the increased pro-inflammatory CD4+ T cell response occurred despite the expansion of T CD4+ Foxp3+ regulatory cells (Tregs), found in higher numbers in lymphoid tissues of CCR4-deficient mice, suggesting that CCR4 deficiency interfered with Treg's regulatory actions. In addition, CCR4 deficiency induced an augmented Th1/Treg ratio in the aortic lesions. The CCR4-mediated mechanisms underlying the control of early inflammation and atherosclerosis development were not completely elucidated. In vitro studies suggest that CCR4 expression in Tregs plays a role in controlling DC activation and, in turn, the extent of CD4+T cell activation and proliferation. Dependence on CCR4 expression for Treg migration to the atherosclerotic aorta was not proved. The findings contrast with earlier studies in a murine model of advanced atherosclerosis, where CCR4 deficiency did not alter the development of the aortic lesions. The authors included a thoughtful discussion about hypothetical mechanisms explaining these contrasting results, including putative differences in the role played by the CCL17/CCL22-CCR4 axis along the stages of atherosclerosis development in this murine model.

Major strengths:

• Demonstration of CCR4 deficiency's impact on early atherosclerosis. CCR4 deficiency effects on the early atherosclerosis development in the Apoe-/-mice model were demonstrated by a quantitative analysis of the lesion area, inflammatory cell content and the expression profile of several pro- and anti-inflammatory markers.<br /> • Analysis of the T CD4+ response in various lymphoid tissues (peripheral and para-aortic lymph nodes and spleen) and the atherosclerotic aorta during the early phase of atherosclerosis in the Apoe-/-mice model. This analysis, combining flow cytometry and mRNA expression, showed that CCR4 deficiency enhanced T CD4+ cell activation, favouring the amplification of the typical biased Th1-mediated inflammatory response observed in the lymphoid tissues of hypercholesterolemic mice.<br /> • Treg transference experiments. Transference of Treg from Apoe-/- or Ccr4-/- Apoe-/- mice to Apoe-/- mice under a standard chow diet was useful for addressing the relevance of CCR4 expression on Tregs for the atheroprotective effect of this regulatory T cell subset during early atherosclerosis.

Major weaknesses:

• The effect of CCR4 deficiency on the Th1/Th17 balance was not evaluated. Although the role of Th17 cells in atherosclerosis remains controversial, RORγt+ cells constituted, on average, more than 10% of the effector TCD45+CD3+CD4+ lymphocytes in the aorta of Apoe-/- mice (Fig 4H). Changes in the Th1/Th17 balance in lymphoid tissues and aortic lesions may influence the type and functional properties of inflammatory cells recruited to the atherosclerotic aorta.

• Lack of in vivo evidence for Treg suppressive effects on DC activation. The proposed CCR4 requirement for the Treg suppressive activity on DC activation is supported by in vitro co-culture assays, in which CCR4-deficiency partially reverted Treg regulatory actions. Higher expression of CD86, a DC activation marker, was found in spleen DCs from Ccr4-/- Apoe-/- mice compared to Apoe-/- mice (Supplementary Fig 5), which would be worth commenting on and discussing.

• Methodological limitations. Controls in flow cytometry analysis were suboptimal (no viability and doublets were checked) which may have introduced artefacts, especially when measuring less-represented cell populations within complex samples. In addition, assessing Treg migration to the aorta in atherosclerotic mice faced methodological limitations that hindered statistical comparisons between Tregs from Apoe-/- and Ccr4-/- Apoe-/- mice, leading to inconclusive results. The dependence on CCR4 expression for Treg migration to the atherosclerotic aorta was not established.

• Treg transference experiments did not allow the detection of a reduction in the aortic lesion area by transferred CCR4 expressing Tregs (comparison between saline and Apoe-/- Tregs groups). Using Apoe-/- mice as recipients, the CCR4-dependent protective effect of Tregs was mostly evidenced by analysis of aortic inflammation, which was valuable. When using Ccr4-/- Apoe-/- mice as recipients, analysis of aortic inflammation was not mentioned.

Study limitations:

This investigation has some limitations. Current tools for single-cell characterization have revealed the phenotypic heterogeneity and dynamics of aortic leukocytes, including T cells, which are among the principal aortic leukocytes found in mouse and human atherosclerotic lesions (doi:10.1161/CIRCRESAHA.117.312513). The flow cytometry analysis applied in this study cannot distinguish the generation of particular phenotypes within T CD4+ subsets, including putative phenotypes of no-suppressive T cells expressing low levels of Foxp3, as seems could occur in other chronic inflammatory disorders (doi: 10.1038/nm.3432; doi: 10.1172/JCI79014). Limitations due to the use of a complete CCR4 knockout mouse and putative differences in CCR4-mediated mechanisms along atherosclerosis stages and in human atherosclerosis were commented on by the authors in the discussion.

Global Impact:

This work opens the way for a deeper analysis of the contribution of CCR4 and its ligands to the activation and differentiation of T CD4+ lymphocytes during atherosclerosis development, with these lymphocytes being fundamental players in the generation of pro-atherogenic and anti-atherogenic immune responses. Differences in the mechanisms mediated by the CCL17/CCL22-CCR4 axis among early and advanced atherosclerosis highlight the complex landscape to examine and validate in human samples and the need to achieve a deep knowledge for identifying genuine and safe targets capable of promoting protective anti-atherogenic immune responses.

Reviewer #2 (Public review):

Summary:

Using C. elegans as a model, the authors present an interesting story demonstrating a new regulatory connection between olfactory neurons and the digestive system. Mechanistically, they identified key factors (NSY-1, STR-130 et.al) in neurons, as well as critical 'signaling factors' (INS-23, DAF-2) that bridge different cells/tissues to execute the digestive shutdown induced by poor-quality food (Staphylococcus saprophyticus, SS).

Strengths:

The conclusions of this manuscript are mostly well supported by the experimental results shown.

Weaknesses:

Several issues could be addressed and clarified to strengthen their conclusions.

(1) The word "olfactory" should be carefully used and checked in this manuscript. Although AWCs are classic olfactory neurons in C. elegans, no data in this manuscript supports the idea that olfactory signals from SS drive the responses in the digestive system. To validate that it is truly olfaction, the authors may want to check the responses of worms (e.g. AWC, digestive shutdown, INS-23 expression) to odors from SS.

(2) In line 113, what does "once the digestive system is activated" mean? The authors need to provide a clearer statement about 'digestive activation' and 'digestive shutdown'.

(3) No control data on OP50. This would affect the conclusions generated from Figures 2A, 2B, 2D, 3B, 3C, 3G, 4D-G, 5D-E, 6B-D.

(4) Do the authors know which factors are released from AWC neurons to drive the digestive shutdown?

Reviewer #2 (Public review):

Summary:

This study aimed to investigate changes in neural responses over time after acute stress and their association with real-life stress. To this end, functional MRI data was collected from 3 tasks (Oddball, 2-back, Associative retrieval) early and late following stress and control conditions. Emotional ratings during a stressful week before an exam and a non-stressful week without an exam were used to index real-world stress. In total, data from 70 individuals were used for the analyses in the paper. Results showed increased oddball related activation early after stress whereas activation to the associative retrieval was reduced across early and late trials following stress compared with control. Brain activation during the oddball task after stress contrasted against control correlated with the index used to measure stress in the real-world. This is a very ambitious study and the findings that stress has opposite effects on the oddball and the associative retrieval tasks is new. However, I am not convinced that brain responses are correlated with real-world stress from the results presented in the paper. I also have several other concerns listed below.

Strengths:

The study uses a unique design based on hypothesis firmly grounded in theories of stress related brain function. Large amounts of data are collected for all of the 70 participants included in the analyses and the hypotheses tested using paired tests have strong statistical power. Data collection methods are sound aiming to reduce stress induced by being in the scanner environment for the first time and reducing variation in cortisol due to circadian rhythm.

Weaknesses:

An important argument in the paper is that neural responses associated with stress in the lab correspond to stress in real life. This conclusion is based on a single correlation analysis. This is weak evidence because the correlation is based on 70 individuals and may be driven by outliers. In fact, the correlation between the difference in stress-related SN activation (Stress-Control) and real life stress residual is likely to be driven by outliers. In fig 5b, there are 3 persons with SN values of around 2, which is twice as much as the fourth highest value. There is also 1 person with a Real life stress residual of -3 or -4, which is three to four times as much as the person with the second lowest value. These 4 outliers should be removed before calculating the correlation coefficient. Also, no power analysis is presented in the paper showing what effect size is needed for significant results given a sample size of 70.

It is not clear why the activation maps from the tasks performed in the scanner are referred to as the SN, ECN, and DMN. They are discussed as if they were resting state networks. They are however not resting state networks because they are the results of contrasting two task conditions to each other and not the results from correlating BOLD time-series data from different regions within subjects. Even though masks corresponding to SN, ECN, and DMN are used to calculate means of all voxels, I think these contrasts should be referred to as the tasks that were used to evoke them. It becomes misleading to call them networks which usually refers to nodes and edges in fMRI studies. The first scan was a resting state scan, but these data are not presented in the paper.

Introduction<br /> In the introduction it is said that there are genomically driven effects of cortisol 1 to 2 hours after stress. This is repeated in the discussion: "[the late stress phase] is thought to be dominated by genomically driven effects of glucocorticoids". (There is no reference to this statement however.) This idea, that gene expression should only be regulated by corticosteroids following stress seems unrealistic. The increase in cortisol was only around 60% from baseline in the current study which seems to be similar to other studies. This means that the baseline cortisol level is far from zero. Therefore, effects of cortisol on gene expression must occur all the time and be tightly regulated by circadian clocks. To propose that genomically driven effects of cortisol only exist 1 to 2 hours following stress is therefore too simplistic.

In the last paragraph, it says that n=83. However, the final sample consists of 70 people. Correct this number.

Methods<br /> The EMA data analysis is difficult to understand. Why are the residuals used instead of means for example? I could not understand how the residual values used in the analysis should be interpreted from the way this section was written. Therefore, I cannot judge whether the index is valid or reliable. Using mean values is more common than using residuals when investigating individual differences in stress responses. The use of residuals needs justification and clarification. The results from an analysis using mean values should also be reported.

How was AUCi calculated? What software was used to calculate AUCi?

How was the mediation analysis performed? The only information I found was: "We additionally ran separate models with an interaction term modelled for neural activity in the targeted ROI's to examine the relationship between task performance and neural responses, with random slopes and intercepts also modelled for ROI activity." This is not how mediation analyses are done conventionally. It is common to use structural equation modelling or a series of regression analyses. What is meant by separate models? Was a reduced model compared to a full model with an interaction term? In this case, this is not a mediation analysis. I think the term moderation is better to describe this analysis.

Reviewer #2 (Public review):

Summary:

Hiramatsu et al. investigated how cognate neurotransmitter receptors with antagonizing downstream effects localize within neurons when co-expressed. They focus on mapping the dopaminergic Dop1R1 and Dop2R receptors, corresponding to the mammalian D1- and D2-like dopamine receptors, which have opposing effects on intracellular cAMP levels, in neurons of the Drosophila mushroom body (MB). To visualize specific receptors in single neuron types within the crowded MB neuropil, the authors use existing dopamine receptor alleles tagged with 7 copies of split GFP to target the reconstitution of GFP tags specifically in the neurons of interest, providing a readout of receptor localization.

The authors demonstrate that both Dop1R1 and Dop2R are enriched, to differing degrees, in the axonal compartments of Kenyon cells cholinergic presynaptic inputs and in different dopamine neurons (DANs) that project axons to the MB. Co-localization studies of dopamine receptors with the presynaptic marker Brp suggest that Dop1R1, and to a greater extent Dop2R, localize near release sites. This pattern in DANs suggests Dop1R1 and Dop2R serve as dual-feedback autoreceptors. Finally, they provide evidence that the balance of Dop1R1 and Dop2R in the axons of two different DAN populations is differentially modulated by starvation, which plays a role in regulating appetitive behaviors.

In their revised manuscript, Hiramatsu et al. revisited the localization and functional integrity of Dop1R1 and Dop2R within the Drosophila mushroom body. This revision strengthens their claims with new high-resolution imaging data and additional behavioral assays, supporting the functional integrity of 7X split GFP-tagged receptors and their distinct localizations within neural circuits.

The revised manuscript by Hiramatsu et al. demonstrates substantial improvements in experimental design and data presentation, effectively addressing concerns raised during the initial review. The addition of advanced imaging techniques and behavioral data confirms the functionality of tagged receptors, while providing deeper insights into their spatial and functional dynamics within neural circuits modulating responses to environmental changes like starvation. This study makes an important contribution to neuroscience, enhancing our understanding of dopamine receptor distribution in circuits underlying learning and memory.

Strengths:

The authors use reconstitution of GFP fluorescence of split GFP tags integrated at the endogenous locus of dopamine receptors, providing a precise readout of receptor localization. This method preserves endogenous transcriptional and post-transcriptional regulation, a critical feature for protein localization studies.

The choice of the Drosophila mushroom body as a model system is excellent, as it is well-studied, its connectome is carefully reconstructed, and its role in behaviors and associative memory enables linking receptor localization patterns to circuit function and behavior. This approach allows the authors to demonstrate that antagonizing dopamine receptors can act as autoreceptors within the axonal compartments of MB-innervating DANs. Moreover, they show that starvation differentially modulates the balance of these receptors in distinct DANs, highlighting the role of this regulation in circuit function and behavior.

The incorporation of higher-resolution Airyscan microscopy and functional assays in the revision provide evidence that tagged receptors retain functionality and predominantly localize at presynaptic sites within Kenyon cells and DANs. These findings support the dual autoreceptor feedback model proposed.

Weaknesses:

While the revision significantly strengthens the manuscript, the absence of specific antibodies against these receptors remains a limitation. This is understandable given the challenges of generating antibodies against such proteins. However, the use of more direct validation methods, such as specific antibodies (if available), and employing higher-resolution techniques like expansion microscopy, could further validate and enhance the robustness of the findings.

Reviewer #2 (Public review):

The authors evaluate spectral changes in electroencephalography (EEG) data as a function of the congruency of audio and visual information associated with biological motion (BM) or non-biological motion. The results show supra-additive power gains in the neural response to gait dynamics, with trials in which audio and visual information was presented simultaneously producing higher average amplitude than the combined average power for auditory and visual conditions alone. Further analyses suggest that such supra-additivity is specific to BM and emerges from temporoparietal areas. The authors also find that the BM-specific supra-additivity is negatively correlated with autism traits.

Reviewer #2 (Public review):

Nichols et al studied the role of axon guidance molecules and their receptors and how these work as long-range and/or local cues, using in-vivo time-lapse imaging in C. elegans. They found that the Netrin axon guidance system, work in different modes when acting as a long-range (chemotaxis) cue vs local cue (haptotaxis). As an initial context, they take advantage of the postembryonic-born neuron, PDE, to understand how its axon grows and then is guided into its target. They found that this process occurs in various discrete steps, during which the growth cone migrates and pauses at specific structures, such as the vSLNC. The role of the UNC-6/Netrin and UNC-40/DCC axon guidance ligand-receptor pair was then looked at in terms of its requirement for (1) initial axon outgrowth direction, (2) stabilization at the intermediate target, (3) directional branching from the sublateral region or (4) ventral growth from intermediate target to the VNC. They found that each step is disrupted in the unc-6/Netrin and unc-40/DCC mutants and observed how the localization of these proteins changed during the process of axon guidance in wild type and mutant contexts. These observations were further supported by analysis of a mutant important for the regulation of Netrin signaling, the E3 ubiquitin ligase madd-2/Trim9/Trim67. Remarkably, the authors identified that this mutant affected axonal adhesion and stabilization, but not directional growth. Using membrane-tethered UNC-6 to specific localities, they then found this to be a consequence of the availability of UNC-6 at specific localities within the axon growth path. Altogether, this data and in-vivo analysis provide compelling evidence of the mechanistic foundation of Netrin-mediated axon guidance and how it works step by step.

The conclusions are well-supported, with both imaging and quantification of each step of axon guidance and localization of UNC-6 and UNC-40. Using a different type of neuron to validate their findings further supports their conclusions and strengthens their model. They also probe the role of the axon guidance ligand-receptor pair SLT-1/Slit and SAX-3/ROBO in this process and find it to work in parallel to UNC-6. This work sets up the stage for future analysis of other axon guidance molecules or regulators using time-lapse in-vivo imaging to better understand their role as long-range and/or local cues.

Reviewer #2 (Public review):

Summary:

Members of a conserved family of flavin-containing monooxygenases (FMOs) play key roles in lifespan extension induced by diet restriction and hypoxia. In C. elegans, fmo-2 has received the majority of attention, but there are multiple fmo genes in both worms and mammals, and how overlapping or distinct the functional roles of these paralogs are remains unclear. Here Tuckowski et al. identify that a new family member, fmo-4, is also a positive modulator of lifespan. Based on differential requirements of fmo-2 and fmo-4 in stress resistance and lifespan extension paradigms, however, the authors conclude that fmo-4 acts through mechanisms that are distinct from fmo-2. Ultimately, the authors place fmo-2 genetically within a pathway involving atf-6, calreticulin, the IP3 receptor, and mitochondrial calcium uniporter, which was previously shown to link ER calcium homeostasis to mitochondrial homeostasis and longevity. The authors thus achieve their overarching aim to reveal that different FMO family members regulate stress resistance and lifespan through distinct mechanisms. Furthermore, because the known enzymatic activity of FMOs involves oxygenating xenobiotic and endogenous metabolites, these findings highlight a potential new link between redox/metabolic homeostasis and ER-mitochondrial calcium signaling.

Strengths:

The authors demonstrate links between multiple conserved life-extending signaling pathways and fmo-4, expanding both the significance and mechanistic diversity of FMO-family genes in aging and stress biology.

The authors use genetics to discover an interesting and unanticipated new link between FMOs and calcium pathways known to regulate lifespan.

The genetic epistasis patterns for lifespan and stress resistance phenotypes are generally clean and compelling.

Weaknesses:

The authors achieve a necessary and valuable first step with regard to linking FMO-4 to calcium homeostasis, but the mechanisms involved remain preliminary at this stage. Specifically, the genetic interactions between fmo-4 and conserved mediators of calcium transport and signaling are convincing, but a putative molecular mechanism by which the activity of FMO-4 would alter subcellular calcium transport remains unclear and potentially indirect. The authors effectively highlight this gap as a key pursuit for subsequent studies.

The authors have shown that carbachol and EDTA produce the expected effects on a cytosolic calcium reporter in neurons, supporting the utility of the chemical approach in general, but validating that carbachol, EDTA and fmo-4 itself have an impact on calcium in the tissues and subcellular compartments relevant to the lifespan phenotypes would still be valuable in supporting the overall model. Notably, however, the hypodermal-specific role of FMO-4 suggests potential cell non-autonomous regulation of lifespan, such that this pathway may ultimately involve complex inter-cellular signaling that would necessitate substantially more time and effort.

Employing mutants and more sophisticated genetic tools for modulating calcium transport or signaling (in addition to RNAi) would strengthen key conclusions and/or help to elucidate tissue- or age-specific aspects of the proposed mechanism.

Reviewer #2 (Public review):

Summary:

This manuscript provides experimental evidence on circadian behavioural cycles in Antarctic krill. The krill were obtained directly from krill fishing vessels and the experiments were carried out on board using an advanced incubation device capable of recording activity levels over a number of days. A number of different experiments were carried out where krill were first exposed to simulated light:dark (L:D) regimes for some days followed by continuous darkness (DD). These were carried out on krill collected during late autumn and late summer. A further set of experiments was performed on krill across three different seasons (summer, autumn, winter), where incubations were all DD conditions. Activity was measured as the frequency by which an infrared beam close to the top of the incubation tube was broken over unit time. Results showed that patterns of increased and decreased activity that appeared synchronised to the LD cycle persisted during the DD period. This was interpreted as evidence of the operation of an internal (endogenous) clock. The amplitude of the behavioural cycles decreased with time in DD, which further suggests that this clock is relatively weak. The authors argued that the existence of a weak endogenous clock is an adaptation to life at high latitudes since allowing the clock to be modulated by external (exogenous) factors is an advantage when there is a high degree of seasonality. This hypothesis is further supported by seasonal DD experiments which showed that the periodicity of high and low activity levels differed between seasons.

Strengths

Although there has been a lot of field observations of various circadian type behaviour in Antarctic krill, relatively few experimental studies have been published considering this behaviour in terms of circadian patterns of activity. Krill are not a model organism and obtaining them and incubating them in suitable conditions are both difficult undertakings. Furthermore, there is a need to consider what their natural circadian rhythms are without the overinfluence of laboratory-induced artefacts. For this reason alone, the setup of the present study is ideal to consider this aspect of krill biology. Furthermore, the equipment developed for measuring levels of activity is well-designed and likely to minimise artefacts.

Weaknesses

I have little criticism of the rationale for carrying out this work, nor of the experimental design. Nevertheless, the manuscript would benefit from a clearer explanation of the experimental design, particularly aimed at readers not familiar with research into circadian rhythms. Furthermore, I have a more fundamental question about the relationship between levels of activity and DVM on which I will expand below. Finally, it was unclear how the observational results made here related to the molecular aspects considered in the Discussion.

(1) Explanation of experimental design - I acknowledge that the format of this particular journal insists that the Results are the first section that follows the Introduction. This nevertheless presents a problem for the reader since many of the concepts and terms that would generally be in the Methods are yet to be explained to the reader. Hence, right from the start of the Results section, the reader is thrown into the detail of what happened during the LD-DD experiments without being fully aware of why this type of experiment was carried out in the first place. Even after reading the Methods, further explanation would have been helpful. Circadian cycle type research of this sort often entrains organisms to certain light cycles and then takes the light away to see if the cycle continues in complete darkness, but this critical piece of knowledge does not come until much later (e.g. lines 369-372) leaving the reader guessing until this point why the authors took the approach they did. I would suggest the following (1) that more effort is made in the Introduction to explain the exact LD/DD protocols adopted (2) that a schematic figure is placed early on in the manuscript where the protocol is explained including some logical flow charts of e.g. if behavioural cycle continues in DD then internal clock exists versus if cycle does not continue in DD, the exogenous cues dominate - followed by - major decrease in cyclic amplitude = weak clock versus minor decrease = strong clock and so on

(2) Activity vs kinesis - in this study, we are shown data that (i) krill have a circadian cycle - incubation experiments; (ii) that krill swarms display DVM in this region - echosounder data (although see my later point). My question here is regarding the relationship between what is being measured by the incubation experiments and the in situ swarm behaviour observations. The incubation experiments are essentially measuring the propensity of krill to swim upwards since it logs the number of times an individual (or group) break a beam towards the top of the incubation tube. I argue that krill may be still highly active in the rest of the tube but just do not swim close to the surface, so this approach may not be a good measure of "activity". Otherwise, I suggest a more correct term of what is being measured is the level of "upward kinesis". As the authors themselves note, krill are negatively buoyant and must always be active to remain pelagic. What changes over the day-night cycle is whether they decide to expend that activity on swimming upwards, downwards or remaining at the same depth. Explaining the pattern as upward kinesis then also explains by swarms move upwards during the night. Just being more active at night may not necessarily result in them swimming upwards.

(3) Molecular relevance - Although I am interested in molecular clock aspects behind these circadian rhythms, it was not made clear how the results of the present study allow any further insight into this. In lines 282 to 284, the findings of the study by Biscontin et al (2017) are discussed with regard to how TIM protein is degraded by light via the clock photreceptor CRYTOCHROME 1. This element of the Discussion would be a lot more relevant if the results of the present study were considered in terms of whether they supported or refuted this or any other molecular clock model. As it stands, this paragraph is purely background knowledge and a candidate for deletion in the interest of shortening the Discussion.

Other aspects<br /> (i) 'Bimodal swimming' was used in the Abstract and later in the text without the term being fully explained. I could interpret it to mean a number of things so some explanation is required before the term is introduced.<br /> (ii) Midnight sinking - I was struck by Figure 2b with regards to the dip in activity after the initial ascent, as well as the rise in activity predawn. Cushing (1951) Biol Rev 26: 158-192 describes the different phases of a DVM common to a number of marine organisms observed in situ where there is a period of midnight sinking following the initial dusk ascent and a dawn rise prior to dawn descent. Tarling et al (2002) observe midnight sinking pattern in Calanus finmarchicus and consider whether it is a response to feeding satiation or predation avoidance (i.e. exogenous factors). Evidence from the present study indicates that midnight sinking (and potential dawn rise) behaviour could alternatively be under endogenous control to a greater or lesser degree. This is something that should certainly be mentioned in the Discussion, possibly in place of the molecular discussion element mentioned above - possibly adding to the paragraph Lines 303-319.

(iii) Lines 200-207 - I struggled to follow this argument regarding Piccolin et al identifying a 12 h rhythm whereas the present study indicates a ~24 h rhythm. Is one contradicting the other - please make this clear.

(iv) Although I agree that the hydroacoustic data should be included and is generally supportive of the results, I think that two further aspects should be made clear for context (a) whether there was any groundtruthing that the acoustic marks were indeed krill and not potentially some other group know to perform DVM such as myctophids (b) how representative were these patterns - I have a sense that they were heavily selected to show only ones with prominent DVM as opposed to other parts of the dataset where such a pattern was less clear - I am aware of a lot of krill research where DVM is not such a clear pattern and it is disingenuous to provide these patterns as the definitive way in which krill behaves. I ask this be made clear to the reader (note also that there is a suggestion of midnight sinking in Fig 5b on 28/2).

Reviewer #2 (Public review):

Summary:

authors had previously identified that a colorectal cancer cell line generates small extracellular vesicles (sEVs) via a mechanism where a larger intracellular compartment containing these sEVs is secreted from the surface of the cell and then tears to release its contents. Previous studies had suggested that intraluminal vesicles (ILVs) inside endosomal multivesicular bodies and amphisomes can be secreted by fusion of the compartment with the plasma membrane. The 'torn bag mechanism' considered in this manuscript is distinctly different, because it involves initial budding off of a plasma membrane-enclosed compartment (called the amphiectosome in this manuscript, or MV-lEV). The authors successfully set out to investigate whether this mechanism is common to many cell types and to determine some of the subcellular processes involved.

The strengths of the study are:

(1) The high-quality imaging approaches used, including live-cell imaging and EN, which seem to show good examples of the proposed mechanism.<br /> (2) They screen several cell lines for these structures, also search for similar structures in vivo, and show the tearing process by real-time imaging.<br /> (3) Regarding the intracellular mechanisms of ILV production, the authors also try to demonstrate the different stages of amphiectosome production and differently labelled ILVs using immuno-EM.

Several of the techniques employed are technically challenging to do well, and so these are critical strengths of the manuscript.

Overall, I think the authors have been successful in identifying amphiectosomes secreted from multiple cell lines and cells in vivo, and in demonstrating that the ILVs inside them have at least two origins (autophagosome membrane and late endosomal multivesicular body) based on the markers that they carry. Inevitably, it remains unclear how universal this mechanism is in vivo and its overall contribution to EV function.<br /> I think there could be a significant impact on the EV field and consequently on our understanding of cell-cell signalling based on these findings. It will flag the importance of investigating the release of amphiectosomes in other studies, especially as the molecular mechanisms involved in this type of 'ectosomal-style' release will be different from multivesicular compartment fusion to the plasma membrane and should be possible to be manipulated independently.<br /> In general, the EV field has struggled to link up analysis of the subcellular biology of sEV secretion and the biochemical/physical analysis of the sEVs themselves, so from that perspective, the manuscript provides a novel angle on this problem.

Reviewer #1 (Public review):

The study by Aguirre-Botero et al. shows the dynamics of 3D11 anti-CSP monoclonal antibody (mAb) mediated elimination of rodent malaria Plasmodium berghei (Pb) parasites in the liver. The authors show that the anti-CSP mAb could protect against intravenous (i.v.) Pb sporozoite challenge along with the cutaneous challenge, but requires higher concentration of antibody. Importantly, the study shows that the anti-CSP mAb not only affects sporozoite motility, sinusoidal extravasation, and cell invasion but also partially impairs the intracellular development inside the liver parenchyma, indicating a late effect of this antibody during liver stage development. While the study is interesting and conducted well, the only novel yet very important observation made in this manuscript is the effect of the anti-CSP mAb on liver stage development.

Comments on latest version:

No further comments.

Reviewer #2 (Public review):

Summary:

Kaya et al uncover an intriguing relationship between hippocampal sharp wave-ripple production and peripheral hormone exposure, food intake, and lateral hypothalamic function. These findings significantly expand our understanding of hippocampal function beyond mnemonic processes and point a direction for promising future research.

Strengths:

Some of the relationships observed in this paper are highly significant. In particular, the inverse relationship between GLP1/Leptin and Insulin/Ghrelin are particularly compelling as this aligns well with opposing hormone functions on satiety.

Weaknesses: I would be curious if there were any measurable behavioral differences that occur with different hormone manipulations.

Reviewer #2 (Public review):

Summary:

This study elucidated the mechanism underlying drug resistance induced by CDK4/6i as a single agent and proposed a novel and efficacious second-line therapeutic strategy. It highlighted the potential of combining CDK2i with CDK4/6i for the treatment of HR+/HER2- breast cancer.

Strengths:

The study demonstrated that CDK4/6 induces drug resistance by impairing Rb activation, which results in diminished E2F activity and a delay in G1 phase progression. It suggests that the synergistic use of CDK2i and CDK4/6i may represent a promising second-line treatment approach. Addressing critical clinical challenges, this study holds substantial practical implications.

Weaknesses:

(1) Drug-resistant cell lines: Was a drug concentration gradient treatment employed to establish drug-resistant cell lines? If affirmative, this methodology should be detailed in the materials and methods section.

(2) What rationale informed the selection of MCF-7 cells for the generation of CDK6 knockout cell lines? Supplementary Figure 3. A indicates that CDK6 expression levels in MCF-7 cells are not notably elevated.

(3) For each experiment, particularly those involving mice, the author must specify the number of individuals utilized and the number of replicates conducted, as detailed in the materials and methods section.

(4) Could this treatment approach be extended to triple-negative breast cancer?

Reviewer #2 (Public review):

Summary:

The manuscript describes how synthetic polymers, primarily poloxamers of different sizes, influence bacterial mechanosensitive channel MscL gating by modifying the interfacial tension of the membrane. The authors expressed MscL in U2OS cells and chemically blebbed the cells to derive giant plasma membrane vesicles (GPMVs) containing MscL G22S. They applied micropipette aspiration on GPMVs to obtain bending rigidity (kc) and area expansion modulus (kA) and used patch clamping to obtain activation pressure. They found a negative correlation between kc and kA with activation pressure and attributed the changes to activation pressure to the lowering of the interfacial tension in the presence of polymers. They carried out coarse-grain molecular dynamics simulations and showed that under tension the hydrophilic PEO group adsorbs to the bilayer more, thereby lowering the interfacial tension. Besides MscL, they showed similar results with TREK-1 activation. The conclusion that differences in interfacial tension are what drive the changes in activation pressure is based on using a thermodynamic model.

Strengths:

(1) Reveals that synthetic polymer that lowers bending rigidity and area expansion modulus increases activation pressure of mechanosensitive channel by lowering interfacial tension - this is an important finding.

(2) General data quality is high with detailed and thorough analysis. The use of both micropipette aspiration and patch clamp in the same study is noteworthy.

(3) Discussion on nanoplastics and their effect on membrane properties and therefore their impact on mechanosensitivity is interesting.

Weaknesses:

Interfacial tension is not experimentally measured. Given the main argument of this paper is that synthetic polymers reduce interfacial tension, which increases MS channel activation pressure, it would be prudent to show experimental measurements to bolster their analysis.

Reviewer #2 (Public review):

Summary:

This manuscript presents a new approach for non-invasive, MRI-based, measurements of cerebral blood volume (CBV). Here, the authors use ferumoxytol, a high-contrast agent and apply specific sequences to infer CBV. The authors then move to statistically compare measured regional CBV with known distribution of different types of neurons, markers of metabolic load and others. While the presented methodology captures and estimated 30% of the vasculature, the authors corroborated previous findings regarding lack of vascular compartmentalization around functional neuronal units in the primary visual cortex.

Strengths:

Non invasive methodology geared to map vascular properties in vivo.

Implementation of a highly sensitive approach for measuring blood volume.

Ability to map vascular structural and functional vascular metrics to other types of published data.

Weaknesses:

The key issue here is the underlying assumption about the appropriate spatial sampling frequency needed to captures the architecture of the brain vasculature. Namely, ~7 penetrating vessels / mm2 as derived from Weber et al 2008 (Cer Cor). The cited work, begins by characterizing the spacing of penetrating arteries and ascending veins using vascular cast of 7 monkeys (Macaca mulatta, same as in the current paper). The ~7 penetrating vessels / mm2 is computed by dividing the total number of identified vessels by the area imaged. The problem here is that all measurements were made in a "non-volumetric" manner and only in V1. Extrapolating from here to the entire brain seems like an over-assumption, particularly given the region-dependent heterogeneity that the current paper reports.

Comments on revisions:

I appreciate the effort made to improve the manuscript. That said, the direct validation of the underlying assumption about spatial resolution sampling remains unaddressed in the final version of this manuscript. With the only intention to further strengthen the methodology presented here, I would encourage again the authors to seek a direct validation of this assumption for other brain areas.

In their reply, the authors stated "... line scanning or single-plane sequences, at least on first impression, seem inadequate for whole-brain coverage and cortical surface mapping. ". This seems to emanate for a misunderstanding as the method could be used to validate the mapping, not to map per-se.

Reviewer #2 (Public review):

Summary:

Boldt et al., investigated whether previously established relationships between transdiagnostic psychiatric symptom dimensions and confidence distortions would result in downstream influences on the confidence-related behaviour of reminder setting. 600 individuals from the general population completed a battery of psychiatric symptom questionnaires and an online reminder-setting task. In line with previous studies, individuals high in compulsivity (CIT) showed over-confidence in their task performance, whereas individuals high in anxious-depression (AD) tended to be under-confident. Crucially, the over-confidence associated with CIT partially mediated a decreased tendency to use external reminders during task performance, whereas the under-confidence associated with AD did not result in any alteration in external reminder setting. The authors suggest that metacognitive monitoring is impaired in CIT which has a knock-on effect on reminder setting behaviour, but that a direct link also exists between CIT and reduced reminder setting independently of confidence.

Strengths:

The study combines the latest advances in transdiagnostic approaches to psychopathology with a cleverly designed external reminder-setting task. The approach allows for investigation of what some of the downstream consequences associated with impaired metacognition in sub-clinical psychopathology may be.

The experimental design and hypotheses were pre-registered prior to data collection.

The manuscript is well written and rigorous analysis approaches are used throughout.

Weaknesses:

Participants only performed a single task so it remains unclear if the observed effects would generalise to reminder setting in other cognitive domains.

The sample consisted of participants recruited from the general population. Future studies should investigate whether the effects observed extend to individuals with the highest levels of symptoms (including clinical samples).

Reviewer #2 (Public review):

Summary:

The authors aimed to determine whether goal-directed and cue-driven attentional strategies (goal- and sign-tracking phenotypes) were associated with variation in cued motor responses and dorsomedial striatal (DMS) glutamate transmission. They used a treadmill task in which cues indicated whether rats should turn or stop to receive a reward. They collected and analyzed several behavioral measures related to task performance with a focus on turns (performance, latency, duration) for which there are more measures than for stops. First, they established that goal-trackers perform better than sign-trackers in post-criterion turn performance (cued turns completed) and turn initiation. They used glutamate sensors to measure glutamate transmission in DMS. They performed analyses on glutamate traces that suggest phasic glutamate DMS dynamics to cues were primarily associated with successful turn performance and were more characteristic of goal-trackers (ie. rats with "goal-directed" attentional strategy). Smaller and more frequent DMS glutamate peaks were associated with other task events, cued misses (missed turns), cued stops, and reward delivery and were more characteristic of sign-trackers (i.e. rats with "cue-driven" attentional strategies). Consistent with the reported glutamate findings, chemogenetic inhibition of prelimbic-DMS glutamate transmission had an effect on goal-trackers' turn performance without affecting sign-trackers' performance in the treadmill task.

Strengths:

The power of the sign- and goal-tracking model to account for neurobiological and behavioral variability is critically important to the field's understanding of heterogeneity of the brain in health and disease. The approach and methodology are sound in their contribution to this important effort.

The authors establish behavioral differences, measure a neurobiological correlate of relevance, and then manipulate that correlate in a broader circuitry and show a causal role in behavior that is consistent with neurobiological measurements and phenotypic differences.

Sophisticated analyses provide a compelling description of the authors' observations.

Limitations:

Considerable transparency was added in the revised preprint. The "n" for each analysis is now available in Tables 1 and 3, carefully cross-referenced by figure. Readers may now carefully consider the n's in drawing their own conclusions from reported data.

While more conventional trial-averaged population activity traces are not presented or analyzed, the unique nature of the peak phenotypes is likely to "wash out" potentially meaningful signals if averaged across subjects. The distribution of peaks analyses (and shifts observed with chemogenetic inhibition) are improved in the revised preprint and are informative to illustrate this likelihood. Representative traces should theoretically be consistent with population averages within phenotype, and if not, discussion of such inconsistencies may have enriched the conclusions drawn from the study. For example, population traces of the phasic cue response in GT may resemble the representative peak examples, while smaller irregular peaks of ST may "wash out" in a population average (possibly resulting in a prolonged elevation) and could have strengthened the rationale for more sophisticated analyses of peak probability that remain the focus of the revised preprint.

Reviewer #2 (Public review):

Summary:

Sleep has not only been shown to support the strengthening of memory traces, but also their transformation. A special form of such transformation is the abstraction of general rules from the presentation of individual exemplars. The current work used large online experiments with hundreds of participants to shed further light on this question. In the training phase participants saw composite items (scenes) that were made up of pairs of spatially coupled (i.e., they were next to each other) abstract shapes. In the initial training, they saw scenes made up of six horizontally structured pairs and in the second training phase, which took place after a retention phase (2 min awake, 12 hour incl. sleep, 12 h only wake, 24 h incl. sleep), they saw pairs that were horizontally or vertically coupled. After the second training phase, a two-alternatives-forced-choice (2-AFC) paradigm, where participants had to identify true pairs versus randomly assembled foils, was used to measure performance on all pairs. Finally, participants were asked five questions to identify, if they had insight into the pair structure and post-hoc groups were assigned based on this. Mainly the authors find that participants in the 2 minute retention experiment without explicit knowledge of the task structure were at chance level performance for the same structure in the second training phase, but had above chance performance for the vertical structure. The opposite was true for both sleep conditions. In the 12 h wake condition these participants showed no ability to discriminate the pairs from the second training phase at all.

Strengths:

All in all, the study was performed to a high standard and the sample size in the implicit condition was large enough to draw robust conclusions. The authors make several important statistical comparisons and also report an interesting resampling approach. There is also a lot of supplemental data regarding robustness.

Weaknesses:

My main concern regards the small sample size in the explicit group and the lack of experimental control.

Reviewer #2 (Public review):

Summary:

This interesting manuscript describes a study investigating the role of MC4R signalling on kisspeptin neurons. The initial question is a good one. Infertility associated with MC4 mutations in humans has typically been ascribed to the consequent obesity and impaired metabolic regulation. Whether there is a direct role for MC4 in regulating the HPG axis has not been thoroughly examined. Here, the researchers have assembled an elegant combination of targetted loss of function and gain of function in vivo experiments, specifically targetting MC4 expression in kisspeptin neurons. This excellent experimental design should provide compelling evidence for whether melanocortin signalling dirently affects arcuate kisspeptin neurons to support normal reproductive function. There were definite effects on reproductive function (irregular estrous cycle, reduced magnitude of LH surge induced by exogenous estradiol). However, the magnitude of these responses and the overall effect on fertility were relatively minor. The mice lacking MC4R in kisspeptin neurons remained fertile despite these irregularities. The second part of the manuscript describes a series of electrophysiological studies evaluating the pharmacological effects of melanocortin signalling in kisspeptin cells in ex-vivo brain slides. These studies characterised interesting differential actions of melanocortins in two different populations of kisspeptin neurons. Collectively, the study provides some novel insights into how direct actions of melanocortin signalling via the MC4 receptor in kisspeptin neurons contribute to the metabolic regulation of the reproductive system. Importantly, however, it is clear that other mechanisms are also at play.

Strengths:

The loss of function/gain of function experiments provides a conceptually simple but hugely informative experimental design. This is the key strength of the current paper - especially the knock-in study that showed improved reproductive function even in the presence of ongoing obesity. This is a very convincing result that documents that reproductive deficits in MC4R knockout animals (and humans with deleterious MC4R gene variants) can be ascribed to impaired signalling in the hypothalamic kisspeptin neurons and not necessarily caused as a consequence of obesity. As concluded by the authors: "reproductive impairments observed in MC4R deficient mice, which replicate many of the conditions described in humans, are largely mediated by the direct action of melanocortins via MC4R on Kiss1 neurons and not to their obese phenotype." This is important, as it might change how such fertility problems are treated.

I would like to see the validation experiments for the genetic manipulation studies given greater prominence in the manuscript because they are critical to interpretation. Presently, only single unquantified images are shown, and a much more comprehensive analysis should be provided.

Weaknesses:

(1) Given that mice lacking MC4R in kisspeptin neurons remained fertile despite some reproductive irregularities, this can be described as a contributing pathway, but other mechanisms must also be involved in conveying metabolic information to the reproductive system. This is now appropriately covered in the discussion.

(2) The mechanistic studies evaluating melanocortin signalling in kisspeptin neurons were all completed in ovariectomised animals (with and without exogenous hormones) that do not experience cyclical hormone changes. Such cyclical changes are fundamental to how these neurons function in vivo and may dynamically alter how they respond to hormones and neuropeptides. Eliminating this variable makes interpretation difficult, but the authors have justified this as a reductionist approach to evaluate estradiol actions specifically. However, this does not reflect the actual complexity of reproductive function.

For example, the authors focus on a reduced LH response to exogenous estradiol in ovariectomised mice as evidence that there might be a sub-optimal preovulatory LH surge. However, the preovulatory LH sure (in intact animals) was not measured.

They have not assessed why some follicles ovulated, but most did not. They have focused on the possibility that the ovulation signal (LH surge) was insufficient rather than asking why some follicles responded and others did not. This suggests some issue with follicular development, likely due to changes in gonadotropin secretion during the cycle and not simply due to an insufficient LH surge.

Reviewer #2 (Public review):

Summary:

This study by Tünte et al. investigated the development of interoceptive sensitivity during the first year of life, focusing specifically on cardiac and respiratory sensitivity in infants aged 3, 9, and 18 months. The research employed a previously developed experimental paradigm for the cardiac domain and adapted it for a novel paradigm in the respiratory domain. This approach assessed infants' cardiac and respiratory sensitivity based on their preferential looking behavior toward visuo-auditory stimuli displayed on a monitor, which moved either in sync or out of sync with the infants' own heartbeats or breathing. The results in the cardiac domain showed that infants across all age groups preferred stimuli moving synchronously rather than asynchronously with their heartbeat, suggesting the presence of cardiac sensitivity as early as 3 months of age. However, it is noteworthy that this preference direction contradicts a previous study, which found that 5-month-old infants looked longer at stimuli moving asynchronously with their heartbeat (Maister et al., 2017). In the respiratory domain, only the group of 9-month-old infants showed a preference for stimuli presented synchronously with their breathing. The authors conducted various statistical analyses to thoroughly examine the obtained data, providing deeper insights valuable for future research in this field.

Strengths:

Few studies have explored the early development of interoception, making the replication of the original study by Maister et al. (2017) particularly valuable. Beyond replication, this study expands the investigation into the respiratory domain, significantly enhancing our understanding of interoceptive development. The provision of longitudinal and cross-sectional data from infants at 3, 9, and 18 months of age is instrumental in understanding their developmental trajectory.

Weaknesses:

Due to a technical error, this study failed to counterbalance the conditions of the first trial in both the iBEAT and iBREATH tests. Although the authors addressed this issue as much as possible by employing alternative analyses, it should be noted that this error may have critically influenced the results and, thus, the conclusions.

Reviewer #2 (Public Review):

In the manuscript, the authors aimed to elucidate the molecular mechanism that explains neurodegeneration caused by the depletion of axonal mitochondria. In Drosophila, starting with siRNA depletion of Milton and Miro, the authors attempted to demonstrate that the depletion of axonal mitochondria induces the defect in autophagy. From proteome analyses, the authors hypothesized that autophagy is impacted by the abundance of eIF2β and the phosphorylation of eIF2α. The authors followed up the proteome analyses by testing the effects of eIF2β overexpression and depletion on autophagy. With the results from those experiments, the authors proposed a novel role of eIF2β in proteostasis that underlies neurodegeneration derived from the depletion of axonal mitochondria.

The manuscript has several weaknesses. The reader should take extra care while reading this manuscript and when acknowledging the findings and the model in this manuscript.

The defect in autophagy by the depletion of axonal mitochondria is one of the main claims in the paper. The authors should work more on describing their results of LC3-II/LC3-I ratio, as there are multiple ways to interpret the LC3 blotting for the autophagy assessment. Lysosomal defects result in the accumulation of LC3-II thus the LC3-II/LC3-I ratio gets higher. On the other hand, the defect in the early steps of autophagosome formation could result in a lower LC3-II/LC3-I ratio. From the results of the actual blotting, the LC3-I abundance is the source of the major difference for all conditions (Milton RNAi and eIF2β overexpression and depletion).

Another main point of the paper is the up-regulation of eIF2β by depleting the axonal mitochondria leads to the proteostasis crisis. This claim is formed by the findings from the proteome analyses. The authors should have presented their proteomic data with much thorough presentation and explanation. As in the experiment scheme shown in Figure 4A, the author did two proteome analyses: one from the 7-day-old sample and the other from the 21-day-old sample. The manuscript only shows a plot of the result from the 7-day-old sample, but that of the result from the 21-day-old sample. For the 21-day-old sample, the authors only provided data in the supplemental table, in which the abundance ratio of eIF2β from the 21-day-old sample is 0.753, meaning eIF2β is depleted in the 21-day-old sample. The authors should have explained the impact of the eIF2β depletion in the 21-day-old sample, so the reader could fully understand the authors' interpretation of the role of eIF2β on proteostasis.

Reviewer #3 (Public review):

Summary:

In the manuscript 'Mapping kinase domain resistance mechanisms for the MET receptor tyrosine kinase via deep mutational scanning' by Estevam et al, deep mutational scanning is used to assess the impact of ~5,764 mutants in the MET kinase domain on the binding of 11 inhibitors. Analyses were divided by individual inhibitor and kinase inhibitor subtype (I,II, I 1/2, and III). While a number of mutants were consistent with previous clinical reports, novel potential resistance mutants were also described. This study has implications for the development of combination therapies, namely which combination of inhibitors to avoid based on overlapping resistance mutant profiles. While one suggested pair of inhibitors with least overlapping resistance mutation profiles was suggested, this manuscript presents a proof of concept toward a more systematic approach for improved selection of combination therapeutics. Furthermore, in a final part of this manuscript the data was used to train a machine learning model, the ESM-1b protein language model augmented with an XG Boost Regressor framework, and found that they could improve predictions of resistance mutations above the initial ESM-1b model.

Strengths:

Overall this paper is a tour-de-force of data collection and analysis to establish a more systematic approach for the design of combination therapies, especially in targeting MET and other kinases, a family of proteins significant to therapeutic intervention for a variety of diseases. The presentation of the work is mostly concise and clear with thousands of data points presented neatly and clearly. The discovery of novel resistance mutants for individual MET inhibitors, kinase inhibitor subtypes within the context of MET, and all resistance mutants across inhibitor subtypes for MET has clinical relevance. However, probably the most promising outcome of this paper is the proposal of the inhibitor combination of Crizotinib and Cabozantib as Type I and Type II inhibitors, respectively, with the least overlapping resistance mutation profiles and therefore potentially the most successful combination therapy for MET. While this specific combination is not necessarily the point, it illustrates a compelling systematic approach for deciding how to proceed in developing combination therapy schedules for kinases. In an insightful final section of this paper, the authors approach using their data to train a machine learning model, perhaps understanding that performing these experiments for every kinase for every inhibitor could be prohibitive to applying this method in practice.

Weaknesses:

This paper presents a clear set of experiments with a compelling justification. The content of the paper is overall of high quality. Below are mostly regarding clarifications in presentation.

Two places could use more computational experiments and analysis, however. Both are presented as suggestions, but at least a discussion of these topics would improve the overall relevance of this work. In the first case it seems that while the analyses conducted on this dataset were chosen with care to be the most relevant to human health, further analyses of these results and their implications of our understanding of allosteric interactions and their effects on inhibitor binding would be a relevant addition. For example, for any given residue type found to be a resistance mutant are there consistent amino acid mutations to which a large or small or effect is found. For example is a mutation from alanine to phenylalanine always deleterious, though one can assume the exact location of a residue matters significantly. Some of this analysis is done in dividing resistance mutants by those that are near the inhibitor binding site and those that aren't, but more of these types of analyses could help the reader understand the large amount of data presented here. A mention at least of the existing literature in this area and the lack or presence of trends would be worthwhile. For example, is there any correlation with a simpler metric like the Grantham score to predict effects of mutations (in a way the ESM-1b model is a better version of this, so this is somewhat implicitly discussed).

Indeed, this discussion relates to the second point this manuscript could improve upon: the machine learning section. The main actionable item here is that this results section seems the least polished and could do a better job describing what was done. In the figure it looks like results for certain inhibitors were held out as test data - was this all mutants for a single inhibitor, or some other scheme? Overall I think the implications of this section could be fleshed out, potentially with more experiments. As mentioned in the 'Strengths' section, one of the appealing aspects of this paper is indeed its potential wide applicability across kinases -- could you use this ML model to predict resistance mutants for an entirely different kinase? This doesn't seem far-fetched, and would be an extremely compelling addition to this paper to prove the value of this approach.

Another area in which this paper could improve its clarity is in the description of caveats of the assay. The exact math used to define resistance mutants and its dependence on the DMSO control is interesting, it is worth discussing where the failure modes of this procedure might be. Could it be that the resistance mutants identified in this assay would differ significantly from those found in patients? That results here are consistent with those seen in the clinic is promising, but discrepancies could remain. Furthermore a more in depth discussion of the MetdelEx14 results is warranted. For example, why is the DMSO signature in Figure 1 - supplement 4 so different from that of Figure 1? And finally, there is a lot of emphasis put on the unexpected results of this assay for the tivantinib "type III" inhibitor - could this in fact be because the molecule "is highly selective for the inactive or unphosphorylated form of c-Met" according to Eathiraj et al JBC 2011? These points are addressed in previous work (Estevam et al 2024) or in the detailed methods section, but are not obvious in the main text of the paper.

This paper is crisply written with beautiful figures, and the complexity of the data is easy to understand from an in depth discussion of the mutants that have been previously reported.

Finally, the potential impacts and follow-ups of this excellent study could be used as a resource for the community both as a dataset and as a proof of concept. It is exciting that his approach can be altered and/or improved in the future to facilitate the general application of this approach for combination therapies and the understanding of mechanism for other targets.

Comments on revisions:

Thank you for your additions and changes - they have improved the quality of this paper.

Reviewer #2 (Public review):

Summary:

The manuscript by Zhu et al describes a novel role for MED26, a subunit of the Mediator complex, in erythroid development. The authors have discovered that MED26 promotes transcriptional pausing of RNA Pol II, by recruiting pausing-related factors.

Strengths:

This is a well-executed study. The authors have employed a range of cutting-edge and appropriate techniques to generate their data, including: CUT&Tag to profile chromatin changes and mediator complex distribution; nuclear run-on sequencing (PRO-seq) to study Pol II dynamics; knockout mice to determine the phenotype of MED26 perturbation in vivo; an ex vivo erythroid differentiation system to perform additional, important, biochemical and perturbation experiments; immunoprecipitation mass spectrometry (IP-MS); and the "optoDroplet" assay to study phase-separation and molecular condensates.

This is a real highlight of the study. The authors have managed to generate a comprehensive picture by employing these multiple techniques. In doing so, they have also managed to provide greater molecular insight into the workings of the MEDIATOR complex, an important multi-protein complex that plays an important role in a range of biological contexts. The insights the authors have uncovered for different subunits in erythropoiesis will very likely have ramifications in many other settings, in both healthy biology and disease contexts.

Weaknesses:

There are almost no discernible weaknesses in the techniques used, nor the interpretation of the data. The IP-MS data was generated in HEK293 cells when it could have been performed in the human CD34+ HSPC system that they employed to generate a number of the other data. This would have been a more natural setting and would have enabled a more like-for-like comparison with the other data.

Reviewer #3 (Public review):

Summary:

In this paper Hajra et al have attempted to identify the role of Sirt1 and Sirt3 in regulating metabolic reprogramming and macrophage host defense. They have performed gene knock down experiments in RAW macrophage cell line to show that depletion of Sirt1 or Sirt3 enhances the ability of macrophages to eliminate Salmonella Typhimurium. However, in mice inhibition of Sirt1 resulted in dissemination of the bacteria but the bacterial burden was still reduced in macrophages. They suggest that the effect they have observed is due to increased inflammation and ROS production by macrophages. They also try to establish a weak link with metabolism. They present data to show that the switch in metabolism from glycolysis to fatty acid oxidation is regulated by acetylation of Hif1a, and PDHA1.

Strengths:

The strength of the manuscript is that the role of Sirtuins in host-pathogen interactions have not been previously explored in-depth making the study interesting. It is also interesting to see that depletion of either Sirt1 or Sirt3 result in a similar outcome.

Weaknesses:

The major weakness of the paper is the low quality of data, making it harder to substantiate the claims. Also, there are too many pathways and mechanisms being investigated. It would have been better if the authors had focussed on either Sirt1 or Sirt3 and elucidated how it reprograms metabolism to eventually modulate host response against Salmonella Typhimurium. Experimental evidences are also lacking to prove the proposed mechanisms. For instance they show correlative data that knock down of Sirt1 mediated shift in metabolism is due to HIF1a acetylation but this needs to be proven with further experiments.

Reviewer #2 (Public review):

This focused study by Lowry and colleagues that identifies a key molecular motif that controls ion permeation vs combined ion permeation and lipid transport in three families of channel/scramblase proteins, in TMEM16 channels, in the plant-expressed and stress-gated cation channel OSCA, and in the mammalian homolog and mechanosensitive cation channel, TMEM63. Between them, these three channels share low sequence similarity and have seemingly differing functions, as anion (TMEM16 channels), or stress-activated cation channels (OSCA/TMEM63). The study finds that in all three families, mutating a single hydrophobic residue in the ion permeation pathway of the channels confers lipid transport through the pores of the channels, indicating that TMEM16 and related OSCA and TMEM63 channels have a conserved potential for both ion and lipid permeation. The authors interpret the findings as revealing that these channel/scramblase proteins have a relatively low "energetic barrier for scramblase" activity. The experiments are done with a high level of rigor and the revised paper is very well written and addresses the previous concerns.

Reviewer #2 (Public review):

Summary:

The authors propose that DKK2 is necessary for the metastasis of colon cancer organoids. They then claim that DKK2 mediates this effect by permitting the generation of lysozyme-positive Paneth-like cells within the tumor microenvironmental niche. They argue that these lysozyme-positive cells have Paneth-like properties in both mouse and human contexts. They then implicate HNF4A as the causal factor responsive to DKK2 to generate lysozyme-positive cells through Sox9.

Strengths:

The use of a genetically defined organoid line is state-of-the-art. The data in Figure 1 and the dependence of DKK2 for splenic injection and liver engraftment, as well as the long-term effect on animal survival, are interesting and convincing. The rescue using DKK2 administration for some of their phenotype in vitro is good. The inclusion and analysis of human data sets help explore the role of DKK2 in human cancer and help ground the overall work in a clinical context.

Remaining Weaknesses after revision:

(1) The authors have effectively explained the regulation of HNF4A at both mRNA and protein levels. To further strengthen their findings, I recommend using CRISPR technology to generate DKK2 and HNF4A double knockout organoids. This approach would allow the authors to investigate whether the AKP liver metastasis is restored in the double knockout condition. Such an experiment would provide more direct evidence that HNF4A protein stabilization is the crucial mechanism for liver metastasis suppression following DKK2 knockout.

Reviewer #2 (Public review):

Summary:

The author developed a new device to overcome current limitations in the imaging process of 3D spheroidal structures. In particular, they created a system to follow in real-time tumour spheroid formation, fusion and cell migration without disrupting their integrity. The system has also been exploited to test the effects of a therapeutic agent (chemotherapy) and immune cells.

Strengths:

The system allows the in situ observation of the 3D structures along the 3 axes (x,y and z) without disrupting the integrity of the spheroids; in a time-lapse manner it is possible to follow the formation of the 3D structure and the spheroids fusion from multiple angles, allowing a better understanding of the cell aggregation/growth and kinetic of the cells.

Interestingly the system allows the analysis of cell migration/ escape from the 3D structure analysing not only the morphological changes in the periphery of the spheroids but also from the inner region demonstrating that the proliferating cells in the periphery of the structure are more involved in the migration and dissemination process. The application of the system in the study of the effects of doxorubicin and NK cells would give new insights in the description of the response of tumor 3D structure to killing agents.

Reviewer #3 (Public review):

Summary:

The authors have performed endoscopic calcium recordings of individual CeA neuron responses to food and shock, as well as to cues predicting food and shock. They claim that a majority of neurons encode valence, with a substantial minority encoding salience.

Strengths:

The use of endoscopic imaging is valuable, as it provides the ability to resolve signals from single cells, while also being able to track these cells across time (though the latter capability was not extensively utilized). Another strength is the use of a sophisticated circular shifting analysis to avoid statistical errors caused by correlations between neighboring image pixels.

Weaknesses:

In the first version of this manuscript, my main critique was that the authors didn't fully test whether neurons encode valence. In their rebuttal, the authors justify their use of the terms valence and salience by citing prior works from different labs:

(1) Li et al., 2019, doi: 10.7554/eLife.41223<br /> (2) Yang et al., 2023, doi: 10.1038/s41586-023-05910-2<br /> (3) Huang et al., 2024, doi: 10.1038/s41586-024-07819<br /> (4) Lin and Nicolelis, 2008, doi: 10.1016/j.neuron.2008.04.031<br /> (5) Stephenson-Jones et al., 2020, doi: 10.1016/j.neuron.2019.12.006<br /> (6) Zhu et al., 2018, doi: 10.1126/science.aat0481<br /> (7) Comoli et al., 2003, doi: 10.1038/nn1113P

Among these, items #1 and #3 primarily discuss valence, while #2, #4, #6, and #7 discuss salience, and #5 discusses both.

Upon reviewing these references, the authors' identification of valence encoding patterns is still problematic, and indeed studies cited above show several lines of evidence for valence encoding that are absent here. For example, item #3 ranked behavioral responses to five different odors in drosophila, from most attractive to most repulsive, and saw neuronal responses correlated with the degree of attraction versus repulsion across all five odors. This is robust evidence for valence encoding that is absent here. Items #1 and #5 above are the other two valence-addressing studies cited, and although those only used one rewarding and one aversive stimulus (in rodents), both also added a neutral cue, and most critically, identified substantial subsets of neurons showing a rank-order response, e.g. either aversion > neutral > reward or aversion < neutral < reward. Again, that level of demonstration of valence encoding is not shown in the current study.

Finally, two of the valence studies above tested responses to omission of reward/punishment, providing yet more evidence of valence encoding that is absent in the current study.

While there is much to like about the current study, the claims of valence encoding appear hard to justify, and should be toned down.

Reviewer #2 (Public review):

Summary:

The authors develop a computational model (and a simplified version thereof) to treat an extremely important issue regarding tumor growth. Specifically, it has been argued that fibroblasts have the ability to support tumor growth by creating physical conditions in the tumor microenvironment that prevent the relevant immune cells from entering into contact with, and ultimately killing, the cancer cells. This inhibition is referred to as immune exclusion. The computational approach follows standard procedures in the formulation of models for mixtures of different material species, adapted to the problem at hand by making a variety of assumptions as to the activity of different types of fibroblasts, namely "normal" versus "cancer-associated". The model itself is relatively complex, but the authors do a convincing job of analyzing possible behaviors and attempting to relate these to experimental observations.

Strengths:

As mentioned, the authors do an excellent job of analyzing the behavior of their model both in its full form (which includes spatial variation of the concentrations of the different cellular species) and in its simplified mean field form. The model itself is formulated based on established physical principles, although the extent to which some of these principles apply to active biological systems is perhaps debatable (see Weaknesses). The results of the model do indeed offer some significant insights into the critical factors which determine how fibroblasts might affect tumor growth; these insights could lead to new experimental ways of unraveling these complex sets of issues and enhancing immunotherapy. In this revised version, the authors have properly placed this work within the general context of other research on modeling the tumor-immune ecology.

Weaknesses:

Models of the form being studied here rely on a large number of assumptions regarding cellular behavior. One major issue is the degree to which close-to-equilibrium assumptions (such as the dynamics being driven by free energy minimization) can be taken as reliable predictors of the obviously active dynamics of biological cells. The authors have recognized this conceptual issue and have argued that these assumptions provide a reasonable first step for understanding the full complexity of dynamics in the tumor microenvironment.

The problem of T cell infiltration as well as the patterning of the extracellular matrix (ECM) by fibroblasts necessarily involve understanding cell proliferation, cell motion and cell interactions due e.g. to cell signaling. There is evidence that inherently non-equilibrium interactions between the fibroblasts and the extracellular matrix can lead to patterning of the fiber network and trapping of potentially infiltrating T-cells. it is not clear the extent to which this type of interaction can be captured by the approach being used here, although the authors propose that they can be mimicked by proper terms in their formulation. This to me is the primary concern that I had with this paper.

The authors have now addressed what used to be a separate weakness concerning the assumption that fibroblasts affect T cell behavior primarily by just making a more dense ECM. Instead, the organization of the ECM (for example, its anisotropy) could be playing a much more essential role than is given credit for here. This possibility is now discussed in some detail and the authors have suggested that the introduction of a nematic order parameter field would be a useful way to treat this effect.

Reviewer #2 (Public review):

Summary:

In this paper, the authors create transgenic animals with a CMV promoter driving expression of their DIO-SPOTlight construct in which uORF2 and the authentic ORF of Atf4 are replaced by GFP and tdTomato respectively, such that ISR activation is predicted to diminish GFP expression and enhance RFP expression. The major experimental finding of the paper is that cholinergic neurons have the most robust activation of the reporter, consistent with and extending upon their previous work.

Strengths:

It is very likely that the reporter does indeed read out on ISR activation at some level. It is mostly likely to be useful for screening and hypothesis testing than for gaining mechanistic insight, because, as the authors note in the present version, ATF4 itself is but one component of ISR activation. Cells might have robust eIF2a phosphorylation but have suppressed translational regulation (for instance by regulating the expression of eIF2B). The mRNA and protein half-lives of the GFP and Tomato are likely quite different from that of the equivalent components in ATF4, which means that the reporter is likely to behave differently from ATF4 itself over time.

Weaknesses:

The major element that the current manuscript lacks is a detailed comparison between how the reporter behaves and how it tracks with eIF2a phosphorylation, ATF4, and the initiation of the gene expression program downstream of ATF4. While this would be difficult to do in vivo, it would seem much more feasible to isolate primary cells (neurons, fibroblasts, hepatocytes, etc.) from the animals and thoroughly characterize the kinetics of reporter-versus-ISR activation. In that way, the reader can have a better idea of how to interpret the behavior of the reporter. As it is, the authors' attempt to account for the reporter's behavior in Figure 3F is purely speculative and not backed by experiment or modeling.

Reviewer #2 (Public review):

The authors first identify Ankle2 as a regulatory subunit and direct interactor of PP2A, showing they interact both in vitro and in vivo to promote BAF dephosphorylation. The Ankyrin domain of Ankle2 is important for the interaction with PP2A. They then show Ankle2 also interacts with the ER protein Vap33 through FFAT motifs and they particularly co-localize during mitosis. The recruitment of Ankle2 to Vap33 is essential to ER and nuclear envelop membrane in telophase while earlier in mitosis, it relies on the C terminus but not the FFAT motifs for recruitments to the nuclear membrane and spindle envelop in early mitosis. The molecular determinants and receptors are currently not known. The authors check the function of the PP2A recruitment to Ankle2/Vap33 in the context of embryos and show this recruitment pathway is functionally important. While the Ankle2/Vap33 interaction is dispensable in adult flies -looking at wing development, the PP2A/Ankle2 interaction is essential for correct wing and fly development. Overall, this is a very complete paper that reveals the molecular mechanism of PP2A recruitment to Ankle2 and studies both the cellular and the physiological effect of this interaction in the context of fly development.

The paper is well-written and the narrative is well developed. The figures are of high quality, well-controlled, clearly labelled and easy to understand. They support the claims made by the authors.

Comments on revisions:

There are still issues with the statistics. On graphs where multiple conditions are shown, you cannot perform a T-test. You have to use other tests such as ANOVA if the data is normal, and other tests such as KS test if the data is not normally distributed.

Reviewer #2 (Public review):

Summary:

In their manuscript the authors address the question whether the inversion polymorphism in D. melanogaster can be explained by sexually antagonistic selection. They designed a new simulation tool to perform computer simulations, which confirmed their hypothesis. They also show a tradeoff between male reproduction and survival. Furthermore, some inversions display sex-specific survival.

Strengths:

It is an interesting idea on how chromosomal inversions may be maintained

Weaknesses:

The authors motivate their study by the observation that inversions are maintained in D. melanogaster and because inversions are more frequent closer to the equator, the authors conclude that it is unlikely that the inversion contributes to adaptation in more stressful environments. Rather the inversion seems to be more common in habitats that are closer to the native environment of ancestral Drosophila populations.<br /> While I do agree with the authors that this observation is interesting, I do not think that it rules out a role in local adaptation. After all, the inversion is common in Africa, so it is perfectly conceivable that the non-inverted chromosome may have acquired a mutation contributing to the novel environment.

Based on their hypothesis, the authors propose an alternative strategy, which could maintain the inversion in a population. They perform some computer simulations, which are in line with the predicted behavior. Finally, the authors perform experiments and interpret the results as empirical evidence for their hypothesis. While the reviewer is not fully convinced about the empirical support, the key problem is that the proposed model does not explain the patterns of clinal variation observed for inversions in D. melanogaster. According to the proposed model, the inversions should have a similar frequency along latitudinal clines. So in essence, the authors develop a complicated theory because they felt that the current models do not explain the patterns of clinal variation, but this model also fails to explain the pattern of clinal variation.

Reviewer #2 (Public review):

Summary:

Vladimir Khayenko et al. discovered two novel binding pockets on HBc with in vitro binding and electron microscopy experiments. While the geranyl dimer targeting a central hydrophobic pocket displayed a micromolar affinity, the P1-dimer binding to the spike tip of HBc has a nanomolar affinity. In the turbidity assay and at the cellular level, an HBc aggregation from peptide crosslinking was demonstrated.

Strengths:

The study identifies two previously unexplored binding pockets on HBc capsids and develops novel binders targeting these sites with promising affinities.

Weaknesses:

While the in vitro and cellular HBc aggregation effects are demonstrated, the antiviral potential against HBV infection is not directly evaluated in this study.

Reviewer #2 (Public Review):

Summary:

The authors showed the applicability and usefulness of a new AlphaFold2 pipeline called PabFold, which can predict linear antibody epitopes (B-cell epitopes) that can be helpful for the selection of reagents to be applied in competitive ELISA assay.

Strengths:

The authors showed the accuracy of the pipeline to identify correctly the binding epitope for three different antibody-antigen systems (Myc, HA, and Sars-Cov2 nucleocapsid protein). The design of scFvs from Fab of the three antibodies to speed up the analysis time is extremely interesting.

Weaknesses:

The article justifies correctly the findings and no great weaknesses are present. However, it could be useful for a broader audience to show in detail how pLDDT was calculated for both Simple-Max approach (per residue-pLDDT) and Consensus analysis ( average pLDDT for each peptide), with associated equations.

Comments on revisions:

I have read the author's responses to my comments and the revised paper. They addressed the minor comments and concerns. However, I agree with Reviewer #1 that these findings cannot be reproduced without local MSAs and this is a major issue.

Reviewer #2 (Public review):

Summary:

ZFHX3 is a transcription factor expressed in discrete populations of adult SCN and was shown by the authors previously to control circadian behavioral rhythms using either a dominant missense mutation in Zfhx3 or conditional null Zfhx3 mutation using the Ubc-Cre line (Wilcox et al., 2017). In the current manuscript, the authors assess the function of ZFHX3 by using a multi-omics approach including ChIPSeq in wildtype SCNs and RNAseq of SCN tissues from both wildtype and conditional null mice. RNAseq analysis showed a loss of oscillation in Bmal1 and changes in expression levels of other clock output genes. Moreover, a phase advance gene transcriptional profile using the TimeTeller algorithm suggests the presence of a regulatory network that could underlie the observed pattern of advanced activity onset in locomotor behavior in knockout mice.

In figure1, the authors identified tthe ZFHX3 bound sites using ChIPseq and compared the loci with other histone marks that occur at promoters, TSS, enhancers and intergenic regions. And the analysis broadly points to a role for ZFHX3 in transcriptional regulation. The vast majority of nearly 40000 peaks overlapped H3K4me3 and K27ac marks, active promoters which also included genes falling under the GO category circadian rhythms. However, no significant differential ZFHX3 bound peaks were detected between ZT3 and ZT15. In these experiments, it is not clear if and how the different ChIP samples (ZFHX3 and histone PTM ChIPs) were normalized/downsampled for analysis. Moreover, it seems that ZFHX3 binding or recruitment has little to do with whether the promoters are active.

Based on a enrichment of ARNT domains next to K4Me3 and K27ac PTMs, the authors propose a model where the core-clock TFs and ZFHX3 interact. If the authors develop other assays beyond just predictions to test their hypothesis, it would strengthen the argument for role in circadian transcription in the SCN. It would be important in this context to perform a ChIP-seq experiment for ZFHX3 in the knockout animal (described from Figure 2 onwards) to eliminate the possibility of non-specific enrichment of signal from "open chromatin'. Alternatively, a ChIPseq analysis for BMAL1 or CLOCK could also strengthen this argument to identify the sites co-occupied by ZFHX3 and core-clock TFs.

Next, they compared locomotor activity rhythms in floxed mice with or without tamoxifen treatment. As reported before in Wilcox et al 2017, the loss of ZFHX3 led to a shorter free running period and reduced amplitude and earlier onset of activity. Overall, the behavioral data in Figure 2 and supplementary figure 2 has been reported before and are not novel.

Next, the authors performed RNAseq at 4hr intervals on wildtype and knockout animals maintained in light/dark cycles to determine the impact of loss of ZFHX3. Overall transcriptomic analysis indicated changes in gene expression in nearly 36% of expressed genes, with nearly half being upregulated while an equal fraction was downregulated. Pathways affected included mostly neureopeptide neurotransmitter pathways. Surprisingly, there was no correlation between the direction in change in expression and TF binding since nearly all the sites were bound by ZFHX3 and the active histone PTMs. The ChIP-seq experiment for ZFHX3 in the UBC-Cre+Tam mice again could help resolve the real targets of ZFHX3 and the transcriptional state in knockout animals.

To determine the fraction of rhythmic transcripts, Using dryR, the authors categorise the rhythmic transcriptome into modules that include genes that lose rhythmicity in the KO, gain rhythmicity in the KO or remain unaffected or partially affected. The analysis indicates that a large fraction of the rhythmic transcriptome is affected in the KO model. However, among core-clock genes only Bmal1 expression is affected showing a complete loss of rhythm. The authors state a decrease in Clock mRNA expression (line 294) but the panel figure 4A does not show this data. Instead it depicts the loss in Avp expression - {{ misstated in line 321 ( we noted severe loss in 24-h rhythm for crucial SCN neuropeptides such as Avp (Fig. 3a).}}

However, core-clock genes such as Pers and Crys show minor or no change in expression patterns while Per2 and Per3 show a ~2hr phase advance. While these could only weakly account for the behavioral phase advance, the authors used TimeTeller to assess circadian phase in wildtype and ZFHX3 deficient mice. This approach clearly indicated that while the clock is not disrupted in the knockout animals, the phase advance can be correctly predicted from a network of gene expression patterns.

Strengths:

The authors use a multiomic strategy in order to reveal the role of the ZFHX3 transcription factor with a combination of TF and histone PTM ChIPseq, time-resolved RNAseq from wildtype and knockout mice and modeling the transcriptomic data using TimeTeller. The RNAseq experiments are nicely controlled and the analysis of the data indicates a clear impact on gene-expression levels in the knockout mice and the presence of a regulatory network that could underlie the advanced activity onset behavior.

Weaknesses:

It is not clear whether ZFHX3 has a direct role in any of the processes and seems to be a general factor that marks H3K4me3 and K27ac marked chromatin. Why it would specifically impact the core-clock TTFL clock gene expression or indeed daily gene expression rhythms is not clear either. Details for treatment of different ChIP samples (ZFHX3 and histone PTM ChIPs) on data normalization for analysis are needed. The loss of complete rhythmicity of Avp and other neuropeptides or indeed other TFs could instead account for the transcriptional deregulation noted in the knockout mice.

Reviewer #2 (Public review):

Summary:

This work addresses the question of how 'leading' and 'lagging' PGCs differ, molecularly, during their migration to the mouse genital ridges/gonads during fetal life (E9.5, E10.5, E11.5), and how this is regulated by different somatic environments encountered during the process of migration. E9.5 and E10.5 cells differed in expression of genes involved in canonical WNT signaling and focal adhesions. Differences in cell adhesion, actin cytoskeletal dynamics were identified between leading and lagging cells, at E9.5, before migration into the gonads. At E10.5, when some PGCs have reached the genital ridges, differences in Nodal signaling response genes and reprogramming factors were identified. This last point was verified by whole mount IF for proteins downstream of Nodal signaling, Lefty1/2. At E11.5, there was upregulation of genes associated with chromatin remodeling and oxidative phosphorylation. Some aspects of the findings were also found to be likely true in human development, established via analysis of a dataset previously published by others.

Strengths:

The work is strong in that a large number of PGCs were isolated and sequenced, along with associated somatic cells. The authors dealt with problem of very small number of migrating mouse PGCs by pooling cells from embryos (after ascertaining age matching using somite counting). 'Leading' and 'lagging' populations were separated by anterior and posterior embryo halves and the well-established Oct4-deltaPE-eGFP reporter mouse line was used.

Weaknesses:

The work seems to have been carefully done, but I do not feel the manuscript is very accessible, and I do not consider it well written. The novel findings are not easy to find. The addition of at least one figure to show the locations of putative signaling etc. would be welcome.

(1) The initial discussion of CellRank analysis (under 'Transcriptomic shifts over developmental time...' heading) is somewhat confusing - e.g. If CellRank's 'pseudotime analysis' produces a result that seems surprising (some E9.5 cells remain in a terminal state with other E9.5 cells) and 'realtime analysis' produces something that makes more sense, is there any point including the pseudotime analysis (since you have cells from known timepoints)? Perhaps the 'batch effects' possible explanation (in Discussion) should be introduced here. Do we learn anything novel from this CellRank analysis? The 'genetic drivers' identified seem to be genes already known to be key to cell transitions during this period of development.

(2) In Discussion - with respect to Y-chromosome correlation, it is not clear why this analysis would be done at E10.5, when E11.5 data is available (because some testis-specific effect might be more apparent at the later stage).

(3) Figure 2A - it seems surprising that there are two clusters of E9.5 anterior cells

(4) Figure 5F - there does seem to be more LEFTY1/2 staining in the anterior region, but also more germ cells as highlighted by GFP

Reviewer #2 (Public review):

Summary:

Antibodies, thanks to their high binding affinity and specificity to cognate protein targets, are increasingly used as research and therapeutic tools. In this work, Zhou et al. have created, curated, and made publicly available a new database of antibody-antigen complexes to support research in the field of antibody modelling, development, and engineering.

Strengths:

The authors have performed a manual curation of antibody-antigen complexes from the Protein Data Bank, rectifying annotation errors; they have added two methods to estimate paratope-epitope interfaces; they have produced a web interface that is capable of both effective visualisation and of summarising the key useful information in one page. The database is also cross-linked to other databases that contain information relevant to antibody developability and therapeutic applications.

Weaknesses:

The database does not import all the experimental information from PDB and contains only complexes with large protein targets.

Reviewer #2 (Public review):

Summary:

In this manuscript, Mackie et al. investigate gustatory behavior and the neural basis of gustation in the predatory nematode Pristionchus pacificus. First, they show that the behavioral preferences of P. pacificus for gustatory cues differ from those reported for C. elegans. Next, they investigate the molecular mechanisms of salt sensing in P. pacificus. They show that although the C. elegans transcription factor gene che-1 is expressed specifically in the ASE neurons, the P. pacificus che-1 gene is expressed in the Ppa-ASE and Ppa-AFD neurons. Moreover, che-1 plays a less critical role in salt chemotaxis in P. pacificus than C. elegans. Chemogenetic silencing of Ppa-ASE and Ppa-AFD neurons results in more severe chemotaxis defects. The authors then use calcium imaging to show that both Ppa-ASE and Ppa-AFD neurons respond to salt stimuli. Calcium imaging experiments also reveal that the left and right Ppa-ASE neurons respond differently to salts, despite the fact that P. pacificus lacks lsy-6, a microRNA that is important for ASE left/right asymmetry in C. elegans. Finally, the authors show that the receptor guanylate cyclase gene Ppa-gcy-23.3 is expressed in the right Ppa-ASE neuron (Ppa-ASER) but not the left Ppa-ASE neuron (Ppa-ASEL) and is required for some of the gustatory responses of Ppa-ASER, further confirming that the Ppa-ASE neurons are asymmetric and suggesting that Ppa-GCY-23.3 is a gustatory receptor. Overall, this work provides insight into the evolution of gustation across nematode species. It illustrates how sensory neuron response properties and molecular mechanisms of cell fate determination can evolve to mediate species-specific behaviors. However, the paper would be greatly strengthened by a direct comparison of calcium responses to gustatory cues in C. elegans and P. pacificus, since the comparison currently relies entirely on published data for C. elegans, where the imaging parameters likely differ. In addition, the conclusions regarding Ppa-AFD neuron function would benefit from additional confirmation of AFD neuron identity. Finally, how prior salt exposure influences gustatory behavior and neural activity in P. pacificus is not discussed.

Strengths:

(1) This study provides exciting new insights into how gustatory behaviors and mechanisms differ in nematode species with different lifestyles and ecological niches. The results from salt chemotaxis experiments suggest that P. pacificus shows distinct gustatory preferences from C. elegans. Calcium imaging from Ppa-ASE neurons suggests that the response properties of the ASE neurons differ between the two species. In addition, an analysis of the expression and function of the transcription factor Ppa-che-1 reveals that mechanisms of ASE cell fate determination differ in C. elegans and P. pacificus, although the ASE neurons play a critical role in salt sensing in both species. Thus, the authors identify several differences in gustatory system development and function across nematode species.

(2) This is the first calcium imaging study of P. pacificus, and it offers some of the first insights into the evolution of gustatory neuron function across nematode species.

(3) This study addresses the mechanisms that lead to left/right asymmetry in nematodes. It reveals that the ASER and ASEL neurons differ in their response properties, but this asymmetry is achieved by molecular mechanisms that are at least partly distinct from those that operate in C. elegans. Notably, ASEL/R asymmetry in P. pacificus is achieved despite the lack of a P. pacificus lsy-6 homolog.

Weaknesses:

(1) The authors observe only weak attraction of C. elegans to NaCl. These results raise the question of whether the weak attraction observed is the result of the prior salt environment experienced by the worms. More generally, this study does not address how prior exposure to gustatory cues shapes gustatory responses in P. pacificus. Is salt sensing in P. pacificus subject to the same type of experience-dependent modulation as salt sensing in C. elegans?

(2) A key finding of this paper is that the Ppa-CHE-1 transcription factor is expressed in the Ppa-AFD neurons as well as the Ppa-ASE neurons, despite the fact that Ce-CHE-1 is expressed specifically in Ce-ASE. However, additional verification of Ppa-AFD neuron identity is required. Based on the image shown in the manuscript, it is difficult to unequivocally identify the second pair of CHE-1-positive head neurons as the Ppa-AFD neurons. Ppa-AFD neuron identity could be verified by confocal imaging of the CHE-1-positive neurons, co-expression of Ppa-che-1p::GFP with a likely AFD reporter, thermotaxis assays with Ppa-che-1 mutants, and/or calcium imaging from the putative Ppa-AFD neurons.

(3) Loss of Ppa-che-1 causes a less severe phenotype than loss of Ce-che-1. However, the loss of Ppa-che-1::RFP expression in ASE but not AFD raises the question of whether there might be additional start sites in the Ppa-che-1 gene downstream of the mutation sites. It would be helpful to know whether there are multiple isoforms of Ppa-che-1, and if so, whether the exon with the introduced frameshift is present in all isoforms and results in complete loss of Ppa-CHE-1 protein.

(4) The authors show that silencing Ppa-ASE has a dramatic effect on salt chemotaxis behavior. However, these data lack control with histamine-treated wild-type animals, with the result that the phenotype of Ppa-ASE-silenced animals could result from exposure to histamine dihydrochloride. This is an especially important control in the context of salt sensing, where histamine dihydrochloride could alter behavioral responses to other salts.

(5) The calcium imaging data in the paper suggest that the Ppa-ASE and Ce-ASE neurons respond differently to salt solutions. However, to make this point, a direct comparison of calcium responses in C. elegans and P. pacificus using the same calcium indicator is required. By relying on previously published C. elegans data, it is difficult to know how differences in growth conditions or imaging conditions affect ASE responses. In addition, the paper would be strengthened by additional quantitative analysis of the calcium imaging data. For example, the paper states that 25 mM NH4Cl evokes a greater response in ASEL than 250 mM NH4Cl, but a quantitative comparison of the maximum responses to the two stimuli is not shown.

(6) It would be helpful to examine, or at least discuss, the other P. pacificus paralogs of Ce-gcy-22. Are they expressed in Ppa-ASER? How similar are the different paralogs? Additional discussion of the Ppa-gcy-22 gene expansion in P. pacificus would be especially helpful with respect to understanding the relatively minor phenotype of the Ppa-gcy-22.3 mutants.

(7) The calcium imaging data from Ppa-ASE is quite variable. It would be helpful to discuss this variability. It would also be helpful to clarify how the ASEL and ASER neurons are being conclusively identified during calcium imaging.

(8) More information about how the animals were treated prior to calcium imaging would be helpful. In particular, were they exposed to salt solutions prior to imaging? In addition, the animals are in an M9 buffer during imaging - does this affect calcium responses in Ppa-ASE and Ppa-AFD? More information about salt exposure, and how this affects neuron responses, would be very helpful.

(9) In Figure 6, the authors say that Ppa-gcy-22.3::GFP expression is absent in the Ppa-che-1(ot5012) mutant. However, based on the figure, it looks like there is some expression remaining. Is there a residual expression of Ppa-gcy-22.3::GFP in ASE or possibly ectopic expression in AFD? Does Ppa-che-1 regulate rGC expression in AFD? It would be helpful to address the role of Ppa-che-1 in AFD neuron differentiation.

Reviewer #2 (Public review):

Summary:

In this study, the authors report that Meioc is required to upregulate rRNA transcription and promote differentiation of spermatogonial stem cells in zebrafish. The authors show that upregulated protein synthesis is required to support spermatogonial stem cells' differentiation into multi-celled cysts of spermatogonia. Coiled coil protein Meioc is required for this upregulated protein synthesis and for increasing rRNA transcription, such that the Meioc knockout accumulates 1-2 cell spermatogonia and fails to produce cysts with more than 8 spermatogonia. The Meioc knockout exhibits continued transcriptional repression of rDNA. Meioc interacts with and sequesters Piwil1 to the cytoplasm. Loss of Meioc increases Piwil1 localization to the nucleolus, where Piwil1 interacts with transcriptional silencers that repress rRNA transcription.

Strengths:

This is a fundamental study that expands our understanding of how ribosome biogenesis contributes to differentiation and demonstrates that zebrafish Meioc plays a role in this process during spermatogenesis. This work also expands our evolutionary understanding of Meioc and Ythdc2's molecular roles in germline differentiation. In mouse, the Meioc knockout phenocopies the Ythdc2 knockout, and studies thus far have indicated that Meioc and Ythdc2 act together to regulate germline differentiation. Here, in zebrafish, Meioc has acquired a Ythdc2-independent function. This study also identifies a new role for Piwil1 in directing transcriptional silencing of rDNA.

Weaknesses:<br /> There are limited details on the stem cell-enriched hyperplastic testes used as a tool for mass spec experiments, and additional information is needed to fully evaluate the mass spec results. What mutation do these testes carry? Does this protein interact with Meioc in the wildtype testes? How could this mutation affect the results from the Meioc immunoprecipitation?

Reviewer #2 (Public review):

Summary:

This work assesses the genetic interaction between the Bmp signaling pathway and the factor Numb, which can inhibit Notch signalling. It follows up on the previous studies of the group (Tian, Elife, 2014; Tian, PNAS, 2014) regarding BMP signaling in controlling stem cell fate decision as well as on the work of another group (Sallé, EMBO, 2017) that investigated the function of Numb on enteroendocrine fate in the midgut. This is an important study providing evidence of a Numb-mediated back up mechanism for stem cell maintenance.

Strengths:

(1) Experiments are consistent with these previous publications while also extending our understanding of how Numb functions in the ISC.<br /> (2) Provides an interesting model of a "back up" protection mechanism for ISC maintenance.

Weaknesses:<br /> (1) Aspects of the experiments could be better controlled or annotated:<br /> (a) As they "randomly chose" the regions analyzed, it would be better to have all from a defined region (R4 or R2, for example) or to at least note the region as there are important regional differences for some aspects of midgut biology.<br /> (b) It is not clear to me why MARCM clones were induced and then flies grown at 18{degree sign}C? It would help to explain why they used this unconventional protocol.

(2) There are technical limitations with trying to conclude from double-knockdown experiments in the ISC lineage, such as those in Figure 1 where Dl and put are both being knocked down: depending on how fast both proteins are depleted, it may be that only one of them (put, for example) is inactivated and affects the fate decision prior to the other one (Dl) being depleted. Therefore, it is difficult to definitively conclude that the decision is independent of Dl ligand.

(3) Additional quantification of many phenotypes would be desired.<br /> (a) It would be useful to see esg-GFP cells/total cells and not just field as the density might change (2E for example).<br /> (b) Similarly, for 2F and 2G, it would be nice to see the % of ISC/ total cell and EB/total cell and not only per esgGFP+ cell.<br /> (c) Fig1: There is no quantification - specifically it would be interesting to know how many esg+ are su(H)lacZ positive in Put- Dl- condition compared to WT or Put- alone. What is the n?<br /> (d) Fig2: Pros + cells are not seen in the image? Are they all DllacZ+?<br /> (e) Fig3: it would be nice to have the size clone quantification instead of the distribution between groups of 2 cell 3 cells 4 cell clones.<br /> (f) How many times were experiments performed?

(4) The authors do not comment on the reduction of clone size in DSS treatment in Figure 6K. How do they interpret this? Does it conflict with their model of Bleo vs DSS?

(5) There is probably a mistake on sentence line 314 -316 "Indeed, previous studies indicate that endogenous Numb was not undetectable by Numb antibodies that could detect Numb expression in the nervous system".

Reviewer #2 (Public review):

Summary:<br /> Epigenetic regulation is critical for maintaining cellular function, and its dysregulation contributes to senescence and disease. This manuscript investigates the role of TET2 in β cell aging, proposing that TET2-mediated PTEN DNA methylation promotes H4K16 acetylation (H4K16ac) through MOF, driving β cell senescence. Using TET2 inhibitors, RNA interference, lentiviral overexpression, and knockout mouse models, the authors aim to establish TET2 as a key player in β cell aging and a potential therapeutic target in type 2 diabetes mellitus (T2DM).<br /> However, significant limitations reduce the manuscript's impact. Figures are poorly presented, with illegible fonts and unquantified staining panels, while key analyses, such as β cell specificity and senescence inducers, are missing. The rationale for focusing on H4K16ac and MOF is unclear, and the authors fail to address whether β cell identity gene changes reflect altered gene expression or mass. Additionally, critical controls, such as low-fat diet cohorts, are absent, and the writing lacks clarity and coherence. Together, these weaknesses undermine the validity of the findings.

Main Comments<br /> Figures 1 and 2:<br /> The fonts in Figures 1 and 2 are barely visible and should be improved for readability. Additionally, do TET2 protein levels change in mouse and human β cells with aging? Is there evidence from regression analyses using single-cell RNA sequencing on human islets that TET2 expression correlates with age-associated gene signatures in β cells? Are these correlations specific to β cells, or do they extend to other islet cell types? It would also be informative to assess whether TET2 levels increase with senescence inducers such as DNA damage agents (e.g., bleomycin, doxorubicin) or reactive oxygen species (e.g., H₂O₂).<br /> Figure 3:<br /> Why do TET2 protein levels appear stronger in acinar cells? Additionally, the predominant cellular localization of TET2 seems to be cytoplasmic. Can the authors clarify or expand on this observation?<br /> Figure 4:<br /> The data on the impact of TET2 insufficiency in vivo is compelling. There are several quality control experiments to validate their model and main hypothesis (That T2t2 expression increases with aging in beta-cells). Here, authors have the right system to validate their initial Tet2 protein dynamics in the mouse, since they have a KO mouse model. Here, it would be useful to co-stain Tet2 with insulin and glucagon, to infer the dynamics of Tet2 in the two most abundant islet cell types.<br /> Figure 5:<br /> The upregulation of β-cell identity genes in the KO mouse model raises an important question: Is this effect due to an actual increase in gene expression or simply a higher proportion of β cells? Quantifying β-cell mass and performing gene expression analyses on FACS-sorted β cells would help address this. Additionally, the staining panels lack quantification. For instance, GLUT2 staining appears cytoplasmic when it should be membranous. The authors focus on cellular senescence, but does apoptosis increase in wild-type mice under a high-fat diet (HFD)? Including animals on a low-fat diet (LFD) for comparison would add valuable context.<br /> Figure 6:<br /> The data suggest an increase in cell numbers in TET2-overexpressing cells. Does this indicate an effect on β-cell proliferation? Quantification would provide clarity.<br /> Figure 8:<br /> The rationale for focusing on H4K16ac is insufficiently discussed. What is the mechanism linking TET2-induced changes to decreased H4K16ac levels? Including a more thorough explanation in the introduction and discussion would enhance the manuscript.<br /> Figure 9:<br /> The introduction lacks any discussion of H4K16ac or MOF. The discussion paragraph (lines 530-540) that elaborates on these points should instead be moved to the introduction to improve the manuscript's flow. Furthermore, the authors should cite their 2022 paper on H4K16ac as part of the rationale for focusing on this histone modification.

Minor Comments:<br /> The manuscript would benefit from language refinement. Examples include:<br /> Line 183: Replace "the blood included" with a more precise description.<br /> Line 315: "treated with RNA seq" should be rephrased to clarify methodology (e.g., "analyzed via RNA sequencing").<br /> Line 456: Replace "expression of H4K16ac" with "levels of H4K16ac."<br /> Line 496: The phrase "can solve scientific problems from multiple dimensions" sounds vague and overly broad; consider rephrasing to be more specific.

Reviewer #2 (Public review):

Summary:

Previous studies have shown that Topoisomerase 2 (Top2) depletion in yeast can extend the lifespan of the organism, but no known mechanisms have been reported. In the current study, Zhu et al. reported that reduction of Top2 enhances longevity and mitigates aging phenotypes across multiple model organisms, including not yeast, but also C. elegans and mouse. The evidence of reduction of aging phenotypes is particularly strong, which include markers of cellular senescence, nutrient sensing, epigenetic markers, and lysosome biogenesis. They propose that Top2b reduction confers longevity through a conserved mechanism, and may be used a novel therapeutic strategy for countering aging. Overall, their findings should be of broad interest to the fields of Aging and Topoisomerase research. The technical quality of the work is in general solid but can be improved.

Strengths:

Top2 is an essential type II topoisomerase that resolves DNA topological stress generated during transcription, replication, chromosome segregation, and other DNA metabolic processes by introducing transient double-strand breaks (DSBs), passing the DNA strands, and re-ligating them. Top2 is a target for anticancer therapies, but its connection to aging and longevity remains largely unexplored. The authors' findings are notable, as Top2 has been deemed indispensable for normal development. Yet, this study suggests that its reduction confers benefits in the context of healthy aging. Their results convincingly show extended lifespan and improvements in physiological and molecular aging phenotypes, supported by behavioral assays and tissue morphology analyses.

Weaknesses:

Despite these strengths, the manuscript is weak on the proposed "conserved mechanism". The authors proposed in Discussion that Top2/Top2b knockdown may be similar to the classical insulin/IGF1 and the mTORC pathway, but did not provide any genetic evidence to support this.

The authors also mentioned in the Discussion that the potential mechanism could be selective down-regulation of transcription of genes of active promoter and high abundance, such as ribosomal genes, which could be relevant to yeast aging. But there is no evidence in worms or mouse that Top2b directly binds and promotes transcription of certain high abundance genes critical for aging.

I understand that this mechanism issue may be difficult to address, and I do not expect that the authors can fully address this issue. However, as both yeast and worms have been widely-used in aging studies with many tools available, I suggest that the authors can improve their studies by performing the following experiments.

Reviewer #2 (Public review):

Summary:

In this work, the authors present a biologically plausible, efficient E-I spiking network model and study various aspects of the model and its relation to experimental observations. This includes a derivation of the network into two (E-I) populations, the study of single-neuron perturbations and lateral-inhibition, the study of the effects of adaptation and metabolic cost, and considerations of optimal parameters. From this, they conclude that their work puts forth a plausible implementation of efficient coding that matches several experimental findings, including feature-specific inhibition, tight instantaneous balance, a 4 to 1 ratio of excitatory to inhibitory neurons, and a 3 to 1 ratio of I-I to E-I connectivity strength.

Strengths:

While many network implementations of efficient coding have been developed, such normative models are often abstract and lacking sufficient detail to compare directly to experiments. The intention of this work to produce a more plausible and efficient spiking model and compare it with experimental data is important and necessary in order to test these models. In rigorously deriving the model with real physical units, this work maps efficient spiking networks onto other more classical biophysical spiking neuron models. It also attempts to compare the model to recent single-neuron perturbation experiments, as well as some long-standing puzzles about neural circuits, such as the presence of separate excitatory and inhibitory neurons, the ratio of excitatory to inhibitory neurons, and E/I balance. One of the primary goals of this paper, to determine if these are merely biological constraints or come from some normative efficient coding objective, is also important. Lastly, though several of the observations have been reported and studied before, this work arguably studies them in more depth, which could be useful for comparing more directly to experiments.

Weaknesses:

This work is the latest among a line of research papers studying the properties of efficient spiking networks. Many of the characteristics and findings here have been discussed before, thereby limiting the new insights that this work can provide. Thus, the conclusions of this work should be considered and understood in the context of those previous works, as the authors state. Furthermore, the number of assumptions and free parameters in the model, though necessary to bring the model closer to biophysical reality, make it more difficult to understand and to draw clear conclusions from. As the authors state, many of the optimality claims depend on these free parameters, such as the dimensionality of the input signal (M=3), the relative weighting of encoding error and metabolic cost, and several others. This raises the possibility that it is not the case that the set of biophysical properties measured in the brain are accounted for by efficient coding, but rather that theories of efficient coding are flexible enough to be consistent with this regime. With this in mind, some of the conclusions made in the text may be overstated and should be considered in this light.

Conclusions, Impact, and additional context:

Notions of optimality are important for normative theories, but they are often studied in simple models with as few free parameters as possible. Biophysically detailed and mechanistic models, on the other hand, will often have many free parameters by their very nature, thereby muddying the connection to optimality. This tradeoff is an important concern in neuroscientific models. Previous efficient spiking models have often been criticized for their lack of biophysically-plausible characteristics, such as large synaptic weights, dense connectivity, and instantaneous communication. This work is an important contribution in showing that such networks can be modified to be much closer to biophysical reality without losing their essential properties. Though the model presented does suffer from complexity issues which raise questions about its connections to "optimal" efficient coding, the extensive study of various parameter dependencies offers a good characterization of the model and puts its conclusions in context.

Reviewer #2 (Public review):

Summary:

The study of Rollenhagen et al examines the ultrastructural features of Layer 1 of human temporal cortex. The tissue was derived from drug-resistant epileptic patients undergoing surgery, and was selected as further from the epilepsy focus, and as such considered to be non-epileptic. The analyses has included 4 patients with different age, sex, medication and onset of epilepsy. The MS is a follow-on study with 3 previous publications from the same authors on different layers of the temporal cortex:

Layer 4 - Yakoubi et al 2019 eLife<br /> Layer 5 - Yakoubi et al 2019 Cerebral Cortex,<br /> Layer 6 - Schmuhl-Giesen et al 2022 Cerebral Cortex

They find, the L1 synaptic boutons mainly have single active zone a very large pool of synaptic vesicles and are mostly devoid of astrocytic coverage.

Strengths:

The MS is well written easy to read. Result section gives a detailed set of figures showing many morphological parameters of synaptic boutons and surrounding glial elements. The authors provide comparative data of all the layers examined by them so far in the Discussion. Given that anatomical data in human brain are still very limited, the current MS has substantial relevance.<br /> The work appears to be generally well done, the EM and EM tomography images are of very good quality. The analyses is clear and precise.

Weaknesses:

The authors made all the corrections required, answered most of my concerns, included additional data sets, and clarified statements where needed.

My remaining points are:

Synaptic vesicle diameter (that has been established to be ~40nm independent of species) can properly be measured with EM tomography only, as it provides the possibility to find the largest diameter of every given vesicle. Measuring it in 50 nm thick sections result in underestimation (just like here the values are ~25 nm) as the measured diameter will be smaller than the true diameter if the vesicle is not cut in the middle, (which is the least probable scenario). The authors have the EM tomography data set for measuring the vesicle diameter properly.

It is a bit misleading to call vesicle populations at certain arbitrary distances from the presynaptic active zone as readily releasable pool, recycling pool and resting pool, as these are functional categories, and cannot directly be translated to vesicles at certain distances. Even it is debated whether the morphologically docked vesicles are the ones, that are readily releasable, as further molecular steps, such as proper priming is also a prerequisite for release.<br /> It would help to call these pools as "putative" correlates of the morphological categories.

Reviewer #2 (Public review):

Summary:

The study reported by Trutti et al. uses high-field fMRI to test the hypothesized involvement of subcortical structure, particularly striatum, in WM updating. Specifically, participants were scanned while performing the Reference Back task (e.g., Rac-Lubashevsky and Kessler, 2016), which tests constructs like working memory gate opening and closing and substitution. While striatal activation was involved in substitution, it was not observed in gate opening.

While there have been prior fMRI studies of the reference back task (Nir-Cohen et al., 2020), the present study overcomes limitations in prior work, particularly with regard to subcortical structures, by applying high-field imaging with more precise definition of ROIs. And, the fMRI methods are careful and rigorous, overall. Thus, the empirical observations here are useful and will be of interest to specialists interested in working memory gating or the reference back task specifically. I do not have additional concerns about this contribution.

Reviewer #2 (Public review):

Summary:

This Phase II clinical trial investigates the combination of Gamma Knife Stereotactic Body Radiation Therapy (SBRT) with Tislelizumab for the treatment of metastatic colorectal cancer (mCRC) in patients with proficient mismatch repair (pMMR). The study addresses a critical clinical challenge in the management of pMMR CRC, focusing on the selection of appropriate candidates. The results suggest that the combination of Gamma Knife SBRT and Tislelizumab provides a safe and potent treatment option for patients with pMMR/MSS/MSI-L mCRC who have become refractory to first- and second-line chemotherapy. The study design is rigorous, and the outcomes are promising.

Advantage:

The trial design was meticulously structured, and appropriate statistical methods were employed to rigorously analyze the results. Bioinformatics approaches were utilized to further elucidate alterations in the patient's tumor microenvironment and to explore the underlying factors contributing to the observed differences in treatment efficacy. The conclusions drawn from this trial offer valuable insights for managing advanced colorectal cancer in patients who have not responded to first- and second-line therapies.

Weakness:

(1) Clarity and Structure of the Abstract<br /> - Results Section: The results section should contain important data, I suggest some important sequencing data should be shown to enhance understanding.<br /> (2) As the author using the NanoString assay for transcriptome analysis, more detail should be shown such as the version of R, and the bioinformatics analysis methods.<br /> (3) It is interesting for included patients that PD-L1 increase expression after Gamma Knife Stereotactic Body Radiation Therapy (SBRT) treatment, How to explain it?<br /> (4) It would be helpful to include a brief discussion of the limitations of the study, such as sample size constraints and their impact on the generalizability of the results. This will give readers a more comprehensive understanding of the findings.<br /> (5) Language Accuracy: There are a few instances where wording could be more professional or precise.

Reviewer #2 (Public review):

Franziska Auer et al. successfully applied the TRPV1/capsaicin tool to study the contribution of Purkinje cells to postural control. They leveraged the ability of this tool to both activate and ablate neurons within the same construct and tested its effects using their smart, high-throughput behavioral setup for postural control monitoring. With Purkinje cells ablated, balance did not appear to be disrupted; however, postural control was clearly modified along the pitch axis, with larval zebrafish maintaining, on average, a more nose-down posture compared to controls. While this effect is subtle, it is statistically robust and consistent with the group's previous findings using KillerRed-mediated ablation of Purkinje cells, where the observed postural angle change was explained by a disruption in cerebellar-mediated fin-trunk coordination. Here, the authors present a novel insight, demonstrating that this coordination is swim-speed dependent.

Furthermore, the authors convincingly activated Purkinje cells at 7 dpf, and reported modifications in posture pitch angle comparable to those observed when ablating Purkinje cells. The authors suggest a potential desynchronization of Purkinje cells to explain this observation. Future characterization and application of this activation method to other developmental time points could be of major interest. The authors successfully validated the transfer of the TRPV1/capsaicin method for targeted cell ablation and activation to the study of cerebellar functions and reinforced our current understanding of the role of Purkinje cells in postural control.

This study also explores the developmental evolution of cerebellar function in postural control by comparing the effects of Purkinje cell ablation at 7 dpf and 14 dpf. Interestingly, only dive bout posture showed differential effects across these time points, with no significant impact at 7 dpf but a significant change in postural pitch angle at 14 dpf. In contrast, the effect of Purkinje cell ablation on the climbing bout postural angle remained comparable at both ages. Including additional developmental time points would further strengthen this critical characterization of cerebellar maturation in the context of postural control.

To examine whether Purkinje cell activity encodes postural tilt angle, the authors performed calcium imaging on 31 cells from 8 fish using their Tilt In Place Microscope (TIPM). They found that tilt-angle could be decoded from individual neurons with highly tuned responses, as well as from neurons that were not obviously tuned when pooling their data. The authors refer to this effect as pseudo-population coding because recordings were performed non-simultaneously across animals.

This study successfully integrates cutting-edge genetic tools, high-throughput behavioral assays, and advanced optical microscopy to investigate the role of populations of Purkinje cells in postural control. The authors have not only validated these powerful tools but have also provided novel insights into the cerebellar involvement in postural control, including the swim-speed dependence of fin-trunk coordination.

This work represents an important step toward a detailed understanding of cerebellar contributions to postural control and highlights the potential of combining genetically targeted perturbation with quantitative behavioral analysis.

The authors have addressed my previous concerns, and I congratulate them for their excellent work.

Reviewer #2 (Public review):

Summary:

We have known for some time that neural progenitors in the cerebral cortex switch their output from cortical neurons to glia at late embryonic stages, however little is known about how this switch is regulated at the molecular level. Bose et al present a convincing set of findings, demonstrating that the transcription factor Foxg1 plays a key role in this process, mediated through FGF signalling. Foxg1 cell-autonomously inhibits gliogenesis in progenitor cells (thereby promoting neuronal identity), and lower Foxg1 expression in postnatal neurons leads to increased expression of FGF ligand, promoting glial development from nearby progenitors.

Strengths:

The study is very well designed, having a systematic, thorough, and logical approach. The data is convincing. The authors make full use of a range of existing transgenic strains, published 'omics data, and elegant genetic approaches such as MADM. This combination of approaches is particularly rigorous, lending significant weight to the study. The manuscript is well-written, clear, and easy to follow.

Impact

This manuscript identifies a previously unknown role for Foxg1 in forebrain development and a mechanism underlying the neurogenic-to-gliogenic switch that occurs at late embryonic stages of cortex development. These findings will stimulate further research to uncover more details of how this important switch is controlled and may provide useful insight into some of the symptoms experienced by children with FOXG1 Syndrome.

Reviewer #2 (Public review):

Summary:

Using a gerbil model, the authors tested the hypothesis that loss of synapses between sensory hair cells and auditory nerve fibers (which may occur due to noise exposure or aging) affects behavioral discrimination of the rapid temporal fluctuations of sounds. In contrast to previous suggestions in the literature, their results do not support this hypothesis; young animals treated with a compound that reduces the number of synapses did not show impaired discrimination compared to controls. Additionally, their results from older animals showing impaired discrimination suggest that age-related changes aside from synaptopathy are responsible for the age-related decline in discrimination.

Strengths:

(1) The rationale and hypothesis are well-motivated and clearly presented.

(2) The study was well conducted with strong methodology for the most part, and good experimental control. The combination of physiological and behavioral techniques is powerful and informative. Reducing synapse counts fairly directly using ouabain is a cleaner design than using noise exposure or age (as in other studies), since these latter modifiers have additional effects on auditory function.

(3) The study may have a considerable impact on the field. The findings could have important implications for our understanding of cochlear synaptopathy, one of the most highly researched and potentially impactful developments in hearing science in the past fifteen years.

Weaknesses:

(1) My main concern is that the stimuli may not have been appropriate for assessing neural temporal coding behaviorally. Human studies using the same task employed a filter center frequency that was (at least) 11 times the fundamental frequency (Marmel et al., 2015; Moore and Sek, 2009). Moore and Sek wrote: "the default (recommended) value of the centre frequency is 11F0." Here, the center frequency was only 4 or 8 times the fundamental frequency (4F0 or 8F0). Hence, relative to harmonic frequency, the harmonic spacing was considerably greater in the present study. By my calculations, the masking noise used in the present study was also considerably lower in level relative to the harmonic complex than that used in the human studies. These factors may have allowed the animals to perform the task using cues based on the pattern of activity across the neural array (excitation pattern cues), rather than cues related to temporal neural coding. The authors show that mean neural driven rate did not change with frequency shift, but I don't understand the relevance of this. It is the change in response of individual fibers with characteristic frequencies near the lowest audible harmonic that is important here.

The case against excitation pattern cues needs to be better made in the Discussion. It could be that gerbil frequency selectivity is broad enough for this not to be an issue, but more detail needs to be provided to make this argument. The authors should consider what is the lowest audible harmonic in each case for their stimuli, given the level of each harmonic and the level of the pink noise. Even for the 8F0 center frequency, the lowest audible harmonic may be as low as the 4th (possibly even the 3rd). In human, harmonics are thought to be resolvable by the cochlea up to at least the 8th.

(2) The synapse reductions in the high ouabain and old groups were relatively small (mean of 19 synapses per hair cell compared to 23 in the young untreated group). In contrast, in some mouse models of the effects of noise exposure or age, a 50% reduction in synapses is observed, and in the human temporal bone study of Wu et al. (2021, https://doi.org/10.1523/JNEUROSCI.3238-20.2021) the age-related reduction in auditory nerve fibres was ~50% or greater for the highest age group across cochlear location. It could be simply that the synapse loss in the present study was too small to produce significant behavioral effects. Hence, although the authors provide evidence that in the gerbil model the age-related behavioral effects are not due to synaptopathy, this may not translate to other species (including human). This should be discussed in the manuscript.

It would be informative to provide synapse counts separately for the animals who were tested behaviorally, to confirm that the pattern of loss across the group was the same as for the larger sample.

(3) The study was not pre-registered, and there was no a priori power calculation, so there is less confidence in replicability than could have been the case. Only three old animals were used in the behavioral study, which raises concerns about the reliability of comparisons involving this group.

Reviewer #2 (Public review):

Summary:

The authors investigated DG neuronal activity at the population and single cell level across sleep/wake periods. They found an infraslow oscillation (0.01-0.03 Hz) in both granule cells (GC) and mossy cells (MC) during NREM sleep. The important findings are 1) the antiparallel temporal dynamics of DG neuron activities and serotonin neuron activities/extracellular serotonin levels during NREM sleep, and 2) the GC Htr1a-mediated GC infraslow oscillation.

Strengths:

(1) The combination of polysomnography, Ca-fiber photometry, two-photon microscopy and gene depletion is technically sound. The coincidence of microarousals and dips in DG population activity is convincing. The dip in activity in upregulated cells is responsible for the dip at the population level.<br /> (2) DG GCs express excitatory Htr4 and Htr7 in addition to inhibitory Htr1a, but deletion of Htr1a is sufficient to disrupt DG GC infraslow oscillation, supporting the importance of Htr1a in DG activity during NREM sleep.

Weaknesses:

(1) The current data set and analysis are insufficient to interpret the observation correctly.<br /> a. In Fig 1A, during NREM, the peaks and troughs of GC population activities seem to gradually decrease over time. Please address this point.<br /> b. In Fig 1F, about 30% of Ca dips coincided with MA (EMG increase) and 60% of Ca dips did not coincide with EMG increase. If this is true, the readers can find 8 Ca dips which are not associated with MAs from Fig 1E. If MAs were clustered, please describe this properly.<br /> c. In Fig 1F, the legend stated the percentage during NREM. If the authors want to include the percentage of wake and REM, please show the traces with Ca dips during wake and REM. This concern applies to all pie charts provided by the authors.<br /> d. In Fig 1C, please provide line plots connecting the same session. This request applies to all related figures.<br /> e. In Fig 2C, the significant increase during REM and the same level during NREM are not convincing. In Fig 2A, the several EMG increasing bouts do not appear to be MA, but rather wakefulness, because the duration of the EMG increase is greater than 15 seconds. Therefore, it is possible that the wake bouts were mixed with NREM bouts, leading to the decrease of Ca activity during NREM. In fact, In Fig 2E, the 4th MA bout seems to be the wake bout because the EMG increase lasts more than 15 seconds.<br /> f. Fig 5D REM data are interesting because the DRN activity is stably silenced during REM. The varied correlation means the varied DG activity during REM. The authors need to address it.<br /> g. In Fig 6, the authors should show the impact of DG Htr1a knockdown on sleep/wake structure including the frequency of MAs. I agree with the impact of Htr1a on DG ISO, but possible changes in sleep bout may induce the DG ISO disturbance.

(2) It is acceptable that DG Htr1a KO induces the reduced freezing in the CFC test (Fig. 6E, F), but it is too much of a stretch that the disruption of DG ISO causes impaired fear memory. There should be a correlation.

(3) It is necessary to describe the extent of AAV-Cre infection. The authors injected AAV into the dorsal DG (AP -1.9 mm), but the histology shows the ventral DG (Supplementary Fig. 4), which reduces the reliability of this study.

Comments on revisions:

In the first revision, I pointed out the inappropriate analysis of the EEG/EMG/photometry data and gave examples. The authors responded only to the points raised and did not seem to see the need to improve the overall analysis and description. In this second revision, I would like to ask the authors to improve them. The biggest problem is that the detection criteria and the quantification of the specific event are not described at all in Methods and it is extremely difficult to follow the statement. All interpretations are made by the inappropriate data analysis; therefore, I have to say that the statement is not supported by the data.

Please read my following concerns carefully and improve them.

(1) The definition of the event is critical to the detection of the event and the subsequent analysis. In particular, the authors explicitly describe the definition of MA (microarousal), the trough and peak of the population level of intracellular Ca concentrations, or the onset of the decline and surge of Ca levels.

(1-1) The authors categorized wake bouts of <15 seconds with high EMG activity as MA (in Methods). What degree of high EMG is relevant to MA and what is the lower limit of high EMG? In Fig 1E, there are some EMG spikes, but it was unclear which spike/wave (amplitude/duration) was detected as MA-relevant spike and which spike was not detected. In Fig 2E, the 3rd MA coincides with the EMG spike, but other EMG spikes have comparable amplitude to the 3rd MA-relevant EMG spike. Correct counting of MA events is critical in Fig 1F, 2F, 4C.

(1-2) Please describe the definition of Ca trough in your experiments. In Fig 1G, the averaged trough time is clear (~2.5 s), so I can acknowledge that MA is followed by Ca trough. However, the authors state on page 4 that "30% of the calcium troughs during NREM sleep were followed by an MA epoch". This discrepancy should be corrected.

(1-3) Relating comment 1-2, I agree that the latency is between MA and Ca through in page 4, as the authors explain in the methods, but, in Fig 1G, t (latency) is labeled at incorrect position. Please correct this.

(1-4) The authors may want to determine the onset of the decline in population Ca activity and the latency between onset and trough (Fig 1G, latency t). If so, please describe how the onset of the decline is determined. In Fig 1G, 2G, S6, I can find the horizontal dashed line and infer that the intersection of the horizontal line and the Ca curve is considered the onset. However, I have to say that the placement of this horizontal line is super arbitrary. The results (t and Drop) are highly dependent on the position of horizontal line, so the authors need to describe how to set the horizontal line.

(1-5) In order to follow Fig 1F correctly, the authors need to indicate the detection criteria of "Ca dip (in legend)". Please indicate "each Ca dip" in Fig 1E. As a reader, I would like to agree with the Ca dip detection of this Ca curve based on the criteria. Please also indicate "each Ca dip" in Fig 2E and 2F. In the case of the 2nd and 3rd MAs, do they follow a single Ca dip or does each MA follow each Ca dip? This chart is highly dependent on the detection criteria of Ca dip.

As I mentioned above, most of the quantifications are not based on the clear detection criteria. The authors need to re-analyze the data and fix the quantification. Please interpret data and discuss the cellular mechanism of ISO based on the re-analyzed quantification.

Reviewer #4 (Public review):

Summary:

Wilmes and colleagues develop a model for the computation of uncertainty modulated prediction errors based on an experimentally inspired cortical circuit model for predictive processing. Predictive processing is a promising theory of cortical function. An essential aspect of the model is the idea of precision weighting of prediction errors. There is ample experimental evidence for prediction error responses in cortex. However, a central prediction of the theory is that these prediction error responses are regulated by the uncertainty of the input. Testing this idea experimentally has been difficult due to a lack of concrete models. This work provides one such model and makes experimentally testable predictions.

Strengths:

The model proposed is novel and well-implemented. It has sufficient biological accuracy to make useful and testable predictions.

Weaknesses:

One key idea the model hinges on is that stimulus uncertainty is encoded in the firing rate of parvalbumin positive interneurons. While this assumption is rather speculative, the model also here makes experimentally testable predictions.

Comments on revisions:

Congratulations on a very nice paper.

Reviewer #3 (Public review):

The study by Chen et al reports an interesting and previously unknown phenomenon of generation of supernumerary inner hair cells (IHCs) in response to downregulation of Cldn9 during embryonic or postnatal development. The authors developed an inducible doxycycline (dox)-tet-OFF-Cldn9 transgenic mice to regulate expression levels of Cldn9 and show that downregulation of Cldn9 resulted in additional, although incomplete row of IHCs immediately adjacent to the original IHC row. These induced extra IHCs had similar well-developed hair bundles, able to mechanotransduce and were innervated by auditory neurons, resembling wild-type IHCs. In addition, the authors knock down Cldn9 postnatally using shRNA injections in P1-7 mice with similar induction of extranumerary IHCs next to the original row of IHCs. The conclusions of this paper are mostly well supported by the data. However, some data analyses are limited, and some important controls are not shown.<br /> The data from this study are important and promising for future gene therapy applications. The generation of extra IHCs postnatally using downregulation of Cldn9 by shRNA could potentially be used as a replacement of IHCs lost after noise-induced trauma, ototoxic agents, or other environmental trauma. However, it is not clear if downregulation of CLDN9 in adult mice would lead to extranumerary IHCs. On the other hand, the replacement of lost inner hair cells due to various genetic mutations by inducing supernumerary mutant IHCs with the same abnormalities would not be reasonable.

The authors show that postnatally generated ectopic IHCs are viable and mechanotransducive, but the hearing function of the mice with ectopic hair cells is not improved. However, the ectopic hair cells seems to be generated from supporting cell trans-differentiation, and the intricate mosaic of the organ of Corti is altered (the extra row of IHCs seems to be positioned immediately adjacent to the original IHC row), which could by itself lead to hearing issues. It is not clear if the newly formed unusual junctions between the ectopic and original IHCs are sufficiently tight to prevent leakage of the endolymph to the basolateral surface of IHCs. Also, it is not clear if the other organ of Corti tight junctions could lose their tightness due to the downregulation of Cldn9, which could over time affect the endocochlear potential and hearing abilities as shown by this study.

Overall, the manuscript could be of interest to scientists working in the inner ear development and regeneration field, and to the hearing researchers in general and perhaps developmental biologists and cell biologists interested in tight junction proteins and their function.

Strength

The methodologies used are solid and convincing. There is a great potential for practical use of these valuable findings and new knowledge on IHC developmental regulation by Cldn9 expression.

Weakness

Some of the data in this study would benefit from showing corresponding negative controls and higher-resolution images of CLDN9 localization, which the authors chose not to show in the revised manuscript. Importantly, CLDN9 immunofluorescence staining data look different from previously published observations and show cytoplasmic staining of supporting cells only and did not show the staining of tight junctions between the OHCs and supporting cells as well as between the IHCs and supporting cells as reported previously (Kitajiri et al., 2004; Nakano et al., 2009, Ramzan et al., 2021). The organ of Corti schematics showing CLDN9 expression reflects the authors' immunostaining data but is unusual considering that CLDN9 localizes to the tight junctions of the reticular lamina as was shown by immuno-EM in this study and described in previous publications (Kitajiri et al., 2004; Nakano et al., 2009, Ramzan et al., 2021). However, the authors did not provide an explanation for these discrepancies in the Discussion of the manuscript.

Also, more detailed investigations would in some instances clarify the data. For example, it is not clear if the downregulation of Cldn9 affects the other genes known to participate in cell fate determination, and why downregulation of Cldn9 expression resulted in production of extranumerary inner hair cells only and not the other cell types, like OHCs, for example.

Reviewer #2 (Public review):

The author and his team explored a novel neoadjuvant strategy of radiotherapy followed by CDK4/6 inhibitor and exemestane for HR+/HER2- breast cancer. This strategy interestingly reached an ORR of 91.7% and RCB 0-I of 16.7%, with satisfying tolerance.

There are several questions for your further consideration.

Firstly, as this is a single-arm preliminary study, we are curious about the order of radiotherapy and the endocrine therapy. Besides, considering the radiotherapy, we also concern about the recovery of the wound after the surgery and whether related data were collected.

Secondly, in the methodology, please describe the sample size estimation of this study and follow up details.

Thirdly, in Table 1, the item HER2 expression, it's better to categorise HER2 into 0, 1+, 2+ and FISH-.

Reviewer #1 (Public review):

Summary:

The authors set out to evaluate the regulation of interferon (IFN) gene expression in fish, using mainly zebrafish as a model system. Similar to more widely characterized mammalian systems, fish IFN is induced during viral infection through the action of the transcription factor IRF3 which is activated by phosphorylation by the kinase TBK1. It has been previously shown in many systems that TBK1 is subjected to both positive and negative regulation to control IFN production. In this work, the authors find that the cell cycle kinase CDK2 functions as a TBK1 inhibitor by decreasing its abundance through recruitment of the ubiquitinylation ligase, Dtx4, which has been similarly implicated in the regulation of mammalian TBK1. Experimental data are presented showing that CDK2 interacts with both TBK1 and Dtx4, leading to TBK1 K48 ubiqutinylation on K567 and its subsequent degradation by the proteasome.

Strengths:

The strengths of this manuscript are its novel demonstration of the involvement of CDK2 in a process in fish that is controlled by different factors in other vertebrates and its clear and supportive experimental data.

Weaknesses:

The weaknesses of the study include the following. 1) It remains unclear how CDK is regulated during viral infection and how it specifically recruits E3 ligase to TBK1. 2) The implications and mechanisms for a relationship between the cell cycle and IFN production will be a fascinating topic for future studies.