Reviewer #2 (Public review):

This study addresses the question of how UBCs transform synaptic input patterns into spiking output patterns and how different glutamate receptors contribute to their transformations. The first figure utilizes recorded patterns of mossy fiber firing during eye movements in the flocculus of rhesus monkeys obtained from another laboratory. In the first figure, these patterns are used to stimulate mossy fibers in the mouse cerebellum during extracellular recordings of UBCs in acute mouse brain slices. The remaining experiments stimulate mossy fiber inputs at different rates or burst durations, which is described as 'mossy-fiber like', although they are quite simpler than those recorded in vivo. As expected from previous work, AMPA mediates the fast responses, and mGluR1 and mGluR2/3 mediate the majority of longer-duration and delayed responses. The manuscript is well organized and the discussion contextualizes the results effectively.

Comments on revisions:

The authors have adequately addressed my concerns.

Reviewer #2 (Public review):

Summary:

Conceptually, this study is interesting and is the first attempt to account for the potentially interactive effects of seasonality and blood source on mosquito fitness, which the authors frame as a possible explanation for previously observed host-switching of Culex quinquefasciatus from birds to mammals in the fall. The authors hypothesize that if changes in fitness by blood source change between seasons, higher fitness on birds in the summer and on mammals in the autumn could drive observed host switching. To test this, the authors fed individuals from a colony of Cx. quinquefasciatus on chickens (bird model) and mice (mammal model) and subjected each of these two groups to two different environmental conditions reflecting the high and low temperatures and photoperiod experienced in summer and autumn in Córdoba, Argentina (aka seasonality). They measured fecundity, fertility, and hatchability over two gonotrophic cycles. The authors then used generalized linear mixed models to evaluate the impact of host species, seasonality, and gonotrophic cycle on fecundity, fertility, and hatchability. The authors were trying to test their hypothesis by determining whether there was an interactive effect of season and host species on mosquito fitness. This is an interesting hypothesis; if it had been supported, it would provide support for a new mechanism driving host switching. While the authors did report an interactive impact of seasonality and host species, the directionality of the effect was the opposite from that hypothesized. The authors have done a very good job of addressing many of the reviewer's concerns, especially by adding two additional replicates. Several minor concerns remain, especially regarding unclear statements in the discussion.

Strengths:

(1) Using a combination of laboratory feedings and incubators to simulate seasonal environmental conditions is a good, controlled way to assess the potentially interactive impact of host species and seasonality on the fitness of Culex quinquefasciatus in the lab.<br /> (2) The driving hypothesis is an interesting and creative way to think about a potential driver of host switching observed in the field.

Weaknesses:

(1) The methods would be improved by some additional details. For example, clarifying the number of generations for which mosquitoes were maintained in colony (which was changed from 20 to several) and whether replicates were conducted at different time points.<br /> (2) The statistical analysis requires some additional explanation. For example, you suggest that the power analysis was conducted a priori, but this was not mentioned in your first two drafts, so I wonder if it was actually conducted after the first replicate. It would be helpful to include further detail, such as how the parameters were estimated. Also, it would be helpful to clarify why replicate was included as a random effect for fecundity and fertility but as a fixed effect for hatchability. This might explain why there were no significant differences for hatchability given that you were estimating for more parameters.<br /> (3) A number of statements in the discussion are not clear. For example, what do you mean by a mixed perspective in the first paragraph? Also, why is the expectation mentioned in the second paragraph different from the hypothesis you described in your introduction?<br /> (4) According to eLife policy, data must be made freely available (not just upon request).

Reviewer #2 (Public review):

The authors developed the TaG-EM system to address challenges in multiplexing Drosophila samples for behavioral and transcriptomic studies. This system integrates DNA barcodes upstream of the polyadenylation site in a UAS-GFP construct, enabling pooled behavioral measurements and cell type tracking in scRNA-seq experiments. The revised manuscript expands on the utility of TaG-EM by demonstrating its application to complex assays, such as larval gut motility, and provides a refined analysis of its limitations and cost-effectiveness.

Strengths

(1) Novelty and Scope: The study demonstrates the potential for TaG-EM to streamline multiplexing in both behavioral and transcriptomic contexts. The additional application to labor-intensive larval gut motility assays highlights its scalability and practical utility.

(2) Data Quality and Clarity: Figures and supplemental data are mostly clear and significantly enhanced in the revised manuscript. The addition of Supplemental Figures 18-21 addresses initial concerns about scRNA-seq data and driver characterization.

(3) Cost-Effectiveness Analysis: New analyses of labor and cost savings (e.g., Supplemental Figure 8) provide a practical perspective.

(4) Improvements in Barcode Detection and Analysis: Enhanced enrichment protocols (Supplemental Figures 18-19) demonstrate progress in addressing limitations of barcode detection and increase the detection rate of labeled cells.

Weaknesses

(1) Barcode Detection Efficiency: While improvements are noted, the low barcode detection rate (~37% in optimized conditions) limits the method's scalability in some applications, such as single-cell sequencing experiments with complex cell populations.

(2) Sparse Labeling: Sparse labeling of cell populations, particularly in scRNA-seq assays, remains a concern. Variability in driver strength and regional expression introduces inconsistencies in labeling density.

(3) Behavioral Applications: The utility of TaG-EM in quantifying more complex behaviors remains underexplored, limiting the generalizability of the method beyond simpler assays like phototaxis and oviposition.

(4) Driver Line Characterization: While improvements in driver line characterization were made, variability in expression patterns and sparse labeling emphasize the need for further refinement of constructs and systematic backcrossing to standardize the genetic background.

Reviewer #2 (Public review):

Summary:

The authors analyzed Xenopus oocytes at different stages of meiosis using quantitative phosphoproteomics. Their advanced methods and analyses revealed changes in protein abundances and phosphorylation states to an unprecedented depth and quantitative detail. In the manuscript they provide an excellent interpretation of these findings putting them in the context of past literature in Xenopus as well as in other model systems.

Strengths:

High quality data, careful and detailed analysis, outstanding interpretation in the context of the large body of the literature.

Weaknesses:

Merely a resource, none of the findings are tested in functional experiments.

I am very impressed by the quality of the data and the careful and detailed interpretation of the findings. In this form the manuscript will be an excellent resource to the cell division community in general, and it presents a very large number of hypotheses that can be tested in future experiments.

Xenopus has been and still is a popular and powerful model system that led to critical discoveries around countless cellular processes, including the spindle, nuclear envelope, translational regulation, just to name a few. This also includes a huge body of literature on the cell cycle describing its phosphoregulation. It is indeed somewhat frustrating to see that these earlier studies using phospho-mutants and phospho-antibodies were just scratching the surface. The phosphoproteomics analysis presented here reveals much more extensive and much more dynamic changes in phosphorylation states. Thereby, in my opinion, this manuscript opens a completely new chapter in this line of research, setting the stage for more systematic future studies.

Reviewer #2 (Public review):

The work by Gupta et al. addresses the role of tissue compressibility as a driver of cell competition. The authors use a planar epithelial monolayer system to study cell competition between wild type and transformed epithelial cells expressing HRasV12. They combine imaging and traction force measurements from which the authors propose that wild type cells generate compressive forces on transformed epithelial cells. The authors further present a novel setup to directly measure the compressibility of adherent epithelial tissues. These measurements suggest a higher compressibility of transformed epithelial cells, which is causally linked to a reduction in cell-cell adhesion in transformed cells. The authors support their conclusions by theoretical modelling using a self-Propelled Voronoi model that supports differences in tissue compressibility can lead to compression of the softer tissue type.

The experimental framework to measure tissue compressibility of adherent epithelial monolayers establishes a novel tool, however additional controls of this measurement appear required. Moreover, the experimental support of this study is mostly based on single representative images and would greatly benefit from additional data and their quantitative analysis to support the authors' conclusions. Specific comments are also listed in the following:

Major points:

It is not evident in Fig2A that traction forces increase along the interface between wild type and transformed populations and stresses in Fig2C also seem to be similar at the interface and surrounding cell layer. Only representative examples are provided and a quantification of sigma_m needs to be provided.

In Figure 1-3 only panel 2G and 2H provide a quantitative analysis, but it is not clear how many regions of interest and clusters of transform cells were quantified.

Several statements appear to be not sufficiently justified and supported by data.<br /> For example the statement on pg 3. line 38 seems to lack supportive data 'This comparison revealed that the thickness of HRasV12-expressing cells was reduced by more than 1.7-fold when they were surrounded by wild type cells. These observations pointed towards a selective, competition-dependent compaction of HRasV12-expressing transformed cells but not control cells, in the intestinal villi of mice.'<br /> Similarly, the statement about a cell area change of 2.7 fold (pg 3 line 47) lacks support by measurements.

What is the rationale for setting 𝐾p = 1 in the model assumptions if clear differences in junctional membranes of transformed versus wild type cells occur, including dynamic ruffling? This assumption does not seem to be in line with biological observations.

The novel approach to measure tissue compressibility is based on pH dependent hydrogels. As the pH responsive hydrogel pillar is placed into a culture medium with different conditions, an important control would be if the insertion of this hydrogel itself would change the pH or conditions of the culture assays and whether this alters tissue compressibility or cell adhesion. The authors could for example insert a hydrogel pillar of a smaller diameter that would not lead to compression or culture cells in a larger ring to assess the influence of the pillar itself.

The authors focus on the study of cell compaction of the transformed cells, but how does this ultimately lead to a competitive benefit of wild type cells? Is a higher rate of extrusion observed and associated with the compaction of transformed cells or is their cell death rate increased? While transformed cells seem to maintain a proliferative advantage it is not clear which consequences of tissue compression ultimately drive cell competition between wild type and transformed cells.

The argumentation that softer tissues would be more easily compressed is plausible. However, which mechanism do the authors suggest is generating the actual compressive stress to drive the compaction of transformed cells? They exclude a proliferative advantage of wild type cells, which other mechanisms will generate the compressive forces by wild type cells?

Reviewer #2 (Public review):

The work by Gupta et al. addresses the role of tissue compressibility as a driver of cell competition. The authors use a planar epithelial monolayer system to study cell competition between wild type and transformed epithelial cells expressing HRasV12. They combine imaging and traction force measurements from which the authors propose that wild type cells generate compressive forces on transformed epithelial cells. The authors further present a novel setup to directly measure the compressibility of adherent epithelial tissues. These measurements suggest a higher compressibility of transformed epithelial cells, which is causally linked to a reduction in cell-cell adhesion in transformed cells. The authors support their conclusions by theoretical modelling using a self-Propelled Voronoi model that supports differences in tissue compressibility can lead to compression of the softer tissue type.

The experimental framework to measure tissue compressibility of adherent epithelial monolayers establishes a novel tool, however additional controls of this measurement appear required. Moreover, the experimental support of this study is mostly based on single representative images and would greatly benefit from additional data and their quantitative analysis to support the authors' conclusions. Specific comments are also listed in the following:

Major points:

It is not evident in Fig2A that traction forces increase along the interface between wild type and transformed populations and stresses in Fig2C also seem to be similar at the interface and surrounding cell layer. Only representative examples are provided and a quantification of sigma_m needs to be provided.

In Figure 1-3 only panel 2G and 2H provide a quantitative analysis, but it is not clear how many regions of interest and clusters of transform cells were quantified.

Several statements appear to be not sufficiently justified and supported by data.<br /> For example the statement on pg 3. line 38 seems to lack supportive data 'This comparison revealed that the thickness of HRasV12-expressing cells was reduced by more than 1.7-fold when they were surrounded by wild type cells. These observations pointed towards a selective, competition-dependent compaction of HRasV12-expressing transformed cells but not control cells, in the intestinal villi of mice.'<br /> Similarly, the statement about a cell area change of 2.7 fold (pg 3 line 47) lacks support by measurements.

What is the rationale for setting 𝐾p = 1 in the model assumptions if clear differences in junctional membranes of transformed versus wild type cells occur, including dynamic ruffling? This assumption does not seem to be in line with biological observations.

The novel approach to measure tissue compressibility is based on pH dependent hydrogels. As the pH responsive hydrogel pillar is placed into a culture medium with different conditions, an important control would be if the insertion of this hydrogel itself would change the pH or conditions of the culture assays and whether this alters tissue compressibility or cell adhesion. The authors could for example insert a hydrogel pillar of a smaller diameter that would not lead to compression or culture cells in a larger ring to assess the influence of the pillar itself.

The authors focus on the study of cell compaction of the transformed cells, but how does this ultimately lead to a competitive benefit of wild type cells? Is a higher rate of extrusion observed and associated with the compaction of transformed cells or is their cell death rate increased? While transformed cells seem to maintain a proliferative advantage it is not clear which consequences of tissue compression ultimately drive cell competition between wild type and transformed cells.

The argumentation that softer tissues would be more easily compressed is plausible. However, which mechanism do the authors suggest is generating the actual compressive stress to drive the compaction of transformed cells? They exclude a proliferative advantage of wild type cells, which other mechanisms will generate the compressive forces by wild type cells?

Reviewer #2 (Public review):

uORFs, short open reading frames located in the 5' UTR, are pervasive in genomes. However, their roles in maintaining protein abundance are not clear. In this study, the authors propose that uORFs act as "molecular dam", limiting the fluctuation of the translation of downstream coding sequences. First, they performed in silico simulations using an improved ICIER model, and demonstrated that uORF translation reduces CDS translational variability, with buffering capacity increasing in proportion to uORF efficiency, length, and number. Next, they analzed the translatome between two related Drosophila species, revealing that genes with uORFs exhibit smaller fluctuations in translation between the two species and across different developmental stages within the same specify. Moreover, they identified that bicoid, a critical gene for Drosophila development, contains a uORF with substantial changes in translation efficiency. Deleting this uORF in Drosophila melanogaster significantly affected its gene expression, hatching rates, and survival under stress condition. Lastly, by leveraging public Ribo-seq data, the authors showed that the buffering effect of uORFs is also evident between primates and within human populations. Collectively, the study advances our understanding of how uORFs regulate the translation of downstream coding sequences at the genome-wide scale, as well as during development and evolution.

The conclusions of this paper are mostly well supported by data, but some definitions and data analysis need to be clarified and extended.

(1) There are two definitions of translation efficiency (TE) in the manuscript: one refers to the number of 80S ribosomes that complete translation at the stop codon of a CDS within a given time interval, while the other is calculated based on Ribo-seq and mRNA-seq data (as described on Page 7, line 209). To avoid potential misunderstandings, please use distinct terms to differentiate these two definitions.

(2) Page 7, line 209: "The translational efficiencies (TEs) of the conserved uORFs were highly correlated between the two species across all developmental stages and tissues examined, with Spearman correlation coefficients ranging from 0.478 to 0.573 (Fig. 2A)." However, the authors did not analyze the correlation of translation efficiency of conserved CDSs between the two species, and compare this correlation to the correlation between the TEs of CDSs. These analyzes will further support the authors conclusion regarding the role of conserved uORFs in translation regulation.

(3) Page 8, line 217: "Among genes with multiple uORFs, one uORF generally emerged as dominant, displaying a higher TE than the others within the same gene (Fig. 2C)." The basis for determining dominance among uORFs is not explained and this lack of clarification undermines the interpretation of these findings.

(4) According to the simulation, the translation of uORFs should exhibit greater variability than that of CDSs. However, the authors observed significantly fewer uORFs with significant TE changes compared to CDSs. This discrepancy may be due to lower sequencing depth resulting in fewer reads mapped to uORFs. Therefore, the authors may compare this variability specifically among highly expressed genes.

(5) If possible, the author may need to use antibodies against bicoid to test the effect of ATG deletion on bicoid expression, particularly under different developmental stages or growth conditions. According to the authors' conclusions, the deletion mutant should exhibit greater variability in bicoid protein abundance. This experiment could provide strong support for the proposed mechanisms.

Reviewer #2 (Public review):

Summary:

Suzuki and colleagues aim to develop an in vitro organoid system to recapitulate the developmental process of the olfactory epithelium. The authors have succeeded in using a combination of niche factors to induce organoid development, which gives rise to multiple cell types including those with characteristics of mature olfactory sensory neurons. By comparing different cultural media in inducing lineage specification in the organoids, the authors show that the niche factors play an important role in the neuronal lineage whereas serum promotes the development of the respiratory epithelium. The authors further utilized single-cell RNASeq and trajectory analysis to demonstrate that the organoids recapitulate the developmental process of the olfactory epithelium and that some of the factory sensory neurons express only one receptor type per cell. Using these analyses, the authors proposed that a specific set of guidance modules are associated with individual receptor types to enable the formation of the factory map.

Strengths:

The strength of the paper is that the authors have demonstrated that olfactory epithelium organoids can develop from dissociated cells from embryonic or tissue. This provides a valuable tool for studying the development of processes of the factory epithelium in vitro. Defining various factors in the media that influence the development trajectories of various cell types also provides valuable information to guide further development of the method. Single-cell RNA-Seq experiments provide information about the developmental processes of the olfactory system.

Weaknesses:

The manuscript is also marked by a number of weaknesses. The premise of the studies is not well argued. The authors set out to use organoid culture to study the developmental process in order to unravel the mechanisms of single receptor choice, and its role in setting up the factory map. However, the paper has mostly focused on characterizing the organization rather than providing insights into the problem. The statement that the organoids can develop from single cells is misleading, because it's mostly likely that organoids develop after the dissociated cells form aggregates before developing into organoids. It is not known whether coarsely separated tissue chunks can develop into organoids with the same characteristics. Re-aggregation of the cells to form organoids is in and of itself is interesting. Unfortunately, the heterogeneity of the cells and how they contribute to the development of overnight is not explored. There is also a missed opportunity to compare single-cell RNASeq data from this study with existing ones. The in vitro system is likely to be different from embryonic development. It is critical to compare and determine how much the organoid is recapitulating the development of the OSNs in vivo. There are a number of comprehensive datasets from the OE in addition to that presented in the Fletcher paper. Finally, the quality of the functional assay (calcium imaging) of factory sensory neurons is poor. Experiments are of high quality are needed to verify the results.

Major points:

(1) Adding FBS in organoid culture medium has been shown to negatively affect the organoid formation and growth. Previous OE organoids culture method did not use FBS. Also, day 10 is an odd choice to compare the two conditions after showing day 20 of NF+ culture shows a better differentiation state. It is not known whether and how the differentiation may be different on day 20. Moreover, comparing Figure 2R to 2S, FBS treatment alone appears to have not only more Foxj1+ cells but also more Tuj1+ cells than NFs/FBS. This is inconsistent with the model. The authors should provide statistics for Tuj1+ cells as well.

(2) As opposed to the statement in the manuscript, Plxnb2 had been shown to be expressed by the OSNs (Mclntyre et al. 2010; JNR), specifically in immature OSNs. It would be important to mention that Plxnb2 is expressed in OMP+ OSNs in the OE organoid system and its potential reasons to better guide the readers of the system mimicking the in vivo OSNs. Similarly, OSN expression of Cdh2 has been shown by Akins and colleagues. As Plxnb2 showed an expression pattern (immunofluorescence) with an anterior-posterior axis while Cdh2 expression level was not, it would be informative to show the odorant receptor types regarding the expression pattern of Plxnb2 (versus that of Cdh2) using single cell RNAseq data4.

(3) There is no real layering of the organoids, although some cells show biases toward one side or the other in some regions of the organoid. The authors should not make a sweeping claim that the organoids establish layered structures.

(4) Figure 2P, it is clear whether OMP is present in the cell bodies. The signal is not very convincing. Even the DAPI signal does not seem to be on a comparable scale compared to Figures 2N and 2O.

(5) Annotation of the cell types in different single-cell RNA-Seq analysis. The iOSN is only marked in Figure 3A. In the marker expression panel, it appears that those marked as mOSN have high GAP43, which are an iOSN marker. These discrepancies are not detailed nor discussed.

(6) The authors should merge the single-cell datasets from day 10 organoids cultured in NF-medium and FBS-medium to compare their differences.

(7) The quality of the calcium imaging experiment is poor. Labeling and experimental details are not provided. The concentration of IVA, the manner of its delivery, and delivery duration are not provided. How many ROIs have been imaged, and what percentage of them responded to IVA? Do they respond to more than one odor? Do they respond to repeated delivery? There is no control for solution osmolarity. Cell body response was not recorded. Given that only a small number of cells express a receptor, it seems extraordinary that these axons respond to IVA receptors. The authors should also determine whether IVA receptor genes are found in their dataset.

Reviewer #2 (Public review):

Summary:

Van der Linden et al. describe the addition of the T203Y mutation to their previously described fluorescence lifetime calcium sensor Tq-Ca-FLITS to shift the fluorescence to green emission. This mutation was previously described to similarly red-shift the emission of green and cyan FPs. Tq-Ca-FLITS_T203Y behaves as a green calcium sensor with opposite polarity compared with the original (lifetime goes down upon calcium binding instead of up). They then screen a library of variants at two linker positions and identify a variant with slightly improved lifetime contrast (Tq-Ca-FLITS_T203Y_V27A_N271D, named G-Ca-FLITS). The authors then characterize the performance of G-Ca-FLITS relative to Tq-Ca-FLITS in purified protein samples, in cultured cells, and in the brains of fruit flies.

Strengths:

This work is interesting as it extends their prior work generating a calcium indicator scaffold for fluorescent protein-based lifetime sensors with large contrast at a single wavelength, which is already being adopted by the community for production of other FLIM biosensors. This work effectively extends that from cyan to green fluorescence. While the cyan and green sensors are not spectrally distinct enough (~20-30nm shift) to easily multiplex together, it at least shifts the spectra to wavelengths that are more commonly available on commercial microscopes.

The observations of organellar calcium concentrations were interesting and could potentially lead to new biological insight if followed up.

Weaknesses:

The new G-Ca-FLITS sensor doesn't appear to be significantly improved in performance over the original Tq-Ca-FLITS, no specific benefits are demonstrated.

Although it was admirable to attempt in vivo demonstration in Drosophila with these sensors, depolarizing the whole brain with high potassium is not a terribly interesting or physiological stimulus and doesn't really highlight any advantages of their sensors; G-Ca-FLITS appears to be quite dim in the flies.

Reviewer #2 (Public review):

Summary:

With this report, I suggest what are in my opinion crucial additions to the otherwise very interesting and credible research manuscript "Cluster size determines morphology of transcription factories in human cells".

Strengths:

The manuscript in itself is technically sound, the chosen simulation methods are completely appropriate the figures are well-prepared, the text is mostly well-written spare a few typos. The conclusions are valid and would represent a valuable conceptual contribution to the field of clustering, 3D genome organization and gene regulation related to transcription factories, which continues to be an area of most active investigation.

Weaknesses:

However, I find that the connection to concrete biological data is weak. This holds especially given that the data that are needed to critically assess the applicability of the derived cross-over with factory size is, in fact, available for analysis, and the suggested experiments in the Discussion section are actually done and their results can be exploited. In my judgement, unless these additional analysis are added to a level that crucial predictions on TF demixing and transcriptional bursting upon TU clustering can be tested, the paper is more fitted for a theoretical biophysics venue than for a biology journal.

Major points

(1) My first point concerns terminology. The Merriam-Webster dictionary describes morphology as the study of structure and form. In my understanding, none of the analyses carried out in this study actually address the form or spatial structuring of transcription factories. I see no aspects of shape, only size. Unless the authors want to assess actual shapes of clusters, I would recommend to instead talk about only their size/extent. The title is, by the same argument, in my opinion misleading as to the content of this study.

(2) Another major conceptual point is the choice of how a single TF:pol particle in the model relates to actual macromolecules that undergo clustering in the cell. What about the fact that even single TF factories still contain numerous canonical transcription factors, many of which are also known to undergo phase separation? Mediator, CDK9, Pol II just to name a few. This alone already represents phase separation under the involvement of different species, which must undergo mixing. This is conceptually blurred with the concept of gene-specific transcription factors that are recruited into clusters/condensates due to sequence-specific or chromatin-epigenetic-specific affinities. Also, the fact that even in a canonical gene with a "small" transcription factory there are numerous clustering factors takes even the smallest factories into a regime of several tens of clustering macromolecules. It is unclear to me how this reality of clustering and factory formation in the biological cell relates to the cross-over that occurs at approximately n=10 particles in the simulations presented in this paper.

(3) The paper falls critically short in referencing and exploiting for analysis existing literature and published data both on 3D genome organization as well as the process of cluster formation in relation to genomic elements. In terms of relevant literature, most of the relevant body of work from the following areas has not been included:

(i) mechanisms of how the clustering of Pol II, canonical TFs, and specific TFs is aided by sequence elements and specific chromatin states

(ii) mechanisms of TF selectivity for specific condensates and target genomic elements

(iii) most crucially, existing highly relevant datasets that connect 3D multi-point contacts with transcription factor identity and transcriptional activity, which would allow the authors to directly test their hypotheses by analysis of existing data

Here, especially the data under point iii are essential. The SPRITE method (cited but not further exploited by the authors), even in its initial form of publication, would have offered a data set to critically test the mixing vs. demixing hypothesis put forward by the authors. Specifically, the SPRITE method offers ordered data on k-mers of associated genomic elements. These can be mapped against the main TFs that associate with these genomic elements, thereby giving an account of the mixed / demixed state of these k-mer associations. Even a simple analysis sorting these associations by the number of associated genomic elements might reveal a demixing transition with increasing association size k. However, a newer version of the SPRITE method already exists, which combines the k-mer association of genomic elements with the whole transcriptome assessment of RNAs associated with a particular DNA k-mer association. This can even directly test the hypotheses the authors put forward regarding cluster size, transcriptional activation, correlation between different transcription units' activation etc.

To continue, the Genome Architecture Mapping (GAM) method from Ana Pombo's group has also yielded data sets that connect the long-range contacts between gene-regulatory elements to the TF motifs involved in these motifs, and even provides ready-made analyses that assess how mixed or demixed the TF composition at different interaction hubs is. I do not see why this work and data set is not even acknowledged? I also strongly suggest to analyze, or if they are already sufficiently analyzed, discuss these data in the light of 3D interaction hub size (number of interacting elements) and TF motif composition of the involved genomic elements.

Further, a preprint from the Alistair Boettiger and Kevin Wang labs from May 2024 also provides direct, single-cell imaging data of all super-enhancers, combined with transcription detection, assessing even directly the role of number of super-enhancers in spatial proximity as a determinant of transcriptional state. This data set and findings should be discussed, not in vague terms but in detailed terms of what parts of the authors' predictions match or do not match these data.

For these data sets, an analysis in terms of the authors' key predictions must be carried out (unless the underlying papers already provide such final analysis results). In answering this comment, what matters to me is not that the authors follow my suggestions to the letter. Rather, I would want to see that the wealth of available biological data and knowledge that connects to their predictions is used to their full potential in terms of rejecting, confirming, refining, or putting into real biological context the model predictions made in this study.

References for point (iii):

RNA promotes the formation of spatial compartments in the nucleus<br /> https://www.cell.com/cell/fulltext/S0092-8674(21)01230-7?dgcid=raven_jbs_etoc_email

Complex multi-enhancer contacts captured by genome architecture mapping<br /> https://www.nature.com/articles/nature21411

Cell-type specialization is encoded by specific chromatin topologies<br /> https://www.nature.com/articles/s41586-021-04081-2

Super-enhancer interactomes from single cells link clustering and transcription<br /> https://www.biorxiv.org/content/10.1101/2024.05.08.593251v1.full

For point (i) and point (ii), the authors should go through the relevant literature on Pol II and TF clustering, how this connects to genomic features that support the cluster formation, and also the recent literature on TF specificity. On the last point, TF specificity, especially the groups of Ben Sabari and Mustafa Mir have presented astonishing results, that seem highly relevant to the Discussion of this manuscript.

(4) Another conceptual point that is a critical omission is the clarification that there are, in fact, known large vs. small transcription factories, or transcriptional clusters, which are specific to stem cells and "stressed cells". This distinction was initially established by Ibrahim Cisse's lab (Science 2018) in mouse Embryonic Stem Cells, and also is seen in two other cases in differentiated cells in response to serum stimulus and in early embryonic development:

Mediator and RNA polymerase II clusters associate in transcription-dependent condensates<br /> https://www.science.org/doi/10.1126/science.aar4199

Nuclear actin regulates inducible transcription by enhancing RNA polymerase II clustering<br /> https://www.science.org/doi/10.1126/sciadv.aay6515

RNA polymerase II clusters form in line with surface condensation on regulatory chromatin<br /> https://www.embopress.org/doi/full/10.15252/msb.202110272

If "morphology" should indeed be discussed, the last paper is a good starting point, especially in combination with this additional paper:

Chromatin expansion microscopy reveals nanoscale organization of transcription and chromatin<br /> https://www.science.org/doi/10.1126/science.ade5308

(5) The statement "scripts are available upon request" is insufficient by current FAIR standards and seems to be non-compliant with eLife requirements. At a minimum, all, and I mean all, scripts that are needed to produce the simulation outcomes and figures in the paper, must be deposited as a publicly accessible Supplement with the article. Better would be if they would be structured and sufficiently documented and then deposited in external repositories that are appropriate for the sharing of such program code and models.

Reviewer #2 (Public review):

Summary:

ACVR2A is one of a handful of genes for which significant correlations between associated SNPs and the incidences of preeclampsia have been found in multiple populations. It is one of the TGFB family receptors, and multiple ligands of ACVR2A, as well as its coreceptors and related inhibitors, have been implicated in placental development, trophoblast invasion, and embryo implantation. This useful study builds on this knowledge by showing that ACVR2A knockout in trophoblast-related cell lines reduces trophoblast invasion, which could tie together many of these observations. Support for this finding is incomplete, as reduced proliferation may be influencing the invasion results. The implication of cross-talk between the WNT and ACRV2A/SMAD2 pathways is an important contribution to the understanding of the regulation of trophoblast function.

Strengths:

(1) ACVR2A is one of very few genes implicated in preeclampsia in multiple human populations, yet its role in pathogenesis is not very well studied and this study begins to address that hole in our knowledge.

(2) ACVR2A is also indirectly implicated in trophoblast invasion and trophoblast development via its connections to many ligands, inhibitors, and coreceptors, suggesting its potential importance.

(3) The authors have used multiple cell lines to verify their most important observations.

Weaknesses:

(1) There are a number of claims made in the introduction without attribution. For example, there are no citations for the claims that family history is a significant risk factor for PE, that inadequate trophoblast invasion of spiral arteries is a key factor, and that immune responses, and renin-angiotensin activity are involved.

(2) The introduction states "As a receptor for activin A, ACVR2A..." It's important to acknowledge that ACVR2A is also the receptor for other TGFB family members, with varying affinities and coreceptors. Several TGFB family members are known to regulate trophoblast differentiation and invasion. For example, BMP2 likely stimulates trophoblast invasion at least in part via ACVR2A (PMID 29846546).

(3) An alternative hypothesis for the potential role of ACVR2A in preeclampsia is its functions in the endometrium. In the mouse ACVR2A knockout in the uterus (and other progesterone receptor-expressing cells) leads to embryo implantation failure.

(4) In the description of the patient population for placental sample collections, preeclampsia is defined only by hypertension, and this is described as being in accordance with ACOG guidelines. ACOG requires a finding of hypertension in combination with either proteinuria or one of the following: thrombocytopenia, elevated creatinine, elevated liver enzymes, pulmonary, edema, and new onset unresponsive headache.

(5) I believe that Figures 1a and 1b are data from a previously published RNAseq dataset, though it is not entirely clear in the text. The methods section does not include a description of the analysis of these data undertaken here. It would be helpful to include at least a brief description of the study these data are taken from - how many samples, how were the PE/control groups defined, gestational age range, where is it from, etc. For the heatmap presented in B, what is the significance of the other genes/ why are they being shown? If the purpose of these two panels is to show differential expression specifically of ACVR2A in this dataset, that could be shown more directly.

(6) More information is needed in the methods section to understand how the immunohistochemistry was quantified. "Quantitation was performed" is all that is provided. Was staining quantified across the whole image or only in anchoring villous areas? How were HRP & hematoxylin signals distinguished in ImageJ? How was the overall level of HRP/DAB development kept constant between the NC and PE groups?

(7) In Figure 1E it is not immediately obvious to many readers where the EVT are. It is probably worth circling or putting an arrow to the little region of ACVR2A+ EVT that is shown in the higher magnification image in Figure 1E. These are actually easier to see in the pictures provided in the supplement Figure 1. Of note, the STB is also staining positive. This is worth pointing out in the results text.

(8) It is not possible to judge whether the IF images in 1F actually depict anchoring villi. The DAPI is really faint, and it's high magnification, so there isn't a lot of context. Would it be possible to include a lower magnification image that shows where these cells are located within a placental section? It is also somewhat surprising that this receptor is expressed in the cytoplasm rather than at the cell surface. How do the authors explain this?

(9) The results text makes it sound like the data in Figure 2A are from NCBI & Protein atlas, but the legend says it is qPCR from this lab. The methods do not detail how these various cell lines were grown; only HTR-SVNeo cell culture is described. Similarly, JAR cells are used for several experiments and their culture is not described.

(10) Under RT-qPCR methods, the phrase "cDNA reverse transcription cell RNA was isolated..." does not make any sense.

(11) The paragraph beginning "Consequently, a potential association..." is quite confusing. It mentions analyzing ACVR2A expression in placentas, but then doesn't point to any results of this kind and repeats describing the results in Figure 2a, from various cell lines.

(12) The authors should acknowledge that the effect of the ACVR2A knockout on proliferation makes it difficult to draw any conclusions from the trophoblast invasion assays. That is, there might be fewer migrating or invading cells in the knockout lines because there are fewer cells, not because the cells that are there are less invasive. Since this is a central conclusion of the study, it is a major drawback.

(13) The legend and the methods section do not agree on how many fields were selected for counting in the transwell invasion assays in Figure 3C. The methods section and the graph do not match the number of replicate experiments in Figure 3D (the number of replicate experiments isn't described for 3C).

(14) Discussion says "Transcriptome sequencing analysis revealed low ACVR2A expression in placental samples from PE patients, consistent with GWAS results across diverse populations." The authors should explain this briefly. Why would SNPs in ACVR2A necessarily affect levels of the transcript?

(15) "The expression levels of ACVR2A mRNA were comparable to those of tumor cells such as A549. This discovery suggested a potential pivotal role of ACVR2A in the biological functions of trophoblast cells, especially in the nurturing layer." Alternatively, ACVR2A expression resembles that of tumors because the cell lines used here are tumor cells (JAR) or immortalized cells (HTR8). These lines are widely used to study trophoblast properties, but the discussion should at least acknowledge the possibility that the behavior of these cells does not always resemble normal trophoblasts.

(16) The authors should discuss some of what is known about the relationship between the TCF7/c-JUN pathway and the major signaling pathway activated by ACVR2A, Smad 2/3/4. The Wnt and TGFB family cross-talk is quite complex and it has been studied in other systems.

Reviewer #2 (Public review):

Summary:

The authors conducted a comparative analysis of four networks, varying in the presence of excitatory assemblies and the architecture of inhibitory cell assembly connectivity. They found that co-tuned E-I assemblies provide network stability and a continuous representation of input patterns (on locally constrained manifolds), contrasting with networks with global inhibition that result in attractor networks.

Strengths:

The findings presented in this paper are very interesting and cutting-edge. The manuscript effectively conveys the message and presents a creative way to represent high-dimensional inputs and network responses. Particularly, the result regarding the projection of input patterns onto local manifolds and continuous representation of input/memory is very Intriguing and novel. Both computational and experimental neuroscientists would find value in reading the paper.

Weaknesses:

Intuitively, classification (decodability) in discrete attractor networks is much better than in networks with continuous representations. This could also be shown in Figure 5B, along with the performance of the random and tuned E-I networks. The latter networks have the advantage of providing network stability compared to the Scaled I network, but at the cost of reduced network salience and, therefore, reduced input decodability. Thus, tuned E-I networks cannot always perform better than any other network.

Reviewer #2 (Public review):

Summary:

This paper develops an under-flow migration tracker to evaluate all the steps of the extravasation cascade of immune cells across the BBB. The algorithm is useful and has important applications.

Strengths:

The algorithm is almost as accurate as manual tracking and importantly saves time for researchers. The authors have discussed how their tool compares to other tracking methods.

Weaknesses:

Applicability can be questioned because the device used is 2D and physiological biology is in 3D. However, the authors have addressed this point in their manuscript.

Reviewer #3 (Public review):

Summary:

Cell lineage tracing necessitates continuous visible tracking or permanent molecular markers that daughter cells inherit from their progenitors. To successfully trace cell lineages, it is essential to generate and detect sufficient new markers during each cell division. Thus, molecular cell lineages have been predominantly studied with stably inherited genetic markers in animal models and somatic DNA mutations in the human brain. DNA methylation is unstable across cell divisions and differentiation, and is hardly called barcodes. The use of "Human Brain Barcodes" in the title and across the whole paper lacks convincing evidence - it is questionable that CpG methylation is always stably inherited by daughter cells.

Strengths:

Analysis of DNA methylation.

Weaknesses:

The unstable nature of CpG methylation would introduce significant problems in inferring the true cell lineage. To establish DNA methylation as a means for lineage tracing, it is necessary to test whether the DNA methylation patterns can faithfully track cell lineages with in vitro differentiated & visibly tracked cell lineages.

The unreliable CpG methylation status also raises the question of what the "Barcodes" refer to in the title and across this study. Barcodes should be stable in principle and not dynamic across cell generations, as defined in the Reference #1. The CRISPR/Cas9 mutable barcodes or the somatic mutations may be considered barcodes, but the reviewer is not convinced that the "dynamic" CpG methylation fits the "barcodes" terminology. This problem is even more concerning in the last section of the results, where CpG status fluctuates in post-mitotic cells.

The manuscript frequently states assumptions in a tone of conclusions and interprets results without rejecting alternative hypotheses. For example, the title "Human Brain Barcodes" should be backed with solid supporting evidence. For another example, the author assumed that the early-formed brain stem would resemble progenitors better and have a higher average methylation level than the forebrain - however, this difference in DNA methylation status could well reflect cell-type-specific gene expression instead of cell lineage progression.

Other points:

(1) The conclusion that excitatory neurons undergo tangential migration is unclear - how far away did the author mean for the tangential direction? Lateral dispersion is known, but it is hard to believe that the excitatory neurons travel across different brain regions. More importantly, how would the author interpret shared or divergent methylation for the same cell type across different brain regions?

(2) The sparsity and resolution of the single-cell DNA methylation data. The methylation status is detected in only a small fraction (~500/31,000 = 1.6%) of fCpGs per cell, with only 48 common sites identified between cell pairs. Given that the human genome contains over 28 million CpG sites, it is important to evaluate whether these fCpGs are truly representative.

(3) While focusing on the X-chromosome may simplify the identification of polymorphic fCpGs, the confidence in determining its methylation status (0 or 1) is questionable when a CpG site is covered by only one read.

Reviewer #2 (Public review):

Summary:

The main aim of this research was to explore whether and how self-associations (as opposed to other-associations) bias early attentional selection, and whether this can explain well-known self-prioritization phenomena, such as the self-advantage in perceptual matching tasks. The authors adopted the Visual Attention Theory (VAT) by estimating VAT parameters using a hierarchical Bayesian model from the field of attention and applied it to investigate the mechanisms underlying self-prioritization. They also discussed the constraints on the self-prioritization effect in attentional selection. The key conclusions reported were: (1) self-association enhances both attentional weights and processing capacity, (2) self-prioritization in attentional selection occurs automatically but diminishes when active social decoding is required, and (3) social and perceptual salience capture attention through distinct mechanisms.

Strengths:

Transferring the Theory of Visual Attention parameters estimated by a hierarchical Bayesian model to investigate self-prioritization in attentional selection was a smart approach. This method provides a valuable tool for accessing the very early stages of self-processing, i.e., the attention selection. The authors conclude that self-associations can bias visual attention by enhancing both attentional weights and processing capacity, and that this process occurs automatically. These findings offer new insights into the self-prioritization from the perspective of early stage of attentional selection.

Weaknesses:

The results are still not convincing enough to definitively support their conclusions. The generalization of the findings needs further examination. Whether this attentional selection mechanism of self-prioritization can be generalized to other stimuli, such as self-name, self-face, or other domains of self-association advantages, remains to be tested. More empirical data are needed.

Reviewer #2 (Public review):

Summary:

Microglia have been implicated in brain development, homeostasis, and diseases. "Microglia replacement" has gained traction in recent years, using primary microglia, bone marrow or blood-derived myeloid cells, or human iPSC-induced microglia. Here, the authors extended their previous work in the area and provided evidence to support: (1) Estrogen-regulated (ER) homeobox B8 (Hoxb8) conditionally immortalized macrophages from bone marrow can serve as stable, genetically manipulated cell lines. These cells are highly comparable to primary bone marrow-derived (BMD) macrophages in vitro, and, when transplanted into a microglia-free brain, engraft the parenchyma and differentiate into microglia-like cells (MLCs). Taking advantage of this model system, the authors created stable, Adar1-mutated ER-Hoxb8 lines using CRISPR-Cas9 to study the intrinsic contribution of macrophages to the Aicardi-Goutières Syndrome (AGS) disease mechanism.

Strengths:

The studies are carefully designed and well-conducted. The imaging data and gene expression analysis are carried out at a high level of technical competence and the studies provide strong evidence that ER-Hoxb8 immortalized macrophages from bone marrow are a reasonable source for "microglia replacement" exercise. The findings are clearly presented, and the main message will be of general interest to the neuroscience and microglia communities.

Reviewer #2 (Public review):

Summary:

This manuscript describes two new sets of data involving budgerigar hearing: 1) auditory-nerve tuning curves (ANTCs), which are considered the 'gold standard' measure of cochlear tuning, and 2) stimulus-frequency otoacoustic emissions (SFOAEs), which are a more indirect measure (requiring some assumptions and transformations to infer cochlear tuning) but which are non-invasive, making them easier to obtain and suitable for use in all species, including humans. By using a tuning ratio (relating ANTC bandwidths and SFOAE delay) derived from another bird species (chicken), the authors show that the tuning estimates from the two methods are in reasonable agreement with each other over the range of hearing tested (280 Hz to 5.65 kHz for the ANTCs), and both show a slow monotonic increase in cochlear tuning quality over that range, as expected. These new results are then compared with (much) older existing behavioral estimates of frequency selectivity in the same species.

Strengths:

This topic is of interest, because there are some indications from the older behavioral literature that budgerigars have a region of best tuning, which the current authors refer to as an 'acoustic fovea', at around 4 kHz, but that beyond 5 kHz the tuning degrades. Earlier work has speculated that the source could be cochlear or higher (e.g., Okanoya and Dooling, 1987). The current study appears to rule out a cochlear source to this phenomenon.

Weaknesses:

The conclusions are rendered questionable by two major problems.

The first problem is that the study does not provide new behavioral data, but instead relies on decades-old estimates that used techniques dating back to the 1970s, which have been found to be flawed in various ways. The behavioral techniques that have been developed more recently in the human psychophysical literature have avoided these well-documented confounds, such as nonlinear suppression effects (e.g., Houtgast, https://doi.org/10.1121/1.1913048; Shannon, https://doi.org/10.1121/1.381007; Moore, https://doi.org/10.1121/1.381752), perceptual confusion between pure-tone maskers and targets (e.g., Neff, https://doi.org/10.1121/1.393678), beats and distortion products produced by interactions between simultaneous maskers and targets (e.g., Patterson, https://doi.org/10.1121/1.380914), unjustified assumptions and empirical difficulties associated with critical band and critical ratio measures (Patterson, https://doi.org/10.1121/1.380914), and 'off-frequency listening' phenomena (O'Loughlin and Moore, https://doi.org/10.1121/1.385691). More recent studies, tailored to mimic to the extent possible the techniques used in ANTCs, have provided reasonably accurate estimates of cochlear tuning, as measured with ANTCs and SFOAEs (Shera et al., 2003, 2010; Sumner et al., 2010). No such measures yet exist in budgerigars, and this study does not provide any. So the study fails to provide valid behavioral data to support the claims made.

The second, and more critical, problem can be observed by considering the frequencies at which the old behavioral data indicate a worsening of tuning. From the summary shown in the present Fig. 2, the conclusion that behavioral frequency selectivity worsens again at higher frequencies is based on four data points, all with probe frequencies between 5 and 6 kHz. Comparing this frequency range with the absolute thresholds shown in Fig. 3 (as well as from older budgerigar data) shows it to be on the steep upper edge of the hearing range. Thus, we are dealing not so much with a fovea as the point where hearing starts to end. The point that anomalous tuning measures are found at the edge of hearing in the budgerigar has been made before: Saunders et al. (1978) state in the last sentence of their paper that "the size of the CB rapidly increases above 4.0 kHz and this may be related to the fact that the behavioral audibility curve, above 4.0 kHz, loses sensitivity at the rate of 55 dB per octave."

Hearing abilities are hard to measure accurately on the upper frequency edge of the hearing range, in humans as well as in other species. The few attempts to measure human frequency selectivity at that upper edge have resulted in quite messy data and unclear conclusions (e.g., Buus et al., 1986, https://doi.org/10.1007/978-1-4613-2247-4_37). Indeed, the only study to my knowledge to have systematically tested human frequency selectivity in the extended high frequency range (> 12 kHz) seems to suggest a substantial broadening, relative to the earlier estimates at lower frequencies, by as much as a factor of 2 in some individuals (Yasin and Plack, 2005; https://doi.org/10.1121/1.2035594) - in other words by a similar amount as suggested by the budgerigar data. The possible divergence of different measures at the extreme end of hearing could be due to any number of factors that are hard to control and calibrate, given the steep rate of threshold change, leading to uncontrolled off-frequency listening potential, the higher sound levels needed to exceed threshold, as well as contributions from middle-ear filtering. As a side note, in the original ANTC data presented in this study, there are actually very few tuning curves at or above 5 kHz, which are the ones critical to the argument being forwarded here. To my eye, all the estimates above 5 kHz in Fig. 3 fall below the trend line, potentially also in line with poorer selectivity going along with poorer sensitivity as hearing disappears beyond 6 kHz.

The basic question posed in the current study title and abstract seems a little convoluted (why would you expect a behavioral measure to reflect cochlear mechanics more accurately than a cochlear-based emissions measure?). A more intuitive (and likely more interesting) way of framing the question would be "What is the neural/mechanical source of a behaviorally observed acoustic fovea?" Unfortunately, this question does not lend itself to being answered in the budgerigar, as that 'fovea' turns out to be just the turning point at the end of the hearing range. There is probably a reason why no other study has referred to this as an acoustic fovea in the budgerigar.

Overall, a safe interpretation of the data is that hearing starts to change (and becomes harder to measure) at the very upper frequency edge, and not just in budgerigars. Thus, it is difficult to draw any clear conclusions from the current work, other than that the relations between ANTC and SFOAEs estimates of tuning are consistent in budgerigar, as they are in most (all?) other species that have been tested so far.

Reviewer #2 (Public review):

Summary:

The authors tested:

(1) Whether mice learn that they are more/less likely to receive an aversive air puff outcome at different corners of a square-shaped open field apparatus, under 75%/25% probabilistic contingencies;

(2) Whether stimulating basal forebrain cholinergic neurons and terminals in the prefrontal cortex affects learning in this context; and

(3) Whether stimulating cholinergic neurons affects prefrontal cortical single neuron calcium signaling about outcome expectations during learning and contingency changes. They found that mice that received cholinergic stimulation approached high and low aversive outcome probability sites at similar velocities, while control mice approached high probability sites slower, suggesting that cholinergic stimulation impaired learning. Cholinergic stimulation reduced cortical neuron calcium activity during trials on the high-probability corner when the outcome was not delivered. The authors provide additional characterization of cellular responses during delivery/omission trials in high/low probability corners, using running speed as a proxy for low versus high expectations. The study will likely be of interest to those who are interested in prediction and error signaling in the cortex; however, the task and analyses do not permit very easy or clear dissociation of prediction versus prediction error signaling and place field versus place field-expectation multiplexing. The study has several strengths but some weaknesses, which are discussed below.

Strengths:

It is clear the authors were very careful and did a great job with their image processing and segmentation procedures. The details in the methods are appreciated, as are the supplemental descriptive statistics on cell counts.

There are careful experimental controls - for example, the authors showed that the effects of cholinergic stimulation with air puff present are greater than without it, thus ruling out effects of stimulation on cellular physiology that were independent of learning or the task.

The addition of a channelrhodopsin stimulation group is helpful to show that the effects are robust and not wavelength/opsin-specific.

The prefrontal cortex cholinergic terminal stimulation experiment is a great addition. It shows that the behavioral effects of cell body stimulation, which was used in the imaging experiments, are similar to cortical terminal stimulation, where the imaging was performed.

Weaknesses:

The analyses were a bit difficult to follow and therefore it is difficult to determine whether the cells are signaling predictions versus prediction errors - a very important distinction.

The task does not fully dissociate place field coding, since learning about the different probabilities necessarily took place at different areas in the apparatus. Some additional analyses could help address this.

Reviewer #2 (Public review):

Summary:

The authors study a panel of sparsely labeled neuronal lines in Drosophila that each form multiple synapses. Critically, each axonal branch can be injured without affecting the others, allowing the authors to differentiate between injuries that affect all axonal branches versus those that do not, creating spared branches. Axonal injuries are known to cause Wnd (mammalian DLK)-dependent retrograde signals to the cell body, culminating in a transcriptional response. This work identifies a fascinating new phenomenon that this injury response is not all-or-none. If even a single branch remains uninjured, the injury signal is not activated in the cell body. The authors rule out that this could be due to changes in the abundance of Wnd (perhaps if incrementally activated at each injured branch) by Wnd, Hiw's known negative regulator. Thus there is both a yet-undiscovered mechanism to regulate Wnd signaling, and more broadly a mechanism by which the neuron can integrate the degree of injury it has sustained. It will now be important to tease apart the mechanism(s) of this fascinating phenomenon. But even absent a clear mechanism, this is a new biology that will inform the interpretation of injury signaling studies across species.

Strengths:

(1) A conceptually beautiful series of experiments that reveal a fascinating new phenomenon is described, with clear implications (as the authors discuss in their Discussion) for injury signaling in mammals.

(2) Suggests a new mode of Wnd regulation, independent of Hiw.

Weaknesses:

(1) The use of a somatic transcriptional reporter for Wnd activity is powerful, however, the reporter indicates whether the transcriptional response was activated, not whether the injury signal was received. It remains possible that Wnd is still activated in the case of a spared branch, but that this activation is either local within the axons (impossible to determine in the absence of a local reporter) or that the retrograde signal was indeed generated but it was somehow insufficient to activate transcription when it entered the cell body. This is more of a mechanistic detail and should not detract from the overall importance of the study

(2) That the protective effect of a spared branch is independent of Hiw, the known negative regulator of Wnd, is fascinating. But this leaves open a key question: what is the signal?

Reviewer #2 (Public review):

In this manuscript, Hallacy et al. used a compressed sensing-based optogenetic screening method to investigate the crucial neurons that regulate pathogenic avoidance behavior in C. elegans. They further substantiate their findings using complementary optogenetic activation and imaging techniques to confirm the roles of the key neurons identified through extensive screening efforts. Notably, they identified AIY and SIA as pivotal neurons in the dynamic process of pathogenic avoidance. Their significant discovery is the delayed or stalled reentry process, which drives avoidance behavior; to my knowledge, this dynamic has not been previously documented. Additionally, the successful integration of quantitative optogenetic tools and compressed sensing algorithms is noteworthy, demonstrating the potential for obtaining highly quantitative data from the C. elegans nervous system. This approach is quite rare in this field, yet it represents a promising direction for studying this simple nervous system.

However, the paper's main weakness lies in its lack of a detailed mechanism explaining how the delayed reentry process directly influences the actual locomotor output that results in avoidance. The term 'delayed reentry' is used as a dynamic metric for quantifying the screening, yet the causal link between this metric and the mechanistic output remains unclear. Despite this, the study is well-structured, with comprehensive control experiments, and is very well constructed.

Comments on revisions:

The authors have addressed all my concerns and suggestions. They particularly further clarified the AIY's role in navigation by providing a new figure. They also provided supplementary videos representing the re-entry process.

Reviewer #2 (Public review):

Summary:

This manuscript explores in zebrafish the impact of genetic manipulation of individual microexons and two regulators of microexon inclusion (Srrm3 and Srrm4). The authors compare molecular, anatomical, and behavioral phenotypes in larvae and juvenile fish. The authors test the hypothesis that phenotypes resulting from Srrm3 and 4 mutations might in part be attributable to individual microexon deletions in target genes.

The authors uncover substantial alterations in in vitro neurite growth, locomotion, and social behavior in Srrm mutants but not any of the individual microexon deletion mutants. The individual mutations are accompanied by broader transcript level changes which may resemble compensatory changes. Ultimately, the authors conclude that the severe Srrm3/4 phenotypes result from additive and/or synergistic effects due to the de-regulation of multiple microexons.

Strengths:

The work is carefully planned, well-described, and beautifully displayed in clear, intuitive figures. The overall scope is extensive with a large number of individual mutant strains examined. The analysis bridges from molecular to anatomical and behavioral read-outs. Analysis appears rigorous and most conclusions are well-supported by the data.

Overall, addressing the function of microexons in an in vivo system is an important and timely question.

Weaknesses:

The main weakness of the work is the interpretation of the social behavior phenotypes in the Srrm mutants. It is difficult to conclude that the mutations indeed impact social behavior rather than sensory processing and/or vision which precipitates apparent social alterations as a secondary consequence. Interpreting the phenotypes as "autism-like" is not supported by the data presented.

Reviewer #2 (Public review):

Summary:

The authors of this manuscript aim to investigate the formation of place fields (PFs) in hippocampal CA1 pyramidal cells. They focus on the role of behavioral time scale synaptic plasticity (BTSP), a mechanism proposed to be crucial for the formation of new PFs. Using in vivo two-photon calcium imaging in head-restrained mice navigating virtual environments, employing a classification method based on calcium activity to categorize the formation of place cells' place fields into BTSP, non-BTSP-like, and investigated their properties.

Strengths:

A new method to use calcium imaging to separate BTSP and non-BTSP place field formation. This work offers new methods and factual evidence for other researchers in the field.

The method enabled the authors to reveal that while many PFs are formed by BTSP-like events, a significant number of PFs emerge with calcium dynamics that do not match BTSP characteristics, suggesting a diversity of mechanisms underlying PF formation. The characteristics of place fields under the first two categories are comprehensively described, including aspects such as formation timing, quantity, and width.

Weaknesses:

There are some issues about data and statistics that need to be addressed before these research findings can be considered as rigorous conclusions.

While the authors mentioned 3 features of PF generated by BTSP during calcium imaging in the Introduction, the classification method used features 1 and 2. The confirmation by feature 3 in its current form is important but not strong enough.

Some key data is missing such as the excluded PFs, the BTSP/non-BTSP of each animal, etc

Impact:

This work is likely to provide a new method to classify BTSP and non-BTSP place field formation using calsium image to the field.

Reviewer #2 (Public review):

Summary:

This study investigates whether individuals can learn to adopt egalitarian norms that incur a personal monetary cost, such as rejecting offers that benefit them more than the giver (advantageous inequitable offers). While these behaviors are uncommon, two experiments demonstrate that individuals can learn to reject such offers through vicarious learning - by observing and acting in line with a "teacher" who follows these norms. The authors use computational modelling to argue that learners adopt these norms through a sophisticated process, inferring the latent structure of the teacher's preferences, akin to theory of mind.

Strengths:

This paper is well-written and tackles a critical topic relevant to social norms, morality, and justice. The findings, which show that individuals can adopt just and fair norms even at a personal cost, are promising. The study is well-situated in the literature, with clever experimental design and a computational approach that may offer insights into latent cognitive processes. Findings have potential implications for policymakers.

Weaknesses:

Note: in the text below, the "teacher" will refer to the agent from which a participant presumably receives feedback during the learning phase.

(1) Focus on Disadvantageous Inequity (DI): A significant portion of the paper focuses on responses to Disadvantageous Inequitable (DI) offers, which is confusing given the study's primary aim is to examine learning in response to Advantageous Inequitable (AI) offers. The inclusion of DI offers is not well-justified and distracts from the main focus. Furthermore, the experimental design seems, in principle, inadequate to test for the learning effects of DI offers. Because both teaching regimes considered were identical for DI offers the paradigm lacks a control condition to test for learning effects related to these offers. I can't see how an increase in rejection of DI offers (e.g., between baseline and generalization) can be interpreted as speaking to learning. There are various other potential reasons for an increase in rejection of DI offers even if individuals learn nothing from learning (e.g. if envy builds up during the experiment as one encounters more instances of disadvantageous fairness).

(2) Statistical Analysis: The analysis of the learning effects of AI offers is not fully convincing. The authors analyse changes in rejection rates within each learning condition rather than directly comparing the two. Finding a significant effect in one condition but not the other does not demonstrate that the learning regime is driving the effect. A direct comparison between conditions is necessary for establishing that there is a causal role for the learning regime.

(3) Correlation Between Learning and Contagion Effects:<br /> The authors argue that correlations between learning effects (changes in rejection rates during the learning phase) and contagion effects (changes between the generalization and baseline phases) support the idea that individuals who are better aligning their preferences with the teacher also give more consideration to the teacher's preferences later during generalization phase. This interpretation is not convincing. Such correlations could emerge even in the absence of learning, driven by temporal trends like increasing guilt or envy (or even by slow temporal fluctuations in these processes) on behalf of self or others. The reason is that the baseline phase is temporally closer to the beginning of the learning phase whereas the generalization phase is temporally closer to the end of the learning phase. Additionally, the interpretation of these effects seems flawed, as changes in rejection rates do not necessarily indicate closer alignment with the teacher's preferences. For example, if the teacher rejects an offer 75% of the time then a positive 5% learning effect may imply better matching the teacher if it reflects an increase in rejection rate from 65% to 70%, but it implies divergence from the teacher if it reflects an increase from 85% to 90%. For similar reasons, it is not clear that the contagion effects reflect how much a teacher's preferences are taken into account during generalization.

(4) Modeling Efforts: The modelling approach is underdeveloped. The identification of the "best model" lacks transparency, as no model-recovery results are provided, and fits for the losing models are not shown, leaving readers in the dark about where these models fail. Moreover, the reinforcement learning (RL) models used are overly simplistic, treating actions as independent when they are likely inversely related (for example, the feedback that the teacher would have rejected an offer provides feedback that rejection is "correct" but also that acceptance is "an error", and the later is not incorporated into the modelling). It is unclear if and to what extent this limits current RL formulations. There are also potentially important missing details about the models. Can the authors justify/explain the reasoning behind including these variants they consider? What are the initial Q-values? If these are not free parameters what are their values?

(5) Conceptual Leap in Modeling Interpretation: The distinction between simple RL models and preference-inference models seems to hinge on the ability to generalize learning from one offer to another. Whereas in the RL models learning occurs independently for each offer (hence to cross-offer generalization), preference inference allows for generalization between different offers. However, the paper does not explore RL models that allow generalization based on the similarity of features of the offers (e.g., payment for the receiver, payment for the offer-giver, who benefits more). Such models are more parsimonious and could explain the results without invoking a theory of mind or any modelling of the teacher. In such model versions, a learner learns a functional form that allows to predict the teacher's feedback based on said offer features (e.g., linear or quadratic form). Because feedback for an offer modulates the parameters of this function (feature weights) generalization occurs without necessarily evoking any sophisticated model of the other person. This leaves open the possibility that RL models could perform just as well or even show superiority over the preference learning model, casting doubt on the authors' conclusions. Of note: even the behaviourists knew that as Little Albert was taught to fear rats, this fear generalized to rabbits. This could occur simply because rabbits are somewhat similar to rats. But this doesn't mean little Alfred had a sophisticated model of animals he used to infer how they behave.

(6) Limitations of the Preference-Inference Model: The preference-inference model struggles to capture key aspects of the data, such as the increase in rejection rates for 70:30 DI offers during the learning phase (e.g. Figure 3A, AI+DI blue group). This is puzzling.

Thinking about this I realized the model makes quite strong unintuitive predictions that are not examined. For example, if a subject begins the learning phase rejecting the 70:30 offer more than 50% of the time (meaning the starting guilt parameter is higher than 1.5), then overleaning the tendency to reject will decrease to below 50% (the guilt parameter will be pulled down below 1.5). This is despite the fact the teacher rejects 75% of the offers. In other words, as learning continues learners will diverge from the teacher. On the other hand, if a participant begins learning to tend to accept this offer (guilt < 1.5) then during learning they can increase their rejection rate but never above 50%. Thus one can never fully converge on the teacher. I think this relates to the model's failure in accounting for the pattern mentioned above. I wonder if individuals actually abide by these strict predictions. In any case, these issues raise questions about the validity of the model as a representation of how individuals learn to align with a teacher's preferences (given that the model doesn't really allow for such an alignment).

Reviewer #2 (Public review):

Summary:

The authors examine the ability of the human visual system to adapt to optically induced phase shifts. The study shows clear adaptation to the relative phase created by exposure to vertical coma. The study assesses the impact of adaptation to the coma on the perceived relative phase of f and 3f compound gratings. It is observed that during the first couple of minutes of a 1-hour exposure to induced vertical coma, the apparent relative locations of the f and 3f shifted in the opposite direction to that induced by the coma, a classic adaptation effect. This result highlights a neural mechanism by which flawed information is used to create seemingly accurate perceptions of the visual environment.

Strengths:

Sophisticated and rigorous optical and psychophysical methods, and a clear research question. The manuscript is well-written and the data quality is very high. The authors are to be congratulated on this challenging and complex optics and psychophysics study.

Weaknesses:

Some more details on the phase and amplitude consequences of the induced coma would add value to the reader.

Reviewer #2 (Public review):

Summary:

In this present Mendelian randomization-phenome-wide association study, the authors found BMI to be positively associated with many health-related conditions, such as heart disease, heart failure, and hypertensive heart disease. They also found sex differences in some traits such as cancer, psychological disorders, and ApoB.

Strengths:

The use of the UK-biobank study with detailed phenotype and genotype information.

Weaknesses:

Previous studies have performed this analysis using the same cohort, with in-depth analysis. See this paper: Searching for the causal effects of body mass index in over 300,000 participants in UK Biobank, using Mendelian randomization. https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1007951

I believe that the authors' claim, "To our knowledge, no sex-specific PheWAS has investigated the effects of BMI on health outcomes," is not well supported. They have not cited a relevant paper that conducted both overall and sex-stratified PheWAS using UK Biobank data with a detailed analysis. Given the prior study linked above, I am uncertain about the additional contributions of the present research.

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:

In this manuscript, Banse et al. experimentally validate the power of computational approaches that predict anti-aging molecules using the multi-species approach of the Caenorhabditis Intervention Testing Program (CITP). Filtering candidate molecules based on transcriptional profiles, ML models, literature searches, and the DrugAge database, they selected 16 compounds for testing. Of those, eight did not affect C.elegan's lifespan, three shortened it, and five extended C.elegan's lifespan, resulting in a hit rate of over 30%. Of those five, they then focused on all-trans-retinoic acid (atRA), a compound that has previously resulted in contradictory effects. The lifespan-extending effect of atRA was consistent in all C. elegans strains tested, was absent in C. briggsae, and a small effect was observed in some C. tropicalis strains. Similar results were obtained for measures of healthspan. The authors then investigated the mechanism of action of atRA and showed that it was only partially dependent on daf-16 but required akt-1, akt-2, skn-1, hsf-1, and, to some degree, pmk-1. The authors further investigate the downstream effects of atRA exposure by conducting RNAseq experiments in both wild-type and mutant animals to show that some, but surprisingly few, of the gene expression changes that are observed in wild-type animals are lost in the hsf-1 and aak-2 mutants.

Strengths:

Overall, this study is well conceived and executed as it investigates the effect of atRA across different concentrations, strains, and species, including life and health span. Revealing the variability between sites, assays, and the method used is a powerful aspect of this study. It will do a lot to dispel the nonsensical illusion that we can determine a percent increase in lifespan to the precision of two floating point numbers.

An interesting and potentially important implication arises from this study. The computational selection of compounds was agnostic regarding strain or species differences and was predominantly based on observations made in mammalian systems. The hit rate calculated is based on the results of C. elegans and not on the molecules' effectiveness in Briggsae or Tropicalis. If it were, the hit rate would be much lower. How is that? It would suggest that ML models and transcriptional data obtained from mammals have a higher predictive value for C. elegans than for the other two species. This selectivity for C.elegans over C.tropicalis and C.Briggsae seems both puzzling and unexpected. The predictions for longevity were based on the transcriptional data in cell lines. Would it be feasible to compare the mammalian data to the transcriptional data in Figure 5 and see how well they match? While this is clear beyond the focus of this study, an implied prediction is that running RNAseqs for all these strains exposed to atRA would reveal that the transcriptional changes observed in the strains where it extends lifespan the most should match the mammalian data best. Otherwise, how could the mammalian datasets be used to predict the effects of C.elegans over C.Briggsae or C.Tropicalis have more predictive for one species than the other? There are a lot of IFs in this prediction, but such an experiment would reconsider and validate the basis on which the original predictions were made.

Weaknesses:

Many of the most upregulated genes, such as cyps and pgps are xenobiotic response genes upregulated in many transcriptional datasets from C.elegans drug studies. Their expression might be necessary to deal with atRA breakdown metabolites to prevent toxicity rather than confer longevity. Because atRA is very light sensitive and has toxicity of breakdown, metabolites may explain some of the differences observed with the lifespan of machine effects compared to standard assay practices.

Reviewer #2 (Public review):

This paper presents an interesting and fresh approach as it investigates whether female moths utilize plant-emitted ultrasounds, particularly those associated with dehydration stress, in their egg-laying decision-making process.

Female moths showed a preference for moist, fresh plants over dehydrated ones in experiments using actual plants. Additionally, when both plants were fresh but ultrasonic sounds specific to dehydrated plants were presented from one side, the moths chose the silent plant. However, in experiments without plants, contrary to the hypothesis derived from the above results, the moths preferred to oviposit near ultrasonic playback mimicking the sounds of dehydrated plants.　

The results are intriguing, and I think the experiments are very well designed. However, if female moths use the sounds emitted by dehydrated plants as cues to decide where to oviposit, the hypothesis would predict that they would avoid such sounds. The discussion mentions the possibility of a multi-modal moth decision-making process to explain these contradictory results, and I also believe this is a strong possibility. However, since this remains speculative, careful consideration is needed regarding how to interpret the findings based solely on the direct results presented in the results section.

Additionally, the final results describing differences in olfactory responses to drying and hydrated plants are included, but the corresponding figures are placed in the supplementary materials. Given this, I would suggest reconsidering how to best present the hypotheses and clarify the overarching message of the results. This might involve reordering the results or re-evaluating which data should appear in the main text versus the supplementary materials.

There were also areas where more detailed explanations of the experimental methods would be beneficial.

Reviewer #2 (Public review):

This manuscript proposes that primary hepatocytes can replicate their DNA without the six-subunit ORC. This follows previous studies that examined mice that did not express ORC1 in the liver. In this study, the authors suppressed expression of ORC2 or ORC1 plus ORC2 in the liver.

Comments:

(1) I find the conclusion of the authors somewhat hard to accept. Biochemically, ORC without the ORC1 or ORC2 subunits cannot load the MCM helicase on DNA. The question arises whether the deletion in the ORC1 and ORC2 genes by Cre is not very tight, allowing some cells to replicate their DNA and allow the liver to develop, or whether the replication of DNA proceeds via non-canonical mechanisms, such as break-induced replication. The increase in the number of polyploid cells in the mice expressing Cre supports the first mechanism, because it is consistent with few cells retaining the capacity to replicate their DNA, at least for some time during development.

(2) Fig 1H shows that 5 days post infection, there is no visible expression of ORC2 in MEFs with the ORC2 flox allele. However, at 15 days post infection, some ORC2 is visible. The authors suggest that a small number of cells that retained expression of ORC2 were selected over the cells not expressing ORC2. Could a similar scenario also happen in vivo?

(3) Figs 2E-G shows decreased body weight, decreased liver weight and decreased liver to body weight in mice with recombination of the ORC2 flox allele. This means that DNA replication is compromised in the ALB-ORC2f/f mice.

(4) Figs 2I-K do not report the number of hepatocytes, but the percent of hepatocytes with different nuclear sizes. I suspect that the number of hepatocytes is lower in the ALB-ORC2f/f mice than in the ORC2f/f mice. Can the authors report the actual numbers?

(5) Figs 3B-G do not report the number of nuclei, but percentages, which are plotted separately for the ORC2-f/f and ALB-ORC2-f/f mice. Can the authors report the actual numbers?

(6) Fig 5 shows the response of ORC2f/f and ALB-ORC2f/f mice after partial hepatectomy. The percent of EdU+ nuclei in the ORC2-f/f (aka ALB-CRE-/-) mice in Fig 5H seems low. Based on other publications in the field it should be about 20-30%. Why is it so low here? The very low nuclear density in the ALB-ORC2-f/f mice (Fig 5F) and the large nuclei (Fig 5I) could indicate that cells fire too few origins, proceed through S phase very slowly and fail to divide.

(7) Fig 6F shows that ALB-ORC1f/f-ORC2f/f mice have very severe phenotypes in terms of body weight and liver weight (about on third of wild-type!!). Fig 6H and 6I, the actual numbers should be presented, not percentages. The fact that there are EYFP negative cells, implies that CRE was not expressed in all hepatocytes.

(8) Comparing the EdU+ cells in Fig 7G versus 5G shows very different number of EdU+ cells in the control animals. This means that one of these images is not representative. The higher fraction of EdU+ cells in the double-knockout could mean that the hepatocytes in the double-knockout take longer to complete DNA replication than the control hepatocytes. The control hepatocytes may have already completed DNA replication, which can explain why the fraction of EdU+ cells is so low in the controls. The authors may need to study mice at earlier time points after partial hepatectomy, i.e. sacrifice the mice at 30-32 hours, instead of 40-52 hours.

(9) Regarding the calculation of the number of cell divisions during development: the authors assume that all the hepatocytes in the adult liver are derived from hepatoblasts that express Alb. Is it possible to exclude the possibility that pre-hepatoblast cells that do not express Alb give rise to hepatocytes? For example the cells that give rise to hepatoblasts may proliferate more times than normal giving rise to a higher number of hepatoblasts than in wild-type mice.

(10) My interpretation of the data is that not all hepatocytes have the ORC1 and ORC2 genes deleted (eg EYFP-negative cells) and that these cells allow some proliferation in the livers of these mice.

for - article - Windows Central - AI safety researcher warns there's a 99.999999% probability AI will end humanity, but Elon Musk "conservatively" dwindles it down to 20% and says it should be explored more despite inevitable doom - 2024, Ape 2 - AI safety researcher warns there's a 99.999999% probability AI will end humanity

// - Comment - In fact, the heading is misleading. - It should be the other way around. - Elon Musk made the claim first but the AI Safety expert commented on Elon Musk's claim.

Reviewer #2 (Public review):

Summary:

Peng et al. present a study using scRNA-seq to examine phenotypic properties of cervical cancer, contrasting features of both adenocarcinomas (ADC) and squamous cell carcinoma (SCC), and HPV-positive and negative tumours. They propose several key findings: unique malignant phenotypes in ADC with elevated stemness and aggressive features, interactions of these populations with immune cells to promote an immunosuppressive TME, and SLC26A3 as a biomarker for metastatic (>=Stage III ) tumours.

Strengths:

This study provides a valuable resource of scRNA-seq data from a well-curated collection of patient samples. The analysis provides a high-level view of the cellular composition of cervical cancers. The authors introduce some mechanistic explanations of immunosuppression and the involvement of regulatory T cells that is intriguing.

Weaknesses:

I believe many of the proposed conclusions are over-interpretations or unwarranted generalizations of the single-cell analysis. I believe there may also be some artifacts in the data that may not reflect true biology--eg. The presentation of KRT+ neutrophils, which may reflect doublets with cancer cells. In some cases there is mention of quality control steps to remove contaminant cell clusters, but there is no method or supplemental figure to describe and/or justify these steps.

The key limitation is related to the "ADC-specific" Epi_10_CYSTM1 cluster, which is a central focus of the paper. This population only contains cells from one of the 11 ADC samples and represents only a small fraction of the malignant cells from that sample. Yet, this population is used to derive SLC26A3 as a potential biomarker. SLC26A3 transcripts are only detected in this small population of cells (none of the other ADC samples), which makes me question the specificity of the IHC staining on the validation cohort. The manuscript does not address why this marker is so rare in the scRNA-seq data, but abundant in the IHC.

While I understand it may be out of the scope of this individual study, many of the conclusions are inferred from the data analysis with little follow-up in experimental models or orthogonal assays.

Reviewer #2 (Public Review):

Summary:

In the manuscript, Yu et al reported a two-sample Mendelian randomization study to evaluate the causation between polyunsaturated fatty acids (PUFA) and cerebral aneurysm, based on summary statistics from published genome-wide association studies. The authors identified that omega-3 fatty acids and Docosahexaenoic acid decreased the risk for intracranial aneurysm (IA) and aneurysmal subarachnoid haemorrhage (aSAH). COLOC analysis suggested that the acids and IA, aSAH likely share causal variants in gene fatty acid desaturase 2.

Strengths:

The methodology is sound, with appropriate sensitivity analysis.

Weaknesses:

The results did not provide significant novel findings.

Reviewer #2 (Public review):

Summary:

Ziółkowska et al. characterize the synaptic mechanisms at the basis of the RE-dCA1 contribution to the consolidation of fear memory extinction. In particular, they describe a layer specific modulation of RE-dCA1 excitatory synapses modulation associated to contextual fear extinction which is impaired by transient chemogenetic inhibition of this pathway. These results indicate that RE activity-mediated modulation of synaptic morphology contributes to contextual fear extinction

Strengths:

The manuscript is well conceived, the statistical analysis is solid and methodology appropriate. The strength of this work is that it nicely builds up on existing literature and provides new molecular insight on a thalamo-hippocampal circuit previously known for its role in fear extinction. In addition, the quantification of pre- and post-synapses is particularly thorough.

Weaknesses:

The results illustrated in this manuscript show nice incremental evidence about the neural mechanisms contributing to the RE-CA1 modulation of fear extinction. The novelty of this manuscript is therefore not exceptional, but still highly relevant for the field.

Reviewer #2 (Public review):

Summary:

This manuscript introduced a volumetric trans-scale imaging system with an ultra-large field-of-view (FOV) that enables simultaneous observation of millions of cellular dynamics in centimeter-wide 3D tissues and embryos. In term of technique, this paper is just a minor improvement of the authors' previous work, which is a fluorescence imaging system working at visible wavelength region (https://www.nature.com/articles/s41598-021-95930-7).

Strengths:

In this study, the authors enhanced the system's resolution and sensitivity by increasing the numerical aperture (NA) of the lens. Furthermore, they achieved volumetric imaging by integrating optical sectioning and computational sectioning. This study encompasses a broad range of biological applications, including imaging and analysis on organoids, mouse brains, and quail embryos, respectively. Overall, this method is useful and versatile.

Weaknesses:

What is the unique application that only can be done by this high-throughput system remains vague. Meanwhile, there are also several outstanding issues in this paper, such as the lack of technical advances, unclear method details and non-standardized figures.

Comments on revisions:

The revised manuscript has significantly improved in response to the initial review comments, particularly with the detailed additions regarding the objective lens and confocal imaging modes, which enhance the clarity and comprehensibility of the paper. While the structure and arguments are much clearer overall, there are still key issues that need to be addressed, specifically regarding algorithm validation, computational sectioning presentation, and volume imaging rate.

Algorithm Validation:<br /> The validation of the algorithm's accuracy is not sufficiently robust. Reviewer 1's comment is entirely reasonable, and the authors should validate the algorithm's accuracy using well-established methods as ground truth. In the revised version, the authors attempt to demonstrate the fidelity of the algorithm by employing deep learning methods for high-accuracy cell recognition. However, this validation relies solely on comparisons between deep learning results and manual annotation results. The problem lies in the fact that both manual annotations and deep learning outcomes are derived from algorithm-processed data, which fails to prove the authenticity or validity of the data itself. To strengthen the validation, the authors should incorporate independent, gold-standard methods for comparison.

Computational Sectioning:<br /> In the revised manuscript, the authors effectively demonstrate the ability of optical sectioning to improve axial resolution using fluorescent beads, as shown in Fig. S3, which is a strong point. However, the manuscript lacks a direct comparison for computational sectioning and does not provide a clear evaluation of axial resolution before and after applying computational sectioning. While some related information is included in Figs. 5.C and D, the details are insufficient, and intensity profiles are absent. I recommend that the authors include more direct visual demonstrations of computational sectioning, along with comparisons of axial resolution before and after applying computational sectioning. This would better showcase the method's effectiveness.

Volume Imaging Rate:<br /> The manuscript currently omits critical details about the method's volume imaging rate. In the description of the quail embryo imaging experiment, key parameters such as exposure time and imaging speed are missing. Additionally, the manuscript does not discuss the maximum imaging rate supported by the system in confocal mode. The volume imaging rate is an essential factor for biological researchers to evaluate the applicability of the technique. Therefore, this information should be included, ideally in the abstract and introduction. Furthermore, the authors could describe how the volume imaging rate performs under different conditions and discuss its potential applications across various biological research contexts. Including such details would significantly enhance the paper's utility and appeal to the broader research community.

These adjustments will further strengthen the manuscript and address the reviewers' concerns effectively.

Reviewer #2 (Public review):

Summary:

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.

Strengths:

The manuscript is well-written, with a concise and clear writing style. The visual presentation is largely clear. The study involves multiple experiments with different participant groups. Each experiment involves specific considered changes to the experimental paradigm that both replicate the previous experiment's finding yet extend it in a relevant manner.

Weaknesses:

In the revised version of the paper, the manuscript better relays the results and anticipates analyses, and this version adequately resolves some concerns I had about analysis details. Still, it is my view that the findings of the study are basic neural correlate results that do not provide insights into neural mechanisms or the causal relevance of neural effects towards behavior and cognition. The presence of an inversion effect suggests that the supra-additivity is related to cognition, but that leaves open whether any detected neural pattern is actually consequential for multi-sensory integration (i.e., correlation is not causation). In other words, the fact that frequency-specific neural responses to the [audio & visual] condition are stronger than those to [audio] and [visual] combined does not mean this has implications for behavioral performance. While the correlation to autism traits could suggest some relation to behavior and is interesting in its own right, this correlation is a highly indirect way of assessing behavioral relevance. It would be helpful to test the relevance of supra-additive cortical tracking on a behavioral task directly related to the processing of biological motion to justify the claim that inputs are being integrated in the service of behavior. Under either framework, cortical tracking or entrainment, the causal relevance of neural findings toward cognition is lacking.

Overall, I believe this study finds neural correlates of biological motion, and it is possible that such neural correlates relate to behaviorally relevant neural mechanisms, but based on the current task and associated analyses this has not been shown.

Reviewer #3 (Public review):

Summary:

The authors study temporal summation of caged EPSPs in dendrite-targeting hippocampal CA1 interneurons. The data indicate non-linear summation, which is larger in dendrites of NDNF-expressing neurogliaform cells versus OLM cells. However, the underlying mechanisms are largely unclear.

Strengths:

Synaptic integration in dendrites of cortical GABAergic interneurons is important and still poorly investigated. Focal 2-photon uncaging of glutamate is a nice and detailed method to study temporal summation of small potentials in dendritic segments. 2P calcium imaging is a powerful method to potentially disentangle dendritic signal processing in interneuron dendrites.

Weaknesses:

Due to several experimental limitations of the study including a relatively low number of recorded dendrites, lack of voltage-clamp recordings, lack of NMDA-dependent calcium signals in OLM cells and lack of wash-out during pharmacological experiments (AP5-application), the mechanistic insights are limited.

(1) NMDA-receptor signalling in NDNF-IN. The authors nicely show that temporal summation in dendrites of NDNF-INs is to a certain extent non-linear. Pharmacology with AP5 hints towards contribution of NMDA receptors. However, the authors report that the non-linearity in not significantly dependent on EPSP amplitude (Fig. S2), which should be the case if NMDA-receptors are involved. Unfortunately, there are no voltage-clamp data showing NMDA and AMPA currents, potentially providing a mechanistic explanation for the non-linear summation.

(2) Recovery of drug effect. Pharmacological application of AP5 is the only argument for the involvement of NMDA receptors. However, as long-lasting experiments were apparently difficult to obtain, there is no washout-data presented - only drug effect versus baseline. For all the other drugs (TTX, Nimodipine, CPA) recordings were even shorter, lacking a baseline recording. Thus, it remains open to what extent the AP5-effect might be affected by rundown of receptors or channels during whole-cell recordings or beginning phototoxicity.

(3) Nonlinear EPSP summation in OLM-IN. The authors do similar experiments in dendrite-targeting OLM-INs and show that the non-linear summation is smaller than in NDNF cells. The reason for this remains unclear. The diameter of proximal dendrites in OLM cells is larger than the diameter in NDNF cells. However, there is probably also an important role of synapse density and glutamate receptor density, which was shown to be very low in proximal dendrites of OLM cells and strongly increase with distance (Guirado et al. 2014, Cerebral Cortex 24:3014-24, Gramuntell et al. 2021, Front Aging Neurosci 13:782737). Therefore, it would have been helpful to see experiments quantifying synapse density (counting spines, PSD95-puncta, ...) and show how this density compares with non-linearity in the analyzed NDNF and OLM dendrites.

(4) NMDA in OLM-IN. Similar to the NDNF cells, the authors argue for an involvement of NMDA receptors in OLM cells, based on bath-application of AP5 (Fig. 8). Again, there seems to be no significant dependence on EPSP amplitude (Fig. S3). Even more remarkable, the authors claim that there is no dendritic calcium increase after activation of NMDA receptors without showing data. Therefore, it remains unclear whether the calcium signals are just below detection threshold, or whether the non-linearity depends on other calcium-impermeable channels and receptors. To understand this phenomenon different calcium sensors, different Ca2+/Mg2+ concentrations or voltage-clamp data would have helped.

Reviewer #2 (Public review):

Summary:

HIV-1 infection induces CPSF6 aggregates in the nucleus that contain the viral protein CA. The study of the functions and composition of these nuclear aggregates have raised considerable interest in the field, and they have emerged as sites in which reverse transcription is completed and in the proximity of which viral DNA becomes integrated. In this work, the authors have mutated several regions of the CPSF6 protein to identify the domains important for nuclear aggregation, in addition to the already-known FG region; they have characterized the kinetics of fusion between CPSF6 aggregates and SC35 nuclear speckles and have determined the role of two nuclear speckle components in this process (SRRM2, SUN2).

Strengths:

The work examines systematically the domains of CPSF6 of importance for nuclear aggregate formation in an elegant manner in which these mutants complement an otherwise CPSF6-KO cell line. In addition, this work evidences a novel role for the protein SRRM2 in HIV-induced aggregate formation, overall advancing our comprehension of the components required for their formation and regulation.

Weaknesses:

Some of the results presented in this manuscript, in particular the kinetics of fusion between CPSF6-aggregates and SC35 speckles have been published before (PMID: 32665593; 32997983).

The observations of the different effects of CPSF6 mutants, as well as SRRM2/SUN2 silencing experiments are not complemented by infection data which would have linked morphological changes in nuclear aggregates to function during viral infection. More importantly, these functional data could have helped stratify otherwise similar morphological appearances in CPSF6 aggregates.

Overall, the results could be presented in a more concise and ordered manner to help focus the attention of the reader on the most important issues. Most of the figures extend to 3-4 different pages and some information could be clearly either aggregated or moved to supplementary data.

Reviewer #2 (Public review):

In this manuscript, the authors leverage multiple cellular models including the drosophila fat body and cultured hepatocytes to investigate the metabolic programs governing cell size. By profiling gene programs in the larval fat body during the third instar stage - in which cells cease proliferation and initiate a period of cell growth - the authors uncover a coordinated downregulation of genes involved in mitochondrial pyruvate import and metabolism. Enforced expression of the mitochondrial pyruvate carrier restrains cell size, despite active signaling of mTORC1 and other pathways viewed as traditional determinants of cell size. Mechanistically, the authors find that mitochondrial pyruvate import restrains cell size by fueling gluconeogenesis through the combined action of pyruvate carboxylase and phosphoenolpyruvate carboxykinase. Pyruvate conversion to oxaloacetate and use as a gluconeogenic substrate restrains cell growth by siphoning oxaloacetate away from aspartate and other amino acid biosynthesis, revealing a tradeoff between gluconeogenesis and provision of amino acids required to sustain protein biosynthesis. Overall, this manuscript is extremely rigorous, with each point interrogated through a variety of genetic and pharmacologic assays. The major conceptual advance is uncovering the regulation of cell size as a consequence of compartmentalized metabolism, which is dominant even over traditional signaling inputs. The work has implications for understanding cell size control in cell types that engage in gluconeogenesis but more broadly raise the possibility that metabolic tradeoffs determine cell size control in a variety of contexts.

Reviewer #2 (Public review):

Summary:

Jaber et al. describe the generation and characterization of a knock-in mouse strain expressing the p53 Y217C hot-spot mutation. While the homozygous mutant cells and mice reflect the typical loss-of-p53 functions, as expected, the Y217C mutation also appears to display gain-of-function (GOF) properties, exemplified by elevated metastasis in the homozygous context (as noted with several hot-spot mutations). Interestingly, this mutation does not appear to exhibit any dominant-negative effects associated with most hot-spot p53 mutations, as determined by the absence of differences in overall survival and tumor predisposition of the heterozygous mice, as well as target gene activation upon nutlin treatment.

In addition, the authors noted a severe reduction in the female 217/217 homozygous progeny, significantly more than that observed with the p53 null mice, due to exencephaly, leading them to conclude that the Y217C mutation also has additional, non-cancer-related GOFs. Though this property has been well described and attributed to p53 functional impairment, the authors conclude that the Y217C has additional properties in accelerating the phenotype.

Transcriptomic analyses of thymi found additional gene signature differences between the p53 null and the Y217C strains, indicative of novel target gene activation, associated with inflammation.

Strengths:

Overall, the characterisation of the mice highlights the expected typical outcomes associated with most hot-spot p53 mutations published earlier. The quality of the work presented is well done and good, and the conclusions and reasonably well justified.

Weaknesses:

The manuscript would benefit from the provision of additional data to strengthen the claims made, as follows:

(1) Oncogenic GOF - the main data shown for GOF are the survival curve and enhanced metastasis. Often, GOF is exemplified at the cellular level as enhanced migration and invasion, which are standard assays to support the GOF. As such, the authors should perform these assays using either tumor cells derived from the mice or transformed fibroblasts from these mice. This will provide important and confirmatory evidence for GOF for Y217C.

(2) Novel target gene activation - while a set of novel targets appears to be increased in the Y217C cells compared to the p53 null cells, it is unclear how they are induced. The authors should examine if mutant p53 can bind to their promoters through CHIP assays, and, if these targets are specific to Y217C and not the other hot-spot mutations. This will strengthen the validity of the Y217C's ability to promote GOF.

(3) Dominant negative effect - the authors' claim of lack of DN effect needs to be strengthened further, as most p53 hot-spot mutations do exhibit DN effect. At the minimum, the authors should perform additional treatment with nutlin and gamma irradiation (or cytotoxic/damaging agents) and examine a set of canonical p53 target genes by qRT-PCR to strengthen their claim.

Reviewer #2 (Public review):

Summary:

The manuscript by Fang et al., provides a tour-de-force study uncovering cancer cell's varied dependencies on several gene programs for their survival under different biological contexts. The authors addressed genomic differences in 2D vs 3D cultures and how hypoxia affects gene expression. They used a Myc-driven murine liver cancer model grown in 2D monolayer culture in normoxia and hypoxia as well as cells grown as 3D spheroids and performed CRISPR-based genome-wide KO screen to identify genes that play important roles in cell fitness. Some context-specific gene effects were further validated by in-vitro and in-vivo gene KO experiments.

Strengths:

The key findings in this manuscript are:

(1) Close to 50% of differentially expressed genes were common between 2D Hypoxia and 3D spheroids conditions but they had differences in chromatin accessibility.<br /> (2) VHL-HIF1a pathway had differential cell fitness outcomes under 2D normoxia vs 2D hypoxia and 3D spheroids.<br /> (3) Individual components of the mitochondrial respiratory chain complex had contrasting effects on cell fitness under hypoxia.<br /> (4) Knockout of organogenesis or developmental pathway genes led to better cell growth specifically in the context of 3D spheroids and knockout of epigenetic modifiers had varied effects between 2D and 3D conditions.<br /> (5) Another key program that leads to cells fitness outcomes in normoxia vs hypoxia is the lipid and fatty acid metabolism.<br /> (6) Prmt5 is a key essential gene under all growth conditions, but in the context of 3D spheroids even partial loss of Prmt5 has a synthetic lethal effect with Mtap deletion and Mtap is epigenetically silenced specifically in the 3D spheroids.

Issues to address:

(1) The authors should clarify the link between the findings of the enrichment of TGFb-SMAD signaling REACTOME pathway to the findings that knocking out TGFb-SMAD pathway leads to better cell fitness outcomes for cells in the 3D growth conditions.

(2) Supplementary Figure 4C has been cited in the text but doesn't exist in the supplementary figures section.

(3) A small figure explaining this ABC-Myc driven liver cancer model in Supplementary Figure 1 would be helpful to provide context.

(4) The method for spheroids formation is not found in the method section.

(5) In Supplementary Figure 1b, the comparisons should be stated the opposite way - 3D vs 2D normoxia and 2D-Hypoxia vs 2D-Normoxia.

(6) There are typos in the legend for Supplementary Figure 10.

(7) Consider putting Supplementary Figure 1b into the main Figure 1.

(8) Please explain only one timepoint (endpoint) for 3D spheroids was performed for the CRISPR KO screen experiment, while several timepoints were done for 2D conditions? Was this for technical convenience?

(9) In line 372, it is indicated that Bcor KO (Fig 5e) had growth advantage - this was observed in only one of the gRNA -- same with Kmt2d KO in the same figure where there was an opposite effect. Please justify the use of only one gRNA.

(10) Why was CRISPR based KO strategy not used for the PRMT5 gene but rather than the use of shRNA.? Note that one of the shRNA for PRMT5 had almost no KO (PRMT5-shRNA2 Figure 7B) but still showed phenotype (Figure 7D) - please explain.

(11) In Figure 7D, which samples (which shRNA group) were being compared to do the t-test?

(12) In line 240, it is stated that oxphos gene set is essential for NEJF10 cell survival in both normoxia and hypoxia conditions. But shouldn't oxphos be non-essential in hypoxia as cells move away from oxphos and become glycolytic?

(13) In line 485 it is mentioned that Pmvk and Mvd genes which are involved in cholesterol synthesis when knocked out had a positive effect on cell growth in 3D conditions and since cholesterol synthesis is essential for cell growth how does this not matter much in the context of 3D - please explain.

Reviewer #2 (Public review):

Summary:

Shengsheng Zhao et al. investigated the role of nucleolar and coiled-body phosphoprotein 1 (NOLC1) in relegating gastric cancer (GC) development and cisplatin-induced drug resistance in GC. They found a significant correlation between high NOLC1 expression and the poor prognosis of GC. Meanwhile, upregulation of NOLC1 was associated with cis-resistant GC. Experimentally, the authors demonstrate that knocking down NOLC1 increased GC sensitivity to Cis possibly by regulating ferroptosis. Mechanistically, they found NOLC1 suppressed ferroptosis by blocking the translocation of P53 from the cytoplasm to the nucleus and promoting its degradation. In addition, The authors also evaluated the effect of combinational treatment of anti-PD-1 and cisplatin in NOLC1 -knockdown tumor cells, revealing a potential role of NOLC1 in the targeted therapy for GC.

Strengths:

Chemoresistance is considered a major reason causing failure of tumor treatment and death of cancer patients. This paper explored the role of NOLC1 in the regulation of Cis-mediated resistance, which involves a regulated cell death named ferroptosis. These findings provide more evidence highlighting the study of regulated cell death to overcome drug resistance in cancer treatment, which could give us more potential strategies or targets for combating cancer.

Weaknesses:

More evidence supporting the regulation of ferroptosis induced by Cisplatin by NOLC1 should be added. Particularly, the role of ferroptosis in the cisplatin-resistance should be verified and whether NOLC1 regulates ferroptosis induced by additional FINs should be explored. Besides, the experiments to verify the regulation of ferroptosis sensitivity by NOLC1 are sort of superficial. The role of MDM2/p53 in ferroptosis or cisplatin resistance mediated by NOLC1 should be further studied by genetic manipulation of p53, which is the key evidence to confirm its contribution to NOLC1 regulation of GC and relative cell death.

Reviewer #2 (Public review):

Summary:

This study provides a novel understanding of CoV-host interaction, leading potential therapeutics for SARS-CoV2 infection. Tian et al. identified and demonstrated that the two E3 ligases UBR5 and MARCHF7 both interact with and catalyze the ubiquitination of NSP16 protein of SARS-CoV2, thereby leading to its degradation by the ubiquitin-proteasome system (UPS) and inhibiting SARS-CoV-2 replication. It is interesting to see that the two E3 ligases perform their functions on the same target independently.

Strengths:

Overall, the topic and initial discoveries appear interesting. The experimental designs of this study were rigorous and logical, most of the work has been carefully done, and the conclusions drawn from this study are relatively convincing and reliable.

Weaknesses:

The quality of the presentation could be improved with better organization, a more conservative interpretation of the data, and further clarity in the writing.

Reviewer #2 (Public review):

Summary:

The authors conducted a study to evaluate the potential of circulating HPV cell-free DNA (cfDNA) as a biomarker for monitoring recurrent or metastatic HPV+ cervical cancer. They analyzed serum samples from 28 patients, measuring HPV cfDNA levels via digital droplet PCR and comparing these to squamous cell carcinoma antigen (SCC-Ag) levels in 26 SCC patients, while also testing the association between HPV cfDNA levels and clinical outcomes. The main hypothesis that the authors set out to test was whether circulating HPV cfDNA levels correlated with metastatic patterns and/or treatment response in HPV+ CC.

The main claims put forward by the paper are that:

(1) HPV cfDNA was detected in all 28 CC patients enrolled in the study and levels of HPV cfDNA varied over a median 2-month monitoring period.<br /> (2) 'Median baseline' HPV cfDNA varied according to 'metastatic pattern' in individual patients.<br /> (3) Positivity rate for HPV cfDNA was more consistent than SCC-Ag.<br /> (4) In 20 SCC patients monitored longitudinally, concordance with changes in disease status was 90% for HPV cfDNA.

This study highlights HPV cfDNA as a promising biomarker with advantages over SCC-Ag, underscoring its potential for real-time disease surveillance and individualized treatment guidance in HPV-associated cervical cancer.

Strengths:

This study presents valuable insights into HPV+ cervical cancer with potential translational significance for management and guiding therapeutic strategies. The focus on a non-invasive approach is particularly relevant for women's cancers, and the study exemplifies the promising role of HPV cfDNA as a biomarker that could aid personalized treatment strategies.

Weaknesses:

While the authors acknowledge the study's small cohort and variability in sequential sampling protocols as a limitation, several revisions should be made to ensure that (1) the findings are presented in a way that aligns more closely with the data without overstatement and (2) that the statistical support for these findings is made more clear. Specific suggestions are outlined below.

(1) The authors should provide source data for Figures 2, 3, and 4 as supplementary material.

(2) Description of results in Figure 2: Figure 2 would benefit from clearer annotations regarding HPV virus subtypes. For example, does the color-coding in Figure 2B imply that all samples in the LR subgroup are of type HPV16? If that is the case, is it possible that detection variations are due to differences in subtype detection efficiency rather than cfDNA levels? The authors should clarify these aspects. Annotation of Figure 2B suggests that the p-value comes from comparing the LR and LN+H+DSM groups. This should be clarified in the legend. If this p-value comes from comparing HPV cfDNA copies for the (LR, LNM, HM) and (LN+HM, LN+HM+DSM) groups, did the authors carry out post-hoc pairwise comparisons? It would be helpful to include acronyms for these groups in the legend also.

(3) Interpretation of results in Figure 2 and elsewhere: Significant differences detected in Figure 2B could imply potential associations between HPV cfDNA levels (or subtypes) and recurrence/metastasis patterns. Figure 2C shows that there is a difference in cfDNA levels between the groups compared, suggesting an association but this would not necessarily be a direct "correlation". Overall, interpretation of statistical findings would benefit from more precise language throughout the text and overstatement should be avoided.

(4) The authors state that six patients showed cfDNA elevation with clinically progressive disease, yet only three are represented in Figure 3B1 under "Patients whose disease progressed during treatment." What is the expected baseline variability in cfDNA for patients? If we look at data from patients with early-stage cancer would we see similar fluctuations? And does the degree of variability vary for different HPV subtypes? Without understanding the normal fluctuations in cfDNA levels, interpreting these changes as progression indicators may be premature.

(5) It would be helpful if where p-values are given, the test used to derive these values was also stated within parentheses e.g. (P < 0.05, permutation test with Benjamini-Hochberg procedure).

Reviewer #1 (Public review):

This work presents a self-supervised method for the segmentation of 3D cells in microscopy images, an annotated dataset, as well as a napari plugin. While the napari plugin is potentially useful, there is insufficient evidence in the manuscript to support the claim that the proposed method is able to segment cells in other light-sheet microscopy image datasets than the four specific ones used here.

I acknowledge that the revision is now more upfront about the scope of this work. However, my main point still stands: even with the slight modifications to the title, this paper suggests to present a general method for self-supervised 3D cell segmentation in light-sheet microscopy data. This claim is simply not backed up.

I still think the authors should spell out the assumptions that underlie their method early on (cells need to be well separated and clearly distinguishable from background). A subordinate clause like "often in cleared neural tissue" does not serve this purpose. First, it implies that the method is also suitable for non-cleared tissue (which would have to be shown). Second, this statement does not convey the crucial assumptions of well separated cells and clear foreground/background differences that the method is presumably relying on.

It does appear that the proposed method works very well on the four investigated datasets, compared to other pre-trained or fine-tuned models. However, it still remains unclear whether this is because of the proposed method or the properties of those specific datasets (namely: well isolated cells that are easily distinguished from the background). I disagree with the authors that a comparison to non-learning methods "is unnecessary and beyond the scope of this work". In my opinion, this is exactly what is needed to proof that CellSeg3D's performance can not be matched with simple image processing.

As I mentioned in the original review, it appears that thresholding followed by connected component analysis already produces competitive segmentations. I am confused about the authors' reply stating that "[this] is not the case, as all the other leading methods we fairly benchmark cannot solve the task without deep learning". The methods against which CellSeg3D is compared are CellPose and StarDist, both are deep-learning based methods. That those methods do not perform well on this dataset does not imply that a simpler method (like thresholding) would not lead to competitive results. Again, I strongly suggest the authors include a simple, non-learning based baseline method in their analysis, e.g.:<br /> * comparison to thresholding (with the same post-processing as the proposed method)<br /> * comparison to a normalized cut segmentation (with the same post-processing as the proposed method)

Regarding my feedback about the napari plugin, I apologize if I was not clear. The plugin "works" as far as I tested it (i.e., it can be installed and used without errors). However, I was not able to recreate a segmentation on the provided dataset using the plugin alone (see my comments in the original review). I used the current master as available at the time of the original review and default settings in the plugin.

Reviewer #2 (Public review):

Summary

This study provides a detailed analysis and dissociation between two effects of activation of lateral inhibitory circuits in the olfactory bulb on ongoing single mitral/tufted cell (MTC) spiking activity, namely enhanced synchronization in the gamma frequency range or lateral inhibition of firing rate.

The authors use a clever combination of single cell recordings, optogenetics with variable spatial stimulation of MTCs and sensory stimulation in vivo, and established mathematical methods, to describe changes in autocorrelation/synchronization of a single MTC's spiking activity upon activation of other, lateral glomerular MTC ensembles. This assay is rounded off by a gain of function experiment in which the authors enhance granule cell (GC) excitation to establish a causal relation between GC activation and enhanced synchronization of a single MTC's spiking to the gamma rhythm. They had used the same optogenetic manipulation in their previous paper Dalal & Haddad 2022, but use a smaller illumination spot here for spatially restricted activation.

Strengths

This study is of high interest for olfactory processing since it shows directly that interactions between only two selected active receptor channels are sufficient to enhance synchronization of single neurons to gamma in one receptor channel and thus by inference most likely in both. Such synchronization across co-active receptor channels in turn would enable upstream neurons in olfactory cortices to read out odour identity.

The authors find that these interactions are distance-independent over many 100s of µms and thus can allow for non-topographical inhibitory action across the bulb, in contrast to the center-surround lateral inhibition known from other sensory modalities. In my view, analogies between vision and olfaction might have been overemphasized so far, since the combinatorial encoding of olfactory stimuli across the glomerular map might require different mechanisms of lateral interaction versus vision. This result is indicative of such a major difference.

Such enhanced local synchronization to gamma in one channel was observed in a subset of activated channel pairs; in addition, the authors report another type of lateral interaction that does involve reduction of firing rates, drops off with distance and most likely is caused by a different circuit mediated by PV+ neurons (PVN). The evidence for the latter is more circumstantial since no manipulations of PVNs were performed.

Weaknesses/Room for improvement

This study is an impressive proof of concept that however does not yet allow for broad generalization. Thus the framing of results should be slightly more careful IMHO. While the claims in the initial version of this preprint have been toned down quite substantially, the authors do not provide direct hard evidence for synchronization across channels. Admittedly, this would be hard to achieve since it would require paired recordings from MTCs in different locations in vivo. Therefore, the term „lateral synchronization" as it is used in the abstract is still problematic, as well as the title which should rather say „can enable" instead of „enables". That being said, this study definitely provides important evidence regarding the concept of "lateral synchronization".

The other comments and recommendations have been well taken care of in the new version.

Reviewer #2 (Public review):

Summary:

In this work, the authors trained RNN to perform a reversal task also performed by animals while PFC activity is recorded. The authors devised a new method to train RNN on this type of reversal task, which in principle ensures that the behavior of the RNN matches the behavior of the animal. They then performed some analysis of neural activity, both RNN and PFC recording, focusing on the neural representation of the reversal probability and its evolution across trials. Given the analysis presented, it has been difficult for me to assess at which point RNN can reasonably be compared to PFC recordings.

Strengths:

Focusing on a reversal task, the authors address a challenge in RNN training, as they do not use a standard supervised learning procedure where the desired output is available for each trial. They propose a new way of doing that.

They attempt to confront RNN and neural recordings in behaving animals.

Weaknesses:

The design of the task for the RNN does not seem well suited to support the claim of the paper: no action is required to be performed by neurons in the RNN, instead, the choice of the animal is determined by applying a non-linearity to the RNN's readout (equation 7), no intervening behavior is thus performed by neurons on which the analysis is performed throughout the paper. 
Instead, it would have been nice to mimic more closely the task structure of the experiments on monkeys, with a fixation period where the read-out is asked to be at a zero value, and then asked to reach a target value (not just taking its sign), depending on the expected choice after a cue presentation period.

The comparison between RNN and neural data focuses on very specific features of neural activity. It would have been nice to see how individual units in the RNN behave over the course of the trial, do all units show oscillatory behavior like the readout shown in Figure 1B?

It would be nice to justify why it has been chosen to take a network of inhibitory neurons and to know whether the analysis can also be performed with excitatory neurons.
 All the analysis relies on the dimensionality reduction. It would have been nice to have some other analysis confirming the claim of the absence of a line attractor in the neural data. Or at least to better characterize this dimensionality reduction procedure, e.g. how much of the variance is explained by this analysis for instance?

It is thus difficult to grasp, besides the fact that reversal behavior is similar, to what extent the RNN is comparable to PFC functioning and to what extent we learn anything about the latter.

Other computational works (e.g. [1,2]) have developed procedures to train RNN on reversal-like tasks, it would have been nice to compare the procedure presented here with these other works.

[1] H Francis Song & Xiao-Jing Wang. Reward-based training of recurrent neural networks for cognitive and value-based tasks. eLife doi:10.7554/elife.21492.001.

[2] Molano-Mazón, M. et al. Recurrent networks endowed with structural priors explain suboptimal animal behavior. Current Biology 33, 622-638.e7 (2023).

Reviewer #2 (Public review):

Summary:

The manuscript from Calhoun et al. uses a well-established screening protocol to investigate the functions of microexons in zebrafish neurodevelopment. Microexons have gained prominence recently due to their enriched expression in neural tissues and misregulation in autism spectrum disease. However, screening of microexon functionality has thus far been limited in scope. The authors address this lack of knowledge by establishing zebrafish microexon CRISPR deletion lines for 45 microexons chosen in genes likely to play a role in CNS development. Using their high throughput protocol to test larval behaviour, brain activity, and brain structure, a modest group of 9 deletion lines was revealed to have neurodevelopmental functions, including 2 previously known to be functionally important.

Strengths:

(1) This work advances the state of knowledge in the microexon field and represents a starting point for future detailed investigations of the function of 7 microexons.

(2) The phenotypic analysis using high-throughput approaches is sound and provides invaluable data.

Weaknesses:

(1) There is not enough information on the exact nature of the deletion for each microexon.

(2) Only one deletion is phenotypically analysed, leaving space for the phenotype observed to be due to sequence modifications independent of the microexon itself.

Reviewer #2 (Public review):

Summary:

Li et al. investigated the potential anti-ageing role of 17α-Estradiol on the hypothalamus of aged rats. To achieve this, they employed a very sophisticated method for single-cell genomic analysis that allowed them to analyze effects on various groups of neurons and non-neuronal cells. They were able to sub-categorize neurons according to their capacity to produce specific neurotransmitters, receptors, or hormones. They found that 17α-Estradiol treatment led to an improvement in several factors related to metabolism and synaptic transmission by bringing the expression levels of many of the genes of these pathways closer or to the same levels to those of young rats, reversing the ageing effect. Interestingly, among all neuronal groups, the proportion of Oxytocin-expressing neurons seems to be the one most significantly changing after treatment with 17α-Estradiol, suggesting an important role of these neurons on mediating its anti-ageing effects. This was also supported by an increase in circulating levels of oxytocin. It was also found that gene expression of corticotropin-releasing hormone neurons was significantly impacted by 17α-Estradiol even though it was not different between aged and young rats, suggesting that these neurons could be responsible for side effects related to this treatment. This article revealed some potential targets that should be further investigated in future studies regarding the role of 17α-Estradiol treatment in aged males.

Strengths:

• The single nucleus mRNA sequencing is a very powerful method for gene expression analysis and clustering. The supervised clustering of neurons was very helpful in revealing otherwise invisible differences between neuronal groups and helped identify specific neuronal populations as targets.<br /> • There is a variety of functions used that allowed the differential analysis of a very complex type of data. This led to a better comparison between the different groups in many levels.<br /> • There were some physiological parameters measured such as circulating hormone levels that helped the interpretation of the effects of the changes in hypothalamic gene expression.

Weaknesses:

• One main control group is missing from the study, the young males treated with 17α-Estradiol.<br /> • Even though the technical approach is a sophisticated one, analyzing the whole rat hypothalamus instead of specific nuclei or subregions makes the study weaker.<br /> • Although the authors claim to have several findings, the data fail to support these claims.<br /> • The study is about improving ageing but no physiological data from the study demonstrated such claim with the exception of the testes histology which was not properly analyzed and was not even significantly different between the groups.<br /> • Overall, the study remains descriptive with no physiological data to demonstrate that any of the effects on hypothalamic gene expression is related to metabolic, synaptic or other function.

Comments on revisions:

The authors revised part of the manuscript to address some of the reviewers' comments This improved the language and the text flow to a certain extent. They also added an additional analysis including glial cells. However, they failed to address the main weaknesses brought up by the reviewers and did not add any experimental demonstration of their claims on lifespan expansion induced by 17α-estradiol in rats. In addition, they insisted i keeping parts in the discussion that are not directly linked to any of the papers' findings.

Reviewer #2 (Public review):

In this study, the authors sought to elucidate the neural mechanisms underlying the role of Naa10 in neurodevelopmental disruptions with a focus on its role in the hippocampus. The authors use an impressive array of techniques to identify a chain of events that occurs in the signaling pathway starting from Naa10 acetylating Btbd3 to regulation of F-actin dynamics that are fundamental to neurite outgrowth. They provide convincing evidence that Naa10 acetylates Btbd3, that Btbd3 facilitates CapZb binding to F-actin in a Naa10 acetylation-dependent manner, and that this CapZb binding to F-actin is key to neurite outgrowth. Besides establishing this signaling pathway, the authors contribute novel lists of Naa10 and Btbd3 interacting partners, which will be useful for future investigations into other mechanisms of action of Naa10 or Btbd3 through alternative cell signaling pathways. The evidence presented for an anxiety-like behavioral phenotype as a result of Naa10 dysfunction is mixed and tenuous, and assays for the primary behaviors known to be altered by Naa10 mutations in humans were not tested. As such, behavioral findings and their translational implications should be interpreted with caution. Finally, while not central to the main cell signaling pathway delineated, the characterization of brain region-specific and cell maturity of Naa10 expression patterns was presented in few to single animals and not quantified, and as such should also be interpreted with caution. On a broader level, these findings have implications for neurodevelopment and potentially, although not tested here, synaptic plasticity in adulthood, which means this novel pathway may be fundamental for brain health.

Summarized list of minor concerns

(1) The early claims of the manuscript are supported by very small sample sizes (often 1-3) and/or lack of quantification, particularly in Figures S1 and 1.

(2) Evidence is insufficient for CA1-specific knockdown of Naa10.

(3) The relationship between the behaviors measured, which centered around mood, and Ogden syndrome, was not clear, and likely other behavioral measures would be more translationally relevant for this study. Furthermore, the evidence for an anxiety-like phenotype was mixed.

(4) Btbd3 is characterized by the authors as an OCD risk gene, but its status as such is not well supported by the most recent, better-powered genome-wide association studies than the one that originally implicated Btbd3. However, there is evidence that Btbd3 expression, including selectively in the hippocampus, is implicated in OCD-relevant behaviors in mice.

(5) The reporting of the statistics lacks sufficient detail for the reader to deduce how experimental replicates were defined.

Reviewer #2 (Public review):

Bisht et al detail a novel interaction between the chaperone, Prefoldin 5, microtubules, and tau-mediated neurodegeneration, with potential relevance for Alzheimer's disease and other tauopathies. Using Drosophila, the study shows that Pfdn5 is a microtubule-associated protein, which regulates tubulin monomer levels and can stabilize microtubule filaments in the axons of peripheral nerves. The work further suggests that Pfdn5/6 may antagonize Tau aggregation and neurotoxicity. While the overall findings may be of interest to those investigating the axonal and synaptic cytoskeleton, the detailed mechanisms for the observed phenotypes remain unresolved and the translational relevance for tauopathy pathogenesis is yet to be established. Further, a number of key controls and important experiments are missing that are needed to fully interpret the findings.

The strength of this study is the data showing that Pfdn5 localizes to axonal microtubules and the loss-of-function phenotypic analysis revealing disrupted synaptic bouton morphology. The major weakness relates to the experiments and claims of interactions with Tau-mediated neurodegeneration. In particular, it is unclear whether knockdown of Pfdn5 may cause eye phenotypes independent of Tau. Further, the GMR>tau phenotype appears to have been incorrectly utilized to examine age-dependent, neurodegeneration.

This manuscript argues that its findings may be relevant to thinking about mechanisms and therapies applicable to tauopathies; however, this is premature given that many questions remain about the interactions from Drosophila, the detailed mechanisms remain unresolved, and absent evidence that tau and Pfdn may similarly interact in the mammalian neuronal context. Therefore, this work would be strongly enhanced by experiments in human or murine neuronal culture or supportive evidence from analyses of human data.

Reviewer #2 (Public review):

Summary:

This work addresses an important question of chromosome architecture changes associated with organotopic metastatic traits, showing important trends in genome reorganization. The most important observation is that 3D genome changes consistent with adaptations for new microenvironments, including lung metastatic breast cells exhibiting signatures of the genome architecture typical to a lung cell-like conformation and brain metastatic prostate cancer cells showing compartment shifts toward a brain-like state.

Strengths:

This work presents interesting original results, which will be important for future studies and biomedical implications of epigenetic regulation in norm and pathology.

Weaknesses:

The authors used publicly available data for 15 cell types. They should show how many different sources the data were obtained from and demonstrate that obtained results are consistent if the data from different sources were used.

Reviewer #2 (Public review):

Summary:

This study by Dorn et al. from Dr. Henrike Scholz's group investigates the function of serotonin signaling in state-dependent feeding control for protein and sugar intake. Using a dominant-negative serotonin transporter to block serotonin reuptake and optogenetics to activate serotoninergic neurons, the authors identified that serotonin released from a small group of Sert3-expressing neurons specifically reduces sucrose consumption of the fed files but not in the starved flies. Conversely, blocking serotonin reuptake in broad serotonergic neurons increases yeast consumption only in starved flies but does not affect fed flies. These results suggest prolonged serotonin signals may suppress sucrose appetite in fed flies while promoting protein intake in starved flies.

Although the phenotypes presented are intriguing and fundamental to animal fitness, the data in its current form is insufficient to support the proposed mechanisms underlying the state-dependent diet control by serotonin signals. Specifically, the authors should carefully analyze the requirement of serotonin by showing the efficiency of the serotonin reuptake blockade caused by the dominant-negative serotonin and validating the requirement of serotonin in the optogenetic activation of Sert3-expressing neurons. Additionally, the conclusions based on the overexpressed Sert3::gfp transgene should be retrieved as the overexpression affects sucrose consumption. Therefore, I recommend some alternative interpretations and approaches below for authors to verify the current form of conclusions.

Strengths:

The authors identified the state-dependent diet control for sucrose and yeast intake regulated by a restricted population of serotonin neurons expressing Sert3.

Weaknesses:

The data only partially supports most conclusions. Specifically, findings based on the use of the transgene Sert3::GFP lack sufficient rigor, as the authors overlooked potential overexpression effects.

Major issues

(1) The authors try to distinguish the motivation to feed on sucrose or protein in fed or starved conditions using "sucrose appetite" and "protein hunger", respectively. However, appetite and hunger should be synonymous in the current context. When specifying protein hunger, readers will expect the craving for protein in the protein-deprived situation. In the current study, starved flies were prepared by starvation on wet tissues so the flies are supposed to be hungry for sugar and protein. To avoid confusion, "sucrose appetite in fed flies" and "protein appetite in starved flies" are better descriptions.

(2) In Figure 1A-1I (lines 141-142), it remains unclear whether additional serotonergic neurons are required or if the serotonergic neurons labeled exclusively by R50H05-Gal4 and Tph-Gal4 are necessary to regulate yeast consumption in starved flies. The overlapping expressions of these two drivers with the Sert3-Gal4 make it hard to distinguish these two possibilities.

(3) The data in Figure 1L-1M suggests that the serotonin-dependent regulation in yeast consumption of starved flies is suppressed by sucrose supplementation. However, the neurons required for yeast consumption remain undefined due to the overlapping expression. This result implies that the neurons labeled by R50H05-Gal4 and Tph-Gal4 influence both sucrose and yeast consumption but not specific to yeast.

(4) The regulatory relationship between insulin receptors and serotonin signaling in sucrose appetite remains unclear. How do the authors interpret the result that both the constitutively active and dominant-negative forms of the insulin receptor (InR) reduce sucrose appetite in Figure 4? One possibility is that insulin receptors are involved in two parallel pathways to regulate sucrose consumption that converge to the same phenotype. However, the insulin receptor (InR) pathways can still be independent of the serotonin signaling pathway despite showing a comparable reduction of sucrose consumption in fed flies. This issue should be discussed further following lines 229-231.

(5) The quantification of Figure 5 should be revised. First, as the transgene Sert3::GFP affects sucrose consumption, quantifying the transgene signals may not explain its endogenous function. Second, the quantification lacks a Gal4 expression control using an untagged fluorescent marker, preferably a different color so that the authors can quantify it in the same individual as the comparison. Lastly, it is hard to be convinced that the distance between two layers represents the broad expression of Sert3::GFP in response to insulin receptor alterations. Quantifying the area size of each layer with fixed imaging conditions such as the intervals of brain sections and the laser intensity may be a better alternative approach.

(6) The conclusions drawn based on the Sert3::GFP transgene failed to explain the endogenous function of the serotonin transporter Sert3 in regulating sucrose consumption. Expressing the constitutive-active form of the insulin receptor in Sert3-expressing neurons reduces the total sucrose consumption of fed flies in Figure 4A, which appears inconsistent with the fly line with an additional Sert3::GFP expression shown in Figures 6F, where the suppression of sucrose consumption is not shown for the normalized sucrose intake. This inconsistency suggests that Sert3::GFP transgene itself affects sucrose consumption.

(7) In lines 324-326, the authors should investigate whether IR60b neurons are indeed the downstream of serotoninergic neurons SE1 to regulate sucrose consumption in fed flies. First, synaptic connections could be confirmed by additional approaches. Following this, the authors could demonstrate that the knockdown of serotonin receptors in IR60b neurons eliminates the suppression in sucrose consumption induced by the activation of Sert3-expressing neurons or by the expression of the dominant-negative serotonin transporter in fed flies.

Reviewer #2 (Public review):

Summary:

This manuscript reports high-resolution functional MRI data and MEG data revealing additional mechanistic information about an established paradigm studying how foveal regions of the primary visual cortex (V1) are involved in processing peripheral visual stimuli. Because of the retinotopic organization of V1, peripheral stimuli should not evoke responses in the regions of V1 that represent stimuli in the center of the visual field (the fovea). However, functional MRI responses in foveal regions do reflect the characteristics of peripheral visual stimuli - this is a surprising finding first reported in 2008. The present study uses fMRI data with sub-millimeter resolution to study how responses at different depths in the foveal gray matter do or don't reflect peripheral object characteristics during 2 different tasks: one in which observers needed to make detailed judgments about object identity, and one in which observers needed to make more coarse judgments about object orientation. FMRI results reveal interesting and informative patterns in these two conditions. A follow-on MEG study yields information about the timing of these responses. Put together, the findings settle some questions in the field and add new information about the nature of visual feedback to V1.

Strengths:

(1) Rigorous and appropriate use of "laminar fMRI" techniques.

(2) The introduction does an excellent job of contextualizing the work.

(3) Control experiments and analyses are designed and implemented well

Weaknesses:

(1) While not necessarily a weakness, I do not fully agree with the description of the 2 kinds of feedback information as "low-order" and "high-order". I understand the motivation to do this - orientation is typically considered a low-level visual feature. But when it's the orientation of an entire object, not a single edge, orientation can only be defined after the elements of the object are grouped. Also, the discrimination between spikies and smoothies requires detecting the orientations of particular edges that form the identifying features. To my mind, it would make more sense to refer to discrimination of object orientation as "coarse" feature discrimination, and orientation of object identity as "fine" feature discrimination. Thus, the sentence on line 83, for example, would read "Interestingly, feedback with fine and coarse feature information exhibits different laminar profiles.".

(2) Figure 2 and text on lines 185, and 186: it is difficult to interpret/understand the findings in foveal ROIs for the foveal control task without knowing how big the ROI was. Foveal regions of V1 are grossly expanded by cortical magnification, such that the central half-degree can occupy several centimeters across the cortical surface. Without information on the spatial extent of the foveal ROI compared to the object size, we can't know whether the ROI included voxels whose population receptive fields were expected to include the edges of the objects.

(3) Line 143 and ROI section of the methods: in order for the reader to understand how robust the responses and analyses are, voxel counts should be provided for the ROIs that were defined, as well as for the number (fraction) of voxels excluded due to either high beta weights or low signal intensity (lines 505-511).

(4) I wasn't able to find mention of how multiple-comparisons corrections were performed for either the MEG or fMRI data (except for one Holm-Bonferonni correction in Figure S1), so it's unclear whether the reported p-values are corrected.

Reviewer #2 (Public review):

Summary:

This manuscript examined the impact of sulcal morphology on reading development. A very specific feature on the ventral surface of the brain was identified, namely the presence of an interruption in the posterior portion of the left occipitotemporal sulcus (pOTS). Compared to children with a continuous pOTS, children with an interruption at age 5 years had better reading ability at age 8. This was a large effect measured in 43 children. Surprisingly, this morphological feature was a better predictor of reading ability than measures of pre-literacy cognitive skills, such as phonological awareness. The effect was tested and reproduced across several different measures of reading ability. The authors hypothesised that the mechanism underlying this benefit related to greater local connectivity, which confers a computational advantage. This was demonstrated using analysis of diffusion-weighted imaging data in 29 of the children obtained at age 8.

Strengths:

The novelty of the manuscript is threefold: (i) the measure was made in children who were pre-literate (previous work was in older children and adults); (ii) longitudinal brain imaging and behavioural data were analysed; and (iii) diffusion data were analysed to test a hypothesis about the underlying mechanism.

The manuscript is exceptionally well written. The methods are detailed and easily reproduced. The approach is thoughtful and meticulous. All possible alternatives appear to have been considered. Where possible, further analyses have been done to address these alternatives. For example, the testing of the specificity of the sulcal interruption to left pOTS was an important addition. None predicted reading skills.

Weaknesses:

The correlation of the interruption with all kinds of literacy measures and in particular reading comprehension and then PIQ suggest this interruption might confer a more general cognitive advantage rather than specifically a reading one.

It would be interesting to know if the anatomical difference predicts any other cognitive ability or if there might be any cognitive cost (a negative correlation) of this sulcal interruption.<br /> The location of the interruption in the sulcus is quite variable and in some cases, there is more than one interruption. The sample size is probably not big enough to compare these different patterns or to evaluate the influence of the location of the sulcal interruption.

The sample is quite high-functioning and the generalisability of the findings outside of this specific population is inevitably limited.

for - key insight - leverage point of the 99% - our numbers - from Substack article - The Cosmo-Local Plan for our Next Civilization - Michel Bauwens - 2024, Dec 20 - key insight - 6 levels of individual / collective gestalt - from Substack article - The Cosmo-Local Plan for our Next Civilization - Michel Bauwens - 2024, Dec 20

key insight - 6 embedded levels of individual / collective gestalt, - first level is from individual quanta to collective atoms - second level is from individual atom to collective molecules - third is from individual molecule too collective living cells - fourth is from individual living cells too collective multicellular living organism - fifth is from individual multi-cellular organism to collective culture at local level - sixth is from individual local culture to to collective trans-national alliances - At each level except the first, a perspective shift occursc in which the collective is seen from a different lens as an individual

key insight - leverage point of the 99% - our numbers - The trans-national companies power is in their capital - The trans-national alliances leverage point is our large numbers of people - Through our strength in numbers, we can mobilize trans-alliance resources such as human innovation resources, which most local actors are lacking in

for - similar to - - Daniel Kahnaman's system 1 fast, instinctive, emotional and system 2 slow, deliberative, logical is similar to - Ian McGilhirist's left brain, right brain

for - potential BEing journey - Dzogchen - alternating between 2 related sense fields - from Medium article - Heart Sutra and the nyams of Dzogchen - Aleander Vezhnevets - 2022, Sept 7

Reviewer #3 (Public review):

This paper addresses a long-standing problem in microbiology: the evolution of bacterial cell shape. Bacterial cells can take a range of forms, among the most common being rods and spheres. The consensus view is that rods are the ancestral form and spheres the derived form. The molecular machinery governing these different shapes is fairly well understood but the evolutionary drivers responsible for the transition between rods and spheres is not. Enter Yulo et al.'s work. The authors start by noting that deletion of a highly conserved gene called MreB in the Gram-negative bacterium Pseudomonas fluorescens reduces fitness but does not kill the cell (as happens in other species like E. coli and B. subtilis) and causes cells to become spherical rather than their normal rod shape. They then ask whether evolution for 1000 generations restores the rod shape of these cells when propagated in a rich, benign medium.

The answer is no. The evolved lineages recovered fitness by the end of the experiment, growing just as well as the unevolved rod-shaped ancestor, but remained spherical. The authors provide an impressively detailed investigation of the genetic and molecular changes that evolved. Their leading results are:

(1) the loss of fitness associated with MreB deletion causes high variation in cell volume among sibling cells after cell division;<br /> (2) fitness recovery is largely driven by a single, loss-of-function point mutation that evolves within the first ~250 generations that reduces the variability in cell volume among siblings;<br /> (3) the main route to restoring fitness and reducing variability involves loss of function mutations causing a reduction of TPase and peptidoglycan cross-linking, leading to a disorganized cell wall architecture characteristic of spherical cells.

The inferences made in this paper are on the whole well supported by the data. The authors provide a uniquely comprehensive account of how a key genetic change leads to gains in fitness and the spectrum of phenotypes that are impacted and provide insight into the molecular mechanisms underlying models of cell shape.

Suggested improvements and clarifications include:<br /> (1) A schematic of the molecular interactions governing cell wall formation could be useful in the introduction to help orient readers less familiar with the current state of knowledge and key molecular players;<br /> (2) It remains unclear whether corrections for multiple comparisons are needed when more than one construct or strain is compared to the common ancestor, as in Supp Fig 19A (relative PG density of different constructs versus the SBW25 ancestor). The author's response did not clarify matters: was data for the WT obtained independently alongside each each strain/construct (justifying a paired t-test) or was a single set of data for the WT obtained and used to compare against all other strains/constructs (which would demand a correction for multiple comparisons)?<br /> (3) The authors refrain from making strong claims about the nature of selection on cell shape, perhaps because their main interest is the molecular mechanisms responsible. They identify sources of stabilizing selection favouring an intermediate cell size (lack of DNA in small cells and disorganized DNA in large cells). Their interpretation of stabilizing selection in the review is correct and entirely consistent with the mechanistic causes identified here. I think this is valuable and interesting, although I recognize it is not the focus of the paper.

Comments on revisions:

Please further clarify the experimental design and replication for the contrast between mutants and WT to address the issue of multiple comparisons.

Reviewer #2 (Public review):

Summary:

This study evaluated the aperiodic component in the medial prefrontal cortex (mPFC) using resting-state EEG recordings from 149 individuals with chronic pain and 115 healthy participants. The findings showed no significant differences in the aperiodic component of the mPFC between the two groups, nor was there any correlation between the aperiodic component and pain intensity. These results were consistent across various chronic pain subtypes and were corroborated by whole-brain analyses. The study's robustness was further reinforced by preregistration and multiverse analyses, which accounted for a wide range of methodological choices.

Strengths:

This study was rigorously conducted, yielding clear and conclusive results. Furthermore, it adhered to stringent open and reproducible science practices, including preregistration, blinded data analysis, and Bayesian hypothesis testing. All data and code have been made openly available, underscoring the study's commitment to transparency and reproducibility.

Weaknesses:

The aperiodic exponent of the EEG power spectrum is often regarded as an indicator of the excitatory/inhibitory (E/I) balance. However, this measure may not be the most accurate or optimal for quantifying E/I balance, a limitation that the authors might consider addressing in the future.

Comments on revisions:

All my comments have been well addressed.

Reviewer #2 (Public review):

Summary:

Bloch et al. studied the relationships between aerial foragers (lesser swifts) tracked using an automated radio telemetry system (Atlas) and their prey (flying insects) monitored using a small vertical-looking radar (BirdScan MR1). The aim of the study was to check whether swifts optimise their foraging according to the abundance of their prey. The results provide evidence that small swifts can increase their foraging rate when aerial insect abundance is high, but found no correlation between insect abundance and flight energy expenditure.

Key points:

This study fills gaps in fundamental knowledge of prey-predator dynamics in the air. It describes the coincidence between the abundance of flying insects and the characteristics derived from monitoring individual swifts.

Weaknesses:

The paper uses assumptions largely derived from optimal foraging theory, but mixes up the form of natural selection: parental energy, parental survival (predation risk), nestling foraging and reproductive success. The results are partly inconsistent, and confounding factors (e.g., the brooding phase versus the nestling phase) remained ignored. In conclusion, the analyses performed are insufficient to rigorously assess whether lesser swifts are optimising their foraging beyond making shorter foraging trips.<br /> The filters applied to the monitoring data are necessary but may strongly influence the characteristics derived based on maximum or mean values. Sensitivity tests or the use of characteristics that are less dependent on extreme values could provide more robust results.

Reviewer #2 (Public review):

Summary:

This theoretical paper examines genetic drift in scenarios deviating from the standard Wright-Fisher model. The authors discuss Haldane's branching process model, highlighting that the variance in reproductive success equates to genetic drift. By integrating the Wright-Fisher model with the Haldane model, the authors derive theoretical results that resolve paradoxes related to effective population size.

Strengths:

The most significant and compelling result from this paper is perhaps that the probability of fixing a new beneficial mutation is 2s/V(K). This is an intriguing and potentially generalizable discovery that could be applied to many different study systems.

The authors also made a lot of effort to connect theory with various real-world examples, such as genetic diversity in sex chromosomes and reproductive variance across different species.

Comments on revisions:

The author has addressed some of the concerns in my review, and I think the revised manuscript is more clear. I like the discussion about the caveats of the WFH model.

I hope the authors could also discuss the conditions needed for V(K)/Ne to be a reasonable approximation. It is currently unclear how the framework should be adopted in general.

The idea about estimating male-female V(K) ratios from population genetic data is interesting. Unfortunately, the results fell short. The accuracy of their estimators (derived using approximation Ne/V(K) approximation, and certain choice of theta, and then theta estimated with Watterson's estimator) should be tested with simulated results before applying to real data. The reliability of their estimator and their results from real data are unclear.

Arguments made in this paper sometimes lack precision (perhaps the authors want to emphasize intuition, but it seems more confusing than otherwise). For example: The authors stated that "This independence from N seems intuitively obvious: when an advantageous mutation increases to say, 100 copies in determining a population (depending mainly on s), its fixation would be almost certain, regardless of N.". Assuming large Ne, and with approximation, one could assume the probability of loss is e^(-2sn), but the writing about "100 copies" and "almost certain" is very imprecise, in fact, a mutation with s=0.001 segregating at 100 copies in a large Ne population is most probably lost. Whereas in a small population, it will be fixed. Yet the following sentence states "regardless of N. This may be a most direct argument against equating genetic drift, certainly no less important than 1/ N . with N, or Ne (which is supposed to be a function of N's)." I find this new paragraph misleading.

Some of the statements/wordings in this paper still seem too strong to me.

Reviewer #2 (Public review):

Summary:

In this paper, Lin and colleagues aim to understand the role of different salts on the phase behavior of a model protein of significant biological interest, Caprin1, and its phosphorylated variant, pY-Caprin1. To achieve this, the authors employed a variety of methods to complement experimental studies and obtain a molecular-level understanding of ion partitioning inside biomolecular condensates. A simple theory based on rG-RPA is shown to capture the different salt dependencies of Caprin1 and pY-Caprin1 phase separation, demonstrating excellent agreement with experimental results. The application of this theory to multivalent ions reveals many interesting features with the help of multicomponent phase diagrams. Additionally, the use of CG model-based MD simulations and FTS provides further clarity on how counterions can stabilize condensed phases.

Strengths:

The greatest strength of this study lies in the integration of various methods to obtain complementary information on thermodynamic phase diagrams and the molecular details of the phase separation process. The authors have also extended their previously proposed theoretical approaches, which should be of significant interest to other researchers. Some of the findings reported in this paper, such as bridging interactions, are likely to inspire new studies using higher-resolution atomistic MD simulations.

Reviewer #2 (Public review):

Summary:

This is a well written manuscript describing studies directed at identifying the cell type responsible for pacemaking in murine collecting lymphatics. Using state-of-the-art approaches, the authors identified a number of different cell types in the wall of these lymphatics and then using targeted expression of Channel Rhodopsin and GCaMP, the authors convincingly demonstrate that only activation of lymphatic muscle cells produces coordinated lymphatic contraction and that only lymphatic muscle cells display pressure-dependent Ca2+ transients as would be expected of a pacemaker in these lymphatics.

Strengths:

The use of targeted expression of channel rhodopsin and GCaMP to test the hypothesis that lymphatic muscle cells serve as the pacemakers in musing lymphatic collecting vessels.

Weaknesses:

The only significant weakness was the lack of quantitative analysis of most of the imaging data shown in Figures 1-11. In particular, the colonization analysis should be extended to show cells not expected to demonstrate colocalization as a negative control for the colocalization analysis that the authors present. These weaknesses have been resolved by revision and addition of new and novel RNAseq data, additional colocalization data and membrane potential measurements.

Reviewer #2 (Public Review):

Summary:

In this work, the authors combine diffusion MRI and high-resolution x-ray synchrotron phase-contrast imaging in monkey and mouse brains to investigate the 3D organization of brain white matter across different scales and species. The work is at the forefront of the anatomical investigation of the human connectome and aligns with several current efforts to bridge the resolution gap between what we can see in vivo at the millimeter scale and the complexity of the human brain at the sub-micron scale. The authors compare the 3D white matter organization across modalities within 2 small regions in one monkey brain (body of the corpus callosum, centrum semiovale) and within one region (splenium of the corpus callosum) in healthy mice and in one murine model of focal demyelination. The study compares measures of tissue anisotropy and fiber orientations across modalities, performs a qualitative comparison of fasciculi trajectories across brain regions and tissue conditions using streamlined tractography based on the structure tensor, and attempts to quantify the shape of fasciculi trajectories by measuring the tortuosity index and the maximum deviation for each reconstructed streamline. Results show measures of anisotropy and fiber orientations largely agree across modalities, especially for larger FOV data. The high-resolution data allows us to explore the fiber trajectories in relation to tissue complexity and pathology. The authors claim the study reveals new common organization principles of white matter fibers across species and scales, for which axonal fasciculi arrange into sheet-like laminar structures.

Strengths:

The aim of the study is of central importance within present efforts to bridge the gap between macroscopic structures observable in vivo in humans using conventional diffusion MRI and the microscopic organization of white matter tissue. Results obtained from this type of study are important to interpret data obtained in vivo, inform the development of novel methodologies, and expand our knowledge of the structural and thus functional organization of brain circuits.

Multi-scale data acquired across modalities within the same sample constitute extremely valuable data that is often hard to acquire and represent a precious resource for validation of both diffusion MRI tractography and microstructure methods.

The inclusion of multi-species data adds value to the study, allowing the exploration of common organization principles across species.

The addition of data from a murine cuprizone model of focal demyelination adds interesting opportunities to study the underlying biological changes that follow demyelination and how these impact tissue anisotropy and fiber trajectories. These data can inform the interpretation and development of diffusion MRI microstructure models.

[Editors' note: The Reviewing Editor considers that the authors addressed the reviewers' questions adequately. The original reviews are here: https://elifesciences.org/reviewed-preprints/94917/reviews]

Reviewer #2 (Public review):

Summary:

Here the authors address the idea that postural and movement control are differentially impacted with stroke. Specifically, they examined whether resting postural forces influenced several metrics of sensorimotor control (e.g., initial reach angle, maximum lateral hand deviation following a perturbation, etc.) during movement or posture. The authors found that resting postural forces influenced control only following the posture perturbation for the paretic arm of stroke patients, but not during movement. They also found that resting postural forces were greater when the arm was unsupported, which correlated with abnormal synergies (as assessed by the Fugl-Meyer). The authors suggest that these findings can be explained by the idea that the neural circuitry associated with posture is relatively more impacted by stroke than the neural circuitry associated with movement. They also propose a conceptual model that differentially weights the reticulospinal tract (RST) and corticospinal tract (CST) to explain greater relative impairments with posture control relative to movement control, due to abnormal synergies, in those with stroke.

Comments on revisions:

The authors should be commended for being very responsive to comments and providing several further requested analyses, which have improved the paper. However, there is still some outstanding issues that make it difficult to fully support the provided interpretation.

The authors say within the response, "We would also like to stress that these perturbations were not designed so that responses are directly compared to each other ***(though of course there is an *indirect* comparison in the sense that we show influence of biases in one type of perturbation but not the other)***." They then state in the first paragraph of the discussion that "Remarkably, these resting postural force biases did not seem to have a detectable effect upon any component of active reaching but only emerged during the control of holding still after the movement ended. The results suggest a dissociation between the control of movement and posture." The main issue here is relying on indirect comparisons (i.e., significant in one situation but not the other), instead of relying on direct comparisons. Using well-known example, just because one group / condition might display a significant linear relationship (i.e., slope_1 > 0) and another group / condition does not (slope_2 = 0), does not necessarily mean that the two groups / conditions are statistically different from one another [see Figure 1 in Makin, T. R., & Orban de Xivry, J. J. (2019). Ten common statistical mistakes to watch out for when writing or reviewing a manuscript. eLife, 8, e48175.].

The authors have provided reasonable rationale of why they chose certain perturbation waveforms for different. Yet it still holds that these different waveforms would likely yield very different muscular responses making it difficult to interpret the results and this remains a limitation. From the paper it is unknown how these different perturbations would differentially influence a variety of classic neuromuscular responses, including short-range stiffness and stretch reflexes, which would be at play here.

Much of the results can be interpreted when one considers classic neuromuscular physiology. In Experiment 1, differences in resting postural bias in supported versus unsupported conditions can readily be explained since there is greater muscle activity in the unsupported condition that leads to greater muscle stiffness to resist mechanical perturbations (Rack, P. M., & Westbury, D. R. (1974). The short-range stiffness of active mammalian muscle and its effect on mechanical properties. The Journal of physiology, 240(2), 331-350.). Likewise muscle stiffness would scale with changes in muscle contraction with synergies. Importantly for experiment 2, muscle stiffness is reduced during movement (Rack and Westbury, 1974) which may explain why resting postural biases do not seem to be impacting movement. Likewise, muscle spindle activity is shown to scale with extrafusal muscle fiber activity and forces acting through the tendon (Blum, K. P., Campbell, K. S., Horslen, B. C., Nardelli, P., Housley, S. N., Cope, T. C., & Ting, L. H. (2020). Diverse and complex muscle spindle afferent firing properties emerge from multiscale muscle mechanics. eLife, 9, e55177.). The concern here is that the authors have not sufficiently considered muscle neurophysiology, how that might relate to their findings, and how that might impact their interpretation. Given the differences in perturbations and muscle states at different phases, the concern is that it is not possible to disentangle whether the results are due to classic neurophysiology, the hypothesis they propose, or both. Can the authors please comment.

The authors should provide a limitations paragraph. They should address 1) how they used different perturbation force profiles, 2) the muscles were in different states which would change neuromuscular responses between trial phase / condition, 3) discuss a lack of direct statistical comparisons that support their hypothesis, and 4) provide a couple of paragraphs on classic neurophysiology, such as muscle stiffness and stretch reflexes, and how these various factors could influence the findings (i.e., whether they can disentangle whether the reported results are due to classic neurophysiology, the hypothesis they propose, or both).

Reviewer #2 (Public review):

Summary:

The paper describes an effort to identify the factors responsible for intron retention and alternate exon splicing in a complex system known to be regulated by the O-GlcNAc cycling system. The CRISPR/Cas9 system was used to identify potential factors. The bioinformatic analysis is sophisticated and compelling. The conclusions are of general interest and advance the field significantly.

Strengths:

(1) Exhaustive analysis of potential splicing factors in an unbiased screen.

(2) Extensive genome wide bioinformatic analysis.

(3) Thoughtful discussion and literature survey.

Weaknesses:

(1) No firm evidence linking SFSWA to an O-GlcNAc specific mechanism.

(2) Resulting model leaves many unanswered questions.

Reviewer #2 (Public review):

Summary:

The authors generated three mouse lines harboring ASD, Schizophrenia, and Bipolar-associated variants in the TRIO gene. Anatomical, behavioral, physiological, and biochemical assays were deployed to compare and contrast the impact of these mutations in these animals. In this undertaking, the authors sought to identify and characterize the cellular and molecular mechanisms responsible for ASD, Schizophrenia, and Bipolar disorder development.

Strengths:

The establishment of TRIO dysfunction in the development of ASD, Schizophrenia, and Bipolar disorder is very recent and of great interest. Disorder-specific variants have been identified in the TRIO gene, and this study is the first to compare and contrast the impact of these variants in vivo in preclinical models. The impact of these mutations was carefully examined using an impressive host of methods. The authors achieved their goal of identifying behavioral, physiological, and molecular alterations that are disorder/variant specific. The impact of this work is extremely high given the growing appreciation of TRIO dysfunction in a large number of brain-related disorders. This work is very interesting in that it begins to identify the unique and subtle ways brain function is altered in ASD, Schizophrenia, and Bipolar disorder.

Weaknesses:

(1) Most assays were performed in older animals and perhaps only capture alterations that result from homeostatic changes resulting from prodromal pathology that may look very different.

(2) Identification of upregulated (potentially compensating) genes in response to these disorder-specific Trio variants is extremely interesting. However, a functional demonstration of compensation is not provided.

(3) There are instances where data is not shown in the manuscript. See "data not shown". All data collected should be provided even if significant differences are not observed.

I consider weaknesses 1 and 2 minor. While they would very interesting to explore, these experiments might be more appropriate for a follow-up study. I would recommend that the missing data in 3 should be provided in the supplemental material.

Reviewer #2 (Public review):

Summary:<br /> The authors use a genetic screen in C. elegans to investigate the physiological roles of polyunsaturated fatty acids (PUFAs). They screen for mutations that rescue fat-2 mutants, which have strong reductions in PUFAs. As a result, either mutations in fat-2 itself, or mutations in genes involved in the HIF-1 pathway, were found to rescue fat-2 mutants.

Strengths:<br /> As C. elegans can produce PUFAs de novo as essential lipids, the genetic model is well suited to study the fundamental roles of PUFAs, and the results are very interesting. The genetic screen finds mutations in convergent pathways, suggesting that it has reached near-saturation. The link between the HIF-1 pathway and lipid unsaturation is very interesting. As many of the mutations found to rescue fat-2 mutants are of gain-of-function, it is unlikely that similar discoveries could have been made with other approaches like genome-wide CRISPR screenings, making the current study distinctive.

Weaknesses:<br /> The authors make very important statements, but some are not sufficiently supported by data. In page 5, they conclude that membrane rigidity is a minor cause of fat-2 mutant defects, which is a relevant observation regarding why PUFAs are important. However, they use treatments that have rescued fluidity in another mutant (paqr-2), but do not test if they have the same fluidifying effects in fat-2 mutants.

The screening results seem to converge into the HIF-1 pathway, which is hypothetically correct according to the literature. However, the authors do not validate this hypothesis, which is a critical limitation, especially because many of the mutations they obtained seem to be of gain-of-function. Therefore, without experimental testing, it cannot be concluded that the mutations have the expected effect on the HIF-1 pathway.

In some of the mutants, the rescues in lipid compositions seem to be weak, and it is arguable whether phenotypic rescues are really via a restoration in lipid compositions.

The hypothesis linking iron homeostasis and the rescue of fat-2 mutants is interesting, but the data of rescue by iron repletion seem to be against it. The results might be due to the inefficiency in iron repletion, as the authors suggest, but this has not been formally addressed.

Therefore, the authors propose multiple very interesting and important hypotheses, but experimental validations remain limited.

Reviewer #2 (Public review):

Summary:

In this work, the authors wish to explore the metabolic support mechanisms enabling lamellocyte encapsulation, a critical antiparasitic immune response of insects. They show that S-adenosylmethionine metabolism is specifically important in this process through a combination of measurements of metabolite levels and genetic manipulations of this metabolic process.

Strengths:

The metabolite measurements and the functional analyses are generally very strong and clearly show that the metabolic process under study is important in lamellocyte immune function.

Weaknesses:

The gene expression data are a potential weakness. Not enough is explained about how the RNAseq experiments in Figures 2 and 4 were done, and the representation of the data is unclear. The paper would also be strengthened by the inclusion of some measure of encapsulation effectiveness: the authors show that manipulation of the S-adenosylmethionine pathway in lamellocytes affects the ability of the host to survive infection, but they do not show direct effects on the ability of the host to encapsulate wasp eggs.

Reviewer #2 (Public review):

Summary:

In this study, the authors hypothesize that "causal inferences about illness depend on content-specific semantic representations in the animacy network". They test this hypothesis in an fMRI task, by comparing brain activity elicited by participants' exposure to written situations suggesting a plausible cause of illness with brain activity in linguistically equivalent situations suggesting a plausible cause of mechanical failure or damage and non-causal situations. These contrasts identify PC as the main "culprit" in a whole-brain univariate analysis. Then the question arises of whether the content-specificity has to do with inferences about animates in general, or if there are some distinctions between reasoning about people's bodies versus mental states. To answer this question, the authors localize the mentalizing network and study the relation between brain activity elicited by Illness-Causal > Mech-Causal and Mentalizing > Physical stories. They conclude that inferring about the causes of illness partially differentiates from reasoning about people's states of mind. The authors finally test the alternative yet non-mutually exclusive hypothesis that both types of causal inferences (illness and mechanical) depend on shared neural machinery. Good candidates are language and logic, which justifies the use of a language/logic localizer. No evidence of commonalities across causal inferences versus non-causal situations is found.

Strengths:

(1) This study introduces a useful paradigm and well-designed set of stimuli to test for implicit causal inferences.

(2) Another important methodological advance is the addition of physical stories to the original mentalizing protocol.

(3) With these tools, or a variant of these tools, this study has the potential to pave the way for further investigation of naïve biology and causal inference.

Weaknesses:

(1) This study is missing a big-picture question. It is not clear whether the authors investigate the neural correlates of causal reasoning or of naïve biology. If the former, the choice of an orthogonal task, making causal reasoning implicit, is questionable. If the latter, the choice of mechanical and physical controls can be seen as reductive and problematic.

(2) The rationale for focusing mostly on the precuneus is not clear and this choice could almost be seen as a post-hoc hypothesis.

(3) The choice of an orthogonal 'magic detection' task has three problematic consequences in this study:<br /> (a) It differs in nature from the 'mentalizing' task that consists of evaluating a character's beliefs explicitly from the corresponding story, which complicates the study of the relation between both tasks. While the authors do not compare both tasks directly, it is unclear to what extent this intrinsic difference between implicit versus explicit judgments of people's body versus mental states could influence the results.<br /> (b) The extent to which the failure to find shared neural machinery between both types of inferences (illness and mechanical) can be attributed to the implicit character of the task is not clear.<br /> (c) The introduction of a category of non-interest that contains only 36 trials compared to 38 trials for all four categories of interest creates a design imbalance.

(4) Another imbalance is present in the design of this study: the number of trials per category is not the same in each run of the main task. This imbalance does not seem to be accounted for in the 1st-level GLM and renders a bit problematic the subsequent use of MVPA.

(5) The main claim of the authors, encapsulated by the title of the present manuscript, is not tested directly. While the authors included in their protocol independent localizers for mentalizing, language, and logic, they did not include an independent localizer for "animacy". As such, they cannot provide a within-subject evaluation of their claim, which is entirely based on the presence of a partial overlap in PC (which is also involved in a wide range of tasks) with previous results on animacy.

Reviewer #2 (Public review):

I must note that my comments pertain to the evolutionary interpretations rather than the study's technical results. The techniques appear to be appropriately applied and interpreted, but I do not feel sufficiently qualified to assess this aspect of the work in detail.

I was repeatedly puzzled by the use of the term "function." Part of the issue may stem from slightly different interpretations of this word in different fields. In my understanding, "function" should denote not just what a structure does, but what it has been selected for. In this context, where it is unclear if cfChPs have been selected for in any way, the use of this term seems questionable.

Similarly, the term "predatory genome," used in the title and throughout the paper, appears ambiguous and unjustified. At this stage, I am unconvinced that cfChPs provide any evolutionary advantage to the genome. It is entirely possible that these structures have no function whatsoever and could simply be byproducts of other processes. The findings presented in this study do not rule out this neutral hypothesis. Alternatively, some particular components of the genome could be driving the process and may have been selected to do so. This brings us to the hypothesis that cfChPs could serve as vehicles for transposable elements. While speculative, this idea seems to be compatible with the study's findings and merits further exploration.

I also found some elements of the discussion unclear and speculative, particularly the final section on the evolution of mammals. If the intention is simply to highlight the evolutionary impact of horizontal transfer of transposable elements (e.g., as a source of new mutations), this should be explicitly stated. In any case, this part of the discussion requires further clarification and justification.

In summary, this study presents important new findings on the behavior of cfChPs when introduced into a foreign cellular context. However, it overextends its evolutionary interpretations, often in an unclear and speculative manner. The concept of the "predatory genome" should be better defined and justified or removed altogether. Conversely, the suggestion that cfChPs may function at the level of transposable elements (rather than the entire genome or organism) could be given more emphasis.

Reviewer #2 (Public review):

This article elucidates the biochemical and cellular mechanisms by which the FHOD-family of formins, particularly FHOD3, contributes to sarcomere formation and contractility in cardiomyocytes. Formins are mainly known to nucleate and elongate actin filaments, with certain family members also exhibiting capping, severing, and bundling activities. Although FHOD3 has been well-established as essential for sarcomere assembly in cardiomyocytes, its precise biochemical functions and contributions to actin dynamics remain poorly understood.

In this study, the authors combine in vitro biochemical assays with cellular experiments to dissect FHOD3's roles in actin assembly and sarcomere formation. They demonstrate that FHOD3 nucleates actin filaments and acts as a transient elongator, pausing elongation after an initial burst of filament growth. Using separation-of-function mutants, they show that FHOD3's elongation activity - rather than its nucleation, capping, or bundling capabilities - is key for its sarcomeric function.

The experiments have been conducted rigorously and well-analyzed, and the paper is clearly written. The data presented support the authors' conclusions. I appreciate the detailed description and rationale behind the FHOD3 constructs used in this study.

However, I was somewhat surprised and a bit disappointed that while the authors conducted single-color TIRF experiments to observe the effects of FHOD3 on single filaments, they did not use fluorescently labeled FHOD3 to directly visualize its behavior. Incorporating such experiments would significantly strengthen their conclusions regarding FHOD3's bursts of elongation interspersed with capping activity. While I understand this might require a few additional weeks of experiments, these data would add considerable value by directly testing the proposed mechanism.

There is a typo in the word "required" in line number 30. The authors also use fit data to extract parameters in several panels (e.g., Figures 2b, 2d, 3a, and 3b). While these fit functions may be intuitive to actin experts, explicitly describing the fit functions in the figure legends or methods would greatly benefit the broader readership.

Reviewer #2 (Public review):

Seguchi and Izawa provide robust evidence for the role of vasopressin in modulating same-sex affiliative relationships. Especially striking is that these effects appear to be selective to key relationships within a triadic social context. Overall, this is an interesting and rich dataset with compelling results. I largely have some clarifying questions.

Experiment 1 Comments:

(1) The primary argument/finding in this experiment is that a triadic situation/environment facilitates the development of male-male reciprocal social relationships. Overall, this effect appears striking in that male-male affiliative bonds (defined as reciprocal allopreening) formed in 6 of the 8 triads tested. However, there is no comparison group of dyads to determine whether co-housing for 2 weeks could also support the formation of male-male social bonds. This lack of a comparison group makes it unclear to what extent the triad is the key aspect of the environment that supports social bonding.

(2) More specifically, the authors argue that it is not just that triads support affiliative male-male bonds, but that bonds form between the second "middle" (dominant/subordinate) and third "low" (subordinate/subordinate) individuals in each triad. However, it was difficult to assess this from the results.<br /> a) For example, in Figure 3B is each data point the average of two individuals, since in each triad there are two dominant and two subordinate individuals?<br /> b) For me, using more precise language beyond dominant and subordinate (e.g. middle and low), and more clearly displaying the results of allopreening for each pairwise dyad within a triad would improve the impact of the results and support the authors' argument.

(3) Experiment 2 Comments:<br /> The results here are quite striking, despite the low sample size. In Figure 4, it appears that in every instance of administration V1aRA low and high administration decreased allopreening for both dominant and subordinate individuals.

(4) Some methodological questions:<br /> a) Can you clarify whether the duration of the post-test was also 30 min?<br /> b) As in Experiment 1, how are individual birds represented in the triad? Was the second "Middle" bird (dominant/subordinate) tested as both a dominant and subordinate bird? My understanding is that the dominant and subordinate birds in Figure 4 are different individuals but that they are the same individuals represented between the affiliated dyad and unaffiliated dyad.

(5) Throughout the manuscript (Lines 57-67; 557-566) the authors argue that the role of VP in regulating gregariousness can be extrapolated to understand the role of same-sex affiliative bonding. Importantly, gregariousness does not necessarily reflect affiliative bonding. While allopreening is specifically associated with social bonding (e.g. monogamous pair bonds) independent of broader social systems, gregariousness in general, and specifically as defined in many of the references cited, is independent of social bonds - in fact, it is assessed primarily in novel social contexts.

(6) To clarify, adult prairie voles in the wild do not engage in same-sex affiliative behavior commonly. In fact one of the primary components of opposite-sex pair bonding is same-sex aggression. Thus, while mechanistic studies on the neurobiology of same-sex peer bonds are relevant for this work, I am less convinced that you can make comparisons between the ultimate function of same-sex affiliative relationships in prairie voles.

(17) The results here are consistent with VP having an anxiolytic effect, as has been suggested in birds, with the consequences on social behaviors being directly or indirectly related. This may be a useful point to draw on in the discussion when considering your findings.

Reviewer #2 (Public review):

Summary:

This study examines a novel role of the Hpo signaling pathway, specifically of wts-1/LATS and the downstream regulator of gene expression, yap, in age-related neurodegeneration in C. elegans touch-responsive mechanosensory neurons, ALM and PLM. The study shows that knockdown or deletion of wts-1/LATS causes age-associated morphological abnormalities of these neurons, accompanied by functional loss of touch responsiveness. This is further associated with enhanced, abnormal, microtubule stabilization in these neurons.

Strengths:

This study examines a novel role of the Hpo signaling pathway, specifically of wts-1/LATS and the downstream regulator of gene expression, yap, in age-related neurodegeneration in C. elegans touch-responsive mechanosensory neurons, ALM and PLM. The study shows that knockdown or deletion of wts-1/LATS causes age-associated morphological abnormalities of these neurons, accompanied by functional loss of touch responsiveness. This is further associated with enhanced, abnormal, microtubule stabilization in these neurons. Strong pharmacological and especially genetic manipulations of MT-stabilizing or severing proteins show a strong genetic link between yap and regulation of MTs stability. The study is strong and uses robust approaches, especially strong genetics. The demonstrations on the aging-related roles of the Hpo signaling pathway, and the link to MTs, are novel and compelling. Nevertheless, the study also has mechanistic weaknesses (see below).

Weaknesses:

Specific comments:

(1) The study demonstrates age-specific roles of the Hpo pathway, specifically of wts-1/LATS and yap, specifically in TRN mechanosensory neurons, without observing developmental defects in these neurons, or effects in other neurons. This is a strong demonstration. Nevertheless, the study does not address whether there is a correlation of Hpo signaling pathway activity decline specifically in these neurons, and not other neurons, and at the observed L4 stage and onwards (including the first day of adulthood, 1DA stage). Such demonstrations of spatio-temporal regulation of the Hpo signaling pathway and its activation seem important for linking the Hpo pathway with the observed age-related neurodegeneration. Can this age-related response be correlated to indeed a decline in Hpo signaling during adulthood? Especially at L4 and onwards? It will be informative to measure this by examining the decline in wts1 as well as yap levels and yap nuclear localization.

(2) The Hpo pathway eventually activates gene expression via yap. Although the study uses robust genetic manipulations of yap and wts-1/LATS, it is not clear whether the observed effects are attributed to yap-mediated regulation of gene expression (see 3).

(3) The observations on the abnormal MT stabilization, and the subsequent genetic examinations of MT-stability/severing genes, are a significant strength of the study. Nevertheless, despite the strong genetic links to yap and wts-1/LATS, it is not clear whether MT-regulatory genes are regulated by transcription downstream of the Hpo pathway, thus not enabling a strong causal link between MT regulation and Hpo-mediated gene expression, making this strong part of the study mechanistically circumstantial. Specifically, it will be good to examine whether the genes addressed herein, for example, Spastin, are transcriptionally regulated downstream of the Hpo pathway. This comment is augmented by the finding that in the wts-1/ yap-1 double mutants, MT abnormality, and subsequent neuronal morphology and touch responses are restored, clearly indicating that there is an associated transcriptional regulation

Other comments:

(1) The TRN-specific knockdown of wts-1 and yap-1 is a clear strength. Nevertheless, these do not necessarily show cell-autonomous effects, as the yap transcription factor may regulate the expression of external cues, secreted or otherwise, thus generating non-cell autonomous effects. For example, it is known that yap regulates TGF-beat expression and signaling.

(2) Continuing from comment (3) above, it seems that many of the MT-regulators chosen here for genetic examinations were chosen based on demonstrated roles in neurodegeneration in other studies. It would be good to show whether these MT-associated genes are directly regulated by transcription by the Hpo pathway.

(3) The impairment of the touch response may not be robust: it is only a 30-40% reduction at L4, and even less reduction at 1DA. It would be good to offer possible explanations for this finding.

for - Buddhism - Tibetan - Mandala - is a 2 dimensional representation that the practitioner must imagine as a 3 dimensional object - This is the generation stage practice - from Youtube - Between Life and Death: Understanding Tukdam - John D. Dunne

Reviewer #2 (Public Review):

-Summary of the Authors' Aims:<br /> The authors aimed to investigate the role of calcitonin gene-related peptide (CGRP) neurons in the parabrachial nucleus (PBN) in modulating defensive behaviors in response to threats. They sought to determine whether these neurons, previously shown to be involved in passive freezing behavior, also play a role in active defensive behaviors, such as fleeing, when faced with imminent threats.

-Major Strengths and Weaknesses of the Methods and Results:<br /> The authors utilized an innovative approach by employing a predator-like robot to create a naturalistic threat scenario. This method allowed for a detailed observation of both passive and active defensive behaviors in mice. The combination of electrophysiology, optogenetics, and behavioral analysis provided a comprehensive examination of CGRP neuron activity and its influence on defensive behaviors. The study's strengths lie in its robust methodology, clear results, and the multi-faceted approach that enhances the validity of the findings.

No notable weakness found.

-Appraisal of Aims and Results:<br /> The authors successfully achieved their aims by demonstrating that CGRP neurons in the PBN modulate both passive and active defensive behaviors. The results clearly show that activation of these neurons enhances fear memory and promotes conditioned fleeing behavior, while inhibition reduces these responses. The study provides strong evidence supporting the hypothesis that CGRP neurons act as a comprehensive alarm system in the brain.

-Impact on the Field and Utility of Methods and Data:<br /> This work has significant implications for the field of neuroscience, particularly in understanding the neural mechanisms underlying adaptive defensive behaviors. The innovative use of a predator-like robot to simulate naturalistic threats adds ecological validity to the findings and may inspire future studies to adopt similar approaches. The comprehensive analysis of CGRP neuron activity and its role in defensive behaviors provides valuable data that could be useful for researchers studying fear conditioning, neural circuitry, and behavior modulation.

-Additional Context:<br /> The study builds on previous research that primarily focused on the role of CGRP neurons in passive defensive responses, such as freezing. By extending this research to include active responses, the authors have provided a more complete picture of the role of these neurons in threat detection and response. The findings highlight the versatility of CGRP neurons in modulating different types of defensive behaviors based on the perceived intensity and immediacy of threats.

Overall, this manuscript makes a significant contribution to our understanding of the neural basis of defensive behaviors and offers valuable methodological insights for future research in the field.

Reviewer #2 (Public review):

Summary:

Luo et. al. use SHAPE-MaP to find suitable RNA targets in Porcine Epidemic Diarrhoea Virus. Results show that dynamic and transient structures are good targets for small molecules, and that exposed strand regions are adequate targets for siRNA. This work is important to segment the RNA targeting.

Strengths:

This work is well done and the data supports its findings and conclusions. When possible, more than one technique was used to confirm some of the findings.

Weaknesses:

The study uses a cell line that is not porcine (not the natural target of the virus).

Reviewer #2 (Public review):

Summary:

RNAs can function across cell borders and animal generations as sources of epigenetic information for development and immunity. The specific mechanistic pathways how RNA travels between cells and progeny remains an open question. Here, Shugarts, et al. use molecular genetics, imaging, and genomics methods to dissect specific RNA transport and regulatory pathways in the C. elegans model system. Larvae ingesting double-stranded RNA is noted to not cause continuous gene silencing throughout adulthood. Damage of neuronal cells expressing double-stranded target RNA is observed to repress target gene expression in the germline. Exogenous short or long double-stranded RNA required different genes for entry into progeny. It was observed that the SID-1 double-stranded RNA transporter showed different expression over animal development. Removal of the sid-1 gene caused upregulation of two genes, the newly described sid-1-dependent gene sdg-1 and sdg-2. Both genes were observed to be negatively regulated by other small RNA regulatory pathways. Strikingly, loss then gain of sid-1 through breeding still caused variability of sdg-1 expression for many, many generations. SDG-2 protein co-localizes with germ granules, intracellular sites for heritable RNA silencing machinery. Collectively, sdg-1 presents a model to study how extracellular RNAs can buffer gene expression in germ cells and other tissues.

Strengths:

(1) Very cleaver molecular genetic methods and genomic analyses, paired with thorough genetics, were employed to discover insights into RNA transport, sdg-1 and sdg-2 as sid-1-dependent genes, and sdg-1's molecular phenotype.

(2) The manuscript is well cited, and figures reasonably designed.

(3) The discovery of the sdg genes being responsive to the extracellular RNA cell import machinery provides a model to study how exogenous somatic RNA is used to regulate gene expression in progeny. The discovery of genes within retrotransposons stimulates tantalizing models how regulatory loops may actually permit the genetic survival of harmful elements.

Weaknesses:

(1) The manuscript is broad, making it challenging to read and consider the data presented. Of note, since the original submission, the authors have improved the clarity of the writing and presentation.

Comments on revised version:

This reviewer thanks the authors for their efforts in revising the manuscript. In their rebuttal, the authors acknowledged the broad scope of their manuscript. I concur. While I still think the manuscript is a challenge to read due to its expansive nature, the current draft is substantially improved when compared to the previous one. This work will contribute to our general knowledge of RNA biology, small RNA regulatory pathways, and RNA inheritance.

Reviewer #2 (Public review):

Summary:

The authors describe elevated GSDMD expression in psoriatic skin, and knock-out of GSDMD abrogates psoriasis-like inflammation.

Strengths:

The study is well conducted with transgenic mouse models. Using mouse-models with GSDMD knock-out showing abrogating inflammation, as well as GSDMD fl/fl mice without neutrophils having a reduced phenotype.

My major concern would be the involvement of other inflammasome and GSDMD bearing cell types, esp. Keratinocytes (KC), which could be an explanation why the experiments in Fig 4 still show inflammation.

Comments on revisions:

The authors have sufficiently addressed my questions.

Reviewer #2 (Public review):

Summary:

Unlike previous traditional protein fusion protocols, the author claims their proposed new method is fast, simple, specific, reversible, and results in a complete 1:1 fusion. A multi-disciplinary approach from cloning and purification, biochemical analyses, and proteomic mass spec confirmation revealed fusion products were achieved.

Strengths:

The author provides convincing evidence that an alternative to traditional protein fusion synthesis is more efficient with 100% yields using connectase. The author optimized the protocol's efficiency with assays replacing a single amino acid and identification of a proline aminopeptidase, Bacilius coagulans (BcPAP), as a usable enzyme to use in the fusion reaction. Multiple examples including Ubiquitin, GST, and antibody fusion/conjugations reveal how this method can be applied to a diverse range of biological processes.

Weaknesses:

Though the ~100% ligation efficiency is an advancement, the long recognition linker may be the biggest drawback. For large native proteins that are challenging/cannot be synthesized and require multiple connectase ligation reactions to yield a complete continuous product, the multiple interruptions with long linkers will likely interfere with protein folding, resulting in non-native protein structures. This method will be a good alternative to traditional approaches as the author mentioned but limited to generating epitope/peptide/protein tagged proteins, and not for synthetic protein biology aimed at examining native/endogenous protein function in vitro.

Reviewer #2 (Public review):

Summary:

This manuscript investigates how neural cell development is affected in Lowe syndrome. Using neural cultures differentiated from human iPSCs carrying either an LS mutation or a genetically engineered mutation in OCRL, the authors show a depletion of mitochondrial DNA and a decrease in mitochondrial activities that correlate with an increased formation of astrocytes at the expense of neurons. Similar effects on mitochondria and on astrocyte development were observed in an LS mouse model. Moreover, these mutant brain cells are less likely to be ciliated and show a reduction in Sonic Hedgehog signalling.

Strengths/Weaknesses:

The study derives strength from the analyses of two different models of Lowe syndrome, both reaching similar conclusions. However, the observed changes in mitochondrial defects, neuronal/astrocytic development, and primary cilia are only correlated, with no attempt to investigate a causal relationship. Moreover, the mouse model is only analysed at the adult stage providing no insights into the development of the defects. Different brain regions are analysed with immunostainings and qRT-PCR making it challenging to draw clear correlations between these findings. The quality of the corresponding figures is often poor and the selection of markers is frequently inappropriate. Taken together, these limitations complicate the interpretations of the data and significantly limit the conclusions that can be drawn from the study.

Reviewer #2 (Public review):

Summary:

In this manuscript, the authors employ theoretical analysis of an elastic membrane model to explore membrane vesiculation pathways in clathrin-mediated endocytosis. A complete understanding of clathrin-mediated endocytosis requires detailed insight into the process of membrane remodeling, as the underlying mechanisms of membrane shape transformation remain controversial, particularly regarding membrane curvature generation. The authors compare constant area and constant membrane curvature as key scenarios by which clathrins induce membrane wrapping around the cargo to accomplish endocytosis. First, they characterize the geometrical aspects of the two scenarios and highlight their differences by imposing coating area and membrane spontaneous curvature. They then examine the energetics of the process to understand the driving mechanisms behind membrane shape transformations in each model. In the latter part, they introduce two energy terms: clathrin assembly or binding energy, and curvature generation energy, with two distinct approaches for the latter. Finally, they identify the energetically favorable pathway in the combined scenario and compare their results with experiments, showing that the constant-area pathway better fits the experimental data.

Strengths:

The manuscript is well-written, well-organized, and presents the details of the theoretical analysis with sufficient clarity.<br /> The calculations are valid, and the elastic membrane model is an appropriate choice for addressing the differences between the constant curvature and constant area models.<br /> The authors' approach of distinguishing two distinct free energy terms-clathrin assembly and curvature generation-and then combining them to identify the favorable pathway is both innovative and effective in addressing the problem.<br /> Notably, their identification of the energetically favorable pathways, and how these pathways either lead to full endocytosis or fail to proceed due to insufficient energetic drives, is particularly insightful.

Weaknesses:

Membrane remodeling in cellular processes is typically studied in either a constant area or constant tension ensemble. While total membrane area is preserved in the constant area ensemble, membrane area varies in the constant tension ensemble. In this manuscript, the authors use the constant tension ensemble with a fixed membrane tension, σe. However, they also use a constant area scenario, where 'area' refers to the surface area of the clathrin-coated membrane segment. This distinction between the constant membrane area ensemble and the constant area of the coated membrane segment may cause confusion.

As mentioned earlier, the theoretical analysis is performed in the constant membrane tension ensemble at a fixed membrane tension. The total free energy E_tot of the system consists of membrane bending energy E_b and tensile energy E_t, which depends on membrane tension, σe. Although the authors mention the importance of both E_b and E_t, they do not present their individual contributions to the total energy changes. Comparing these contributions would enable readers to cross-check the results with existing literature, which primarily focuses on the role of membrane bending rigidity and membrane tension.

The authors introduce two different models, (1,1) and (1,2), for generating membrane curvature. Model 1 assumes a constant curvature growth, corresponding to linear curvature growth, while Model 2 relates curvature growth to its current value, resembling exponential curvature growth. Although both models make physical sense in general, I am concerned that Model 2 may lead to artificial membrane bending at high curvatures. Normally, for intermediate bending, ψ > 90, the bending process is energetically downhill and thus proceeds rapidly. the bending process is energetically downhill and thus proceeds rapidly. However, Model 2's assumption would accelerate curvature growth even further. This is reflected in the endocytic pathways represented by the green curves in the two rightmost panels of Fig. 4a, where the energy steeply increases at large ψ. I believe a more realistic version of Model 2 would require a saturation mechanism to limit curvature growth at high curvatures.

Reviewer #2 (Public review):

Summary:

In this manuscript, Al Asafen, Clark et al., use fluorescence correlation spectroscopy (FCS) to quantitatively analyze the mobility of Dl along the DV axis of the early Drosophila embryo. Dl is essential for dorsal-ventral (DV) patterning and its gradient initiates the activation of several genes and thereby orchestrates the formation of the Drosophila body plan. While the mechanisms underlying the formation of the Dl gradient have been extensively studied by this group and others, there are some observations for which there is not yet a mechanistic explanation. For example, the peak of the Dl gradient grows continuously during nuclear cycles 10-14. This is likely due to Cact-dependent Dl diffusion and Dl binding to DNA. However, the biophysical parameters governing Dl nuclear dynamics that would support these claims have not been previously measured. In this work, the authors provide evidence that GFP-tagged Dl may be separated into a mobile pool and an immobile pool. Interestingly, the fraction of immobile Dl is position-dependent along the DV axis, revealing more binding to DNA in the ventral than in the dorsal nuclei. This is either due to higher binding affinity in ventral locations (due to Toll-dependent Dl phosphorylation) or to higher Dl-Cact binding in dorsal nuclei that would prevent Dl from binding to DNA. Using dl-mutant alleles, the authors support the latter hypothesis.

Strengths:

The manuscript is well written and their conclusions are convincingly supported by their methodology and analysis. As a quantitative study, the biophysical analysis seems rigorous, in general.

Although this is not the first study that employs FSC to investigate the dynamics of a morphogen, it further exemplifies how these quantitative tools can be used to uncover mechanistic aspects of morphogen dynamics during development. In particular, the manuscript reports novel biophysical parameters of Dl dynamics that will be helpful in future hypotheses-driven modeling studies.

Weaknesses:

In my opinion, the main weakness of the manuscript is that the main biological implication of the study, namely that the asymmetry in the fraction of immobile Dl is a result of nuclear Dl-Cact binding which prevents Dl from binding DNA (Figure 5), occurs in a region of the embryo where there is very little Dl anyways (Figure 1A, 5A). While it is interesting that the fraction of immobile Dl increases (just a little, but significantly) in dorsal nuclei in mutants expressing a form of Dl with reduced Cact binding it is unclear what is the biological impact of this effect in a location where Dl is nearly absent. As can be seen in Figure 3F, the fraction of immobile is unaffected in Dl-mutant forms with reduced DNA binding, because it is already very low. It is unlikely that Dl binding to Cact in dorsal nuclei would affect shuttling as well since the fraction is very low anyway.

While the authors have a very clear understanding of the biology of the Dl gradient, I feel that the manuscript is more written as a 'tools' paper (i.e., to exemplify how FSC methods and analysis can be used for biological discovery). This is ok, but I think that the authors should discuss further what are the biological implications of these findings other than the contribution to uncovering the biophysical parameters. For example, I think that the implications of the rejected hypothesis (i.e., that Toll-dependent Dl phosphorylation does not seem to have an impact on Dl binding affinities to DNA) are important and should be further discussed (even if no additional experiments are performed). What is then the role of Dl phosphorylation? Perhaps it could have an impact on patterning robustness in lateral regions. The authors should report in Figure 5 also what happens to the fraction of Dl bound to DNA in lateral regions in the reduced Cact binding and reduced Toll phosphorylation mutants.

The way that position along the DV axis is reported using the nuclear-cytoplasmic-ratio (NCR) in Figures 1-3 is not incorrect, but I wonder if it is the best way of doing it. The reason is that it spreads out a relatively small region of the embryo (the ventral-most locations) and shrinks a relatively large region of the embryo (lateral and dorsal regions), see Figure 1A. Perhaps reporting the NCR in log_2 units would be more appropriate.

Reviewer #2 (Public review):

Summary

In this study, Bisen et al. characterized the state-dependency of insulin-producing cells in the brain of Drosophila melanogaster. They successfully established that IPC activity is modulated by the nutritional state and age of the animal. Interestingly, they demonstrate that IPCs respond to the ingestion of glucose, rather than to perfusion with it, an observation reminiscent of the incretin effect in mammals. The study is well conducted and presented and the experimental data convincingly support the claims made.

Strengths

The study makes great use of the tools available in *Drosophila* research, demonstrating the effect that starvation and subsequent refeeding have on the physiological activity of IPCs as well as on the behavior of flies to then establish causal links by making use of optogenetic tools.<br /> It is particularly nice to see how the authors put their findings in context to published research and use for example TDC2 neuron activation or DH44 activity to establish baselines to relate their data to.

Reviewer #2 (Public review):

Although recent cochlear micromechanical measurements in living animals have shown that outer hair cells drive broadband vibration of the reticular lamina, the role of this vibration in cochlear fluid circulation remains unclear. The authors hypothesized that motile outer hair cells facilitate cochlear fluid circulation. To test this, they investigated the effects of acoustic stimuli and salicylate on kainic acid-induced changes in the cochlear nucleus activities. The results reveal that low-frequency tones accelerate the effect of kainic acid, while salicylate reduces the impact of acoustic stimuli, indicating that outer hair cells actively drive cochlear fluid circulation.

The major strengths of this study lie in its high significance and the synergistic use of both electrophysiological recording and computational modeling. Recent in vivo observations of the broadband reticular lamina vibration challenge the traditional view of frequency-specific cochlear amplification. Furthermore, there is currently no effective noninvasive method to deliver the drugs or genes to the cochlea. This study addresses these important questions by observing outer hair cells' roles in the cochlear transport of kainic acid. The author utilized a well-established electrophysiological method to produce valuable new data and a custom-developed computational model to enhanced the interpretation of their experimental results.

The authors successfully validated their hypothesis, showing through the experimental and modeling results that active outer hair cells enhance cochlear fluid circulation in the living cochlea.

These findings have significant implications for advancing our understanding of cochlear amplification and offer promising clinical applications for treating hearing loss by accelerating cochlear drug delivery.

Reviewer #2 (Public review):

Zhang et al. established chronic unpredictable mild stress (CUMS) mouse model, which displayed osteoporosis phenotype, suggesting a potential correlation between psychological stress and bone metabolism. They found that miRNA candidate miR-335-3p is downregulated in the long bone of CUMS mice through microRNA sequencing experiments and qRT-PCR. They further demonstrated that miR-335-3p attenuates osteoclast activity via inhibiting Fos signaling, which can induce NFATC1 expression and regulate osteoclast activity.

My concerns have been addressed. And the quality of the manuscript is improved significantly.

Reviewer #2 (Public review):

Summary:

The authors build a gene expression model based on histone post-translational modifications, and find that H3K27ac is correlated with gene expression. They proceed to perturb H3K27ac at 13 gene promoters in two cell types, and measure gene expression changes to test their model.

Strengths:

The combination of multiple methods to model expression, along with utilizing 6 histone datasets in 13 cell types allowed the authors to build a model that correlates between 0.7-0.79 with gene expression. They use dCas9-p300 fusions to perturb H3K27ac and monitor gene expression to test their model. Ranked correlations of the HEK293 data showed some support for the predictions after perturbation of H3K27ac.

Weaknesses:

The perturbation of 5 genes in K562 with perturb-seq data shows a modest correlation of ~0.5 and isn't included in the main figures. The authors are then left to speculate reasons why the outcome of epigenome editing doesn't fit their predictions, which highlights the limited value in the current version of this method.

As mentioned before, testing genes that were not expressed being most activated by dCas9-p300 weaken the correlations vs. looking at a broad range of different gene expression as the original model was trained on.<br /> If the authors want this method to be used to predict outcomes of epigenome editing, expanding to dCas9-KRAB and other CRISPRa methods (SAM and VPR) would be useful. Those datasets are published and could be analyzed for this manuscript.<br /> The authors don't compare their method to other prediction methods.

Reviewer #2 (Public review):

Summary:

This study investigates the effect of a fed vs hungry state on food decision-making.

70 participants performed a computerized food choice task with eye tracking. Food images came from a validated set with variability in food attributes. Foods ranged from low caloric density unprocessed (fruits) to high caloric density processed foods (chips and cookies).

Prior to the choice task participants rated images for taste, health, wanting, and calories. In the choice task participants simply selected one of two foods. They were told to pick the one they preferred. Screens consisted of two food pictures along with their "Nutri-Score". They were told that one preferred food would be available for consumption at the end.

A drift-diffusion model (DDM) was fit to the reaction time values. Eye tracking was used to measure dwell time on each part of the monitor.

Findings:

Participants tended to select the item they had rated as "tastier", however, health also contributed to decisions.

Strengths:

The most interesting and innovative aspect of the paper is the use of the DDM models to infer from reaction time and choice the relative weight of the attributes.

Were the ratings redone at each session? E.g. were all tastiness ratings for the sated session made while sated? This is relevant as one would expect the ratings of tastiness and wanting to be affected by the current fed state.

Weaknesses:

My main criticism, which doesn't affect the underlying results, is that the labeling of food choices as being taste- or health-driven is misleading. Participants were not cued to select health vs taste. Studies in which people were cued to select for taste vs health exist (and are cited here). Also, the label "healthy" is misleading, as here it seems to be strongly related to caloric density. A high-calorie food is not intrinsically unhealthy (even if people rate it as such). The suggestion that hunger impairs making healthy decisions is not quite the correct interpretation of the results here (even though everyone knows it to be true). Another interpretation is that hungry people in negative calorie balance simply prefer more calories.

Reviewer #2 (Public review):

Summary:

This article reviews the studies on the relationship between slow oscillation (SO)-spindle (SP) coupling and memory consolidation. It innovatively employs non-normal circular linear correlations through a Bayesian meta-analysis. A systematic analysis of the retrieved studies highlighted that co-coupling of SO and the fast SP's phase and amplitude at the frontal part better predicts memory consolidation performance. I only have a few comments that I recommend are addressed.

Major Comments:

Regarding the Moderator of Age: Although the authors discuss the limited studies on the analysis of children and elders regarding age as a moderator, the figure shows a significant gap between the ages of 40 and 60. Furthermore, there are only a few studies involving participants over the age of 60. Given the wide distribution of effect sizes from studies with participants younger than 40, did the authors test whether removing studies involving participants over 60 would still reveal a moderator effect?

Reviewer #2 (Public review):

Summary:

The authors explored the importance of data quality and representation for ligand-based virtual screening approaches. I believe the results could be of potential benefit to the drug discovery community, especially to those scientists working in the field of machine learning applied to drug research. The in silico design is comprehensive and adequate for the proposed comparisons.

This manuscript by Chong A. et al describes that it is not necessary to resort to the use of sophisticated deep learning algorithms for virtual screening, since based on their results considering conventional ML may perform exceptionally well if feeded by the right data and molecular representations.

The article is interesting and well-written. The overview of the field and the warning about dataset composition are very well thought-out and should be of interest to a broad segment of the AI in drug discovery readership. This article further highlights some of the considerations that need to be taken into consideration for the implementation of data-centric AI for computer-aided drug design methods.

Strengths:

This study contributes significantly to the field of machine learning and data curation in drug discovery. The paper is, in general, well-written and structured. However, in my opinion, there are some suggestions regarding certain aspects of the data analyses.

Weaknesses:

The conclusions drawn in the study are based on the analysis of a two dataset. The authors chose BRAF as an example in this study, and expanded with BACE-1 dataset; however a benchmark with several targets would be suitable to evaluate reproducibility or transferability of the method. One concern could be the applicability of the method in other targets.

Reviewer #2 (Public review):

In this manuscript, Menegas et al. classify the "control" behavior of captive marmosets. They combine behavioral screening from video recordings with audio and neural recordings (from the striatum) to better define what can be considered a typical behavioral repertoire for captive marmoset monkeys. A range of analyses is presented, investigating various aspects of behavior, such as social interactions and the detection of atypical individuals.

The manuscript is compelling in many respects, especially due to the richness of the dataset and the breadth of analyses presented. However, a significant issue with the manuscript lies in its writing: the results are conveyed in an overly succinct and superficial manner, and the "Methods" section is nearly absent. Key concepts are often undefined, and the mathematical details underlying the figures are not explained, leaving readers to guess the authors' approach.

Another issue is the vague use of the term "natural behavior." All data presented here appear to have been collected in small cages with limited climbing opportunities and enrichment. Thus, the authors should refrain from using "natural" to describe these conditions.

Below, we elaborate further on the lack of methodological detail. Based on these issues, we believe the manuscript, in its current form, does not meet the scientific standards necessary for proper review. We strongly encourage the authors to undertake an extensive revision.

Major Revision Points:

The methods and results require significantly more detail. A scientific publication should provide readers with enough information to reproduce the study. Here, the detail level is far too low to fully understand, or reproduce, the study, and in many instances, readers are left to guess how the figure panels were produced. Below is a non-exhaustive list of examples illustrating these issues:

(1) "we temporarily placed horizontal cage dividers to reduce the total cage size during data collection": What were the resulting (and initial) cage dimensions?

(2) "After training the network, we hierarchically clustered the latent space": What is the latent space? Based on Figure 2a, it appears related to the network's recurrent layer, but this is not clarified in the text.

(3) Alpha and perplexity parameters: Please define these terms. Since these concepts appear fundamental, readers should not have to consult external references.

(4) "We then traced cluster identities across hierarchical levels": What are hierarchical levels?

(5) "To understand how the input time series data was weighed in the bottleneck layer of the model": What is the bottleneck layer?

(6) "we measured the average attention allocation to previous time points": The authors should define "attention allocation."

(7) "we compared each neuron's firing rate distribution to shuffled data based on the overall frequency of each behavior during the session": This description is insufficient to understand the analysis.

(8) "we hierarchically clustered neurons according to their firing rate enrichment maps": No mathematical explanation is provided for neuron clustering, nor is the concept of a "firing rate enrichment map" clarified.

(9) "Cluster 4 showed higher activity when neurons were 'alone' or 'active'": This is vague and uses unclear jargon (e.g., "neurons alone"). Additionally, no mathematical explanation is provided for assigning neuronal activity to behavioral states.

(10) Figure 3f, right-side panels: The analysis seems to involve cage mate positioning, yet no description is provided.

(11) "we used motion watches to measure activity across all hours": Are these motion-sensitive watches physically attached to the animals? The methodology should be described, including data analysis details.

This list could continue, but we trust the authors understand the point. There is a wealth of analyses and information in this study, but the descriptions are too superficial. We understand that fully describing each analysis may require significant rewriting, including supplementary figures, and will likely make the manuscript longer. This is entirely acceptable, as the ideas presented here are worth the added rigor.

"Natural behavior": Typically, the term "natural" suggests that the dataset reflects the range of behaviors exhibited by animals in the wild. Here, however, recordings were made in a small cage with limited climbing opportunities and enrichment. Under these conditions, it's hard to justify describing the behavior as "natural". In a project aimed at classifying the behavioral repertoire of marmoset monkeys and making this dataset accessible to other laboratories, it would be helpful to include more detailed information about the animals' housing conditions. This might include cage sizes, temperature, humidity, and details on food quantities, quality, and feeding times.

Correlation versus causation: In the section titled "Large-scale data collection reveals variability across days and correlation between cagemates," the authors conclude: "Overall, these results indicate that measurements of animals' behavioral traits depend heavily on their social environment." This interpretation seems incorrect. We know that animal behavior varies throughout the day, with activity peaks typically occurring in the morning and afternoon. Such factors, or other external influences, could induce correlations between animals that are not caused by social interactions.

Figure 4g: What are we intended to conclude from this analysis?

Figure 5: Please specify the type of calls analyzed. For example, did you analyze only long-distance calls (aka 'loud phees' or 'shrills')? In "We split the audio data into 5-minute (non-continuous) segments and found that the average call rate in these segments varied from 0 calls per minute to 60 calls per minute (Fig. 5d-e)," does the call rate refer to individual animals or the entire cage?

"This implies that a high rate of calls in a room can interrupt animals during social resting states and cause them to preferentially exhibit more active/attentive states." Does it? This could simply indicate that more active animals produce more calls.

"We recorded neural activity in the striatum because it is known to contain diverse signals related to movement and social interactions." While I understand that the authors intend to publish neural data separately, a brief discussion of the striatum's role here would be helpful.

Reviewer #2 (Public review):

Summary of the manuscript:

Authors present MGPfactXMBD, a novel model-based manifold-learning framework designed to address the challenges of interpreting complex cellular state spaces from single-cell RNA sequences. To overcome current limitations, MGPfactXMBD factorizes complex development trajectories into independent bifurcation processes of gene sets, enabling trajectory inference based on relevant features. As a result, it is expected that the method provides a deeper understanding of the biological processes underlying cellular trajectories and their potential determinants.

MGPfactXMBD was tested across 239 datasets, and the method demonstrated similar to slightly superior performance in key quality-control metrics to state-of-the-art methods. When applied to case studies, MGPfactXMBD successfully identified critical pathways and cell types in microglia development, validating experimentally identified regulons and markers. Additionally, it uncovered evolutionary trajectories of tumor-associated CD8+ T cells, revealing new subtypes with gene expression signatures that predict responses to immune checkpoint inhibitors in independent cohorts.

Overall, MGPfactXMBD represents a relevant tool in manifold-learning for scRNA-seq data, enabling feature selection for specific biological processes and enhancing our understanding of the biological determinants of cell fate.

Summary of the outcome:

The novel method addresses core state-of-the-art questions in biology related to trajectory identification. The design and the case studies are of relevance.

Comments on revisions:

The authors have addressed all my previous comments to satisfaction.

Reviewer #2 (Public review):

Summary:

The manuscript by Hu et. al presents a clearly-designed examination of the role of tachykinin1-expressing neurons in the parasubthalamic nucleus of the lateral posterior hypothalamus (PTSN) in active avoidance learning. These glutamatergic neurons have previously been implicated in responding to negative stimuli. This manuscript expands the current understanding of PTSNTac1 neurons in learned responses to threats by showing their role in encoding and mediating the active avoidance response. The authors first use bulk fiber photometry imaging to show the encoding of the active avoidance procedure, followed by cell-type specific manipulations of PTSNTac1 neurons during active avoidance. Finally, they show that encoding and mediation of active avoidance in a downstream target of PTSNTac1 neurons, the PVT/intermediodorsal nuclei of the dorsal thalamus (IMD), has the same effect as what was discovered in the cell body. This contrasts other output regions of the PTSN, such as the PBN and CeA, which were not found to promote active avoidance learning. The experiments presented were well-designed to support the conclusions of the authors, however, the manuscript is missing several key control experiments and supplemental information to support their main findings.

Strengths:

The manuscript provides information on a brain region and downstream target that mediates active avoidance learning. The manuscript provides valuable information via necessity and sufficiency experiments to show the role of the population of interest (PTSNTac1 neurons) in active avoidance learning. The authors also performed most behavior experiments in male and female mice, with adequate power to address potential sex differences in the control of active avoidance by PTSNTac1 neurons. Finally, the manuscript provides valuable information about the specificity of the PTSNTac1 downstream target in regulating active avoidance learning, identifying the PVT/intermediodorsal nuclei of the dorsal thalamus as the key target and ruling out the PBN and CeA.

Weaknesses:

However, several main conclusions of the paper must be interpreted carefully due to missing or inadequate control experiments and histological verification.

(1) Inadequate presentation of viral localization. The authors state that expression was "largely restricted within PSTN" however there is no quantification of the amount of viral expression beyond the target region. Given that Tac1 is expressed in neighboring regions, it is critical to show the viral expression and fiber implant location data for all animals included in the figures. Furthermore, criteria for inclusion and exclusion based on mistargeting should be delineated. This should also be clearly outlined for the experiments in Figure S5, where "behavioral effects of activation of sparsely Tac1-expressing neurons in two adjacent areas of PSTN" was tested but the location of viral expression in those cases is unclear.

(2) Lack of motion artifact correction with isosbestic signal for GCamp recordings. It is appreciated that the authors included a separate EGFP-expressing group to compare to the GCamp-expressing group, however, additional explanation is required for the methods used to analyze the raw fluorescent signal. Namely, were fluorescent signals isosbestic-corrected prior to calculating ΔF/F? If no isosbestic signal was used to correct motion artifacts within a recording session, additional explanation is needed to explain how this was addressed. The lack of motion artifacts in the EGFP signal in a separate cohort is inadequate to answer this caveat as motion artifacts are within-animal.

(3) Missing control experiment demonstrating intact locomotor performance in caspase ablation experiments. The authors use caspase ablation of PTSNTac1 neurons prior to active avoidance learning to appraise the necessity of this cell population. However, a control experiment showing intact locomotor ability in ablated mice was not performed.

(4) Missing control experiment demonstrating [lack of] valence with PTSN silencing manipulations. The authors performed a real-time and conditioned place preference experiments for ChR2-expressing mice (Fig 3M) and found stimulation to be negatively-valenced and generate an aversive memory, respectively. Absent this control experiment with silencing, an alternative conclusion remains possible that optogenetic silencing via GtACR2 created nonspecific location preferences in the active avoidance apparatus, confounding the interpretation of those results.

(5) Incomplete analysis of sex differences. Data in female mice is conspicuously missing from inhibition experiments. The rationale for exclusion from this dataset would be useful for the interpretation of the other noted sex differences.

Reviewer #2 (Public review):

Summary:

The authors sequence 45 new samples of S. Gallinarum, a commensal Salmonella found in chickens, which can sometimes cause disease. They combine these sequences with around 500 from public databases, determine the population structure of the pathogen, and coarse relationships of lineages with geography. The authors further investigate known anti-microbial genes found in these genomes, how they associate with each other, whether they have been horizontally transferred, and date the emergence of clades.

Strengths:

- It doesn't seem that much is known about this serovar, so publicly available new sequences from a high burden region are a valuable addition to the literature.<br /> - Combining these sequences with publicly available sequences is a good way to better contextualise any findings.<br /> - The genomic analyses have been greatly improved since the first version of the manuscript, and appropriately analyse the population and date emergence of clades.<br /> - The SNP thresholds are contextualised in terms of evolutionary time.<br /> - The importance and context of the findings are fairly well described.

Weaknesses:

- There are still a few issues with the genomic analyses, although they no longer undermine the main conclusions:

(1) Although the SNP distance is now considered in terms of time, the 5 SNP distance presented still represents ~7yrs evolution, so it is unlikely to be a transmission event, as described. It would be better to use a much lower threshold or describe the interpretation of these clusters more clearly. Bringing in epidemiological evidence or external references on the likely time interval between transmissions would be helpful.

(2) The HGT definition has not fundamentally been changed and therefore still has some issues, mainly that vertical evolution is still not systematically controlled for. Using a 5kb window is not sufficient, as LD may extend across the entire genome. As the authors have now run gubbins correctly, they could use the results from this existing analysis to find recent HGT. To definite mobilisation, perhaps a standard pipeline such (e.g. https://github.com/EBI-Metagenomics/mobilome-annotation-pipeline) would be more convincing.

(3) The invasiveness index is better described, but the authors still did not provide convincing evidence that the small difference is actually biologically meaningful (there was no statistical difference between the two strains provided in response Figure 6). What do other Salmonella papers using this approach find, and can their links be brought in? If there is still no good evidence, a better description of this difference would help make the conclusions better supported.

In summary, the analysis is broadly well described and feels appropriate. Some of the conclusions are still not fully supported, although the main points and context of the paper now appear sound.

Reviewer #2 (Public review):

In this version of manuscript, the author clarified many details and rewrote some sections. This substantially improved the readability of the paper. I also recognized that the author spent substantial efforts in the Appendix to answer the potential questions.

Unfortunately, I am not currently convinced by the theory proposed in this paper. In the next section, I will first recap the logic of the author and explain why I am not convinced. Although the theory fits many experimental results, other theories on overflow metabolism are also supported by experiments. Hence, I do not think based on experimental data we could rule in or rule out different theories.

Recap: To explain the origin of overflow metabolism, the author uses the following logic:

(1) There is a substantial variability of single-cell growth rate<br /> (2) The flux (J_r^E) and (J_f^E) are coupled with growth rate by Eq. 3<br /> (3) Since growth rate varies from cells to cells, flux (J_r^E) and (J_f^E) also varies<br /> (4) The variabilities of above fluxes in above create threshold-analog relation, and hence overflow metabolism.

My opinion:

The logic step (2) and (3) have caveats. The variability of growth rate has large components of cellular noise and external noise. Therefore, variability of growth rate is far from 100% correlated with variability of flux (J_r^E) and (J_f^E) at the single-cell level. Single-cell growth rate is a complex, multivariate functional, including (Jr^E) and (J_f^E) but also many other variables. My feeling is the correlation could be too low to support the logic here.

One example: ribosomal concentration is known to be an important factor of growth rate in bulk culture. However, the "growth law" from bulk culture cannot directly translate into the growth law at single-cell level [Ref1,2]. This is likely due to other factors (such as cell aging, other muti-stability of cellular states) are involved.

Therefore, I think using Eq.3 to invert the distribution of growth rate into the distribution of (Jr^E) and (J_f^E) is inapplicable, due to the potentially low correlation at single-cell level. It may show partial correlations, but may not be strong enough to support the claim and create fermentation at macroscopic scale.

Overall, if we track the logic flow, this theory implies overflow metabolism is originated from variability of k_cat of catalytic enzymes from cells to cells. That is, the author proposed that overflow metabolism happens macroscopically as if it is some "aberrant activation of fermentation pathway" at the single-cell level, due to some unknown partially correlation from growth rate variability.

Compared with other theories, this theory does not involve any regulatory mechanism and can be regarded as a "neutral theory". I am looking forward to seeing single cell experiments in the future to provide evidences about this theory.

[Ref1] https://www.biorxiv.org/content/10.1101/2024.04.19.590370v2<br /> [Ref2] https://www.biorxiv.org/content/10.1101/2024.10.08.617237v2

Reviewer #2 (Public review):

Summary:

This study investigates the impact of mother-child neural synchronization and the quality of parent-child relationships on the development of Theory of Mind (ToM) and social cognition. Utilizing a naturalistic fMRI movie-viewing paradigm, the authors analyzed inter-subject neural synchronization in mother-child dyads and explored the connections between neural maturity, parental caregiving, and social cognitive outcomes. The findings indicate age-related maturation in ToM and social pain networks, emphasizing the importance of dyadic interactions in shaping ToM performance and social skills, thereby enhancing our understanding of the environmental and intrinsic influences on social cognition.

Strengths:

This research addresses a significant question in developmental neuroscience, by linking social brain development with children's behaviors and parenting. It also uses a robust methodology by incorporating neural synchrony measures, naturalistic stimuli, and a substantial sample of mother-child dyads to enhance its ecological validity. Furthermore, the SEM approach provides a nuanced understanding of the developmental pathways associated with Theory of Mind (ToM).

Weaknesses:

(1) Upon reviewing the introduction, I feel that the first goal - developmental changes of the social brain and its relation to age - seems somewhat distinct from the other two goals and the main research question of the manuscript. The authors might consider revising this section to enhance the overall coherence of the manuscript. Additionally, the introduction lacks a clear background and rationale for the importance of examining age-related changes in the social brain.

(2) The manuscript uses both "mother-child" and "parent-child" terminology. Does this imply that only mothers participated in the fMRI scans while fathers completed the questionnaires? If so, have the authors considered the potential impact of parental roles (father vs. mother)?

(3) There is inconsistent usage of the terms ISC and ISS in the text and figures, both of which appear to refer to synchronization derived from correlation analysis. It would be beneficial to maintain consistency throughout the manuscript.

(4) Of the 50 dyads, 16 were excluded due to data quality issues, which constitutes a significant proportion. It would be helpful to know whether these excluded dyads exhibited any distinctive characteristics. Providing information on demographic or behavioral differences-such as Theory of Mind (ToM) performance and age range between the excluded and included dyads would enhance the assessment of the findings' generalizability.

(5) The article does not adhere to the standard practice of using a resting state as a baseline for subtracting from task synchronization. Is there a rationale for this approach? Not controlling for a baseline may lead to issues, such as whether resting state synchronization already differs between subjects with varying characteristics.

(6) The title of the manuscript suggests a direct influence of mother-child interactions on children's social brain and theory of mind. However, the use of structural equation modeling (SEM) may not fully establish causal relationships. It is possible that the development of children's social brain and ToM also enhances mother-child neural synchronization. The authors should address this alternative hypothesis of the potential bidirectional relationship in the discussion and exercise caution regarding terms that imply causality in the title and throughout the manuscript.

(7) I would appreciate more details about the 14 Theory of Mind (ToM) tasks, which could be included in supplemental materials. The authors score them on a scale from 0 to 14 (each task 1 point); however, the tasks likely vary in difficulty and should carry different weights in the total score (for example, the test and the control questions should have different weights). Many studies have utilized the seven tasks according to Wellman and Liu (2004), categorizing them into "basic ToM" and "advanced ToM." Different components of ToM could influence the findings of the current study, which should be further examined by a more in-depth analysis.

Reviewer #2 (Public review):

Summary:

The past five years have seen the publication of both new (Witvliet et al., 2021) and newly analyzed (Cook et al., 2019; Moyle et al., 2021; Brittin et al., 2021) data for the C. elegans connectome. The increase in data availability for a single species allows researchers to examine variability due to both stochastic events and changes over development. The quantity of these data is huge. To help the community make these data more accessible, the authors present a new online tool that allows the examination of 3D models for C. elegans neurons in the central neuropil across development. In addition to visualizing the overall structure of the neuronal processes and locations of synapses, the NeuroSCAN tool also allows users to probe into the C-PHATE visualization results, which this group previously pioneered to describe similarities in neuron adjacency (Moyle et al., 2021).

Strengths:

The ability to visualize the data from both a connectomics and contactomics perspective across developmental time has significant power. The original C. elegans connectome (White et al., 1986) presented their circuits as line drawings with chemical and electrical synapses indicated through arrows and bars. While these line drawings remain incredibly useful, they were also necessary simplifications for a 2D publication and they lack details of the complex architecture seen within each EM image. Koonce et al take advantage of segmented image data of each neuronal process within the nerve ring to create a web interface where users can visualize 3D models for their neuron of choice. The C-PHATE visualization allows users to explore similarities among different neurons in terms of adjacency and then go directly to the 3D model for these neurons. The 3D models it generates are beautiful and will likely be showing up in many future presentations and publications. The tool doesn't require any additional downloading and is open source.

Weaknesses:

While it's impossible to create one tool that will satisfy all potential users, I found myself wanting to have numbers associated with the data. For example, knowing the number of connections or the total surface area of contacts between individual neurons wasn't possible through the viewer, which limits the utility of taking deep analytical dives. While connectivity data are readily accessible through other interfaces such as Nemanode and WormWiring, a more thorough integration may be helpful to some users.

There were several issues with the user interface that made it a bit clunky to use. For example, as I added additional neurons to the filter search box, the loading time got longer and longer. I ran an experiment uploading all of the amphid neurons, one pair at a time. Each additional neuron pair added an additional 5-10 seconds to the loading. By the time I got to the last pair, it took over a minute to load. Issues like these, some of which may be unavoidable given the size of the data, could be conveyed through better documentation. I did not find the tutorial very helpful and the supplementary movies lacked any voiceover, so it wasn't always clear what they were trying to show.

Reviewer #2 (Public review):

Summary:

There are two accounts in the literature that propose that expectations suppress the activity of neurons that are (a) not tuned to the expected stimulus to increase the signal-to-noise ratio for expected stimuli (sharpening model) or (b) tuned to the expected stimulus to highlight novel information (dampening model). One recent account, the opposing process theory, brings the two models together and suggests that both processes occur, but at different time points: initial sharpening is followed by later dampening of the neural activity of the expected stimulus. In this study, the authors aim to test the opposing process theory in a statistical learning task by applying multivariate EEG analyses and finding evidence for the opposing process theory based on the within-trial dynamics.

Strengths:

This study addresses a very timely research question about the underlying mechanisms of expectation suppression. The applied EEG decoding approach offers an elegant way to investigate the temporal characteristics of expectation effects. A major strength of the study lies in the experimental design that aims to control for repetition effects, one of the common confounds in prediction suppression studies. The reported results are novel in the field and have the potential to substantially improve our understanding of expectation suppression in visual perception.

Weaknesses:

The strength in controlling for repetition effects by introducing a neutral (50% expectation) condition also adds a weakness to the current version of the manuscript, as this neutral condition is not integrated into the behavioral (reaction times) and EEG (ERP and decoding) analyses. This procedure remained unclear to me. The reported results would be strengthened by showing differences between the neutral and expected (valid) conditions on the behavioral and neural levels. This would also provide a more rigorous check that participants had implicitly learned the associations between the picture category pairings.

It is not entirely clear to me what is actually decoded in the prediction condition and why the authors did not perform decoding over trial bins in prediction decoding as potential differences across time could be hidden by averaging the data. The manuscript would generally benefit from a more detailed description of the analysis rationale and methods.

Finally, the scope of this study should be limited to expectation suppression in visual perception, as the generalization of these results to other sensory modalities or to the action domain remains open for future research.

Reviewer #2 (Public review):

Summary:

Measurements of the reward positivity, an electrophysiological component elicited during reward evaluation, have previously been used to understand how self-benefitting effort expenditure influences the processing of rewards. The present study is the first to complement those measurements with electrophysiological reward after-effects of effort expenditure during prosocial acts. The results provide solid evidence that effort adds reward value when the recipient of the reward is the self but discounts reward value when the beneficiary is another individual.

Strengths:

An important strength of the study is that the amount of effort, the prospective reward, the recipient of the reward, and whether the reward was actually gained or not were parametrically and orthogonally varied. In addition, the researchers examined whether the pattern of results generalized to decisions about future efforts. The sample size (N=40) and mixed-effects regression models are also appropriate for addressing the key research questions. Those conclusions are plausible and adequately supported by statistical analyses.

Weaknesses:

Although the obtained results are highly plausible, I am concerned whether the reward positivity (RewP) and P3 were adequately measured. The RewP and P3 were defined as the average voltage values in the time intervals 300-400 ms and 300-440 ms after feedback onset, respectively. So they largely overlapped in time. Although the RewP measure was based on frontocentral electrodes (FC3, FCz, and FC4) and the P3 on posterior electrodes (P3, Pz, and P4), the scalp topographies in Figure 3 show that the RewP effects were larger at the posterior electrodes used for the P3 than at frontocentral electrodes. So there is a concern that the RewP and P3 were not independently measured. This type of problem can often be resolved using a spatiotemporal principal component analysis. My faith in the conclusions drawn would be further strengthened if the researchers extracted separate principal components for the RewP and P3 and performed their statistical analyses on the corresponding factor scores.

Reviewer #2 (Public review):

Summary:

The manuscript: "Synergistic effect of inhibiting CHK2 and DNA replication on cancer cell growth" successfully demonstrates that the compounds BKC and IBC found in Psoralea corylifolia act synergistically to inhibit cancer cell proliferation, using a wide range of well-chosen methodologies. Moreover, the authors characterized the mechanisms of action of both drugs, which result in inhibition of cell proliferation. The use of multiple cell lines and the mice models makes the study robust and complete.

Significance:

The manuscript presents a well written study that offers new insights and contributions to the field. Although the inhibitors described have been known in science, the authors present convincingly their mode of action, which is either better characterized (for BKC) or inhibiting a different than previously suggested enzyme (for IBC). Authors also nicely pinpoint and explain the narrow window of concentrations when these two compounds act synergistically rather than additively. The analyses in multiple cell lines, mouse models and in combination with other cancer treatments, make this study of interest not only for fundamental researchers but also for translational scientists and industry.

Reviewer #2 (Public review):

Summary:

Ngo et al. use AlphaFold2 and Rosetta to model closed, open, and inactive states of the human ion channel hERG. Subsequent MD simulations and comparisons with experiments support the plausibility of their models.

Strengths:

This is thorough work studied from many different angles. It provides a self-consistent picture of how conformational changes in hERG may affect its function and binding to different targets.

Weaknesses:

Though this work claims the methodologies can be generalized to other systems, it is not obvious how. Many modeling choices seem arbitrary and also seem to have required extensive expert knowledge of the system. This limits the applicability of the modeling strategy.

Reviewer #2 (Public review):

Summary:

Kume et al. found for the first time that Semaphorin 4A (Sema4A) was downregulated in both mRNA and protein levels in L and NL keratinocytes of psoriasis patients compared to control keratinocytes. In peripheral blood, they found that Sema4A is not only expressed in keratinocytes but is also upregulated in hematopoietic cells such as lymphocytes and monocytes in the blood of psoriasis patients. They investigated how the down-regulation of Sema4A expression in psoriatic epidermal cells affects the immunological inflammation of psoriasis by using a psoriasis mice model in which Sema4A KO mice were treated with IMQ. Kume et al. hypothesized that down-regulation of Sema4A expression in keratinocytes might be responsible for the augmentation of psoriasis inflammation. Using bone marrow chimeric mice, Kume et al. showed that KO of Sema4A in non-hematopoietic cells was responsible for the enhanced inflammation in psoriasis. The expression of CCL20, TNF, IL-17, and mTOR was upregulated in the Sema4AKO epidermis compared to the WT epidermis, and the infiltration of IL-17-producing T cells was also enhanced.

Strengths:

Decreased Sema4A expression may be involved in psoriasis exacerbation through epidermal proliferation and enhanced infiltration of Th17 cells, which helps understand psoriasis immunopathogenesis.

Weaknesses:

The mechanism of decreased Sema4A expression in psoriasis is not clear, although this does not affect the strength of this research.

Reviewer #2 (Public review):

Summary:

In this study, the authors discovered that the chemoresistance in RCC cell lines correlates with the expression levels of the drug transporter ABCA1 and the EMT-related transcription factor Snail. They demonstrate that Snail induces ABCA1 expression and chemoresistance, and that ABCA1 inhibitors can counteract this resistance. The study also suggests that Snail disrupts the cholesterol-sphingomyelin (Chol/SM) balance by repressing the expression of enzymes involved in very long-chain fatty acid-sphingomyelin synthesis, leading to excess free cholesterol. This imbalance activates the cholesterol-LXR pathway, inducing ABCA1 expression. Moreover, inhibiting cholesterol esterification suppresses Snail-positive cancer cell growth, providing potential lipid-targeting strategies for invasive cancer therapy.

Strengths:

This research presents a novel mechanism by which the EMT-related transcription factor Snail confers drug resistance by altering the Chol/SM balance, introducing a previously unrecognized role of lipid metabolism in the chemoresistance of cancer cells. The focus on lipid balance, rather than individual lipid levels, is a particularly insightful approach. The potential for targeting cholesterol detoxification pathways in Snail-positive cancer cells is also a significant therapeutic implication.

Weaknesses:

The study's claim that Snail-induced ABCA1 is crucial for chemoresistance relies only on pharmacological inhibition of ABCA1, lacking additional validation. The causal relationship between the disrupted Chol/SM balance and ABCA1 expression or chemoresistance is not directly supported by data. Some data lack quantitative analysis.

Reviewer #2 (Public review):

Overview

In this manuscript, the authors use deep mutational scanning to assess the effect of ~6,600 protein-coding variants in MC4R, a G protein-coupled receptor associated with obesity. Reasoning that current deep mutational scanning approaches are insufficiently precise for some drug development applications, they focus on articulating new, more precise approaches. These approaches, which include a new statistical model and innovative reporter assay, enable them to probe molecular phenotypes directly relevant to the development of drugs that target this receptor with high precision and statistical rigor.

They use the resulting data for a variety of purposes, including probing the relationship between MC4R's sequence and structure, analyzing the effect of clinically important variants, identifying variants that disrupt downstream MC4R signaling via one but not both pathways, identifying loss of function variants are amenable to a corrector drug and exploring how deep mutational scanning data could guide small molecule drug optimization.

Strengths

The analysis and statistical framework developed by the authors represent a significant advance. In particular, the study makes use of barcode-level internally replicated measurements to more accurately estimate measurement noise.

The framework allows variant effects to be compared across experimental conditions, a task that is currently hard to do with rigor. Thus, this framework will be applicable to a large number of existing and future deep mutational scanning experiments.

The authors refine their existing barcode transcription-based assay for GPCR signaling, and develop a clever "relay" new reporter system to boost signaling in a particular pathway. They show that these reporters can be used to measure both gain of function and loss of function effects, which many deep mutational scanning approaches cannot do.

The use of systematic approaches to integrate and then interrogate high-dimensional deep mutational scanning data is a big strength. For example, the authors applied PCA to the variant effect results from reporters for two different MC4R signaling pathways and were able to discover variants that biased signaling through one or the other pathway. This approach paves the way for analyses of higher dimensional deep mutational scans.

The authors use the deep mutational scanning data they collect to map how different variants impact small molecule agonists activate MC4R signaling. This is an exciting idea, because developing small-molecule protein-targeting therapeutics is difficult, and this manuscript suggests a new way to map small-molecule-protein interactions.

Weaknesses

The authors derive insights into the relationship between MC4R signaling through different pathways and its structure. While these make sense based on what is already known, the manuscript would be stronger if some of these insights were validated using methods other than deep mutational scanning.

Likewise, the authors use their data to identify positions where variants disrupt MC4R activation by one small molecule agonist but not another. They hypothesize these effects point to positions that are more or less important for the binding of different small molecule agonists. The manuscript would be stronger if some of these insights were explored further.

Impact

In this manuscript, the authors present new methods, including a statistical framework for analyzing deep mutational scanning data that will have a broad impact. They also generate MC4R variant effect data that is of interest to the GPCR community.

Reviewer #2 (Public review):

Summary:

This work highlights a novel role for platelet-derived growth factor (PDGF) in mitigating cellular senescence associated with age-related and painful intervertebral disc degeneration. Prior literature has demonstrated the importance of the accumulation of senescent cells in mediating many of the pathological effects associated with the degenerate disc joint such as inflammation and tissue breakdown. In this study, the authors treat clinically relevant human nucleus pulposus and annulus fibrosus cells from patients undergoing discectomy with recombinant PDGF-AB/BB for 5 days and then deep phenotyped the outcomes using bulk RNA sequencing. In addition, they irradiated healthy human disc cells which they subsequently treated with PDGF-AB/BB examining the expression of SASP-related markers and also PDGFRA receptor gene expression. Overall PDGF was able to down-regulate many senescent-associated pathways and the degenerate phenotype in IVD cells. Altered pathways were associated with neurogenesis, mechanical stimuli, metabolism, cell cycle, reactive oxygen species, and mitochondrial dysfunction. Overall the authors achieved their aims and the results by and large support their conclusions although improvements could be made to enhance the rigor of the study and findings.

Strengths:

A major strength of this study is the use of human cells from patients undergoing discectomy for disc herniation as well as access to healthy human cells. Investigating the role of PDGF regarding cellular senescence in the degenerate disc joint is a novel and underexplored area of research which is a significant contribution to the field of spine. This study highlights a potential target for addressing cellular senescence where most of the prior focus has been on senolytic drugs. Such studies have broad implications for other age-related diseases where senescence plays a major role. The use of transcriptomics and therefore an unbiased approach to investigating the role of PDGF is also considered a strength as are the follow-up studies involving irradiating healthy human disc cells and treating these cells with PDGF. The combined assessment of both nucleus pulposus and annulus fibrosus cells in the context of these studies adds to the impact.

Weaknesses:

A weakness of these studies lies in the lack of experimental details provided in the methodology including the rationale for such methods/conditions. Many details such as the specific culture models utilized, substrates, cell density, and media components are missing which impacts rigor. Such details would strengthen the manuscript and the ability to replicate and build on such work/findings. An additional weakness relates to qualitative data presented such as the B-galactosidase assay and immunofluorescence of senescence-associated proteins such as P21 and P16. Quantification of such data sets would greatly strengthen the studies and lend further support to the hypotheses. The study in its current form could be strengthened by the inclusion of mechanistic studies probing the downstream PDGF receptor-associated pathways for example specifically targeting or modulating the activity of the PDGF receptor PDGFRA including validation of the gene data for PDGFRA with protein level data to determine if the transcripts are being translated to protein. The claim that in annulus fibrosus cells, PDGF do not mediate their effects via the PDGFRA does not appear to be supported by the current data as only gene expression for the receptor was assessed with no functional or mechanistic studies being performed. Further discussion, interpretation, and direct comparison of the nucleus pulposus and annulus fibrosus data sets would be helpful for the readers. The magnitude of changes related to the effects of PDGF-BB on the S-phase in irradiated NP and AF cells between control and treated groups seem small making interpretation of these findings challenging.

Reviewer #2 (Public review):

Summary:

The manuscript offers an important contribution to the field of virology, especially concerning NNV entry mechanisms. The major strength of the study lies in the identification of MmMYL3 as a functional receptor for RGNNV and its role in macropinocytosis, mediated by the IGF1R-Rac1/Cdc42 signaling axis. This represents a significant advance in understanding NNV entry mechanisms beyond previously known receptors such as HSP90ab1 and HSC70. The data, supported by comprehensive in vitro and in vivo experiments, strongly justify the authors' claims about MYL3's role in NNV infection in marine medaka.

Strengths:

(1) The identification of MmMYL3 as a functional receptor for RGNNV is a significant contribution to the field. The study fills a crucial gap in understanding the molecular mechanisms governing NNV entry into host cells.

(2) The work highlights the involvement of IGF1R in macropinocytosis-mediated NNV entry and downstream Rac1/Cdc42 activation, thus providing a thorough mechanistic understanding of NNV internalization process. This could pave the way for further exploration of antiviral targets.

Reviewer #2 (Public review):

Summary:

This work investigates transcriptional responses to varying levels of transcription factors (TFs). The authors aim for gradual up- and down-regulation of three transcription factors GFI1B, NFE2, and MYB in K562 cells, by using a CRISPRa- and a CRISPRi line, together with sgRNAs of varying potency. Targeted single-cell RNA sequencing is then used to measure gene expression of a set of 90 genes, which were previously shown to be downstream of GFI1B and NFE2 regulation. This is followed by an extensive computational analysis of the scRNA-seq dataset. By grouping cells with the same perturbations, the authors can obtain groups of cells with varying average TF expression levels. The achieved perturbations are generally subtle, not reaching half or double doses for most samples, and up-regulation is generally weak below 1.5-fold in most cases. Even in this small range, many target genes exhibit a non-linear response. Since this is rather unexpected, it is crucial to rule out technical reasons for these observations.

Strengths:

The work showcases how a single dataset of CRISPRi/a perturbations with scRNA-seq readout and an extended computational analysis can be used to estimate transcriptome dose responses, a general approach that likely can be built upon in the future.

Weaknesses:

(1) The experiment was only performed in a single replicate. In the absence of an independent validation of the main findings, the robustness of the observations remains unclear.

(2) The analysis is based on the calculation of log-fold changes between groups of single cells with non-targeting controls and those carrying a guide RNA driving a specific knockdown. How the fold changes were calculated exactly remains unclear, since it is only stated that the FindMarkers function from the Seurat package was used, which is likely not optimal for quantitative estimates. Furthermore, differential gene expression analysis of scRNA-seq data can suffer from data distortion and mis-estimations (Heumos et al. 2023 (https://doi.org/10.1038/s41576-023-00586-w), Nguyen et al. 2023 (https://doi.org/10.1038/s41467-023-37126-3)). In general, the pseudo-bulk approach used is suitable, but the correct treatment of drop-outs in the scRNA-seq analysis is essential.

(3) Two different cell lines are used to construct dose-response curves, where a CRISPRi line allows gene down-regulation and the CRISPRa line allows gene upregulation. Although both lines are derived from the same parental line (K562) the expression analysis of Tet2, which is absent in the CRISPRi line, but expressed in the CRISPRa line (Figure S3A) suggests substantial clonal differences between the two lines. Similarly, the PCA in S4A suggests strong batch effects between the two lines. These might confound this analysis.