Reviewer #3 (Public Review):

Summary:<br /> This research article reports that a greater number of senescent osteoclasts (SnOCs), which produce Netrin-1 and NGF, are responsible for innervation in the LSI and aging animal models.

Strengths:<br /> The research is based on previous findings in the authors' lab and the fact that the IVD structure was restored by treatment with ABT263. The logic is clear and clarifies the pathological role of SnOCs, suggesting the potential utilization of senolytic drugs for the treatment of LBP. Generally, the study is of good quality and the data is convincing.

Weaknesses:<br /> There are some points that can be improved:<br /> 1. Since this work primarily focuses on ABT263, it resembles a pharmacological study for this drug. It is preferable to provide references for the ABT263 concentration and explain how the administration was determined.<br /> 2. It would strengthen the study to include at least 6 mice per group for each experiment and analysis, which would provide a more robust foundation.<br /> 3. In Figure 4, either use "adult" or "young" consistently, but not both. Additionally, it's important to define "sham," "young," and "adult" explicitly in the methods section.<br /> 4. Assess the protein expression of Netrin 1 and NGF.

Reviewer #3 (Public Review):

Summary:<br /> Grandits and colleagues were trying to develop a new tool to accelerate pharmacological studies by using neural networks to emulate the human ventricular cardiomyocyte action potential (AP). The AP is a complex electrical signal that governs the heartbeat, and it is important to accurately model the effects of drugs on the AP to assess their safety and efficacy. Traditional biophysical simulations of the AP are computationally expensive and time-consuming. The authors hypothesized that neural network emulators could be trained to predict the AP with high accuracy and that these emulators could also be used to quickly and accurately predict the effects of drugs on the AP.

Strengths:<br /> One of the study's major strengths is that the authors use a large and high-quality dataset to train their neural network emulator. The dataset includes a wide range of APs, including normal and abnormal APs exhibiting EADs. This ensures that the emulator is robust and can be used to predict the AP for a variety of different conditions.

Another major strength of the study is that the authors demonstrate that their neural network emulator can be used to accelerate pharmacological studies. For example, they use the emulator to predict the effects of a set of known arrhythmogenic drugs on the AP. The emulator is able to predict the effects of these drugs, even though it had not been trained on these drugs specifically.

Weaknesses:<br /> One weakness of the study is that it is important to validate neural network emulators against experimental data to ensure that they are accurate and reliable. The authors do this to some extent, but further validation would be beneficial. In particular for the inverse problem, where the estimation of pharmacological parameters was very challenging and led to particularly large inaccuracies.

Additional context:<br /> The work by Grandits et al. has the potential to revolutionize the way that pharmacological studies are conducted. Neural network emulation has the promise to reduce the time and cost of drug development and to improve the safety and efficacy of new drugs. The methods and data presented in the paper are useful to the community because they provide a starting point for other researchers to develop and improve neural network emulators for the human ventricular cardiomyocyte AP. The authors have made their code and data publicly available, which will facilitate further research in this area.

It is important to note that neural network emulation is still a relatively new approach, and there are some challenges that need to be addressed before it can be widely adopted in the pharmaceutical industry. For example, neural network emulators need to be trained on large and high-quality datasets. Additionally, it is important to validate neural network emulators against experimental data to ensure that they are accurate and reliable. Despite these challenges, the potential benefits of neural network emulation for pharmacological studies are significant. As neural network emulation technology continues to develop, it is likely to become a valuable tool for drug discovery and development.

Reviewer #3 (Public Review):

This work shows how, in the formation of the immune synapse, the B cell controls the contraction phase, the formation and retraction of actin structures concentrating the antigen (actin foci), and, ultimately, global signal attenuation. The authors use a combination of TIRF microscopy and original image quantification to show that Arp2/3 activated by N-WASP controls a pool of actin concentrated in foci (situated in the synapse), formed and transported centripetally towards the center of the synapse through myosin II mediated contractions. These contractions concentrate the B cell receptors (BCR) in the center, promote disassembly of the stimulatory kinase Syk as well as the the disassociation from the BCR of the inhibitory phosphatase SHIP, process which entails the attenuation of the BCR signal.

The author prove their claims by mean of thorough image analysis, mainly observing and quantifying the fluorescence and the dynamics of single clusters of antigen and actin foci and analyzing two-colors dynamical images. They perform their observation in control cells, on pharmacologically perturbed cells where the action of Arp2/3 or N-WASP is inhibited, and on modified primary cells (primary derived from genetically engineered mice) to silence N-WASP or WASP. The work is sound and complete, the experiments technically excellent and well explained.

In the reviewed manuscript the authors answer to all referees' suggestions and add new data and comments to the manuscript. In particular by suppressing NMII activation (with Blebbistatin), they show that NMII contraction plays a role (in coordination with N-WASP mediated actin polymerization) in the generation of actin foci ring-like structures.

This work adds an important information to the current view of B cell activation, in particular it links the contraction phase to the actin foci that have been recently characterized. Moreover, the late phase of the immune synapse formation is poorly investigated, but it is crucial for the fate of the cell: this work provides an explanation for the attenuation of the signal that might lead to the termination of the synapse.

Reviewer #3 (Public Review):

In addition to ER-Golgi-dependent conventional protein secretion, a wide range of substrates lacking N-terminal signal peptides are secreted through diverse pathways collectively known as unconventional protein secretion (UPS). The translocation mechanism of these different substrates across the membrane remains a fascinating question in this field. In this manuscript, the authors employ a comprehensive combination of biochemistry, cell biology, and structural biology techniques to investigate the mechanism by which two crucial cystine residues, C77 and C95, facilitate the secretion of FGF2. The key finding is that the C95-C95 disulfide bond mediates the formation of an FGF2 dimer, which is essential for pore formation and translocation. Additionally, it is revealed that C77 promotes FGF2 secretion by interacting with a cell surface factor called Na-K ATPase. This observation provides valuable mechanistic insights into a critical step of FGF2 secretion. Overall, the experimental results presented in this study are both clear and convincing.

The authors have well addressed my concern about the formation of disulfide bond in the revision. In addition, the cross-linking mass spectrometry identified an additional dimerization interface, which would be of interest for future studies on its role in regulating high-order FGF2 oligomer formation and secretion.

Reviewer #3 (Public Review):

The goal of this study was to use a combination of fluorescent dyes and genetically encoded reporters to estimate the temperature of mitochondria. The authors provide additional evidence that they claim to support "hot" mitochondria.

Strengths:<br /> 1. The authors use several methods, including a mitochondrial fluorescent reporter dye, as well as a genetically encoded gTEMP temperature probe, to estimate mitochondrial temperature.<br /> 2. The authors couple these measurements with other perturbation of mitochondria, such as OXPHOS inhibitors, to show consistency

Weaknesses:<br /> 1. The methodology for inferring mitochondrial temperature is not well-established to begin with and requires additional controls for interpretation.<br /> a. Very little benchmarking is done of the "basal" fluorescence ratio, and whether that fluorescence ratio actually reflects true organelle temperature. For instance, the authors should in parallel compare between different organelles to see if only mitochondria appear "hot" or whether this is some calibration error. Another control is to use different incubator temperatures and see how mitochondrial (vs other organelle) temperature varies as a function of external temperature.<br /> b. The authors do not rigorously control for other factors that may also be changing fluorescence and may be confounders to the delta fluorescence (eg, delta calcium in response to mito inhibitors, membrane potential, redox status, ROS, etc.). There should be additional calibration for all potential confounders.<br /> c. Can these probes be used in isolated mitochondria and other isolated organelles. Such data would also help to clarify whether the high temperature is specific to mitochondria.<br /> 2. The authors should try to calibrate their fluorescence inference of temperature with an alternative method and benchmark to others in the field. For instance, Okabe et al Nat Comm 2012 used a polymeric thermometer to measure temperature and reported 33degC cytoplasm and 35degC nucleus. Can the authors also show a ~2degC difference in their hands between those two compartments, and under those conditions are mitochondria still 10degC hotter?

Based on the aforementioned weaknesses, in my opinion, the authors did not achieve their Aims to accurately determine the temperature of mitochondria. The results, while interesting, are preliminary and require additional controls before conclusions can be drawn. Previous studies have indicated intra-organelle temperature variations within cells; typically, previous reports have estimated that the variation is within a few degrees (Okabe et al Nat Comm 2012). Only one report has previously suggested that mitochondria are at 50degC (Cretien, Plos biology 2018). The study does not substantially clarify the true temperature of mitochondria or resolve potential discrepancies in previous estimates of mitochondrial temperature.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, the authors have used biochemical approaches to provide compelling evidence for the cleavage of TRMT1 by SARS-CoV-2 Nsp5 protease. This work is of wide interest to biochemists, cell biologists, and structural biologists in the coronavirus (CoV) field. Furthermore, it substantially advances the understanding of how CoV's interact with host factors during infection and modify cellular metabolism.

Strengths:<br /> The authors provide multiple lines of biochemical evidence to report a TRMT1-Nsp5 interaction during SARS-CoV-2 infection. They show that the host enzyme TRMT1 is cleaved at a specific site and that it generates fragments that are incapable of functioning properly. This is an important result because TRMT1 is a critical player in host protein synthesis. This also advances our understanding of virus-host interactions during SARS-CoV-2 infections.

Weaknesses:<br /> The major weakness is the lack of mechanistic insights into TRMT1-Nsp5 interactions. The authors have provided commendable biochemical data on proving the TRMT1-Nsp5 interaction but without clear mechanistic insights into when this interaction takes place in the context of SARS-CoV-2 propagation, what are the functional consequences of this interaction on host biology, and does this somehow benefit the infecting virus? I feel that the authors played it a bit safe despite having access to several reagents and an extremely promising research direction.

Reviewer #3 (Public Review):

In the manuscript titled "Structure and Evolution of Alanine/Serine Decarboxylases and the Engineering of Theanine Production," Wang et al. solved and compared the crystal structures of Alanine Decarboxylase (AlaDC) from Camellia sinensis and Serine Decarboxylase (SerDC) from Arabidopsis thaliana. Based on this structural information, the authors conducted both in vitro and in vivo functional studies to compare enzyme activities using site-directed mutagenesis and subsequent evolutionary analyses. This research has the potential to enhance our understanding of amino acid decarboxylase evolution and the biosynthetic pathway of the plant-specialized metabolite theanine, as well as to further its potential applications in the tea industry.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, the authors have used a combination of enzymatic, crystallographic, and in silico approaches to provide compelling evidence for substrate selectivity of SARS-CoV-2 Mpro for human TRMT1.

Strengths:<br /> In my opinion, the authors came close to achieving their intended aim of demonstrating the structural and biochemical basis of Mpro catalysis and cleavage of human TRMT1 protein. The combination of orthogonal approaches is highly commendable.

Weaknesses:<br /> It would have been of high scientific impact if the consequences of TRMT1 cleavage by Mpro on cellular metabolism were provided. Furthermore, assays to investigate the effect of inhibition of this Mpro activity on SARS-CoV-2 propagation and infection would have been extremely useful in providing insights into host- SARS-CoV-2 interactions.

Reviewer #3 (Public Review):

Summary:<br /> This manuscript reports a comprehensive analysis of Notch-Delta/Jagged signaling inclusive of the human Notch1 and Notch2 receptors and DLL1, DLL4, JAG1, and JAG2 ligands. Measurements encompassed signaling activity for ligand trans-activation, cis-activation, cis-inhibition, and activity modulation by Lfng. The most striking observations of the study are that JAG1 has no detectable activity as a Notch1 ligand when presented on a cell (though it does have activity when immobilized on a surface), even though it is an effective cis-inhibitor of Notch1 signaling by other ligands, and that DLL1 and DLL4 exhibit cis-activating activity for Notch1 and especially for Notch2. Notwithstanding the artificiality of the system and some of its shortcomings, the results should nevertheless be a valuable resource for the Notch signaling community.

Strengths:<br /> 1) The work is systematic and comprehensive, addressing questions that are of importance to the community of researchers investigating mammalian Notch proteins, their activation by ligands, and the modulation of ligand activity by LFng.<br /> 2) A quantitative and thorough analysis of the data is presented.

Weaknesses:<br /> 1) The manuscript is primarily descriptive and does not delve into the underlying, mechanistic origin or source of the different ligand activities.

2) The amount of ligand or receptor expressed is inferred from the flow cytometry signal of a co-translated fluorescent protein-histone fusion, and is not directly measured. The work would be more compelling if the amount of ligand present on the cell surface were directly measured with anti-ligand antibodies, rather than inferred from measurements of the fluorescent protein-histone fusion.

3) It would be helpful to see plots of the raw activity data before transformation and normalization, because the plots present data after several processing steps, and it is not clear how the processed data relate to the original values determined in each measurement.

4) The authors use sparse plating of engineered cells with parental (no ligand or receptor-expressing cell to measure cis activation). However, the cells divide within the cultured period of 22-24 h and can potentially trans-activate each other.

Reviewer #3 (Public Review):

In Okholm et al., the authors evaluate the functional impact of circHIPK3 in bladder cancer cells. By knocking it down and performing an RNA-seq analysis, the authors found thousands of deregulated genes that look unaffected by miRNAs sponging function and that are, instead, enriched for an 11-mer motif. Further investigations showed that the 11-mer motif is shared with the circHIPK3 and able to bind the IGF2BP2 protein. The authors validated the binding of IGF2BP2 and demonstrated that IGF2BP2 KD antagonizes the effect of circHIPK3 KD and leads to the upregulation of genes containing the 11-mer. Among the genes affected by circHIPK3 KD and IGF2BP2 KD (resulting in downregulation and upregulation, respectively) the authors found the STAT3 gene. This was accompanied by consistent concomitant upregulation of one of its targets, TP53. The authors propose a mechanism of competition between circHIPK3 and IGF2BP2 triggered by IGF2BP2 nucleation, potentially via phase separation.

Strengths:<br /> The number of circRNAs continues to drastically grow; however, the field lacks detailed molecular investigations. The presented work critically addresses some of the major pitfalls in the field of circRNAs and there has been a careful analysis of aspects frequently poorly investigated. The time-point KD followed by RNA-seq, investigation of the miRNAs-sponge function of circHIPK3, identification of 11-mer motif, identification, and validation of IGF2BP2, and the analysis of copy number ratio between circHIPK3 and IGF2BP2 in assessing the potential ceRNA mode of action have been extensively explored and, comprehensively are convincing.

Weaknesses:<br /> In some parts, the manuscript lacks appropriate internal controls (eg: comparison with normal bladder cells, linear transcript measurements upon the KD, RIP internal controls/ WB analysis, etc), statistical analysis and significance (in some qPCRs), exhaustive description in the methods of microscopy and image analysis, western blot, and a separate section of cell lines used. The use of certain cell lines bladder cancer cells vs non-bladder cells in some experiments for the purpose of the study is also unclear.

Overall, the presented study adds new knowledge in describing circHIPK3 function, its capability to regulate some downstream genes and its interaction and competition for IGF2BP2. However, whereas the experimental part appears technically logical, it remains unclear the overall goal of this study and the final conclusions. The mechanism of condensation proposed, although interesting and encouraging, would need further experimental support and information, especially in the context of cancer.

In summary, this study is a promising step forward in the comprehension of the functional role of circHIPK3. These data could possibly help to better understand the circHIPK3 role in cancer.

Reviewer #3 (Public Review):

This is a beautifully presented paper combining live imaging and analysis of mutant phenotypes to elucidate the role of laminin γ1-dependent basement membranes in the development of the zebrafish olfactory placode. The work is clearly illustrated and carefully quantified throughout. There are some very interesting observations based on the analysis of wild-type, laminin γ1, and foxd3 mutant embryos. The authors demonstrate the importance of a Laminin γ1-dependent basement membrane in olfactory placode morphogenesis, and in establishing and maintaining both boundaries and neuronal connections between the brain and the olfactory system. There are some very interesting observations, including the identification of different mechanisms for axons to cross basement membranes, either by taking advantage of incompletely formed membranes at early stages, or by actively perforating the membrane at later ones.

This is a valuable and important study but remains quite descriptive. In some cases, hypotheses for mechanisms are stated but are not tested further. For example, the authors propose that olfactory axons must actively disrupt a basement membrane to enter the brain and suggest alternative putative mechanisms for this, but these are not tested experimentally. In addition, the authors propose that the basement membrane of the olfactory placode acts to resist mechanical forces generated by the morphogenetic movement of the developing brain, and thus to prevent passive deformation of the placode, but this is not tested anywhere, for example by preventing or altering the brain movements in the laminin γ1 mutant.

Reviewer #3 (Public Review):

Summary:<br /> The main objective of this work has been to delve into the mechanisms underlying the increment of D-serine in serum, as a marker of renal injury.

Strengths:<br /> With a multi-hierarchical approach, the work shows that Ischemia-Reperfusion Injury in the kidney causes a specific increment in renal reabsorption of D-serine that, at least in part, is due to the increased expression of the apical transporter ASCT2. In this way, the authors revealed that SMCT1 also transports D-serine.

The manuscript also supports that increased expression of ASCT2, even together with the parallel decreased expression of SMCT1, in renal proximal tubules underlies the increased reabsorption of D-serine responsible for the increment of this enantiomer in serum in a murine model of Ischemia-Reperfusion Injury.

Weaknesses:<br /> Remains to be clarified whether ASCT2 has substantial stereospecificity in favor of D- versus L-serine to sustain a ~10-fold decrease in the ratio D-serine/L-serine in the urine of mice under Ischemia-Reperfusion Injury (IRI).<br /> It is not clear how the increment in the expression of ASCT2, in parallel with the decreased expression of SMCT1, results in increased renal reabsorption of D-serine in IRI.

Reviewer #3 (Public Review):

Summary:<br /> The authors follow up on prior studies where they have argued for the existence of cold nociception in Drosophila larvae. In the proposed pathway, mechanosensitive Class III multidendritic neurons are the noxious cold responding sensory cells. The current study attempts to explore the potential roles of second and third order neurons, based on information of the Class III neuron synaptic outputs that have been obtained from the larval connectome.

Strengths:

The major strength of the manuscript is the detailed discussion of the second and third order neurons that are downstream of the mechanosensory Class III multidendritic neurons. These will be useful in further studies of gentle touch mechanosensation and mechanonociception both of which rely on sensory input from these cells. Calcium imaging experiments on Class III activation with optogenetics support the wiring diagram.

Weaknesses:

The scientific premise is that a full body contraction in larvae that are exposed to noxious cold is a sensorimotor behavioral pathway. This premise is, to start with, questionable. A common definition of behavior is a set of "orderly movements with recognizable and repeatable patterns of activity produced by members of a species (Baker et al., 2001)." In the case of nociception behaviors, the patterns of movement are typically thought to play a protective role and to protect from potential tissue damage.

Does noxious cold elicit a set of orderly movements with a recognizable and repeatable pattern in larvae? Can the patterns of movement that are stimulated by noxious cold allow the larvae to escape harm? Based on the available evidence, the answer to both questions is seemingly no. In response to noxious cold stimulation many, if not all, of the muscles in the larva, simultaneously contract (Turner et al., 2016), and as a result the larva becomes stationary. In response to cold, the larva is literally "frozen" in place and it is incapable of moving away. This incapacitation by cold is the antithesis of what one might expect from a behavior that protects the animals from harm.

Extensive literature has investigated the physiological responses of insects to cold (reviewed in Overgaard and MacMillan, 2017). In numerous studies of insects across many genera (excluding cold adapted insects such as snow flies), exposure to very cold temperatures quickly incapacitates the animal and induces a state that is known as a chill coma. During a chill coma, the insect becomes immobilized by the cold exposure, but if the exposure to cold is very brief the insect can often be revived without apparent damage. Indeed, it is common practice for many laboratories that use adult Drosophila for studies of behavior to use a brief chilling on ice as a form of anesthesia because chilling is less disruptive to subsequent behaviors than the more commonly used carbon dioxide anesthesia. If flies were to perceive cold as a noxious nociceptive stimulus, then this "chill coma" procedure would likely be disruptive to behavioral studies but is not. Furthermore, there is no evidence to suggest that larval sensation of "noxious cold" is aversive.

The insect chill coma literature has investigated the effects of extreme cold on the physiology of nerves and muscles and the consensus view of the field is that the paralysis that results from cold is due to complex and combined action of direct effects of cold on muscle and on nerves (Overgaard and MacMillan, 2017). Electrophysiological measurements of muscles and neurons find that they are initially depolarized by cold, and after prolonged cold exposure they are unable to maintain potassium homeostasis and this eventually inhibits the firing of action potentials (Overgaard and MacMillan, 2017). The very small thermal capacitance of a Drosophila larva means that its entire neuromuscular system will be quickly exposed to the effect of cold in the behavioral assays under consideration here. It would seem impossible to disentangle the emergent properties of a complex combination of effects on physiology (including neuronal, glial, and muscle homeostasis) on any proposed sensorimotor transformation pathway.

Nevertheless, the manuscript before us makes a courageous attempt at attempting this. A number of GAL4 drivers tested in the paper are found to affect parameters of contraction behavior (CT) in cold exposed larvae in silencing experiments. However, notably absent from all of the silencing experiments are measurements of larval mobility following cold exposure. Thus, it is not known from the study if these manipulations are truly protecting the larvae from paralysis following cold exposure, or if they are simply reducing the magnitude of the initial muscle contraction that occurs immediately following cold (ie reducing CT). The strongest effect of silencing occurs with the 19-12-GAL4 driver which targets Class III neurons (but is not completely specific to these cells).

Optogenetic experiments for Class III neurons relying on the 19-12-GAL4 driver combined with a very strong optogenetic acuator (ChETA) show the CT behavior that was reported in prior studies. It should be noted that this actuator drives very strong activation, and other studies with milder optogenetic stimulation of Class III neurons have shown that these cells produce behavioral responses that resemble gentle touch responses (Tsubouchi et al 2012 and Yan et al 2013). As well, these neurons express mechanoreceptor ion channels such as NompC and Rpk that are required for gentle touch responses. The latter makes the reported Calcium responses to cold difficult to interpret in light of the fact that the strong muscle contractions driven by cold may actually be driving mechanosensory responses in these cells (ie through deformation of the mechanosensitive dendrites). Are the cIII calcium signals still observed in a preparation where cold induced muscle contractions are prevented?

A major weakness of the study is that none of the second or third order neurons (that are downstream of CIII neurons) are found to trigger the CT behavioral responses even when strongly activated with the ChETA actuator (Figure 2 Supplement 2). These findings raise major concerns for this and prior studies and it does not support the hypothesis that the CIII neurons drive the CT behaviors.

Later experiments in the paper that investigate strong CIII activation (with ChETA) in combination with other second and third order neurons does support the idea activating those neurons can facilitate body-wide muscle contractions. But many of the co-activated cells in question are either repeated in each abdominal neuromere or they project to cells that are found all along the ventral nerve cord, so it is therefore unsurprising that their activation would contribute to what appears to be a non-specific body-wide activation of muscles along the AP axis. Also, if these neurons are already downstream of the CIII neurons the logic of this co-activation approach is not particularly clear. A more convincing experiment would be to silence the different classes of cells in the context of the optogenetic activation of CIII neurons to test for a block of the effects, a set of experiments that is notably absent from the study.

The authors argument that the co-activation studies support "a population code" for cold nociception is a very optimistic interpretation of a brute force optogenetics approach that ultimately results in an enhancement of a relatively non-specific body-wide muscle convulsion.

https://www.legifrance.gouv.fr/codes/article_lc/LEGIARTI000047971046

Reviewer #3 (Public Review):

Summary:

In this manuscript, the authors present a new automated image analysis pipeline named WormPsyQi which allows researchers to quantify various parameters of synapses in C. elegans. Using a collection of newly generated transgenic strains in which synaptic proteins are tagged with fluorescent proteins, the authors showed that WormPsyQi can reliably detect puncta of synaptic proteins, and measure several parameters, including puncta number, location, and size.

Strengths:

The image analysis of fluorescently-labeled synaptic (or other types of) puncta pattern requires extensive experience such that one can tell which puncta likely represent bona fide synapse or background noise. The authors showed that WormPsyQi nicely reproduced the quantifications done manually for most of the marker strains they tested. Many researchers conducting such types of quantifications would receive significant benefits in saving their time by utilizing the pipeline developed by the authors. The collections of new markers would also help researchers examine synapse patterning in different neuron types which may have a unique mechanism in synapse assembly and specificity.

Weaknesses:

As the authors note, the limitations that the use of fluorescently-tagged proteins expressed from the concatemeric transgenes directly apply to WormPsyQi. While I appreciate that WormPsyQi could help researchers in doing repetitive, time-consuming tedious quantifications, it remains unclear whether there are particular kinds of quantifications that WormPsyQi handles better than human experimenters.

Reviewer #3 (Public Review):

Summary:

This paper presents novel and innovative force measurements of the biophysics of gliding cyanobacteria filaments. These measurements allow for estimates of the resistive force between the cell and substrate and provide potential insight into the motility mechanism of these cells, which remains unknown.

Strengths:

The authors used well-designed microfabricated devices to measure the bending modulus of these cells and to determine the critical length at which the cells buckle. I especially appreciated the way the authors constructed an array of pillars and used it to do 3-point bending measurements and the arrangement the authors used to direct cells into a V-shaped corner in order to examine at what length the cells buckled at. By examining the gliding speed of the cells before buckling events, the authors were able to determine how strongly the buckling length depends on the gliding speed, which could be an indicator of how the force exerted by the cells depends on cell length; however, the authors did not comment on this directly.

Weaknesses:

There were two minor weaknesses in the paper.

First, the authors investigate the buckling of these gliding cells using an Euler beam model. A similar mathematical analysis was used to estimate the bending modulus and gliding force for Myxobacteria (C.W. Wolgemuth, Biophys. J. 89: 945-950 (2005)). A similar mathematical model was also examined in G. De Canio, E. Lauga, and R.E Goldstein, J. Roy. Soc. Interface, 14: 20170491 (2017). The authors should have cited these previous works and pointed out any differences between what they did and what was done before.

The second weakness is that the authors claim that their results favor a focal adhesion-based mechanism for cyanobacterial gliding motility. This is based on their result that friction and adhesion forces correlate strongly. They then conjecture that this is due to more intimate contact with the surface, with more contacts producing more force and pulling the filaments closer to the substrate, which produces more friction. They then claim that a slime-extrusion mechanism would necessarily involve more force and lower friction. Is it necessarily true that this latter statement is correct? (I admit that it could be, but is it a requirement?)

Related to this, the authors use a model with isotropic friction. They claim that this is justified because they are able to fit the cell shapes well with this assumption. How would assuming a non-isotropic drag coefficient affect the shapes? It may be that it does equally well, in which case, the quality of the fits would not be informative about whether or not the drag was isotropic or not.

Reviewer #3 (Public Review):

The authors evaluate the effect of high-resolution 2D template matching on template bias in reconstructions and provide a quantitative metric for overfitting. It is an interesting manuscript that made me reevaluate and correct some mistakes in my understanding of overfitting and template bias, and I'm sure it will be of great use to others in the field.

The revised version of this manuscript addresses all of my concerns. The newly added Figure 4 supplement 1 provides a sobering outlook for the fraction of the proteome we can hope to identify in situ.

Reviewer #3 (Public Review):

Summary:<br /> The authors sought to determine, at the level of individual presubiculum pyramidal cells, how allocentric spatial information from the retrosplenial cortex was integrated with egocentric information from the anterior thalamic nuclei. Employing a dual opsin optogenetic approach with patch clamp electrophysiology, Richevaux, and colleagues found that around three-quarters of layer 3 pyramidal cells in the presubiculum receive monosynaptic input from both brain regions. While some interesting questions remain (e.g. the role of inhibitory interneurons in gating the information flow and through different layers of presubiculum, this paper provides valuable insights into the microcircuitry of this brain region and the role that it may play in spatial navigation).

Strengths:<br /> One of the main strengths of this manuscript was that the dual opsin approach allowed the direct comparison of different inputs within an individual neuron, helping to control for what might otherwise have been an important source of variation. The experiments were well-executed and the data was rigorously analysed. The conclusions were appropriate to the experimental questions and were well-supported by the results. These data will help to inform in vivo experiments aimed at understanding the contribution of different brain regions in spatial navigation and could be valuable for computational modelling.

Weaknesses:<br /> Some attempts were made to gain mechanistic insights into how inhibitory neurotransmission may affect processing in the presubiculum (e.g. Figure 5) but these experiments were a little underpowered and the analysis carried out could have been more comprehensively undertaken, as was done for other experiments in the manuscript.

Reviewer #3 (Public Review):

The authors set out to demonstrate the utility of functional ultrasound for evaluating changes in brain hemodynamics elicited acutely and subacutely by middle cerebral artery occlusion model of ischemic stroke in awake rats.<br /> Functional ultrasound affords a distinct set of tradeoffs relative to competing imaging modalities. Acclimatization of rats for awake imaging has proven difficult with most, and the high quality of presented data in awake rats is a major achievement. The major weakness of the approach is in its being restricted to single slice acquisitions, which also complicates registration of acquisition across multiple imaging sessions within the same animal. Establishing that awake imaging represents an advancement in relation to studies under anesthesia hinges upon establishment of the level of stress experienced by the animals in the course of imaging, i.e., requires providing data on the assessment of stress over the course of these long imaging sessions, which was not undertaken. This is particularly significant given that physical restraint has been established to be a particularly potent stressor in experimental models of stress. Assessment of the robustness of these measurements in a larger cohort of animals under varying conditions is of particular significance for supporting its wide applicability.

Reviewer #3 (Public Review):

In the present study, the authors investigated the effects of CIH on the swallowing and breathing responses to PICO stimulation. Their conclusion is that glutamatergic-cholinergic neurons from PICO are not only critical for the gating of post-inspiratory and swallow activity, but also play important roles in the generation of swallow motor patterns. There are several aspects that deserve the authors' attention and comments, mainly related to the study´s conclusions.

- The authors refer to PICO as the generator of post-inspiratory rhythm. However, evidence points to this region as a modulator of post-inspiratory activity rather than a rhythmogenic site (Toor et al., 2019 - 10.1523/JNEUROSCI.0502-19.2019; Oliveira et al., 2021 - 10.1016/j.neuroscience.2021.09.015). For example, sustained activation of PICO for 10 s barely affected the vagus or laryngeal post-inspiratory activity (Huff et al., 2023 - 10.7554/eLife.86103).

- The optogenetic activation of glutamatergic and cholinergic neurons from PICO evoked submental and laryngeal responses, and CIH changed these motor responses. Therefore, the authors proposed that PICO is directly involved in swallow pattern generation and that CIH disrupts the connection between PICO and SPG (swallow pattern generator). However, the experiments of the present study did not provide evidence about connections between these two regions nor their possible disruption after CIH, or even whether PICO is part of SPG.

- CIH affects several brainstem regions which might contribute to generating abnormal motor responses to PICO stimulation. For example, Bautista et al. (1995 - 10.1152/japplphysiol.01356.2011) documented that intermittent hypoxia induces changes in the activity of laryngeal motoneurons by neural plasticity mechanisms involving serotonin.

- To support the hypothesis that PICO is directly involved in swallow pattern generation the authors should perform the inhibition of Vglut2-ChAT neurons from PICO and then evoke swallow motor responses. If swallow is abolished when the neurons from this region are inhibited, it would indicate that PICO is crucial to generate this behavior.

- In almost all the data presented, the authors observed different patterns of changes in the motor submental and laryngeal responses to PICO activation, including that animals submitted to CIH (6%) presented a "normal" motor response. However, the authors did not discuss the possible explanations and functional implications of this variability.

- In Figure 4, the authors need to present low magnification sections showing the PICO transfected neurons as well as the absence of transfection in the ventral respiratory column. The authors could also check the scale since the cAmb seems very small.

- Finally, the title does not reflect the study. The present study did not demonstrate that PICO is a swallow pattern generator.

Reviewer #3 (Public Review):

Summary: The manuscript by Cullinan et al., uses ANAP-tmFRET to test the hypothesis that the NTD and CTD form a complex at rest and to probe these domains for acid-induced conformational changes. They find convincing evidence that the NTD and CTD do not have a propensity to form a complex. They also report these domains are parallel to the membrane and that the NTD moves towards, and the CTD away, from the membrane upon acidification.

Strengths:<br /> The major strength of the paper is the use of tmFRET, which excels at measuring short distances and is insensitive to orientation effects. The donor-acceptor pairs here are also great choices as they are minimally disruptive to the structure being studies.

Furthermore, they conduct these measurements over several positions with the N and C tails, both between the tails and to the membrane. Finally, to support their main point, MST is conducted to measure the association of recombinant N and C peptides, finding no evidence of association or complex formation.

Weaknesses:<br /> While tmFRET is a strength, using ANAP as a donor requires the cells to be unroofed to eliminate background signal. This causes two problems. First, it removes any possible low affinity interacting proteins such as actinin (PMID 19028690). Second, the pH changes now occur to both 'extracellular' and 'intracellular' lipid planes. Thus, it is unclear if any conformational changes in the N and CTDs arise from desensitization of the receptor or protonation of specific amino acids in the N or CTDs or even protonation of certain phospholipid groups such as in phosphatidylserine. The authors do mention this caveat. But until a new approach is developed, the concerns over disruption by unroofing/washing and relevance of the changes remain.

Upon acidification, NTD position Q14 moves towards the plasma membrane (Figure 8B). Q14 also gets closer to C515 or doesn't change relative to 505 (Figures 7C and B) upon acidification. Yet position 505 moves away from the membrane (Figure 8D). It's unclear how the NTD moves closer to the membrane, and to the CTD but yet the CTD moves further from the membrane. Future experiments or approaches may refine this model.

Reviewer #3 (Public Review):

Summary:<br /> The way an unavailable (distractor) alternative impacts decision quality is of great theoretical importance. Previous work, led by some of the authors of this study, had converged on a nuanced conclusion wherein the distractor can both improve (positive distractor effect) and reduce (negative distractor effect) decision quality, contingent upon the difficulty of the decision problem. In very recent work, Cao and Tsetsos (2022) reanalyzed all relevant previous datasets and showed that once distractor trials are referenced to binary trials (in which the distractor alternative is not shown to participants), distractor effects are absent. Cao and Tsetsos further showed that human participants heavily relied on additive (and not multiplicative) integration of rewards and probabilities.

The present study by Wong et al. puts forward a novel thesis according to which interindividual differences in the way of combining reward attributes underlie the absence of detectable distractor effect at the group level. They re-analysed the 144 human participants and classified participants into a "multiplicative integration" group and an "additive integration" group based on a model parameter, the "integration coefficient", that interpolates between the multiplicative utility and the additive utility in a mixture model. They report that participants in the "multiplicative" group show a negative distractor effect while participants in the "additive" group show a positive distractor effect. These findings are extensively discussed in relation to the potential underlying neural mechanisms.

Strengths:<br />  The study is forward-looking, integrating previous findings well, and offering a novel proposal on how different integration strategies can lead to different choice biases.<br />  The authors did an excellent job of connecting their thesis with previous neural findings. This is a very encompassing perspective that is likely to motivate new studies towards a better understanding of how humans and other animals integrate information in decisions under risk and uncertainty.<br />  Despite that some aspects of the paper are very technical, methodological details are well explained and the paper is very well written.

Weaknesses:<br />  The authors quantify the distractor variable as "DV - HV", i.e., the relative distractor variable. Do the conclusions hold when the distractor is quantified in absolute terms (as "DV", see also Cao & Tsetsos, 2023)? Similarly, the authors show in Suppl. Figure 1 that the inclusion of a HV + LV regressor does not alter their conclusions. However, the (HV + LV)*T regressor was not included in this analysis. Does including this interaction term alter the conclusions considering there is a high correlation between (HV + LV)*T and (DV - HV)*T? More generally, it will be valuable if the authors assess and discuss the robustness of their findings across different ways of quantifying the distractor effect.<br />  The central finding of this study is that participants who integrate reward attributes multiplicatively show a positive distractor effect while participants who integrate additively show a negative distractor effect. This is a very interesting and intriguing observation. However, there is no explanation as to why the integration strategy covaries with the direction of the distractor effect. It is unlikely that the mixture model generates any distractor effect as it combines two "context-independent" models (additive utility and expected value) and is fit to the binary-choice trials. The authors can verify this point by quantifying the distractor effect in the mixture model. If that is the case, it will be important to highlight that the composite model is not explanatory; and defer a mechanistic explanation of this covariation pattern to future studies.<br />  Correction for multiple comparisons (e.g., Bonferroni-Holm) was not applied to the regression results. Is the "negative distractor effect in the Additive Group" (Fig. 5c) still significant after such correction? Although this does not affect the stark difference between the distractor effects in the two groups (Fig. 5a), the classification of the distractor effect in each group is important (i.e., should future modelling work try to capture both a negative and a positive effect in the two integration groups? Or just a null and a positive effect?).

Reviewer #3 (Public Review):

Papalamprou et al sought to fine-tune existing tenogenic differentiation protocols to develop a robust multi-step differentiation protocol to induce tendon cells from human GMP-ready iPSCs. In so doing, they found that while existing protocols are capable of driving cells towards a syndetome-like fate, the resultant cultures contain highly heterogeneous cell populations with sub-optimal cell survival. Through single-cell transcriptomic analysis, they identify WNT signaling as a potential driver of an off-target neural population and show that inhibition of WNT signaling at the later 2 stages of differentiation can be used to promote higher efficiency of generation of syndetome-like cells.

This paper includes a useful paradigm for identifying transcriptional modulators of cell fate during differentiation and a clear example where transcriptional data can be used to guide the chemical modulation of a differentiation protocol to improve cell output. The paper's conclusions are mostly well supported by the data, but the image analysis and figure presentation need to be improved to strengthen the impact.

The data outlining the differences between the differentiation outcome of the two tested iPSCs is intriguing, but the authors fail to comment on potential differences between the two iPSC lines that could result in drastically different cell outputs from the same differentiation protocol. This is a critically important point, as the majority of the SCX+ cells generated from the 007i cells using their WNTi protocol were found in the FC subpopulation that failed to form from the 83i line under the same protocol. From the analysis of only these 2 cell lines in vitro, it is difficult to assess whether this WNTi protocol can be broadly used to generate tenogenic cells.

The authors make claims to changes in protein expression but fail to quantify either fluorescence intensity or percent cell expression from their immunofluorescence analyses to substantiate these claims. These claims are not fully supported by the data as presented as it is unclear whether there is increased expression of tendon markers at the protein level or more cells surviving the protocol. Additionally, in images where 3 channels are merged, it would be helpful to show individual channels where genes are shown in similar spectra (ie. Fig 2I SCX/MKX). Furthermore, the current layout and labelling scheme of Figure 4 makes it very difficult to compare conditions between SYN and SYNWNTi protocols.

Individual data points should also be presented for all qPCR experiments (ie. Fig 4A). Biological replicate information is missing from several experiments, particularly the immunofluorescence data, and it is unclear whether the qPCR data was generated from technical or biological replicates.

Reviewer #3 (Public Review):

Scheer and Bargmann use a combination of computational and experimental approaches in C.elegans to investigate the neuronal mechanisms underlying the regulation of foraging decisions by the state of arousal. They showed that, in C.elegans, the decision to leave food substrates is linked to a high arousal state, roaming, and that an increase in speed at different timescales preceded the food leaving decisions. They found that mutants that exhibit increased roaming also leave food substrates more frequently and that both behaviors can be triggered if food intake is inhibited. They further identify a set of chemosensory neurons that express the transduction channel tax-4 that couple the roaming state and the food-leaving decisions. The authors postulate that these neurons integrate foraging decisions with behavioral states and internal feeding cues.

The strength of the paper relies on using quantitative and detailed behavioral analysis over multiple time scales in combination with manipulation of genes and neuron to tackle the state-dependent control of behavioral decisions in C. elegans. The evidence is convincing, the analysis rigorous, and the writing is clear and to the point.

Reviewer #3 (Public Review):

Functional and anatomical studies of spinal circuitry in vertebrates have formed the basis of our understanding of neuronal control of movements. Larval zebrafish provide a simplified system for deciphering spinal circuitry. In this manuscript, the authors performed scRNAseq on spinal cord neurons in larval zebrafish, identifying major classes of neuronal and glial types. Through transcriptome analysis, they validated several key interneuron types previously implicated in zebrafish locomotion circuitry. The authors went beyond identifying transcriptional markers and explored synaptic molecules associated with the strength of motor output. They discovered molecular distinctions causally related to the unique physiology of primary motoneuron (PMn) function, which involves providing strong synaptic outputs for escapes and fast swimming. They defined functional 'cassettes' comprising specific combinations of voltage-dependent ion channel types and synaptic proteins, likely responsible for generating maximal motor outputs.

Comments on revised version:

"However, the reviewer interprets Figure 2c to show that Type I, not Type II, V2a is more highly recruited over the range of higher swimming speeds whereas we conclude just the opposite."

BRE: The preceding is the authors' response to the Reviewer's critique of Version 1 of the manuscript and refers to Figure 2C of Menelaou and McLean, Nat Commun. 10:4197, 2019; PMID: 31519892; PMCID: PMC6744451. Below the Reviewer's second critique elaborates on this point. The authors chose not to modify the manuscript further.

This is not what I would like to maintain in my previous report. Both Type I and Type II V2a neurons are recruited during very fast swimming (70 Hz). The degree of the de-recruitment of Type I V2a neurons during slower swimming (40-60 Hz) is larger than Type II. Thus, what I would like to say is that Type I V2a neurons are more analogous to PMns than Type II V2a neurons (Both PMns and SMns are recruited during very fast swimming, and PMns tend to be de-recruited during slower swimming).

In this sense, I don't like the author's way of relating Type II V2a neurons to escapes and very fast swimming. However, if the authors insist on the current form of the manuscript, I do not strongly object.

Reviewer #3 (Public Review):

Summary:<br /> This manuscript by Mac et al addresses the causes of pituitary dysfunction in patients with DAVID syndrome which is caused by mutations in the NFKB2 gene and leads to ACTH deficiency. The authors seek to determine whether the mutation directly leads to altered pituitary development, as opposed to an autoimmune defect, by using mutating human iPSCs and then establishing organoids that differentiate into pituitary tissue. They first seek to validate the system using a well-characterised mutation of the transcription factor TBX19, which also results in ACTH deficiency in patients. Then they characterise altered pituitary cell differentiation in mutant NFKB2 organoids and show that these lack corticotrophs, which would lead to ACTH deficiency.

Strengths:<br /> The conclusion of the paper that ACTH deficiency in DAVID syndrome is independent of an autoimmune input is strong.

Weaknesses:<br /> 1. The authors correctly emphasise the importance of establishing the validity of an iPSC-based model in being able to recapitulate in vivo dysfunctional pituitary development through characterisation of a TBX19 knock-in mutation. Whilst this leads to the expected failure of functional corticotroph differentiation, other aspects of the normal pituitary differentiation pathway upstream of corticotroph commitment seem to have been affected in surprising ways. In particular, the loss of LHX3 and PITX1 in TBX19 mutant organoids compared with wild type requires explanation, especially as the mutant protein would only be expected to be expressed in a small proportion of anterior pituitary lineage cells. If the developmental expression profile of key transcription factors in mutant organoids does not recapitulate that which occurs in vivo, any interpretation of the relevance of expression differences in the NFKB2 organoids to the mechanism(s) leading to corticotroph function in vivo has to be questionable. It is notable that the manipulation of iPSC cells used to generate mutants through CRISPR/Cas9 editing is not applied to the control iPSC line. It is possible that these manipulations lead to changes to the iPSC cells that are independent of the mutations introduced and this may change the phenotype of the cells. A better control would have been an iPSC line with a benign knock-in (such as GFP into the ROSA26 locus).

2. In the results section of the manuscript the authors acknowledge that hypothalamic tissue in the NFKB2 mutant organoid may be having an effect on the development of pituitary tissue. However, in the discussion the emphasis is entirely on pituitary autonomous mechanisms such as pituitary HESX1 expression or POMC gene regulation; in the conclusion of the abstract, a direct role for NFKB2 in pituitary differentiation is described. Whilst the data here may suggest a non-immune mediated alteration in pituitary function in DAVID syndrome, if this is due to alteration of the developing hypothalamus then this is not direct. A fuller discussion of the potential hypothalamic contribution and/or further characterisation of this aspect is warranted.

3. qRT-PCR data presented in Figure 6A shows negligible alteration of HESX1 expression at all time points in NFKB2 mutant organoids. This is not consistent with the 2-fold increase in HESX1 expression described in day 48 organoids found by bulk RNA sequencing. How do the authors reconcile these results and why is one result focused on in the discussion where a potential mechanism for a blockade of normal pituitary cell differentiation is suggested? Further confirmation of HESX1 expression is required.

4. Throughout the authors focus on POMC gene expression and ACTH antibody immunopositive as being indicative of corticotroph cell identity. In the human fetal pituitary melanotrophs are present and most ACTH antibodies are unable to distinguish these cells from corticotrophs. Is the antibody used specifically for ACTH rather than other products of the POMC gene? It is unlikely that all the ACTH-positive cells are melanotrophs, nevertheless, it is important to know what the proportions of the 2 POMC-positive cell types are. This could be distinguished by looking for the expression of NeuroD1, which would also define whether corticotrophs are committed but not fully differentiated in the NFKB2 mutant organoids. In support of an effect on corticotrophs, it is notable that CRHR1 expression (which would be expected to be restricted to this cell type) is reduced by 84% in bulk RNAseq data (Table 1) and this may be an indicator of the loss of corticotrophs in the model.

5. Notwithstanding the caveats about whether the organoid model recapitulates in vivo pituitary differentiation (see 1 above) and whether the bulk RNAseq accurately reflects expression levels (see 3 above), there are potentially some extremely interesting changes in gene expression shown in Table 1 which warrant further discussion. For example, there is a 25-fold reduction in POU1F1 expression which may be expected to reflect a loss of somatotrophs in the organoid (and possibly lactotrophs) and highlights the importance of characterising the effect of NFKB2 on other anterior pituitary cell types within the organoid. If somatotrophs are affected, this may be relevant to the organoids as a model of DAVID syndrome as GH deficiency has been described in some individuals with NFKB2 mutations. The huge increase in CGA expression may reflect a switch in cell fate to gonadotrophs, as has been described with a loss of TPIT in the mouse. These are examples of the changes that warrant further characterisation and discussion.

6. How do the authors explain the lack of effect of NFKB2 mutation on global NFKB signalling?

Reviewer #3 (Public Review):

In this study, the authors combine electrophysiology, behavioural analyses, and genetic editing techniques on the cotton bollworm to identify the molecular basis of sugar sensing in this species.

The larval and adult forms of this species feed on different plant parts. Larvae primarily consume leaves, which have relatively lower sugar concentrations, while adults feed on nectar, rich in sugar. Through a series of experiments-spanning electrophysiological recordings from both larval and adult sensillae, qPCR expression analysis of identified GRs from these sensillae, response profiles of these GRs to various sugars via heterologous expression in Xenopus oocytes, and evaluations of CRISPR mutants based on these parameters-the authors discovered that larvae and adults employ distinct GRs for sugar sensing. While the larva uses the highly sensitive GR10a, the adult uses the less sensitive and broadly tuned GR6. This differential use of GRs are in keeping with their behavioural ecology.

The data are cohesive and consistently align across the methodologies employed. They are also well presented and the manuscript is clearly written.

Reviewer #3 (Public Review):

Summary:<br /> SMN expression in non-neuronal cells, particularly in limb mesenchymal progenitors is essential for the proper growth of chondrocytes and the formation of adult NMJ junctions.

Strengths:<br /> The authors show copy numbers of smndelta7 in MPC influence NMJ structure.

Weaknesses:<br /> Functional recovery by FAP transplantation is not complete. Mesenchymal progenitors are heterogeneous, and how heterogeneity influences this study is not clear. Part of the main findings to show the importance of SMN expression in non-neuronal cells is partly published by the same group (Kim et al., JCI Insight 2022). In the study, the authors used Dpp4(+) cells. The difference between the current study and the previous study is not so clear.

Reviewer #3 (Public Review):

The authors sought to directly compare the predictions of two models of somatosensory processing: The attenuation model, which states that the sensation of touch on one hand is reduced when it is the predictable result of an active movement by the other hand; and the enhancement model, which states that the sensation of touch is actually increased, as long as the active hand does not receive touch stimultaneously with the passive hand (no double stimulation). The authors achieved their aims, with results clearly demonstrating (1) attenuation in the case of self touch, (2) that previously-observed enhancement is a consequence of the comparison condition (false enhancement), and (3) that attenuation involves predictive mechanisms and does not result simply from double stimulation. These findings, and the methodology, should particularly impact future studies of perceptual attenuation, sensory prediction error, and motor control more generally. The opposite conclusions obtainable by selecting different comparison conditions is particularly striking.

Experiment 1 affirms that a touch to the passive finger caused by the active finger tapping a force sensor is perceived as weaker (attenuated) compared to a baseline not involving the active finger, but that if double stimulation is prevented (active finger moves, but no contact), neither attenuation nor enhancement occurs. Experiment 2 includes the three original conditions, plus the no-go condition used as a comparison in these earlier studies. Results suggest that the comparisons used by previous studies would result in the false appearance of enhancement. Finally, Experiment 3 tests the hypothesis that the lack of attenuation in the no-contact condition is due to the absence of double stimulation rather than predictive mechanisms. When contact and no-contact trials were mixed in an 80:20 ratio, such that participants would form predictions about the consequence of their active finger movement even if some trials lacked contact. In this case, attenuation was observed for both contact and no-contact trials, supporting the idea that attenuation is related to predictive processes linked to moving the active finger, and is not a simple consequence of double stimulation.

The methodology and analysis plans for all three experiments were pre-registered prior to data collection. We can therefore be very confident that the results were not influenced by hypotheses developed only after seeing the data. The three experiments were each performed in a new set of participants. Experiments 2 and 3 included conditions that replicated the Experiment 1 effects, allowing us to be very confident that the results are robust.

While the study has significant strengths, some aspects of the interpretation need to be clarified. In particular, the authors' interpretation depends on the idea that attenuation is absent in the no-contact condition because this action-sensory consequence relationship is an "arbitrary mapping." It is not clear what makes it arbitrary. The self-touch contact condition could also be considered somewhat arbitrary and different from real self-touch; the 2N test force was triggered by the right finger tapping a force sensor. If participants' tapping forces were recorded, it would be useful to include this information, particularly about how variable participants' taps were. In other words, unlike real self-touch, in this paradigm the force of the active finger tap did not affect the force delivered to the passive finger. One additional potential weakness is that participants' vision was occluded in Experiment 3, but not in Experiments 1 and 2. The authors do not discuss whether this difference could confound any of the analyses that compare results across experiments.

Reviewer #3 (Public Review):

I very much enjoyed reading this paper by Shashwat Mishra and team from Joy Alcedo's and from Queelim Ch'ng's laboratories dissecting how sensory signals regulate reproduction in worms. The mechanisms by which sensory inputs affect the function of the germline, the balance between growth and differentiation within this tissue, are of broad interest not only to those interested in reproduction and differentiation, but also to those interested in the mechanisms of plasticity that enable organisms to adjust to changing environmental conditions. These mechanisms are only now beginning to be characterized. Here the focus is on the role of insulin signals expressed in sensory neurons. This work builds on previous findings by the Alcedo lab that sensory perception of bacterial-type dependent signals regulates C. elegans lifespan. Here their focus is on the effects on reproduction, and on the communication of that information by insulin-like signals.

Worms have a huge family of 40 insulin-like genes, which the Alcedo and Ch'ng labs have been studying for many years. The paper starts with the interesting premise that the brood size of the worms is food type dependent. The authors show that this is due to effects on the timing of the onset of oogenesis during larval development (which constrains the size of the pool of sperm available for subsequent oocyte fertilization) as well as on effects on the rate of oocyte fertilization during adulthood. Using clever timing for food switching, they show that the effects on oogenesis onset and on fertilization rate are separable. In addition, these effects did not appear to be merely the outcome of indirect effects of food ingestion, but were, instead, at least in part, due to the perception of environmental information by specific sensory neurons. Using mutants affecting transduction of sensory information in specific neurons and genetic ablation of specific neurons, the authors show that the onset of oogenesis and the rate of reproduction were controlled by different sensory neurons, ASJ and AWA, respectively. One of these neurons, ASJ, transmitted environmental information via the ins-6 neuropeptide.

Altogether, the paper advances our understanding of how environmental determinants influence reproduction.

Reviewer #3 (Public Review):

This is a clearly written report on experiments examining apoptosis and efferocytosis gene alterations in the very early stages of cutaneous wound healing. The authors have identified a number of differentially expressed genes related to apoptosis and efferocytosis in fibroblasts, neutrophils, dendritic cells and monocytes/macrophages. Additional functional experiments were carried out which show that inhibiting efferocytosis pathways can alter different aspects of wound healing, depending on the pathway that is targeted. The scRNA-seq data in mouse wounds is rigorous and follow-up functional studies in mice were done, which is an overall strength of the work. The main weaknesses were related to small sample sizes for some experiments and some conclusions that were not supported by strong data. Overall, this is interesting work that could be bolstered with additional supporting data for some key experiments.

1) The authors suggest in several places that efferocytosis must be occurring rapidly since the number of apoptotic cells are not high in their samples. There are issues with this conclusion in my opinion. They never do show that there is an increase in apoptotic cells in the wounds, which then go down (which would be a sign that the cells are being cleared via efferocytosis. In addition, they are looking for apoptotic cells at very early time points (24-48 hours), times at which large numbers of apoptotic cells would not be expected. As an example, neutrophil infiltration peaks at 24-48 hours and efferocytosis of apoptotic neutrophils would be expected after that. Other types of apoptotic cells would likely be cleared even later. Finally, several of the panels showing apoptotic cells were done with a very small number of samples (1-3 per group) in some cases so it is unclear how rigorous the data are. I would recommend that the authors at the very least soften the wording related to these conclusions and discuss the limitations of their experimental design; ideally data from more samples would be included to provide clear support those statements.

2) The human RNA-seq data is also quite limited, as non-diabetic wound tissue was all from one patient. Again, this limitation should be acknowledged. Also, there are some important published papers by Sashwati Roy's group indicating that there are defects in efferocytosis in diabetic wounds, which may go against what the authors are showing here to some degree. Discussion of the authors' work in relation to these other studies should be discussed.

3) For anti-Axl and anti-Timd4 experiments, the authors conclude that inhibition of Axl does not affect TUNEL+ cells and that Timd4 does not affect reepithelialization. However, in some cases the sample size was only 3 mice per group when measuring these parameters. That is a very small number of samples to draw conclusions about apoptotic cells or reepithelialization since these parameters are key for the overall conclusions of the experiments. Given that these are key data, it would be important to include more than n=3. Additionally, as stated above, a time point later than 24 h may be necessary to actually see changes in apoptotic cells.

4) In Fig 6, there look to be many more TUNEL+ cells in the wound bed of IgG control samples compared to anti-Timd4-treated samples, which contradicts the graph. Perhaps the authors could clarify where they were taking their measurements for panels with image analysis results. Another question related to this experiment is how it is possible that efferocytosis is so drastically different yet there are no changes in wound healing (this is one reason why a larger sample size for reepithelialization may be critical) - this would seem to suggest that efferocytosis is not important in wound healing, which is confusing. Further discussion on this might be useful.

Reviewer #3 (Public Review):

Casp11 plays an important role in host defense against a wide range of pathogens; however, it also promotes autoinflammatory disorders when dysregulated. Unlike other ASC-dependent receptors, Casp11 forms a non-canonical inflammasome via LPS-indued self-assembly. Here, Brodsky and colleagues report that the catalytic activity of casp11 is required to form LPS-induced "SMOCs."

Here are my concerns/questions:

• I'm having some difficulty understanding the logic of Figure 5 in determining cis processing. It is an inverse of figure 4, and in my view, provides further evidence of trans processing. A better experiment would to be use WT-citrine tagged protein with catalytic dead mcherry and image them together. This would show WT cis processing occurs faster than trans processing as citrine specks should appear earlier than the mCherry ones. Can also do colocalization and FRET-based assays with the pair.

• Do those casp11 specks still contain CARDs?- i.e. is the second cleavage necessary for speck formation? Is CARD necessary at all? Would adding the TEV site at CDL and b/w p20 and p10 rescue? i.e. trans-activate?

• What are the equations that fit experimental data points and R2 for? E.g. Figure 1E. What are the parameters being fitted/compared and how are those interpreted? A table of fitted values and proper interpretation should be provided.

Reviewer #3 (Public Review):

Combining dynamical modelling and recent findings of mouse brain anatomy, Ding et al. developed a cell-type-specific connectome-based dynamical model of the mouse brain underlying working memory. The authors find that there is a gradient across the cortex in terms of whether mnemonic information can be sustained persistently or only transiently, and this gradient is negatively correlated to the local density of parvalbumin (PV) positive inhibitory cells but positively correlated with mesoscale-defined cortical hierarchy. In addition, weighing connectivity strength by PV density at target areas provides a more faithful relationship between input strength and delay firing rate. The authors also investigate a model where cortical persistent activity can only be sustained with thalamus input intact, although this result is rather separate from the rest of the study. The authors then use this model to test the causal contributions of different areas to working memory. Although some of the in silico perturbations are consistent with existing experimental data, others are rather surprising and need to be further discussed. Finally, the authors investigate patterns of attractor states as a result of different local and long-range connections and suggest that distinct attractor states could underlie different task demands.

The importance of PV density as a predictor for working memory activity patterns in the mouse brain is in contrast to recent computational findings in the primate brain where the number of spines (excitatory synapses per pyramidal cell) is the key predictor. This finding reveals important species differences and provides complementary mechanisms that can shape distributed patterns of working memory representation across cortical regions. The method of biologically-based near-whole-brain dynamical modeling of a cognitive function is compelling, and the main conclusions are mostly well supported by evidence. However, some aspects of the method, result, and discussion need to be clarified and extended.

1. Based on existing anatomical data, the authors reveal a negative correlation between cortical hierarchy (defined by mesoscale connectivity; this concept needs to be explicitly defined in the Results session, not just in the Method section) and local PV density (Fig. 1). In the dynamical model, the authors find that working memory activity is positively (and strongly) correlated with cortical hierarchy and negatively (and less strongly) correlated with PV cell density (Fig. 2), and conclude that working memory activity depends on both. But could the negative correlation between activity and PV density simply result from the inherent relationship between hierarchy and PV density across regions? To strengthen this result, the authors should quantify the predictive power of local PV density on working memory activity beyond the predictive power of cortical hierarchy.

2. In Fig. 4, the authors find that cell-type-specific graph measures more accurately predict delay-period firing rates. Specifically, the authors weigh connections with a cell-type-projection coefficient, which is smaller when the PV cell fraction is higher in the target area. Considering that local PV cell fraction is already correlated with delay activity patterns, weighing the input with the same feature will naturally result in a better input-output relationship. This result will be strengthened if there is a more independent measure of cell-type-projection coefficient, such as the spine density of PV vs excitatory cells across regions, or even the percentage of inhibitory versus excitatory cells targeted by upstream region (even just for an example set of brain regions).

3. The authors aim to identify a core subnetwork that generates persistent activity across the cortex by characterising delay activity as well as the effects of perturbations during the stimulus and delay period. Consistent with existing data, the model identifies frontal areas and medial orbital areas as core areas. Surprisingly, areas such as the gustatory area are also part of the core areas. These more nuanced predictions from the model should be further discussed. Also surprisingly, the secondary motor cortex (MOs), which has been indicated as a core area for short-term memory and motor planning by many existing studies is classified as a readout area. The authors explain this potential discrepancy as a difference in task demand. The task used in this study is a visual delayed response task, and the task(s) used to support the role of MOs in short-term memory is usually a whisker-based delayed response task or an auditory delay response task. In all these tasks, activity in the delay period is likely a mixture of sensory memory, decision, and motor preparation signals. Therefore, task demand is unlikely the reason for this discrepancy. On the other hand, motor effectors (saccade, lick, reach, orient) could be a potential reason why some areas are recruited as part of the core working-memory network in one task and not in another task. The authors should further discuss both of these points.

4. As a non-expert in the field, it is rather difficult to grasp the relationship between the results in Fig. 7 and the rest of the paper. Are all the attractor states related to working memory? If so, why are the core regions for different attractor states so different? And are the core regions identified in Fig. 5 based on arbitrary parameters that happen to identify certain areas as core (PL)? The authors should at least further clarify the method used and discuss these results in the context of previous results in this study.

Reviewer #3 (Public Review):

The paper presents the novel neuro-simulator BrainPy, which introduces several new concepts compared to existing simulators such as NEST, Brian, or GeNN: 1) a modular and Pythonic interface, which avoids having to use a fixed set of neural/synaptic models or using a textual equation-oriented interface; 2) a common platform for simulation, training, and analysis; 3) the use of just-in-time compilation using JAX/XLA, allowing to transparently access CPU, GPU, and TPU platforms. While none of these features is new per se (apart from TPU support, as far as I know), their combination provides an interesting new direction for the design of neuro-simulators.

Overall, BrainPy is a nice and valuable addition to the already overwhelming list of neuro-simulators, which all have their own advantages and drawbacks and are diversely maintained. The main strengths of BrainPy are 1) its multi-scale modular interface and 2) the possibility for the user to transparently use various hardware platforms for the simulation. The paper succeeds in explaining those two aspects in a convincing manner. The paper is also very didactic in explaining the different strengths and weaknesses of the current simulators, as well as the benefits of JIT compilation.

One potential issue is that the scope of the neuro-simulator is not very clearly explained and the target audience is not well defined: is BrainPy primarily intended for computational neuroscientists or for neuro-AI practitioners? The simulator offers very detailed neural models (HH, fractional order models), classical point-models (LIF, AdEx), rate-coded models (reservoirs), but also deep learning layers (Conv, MaxPool, BatchNorm, LSTM). Is there an advantage to using BrainPy rather than PyTorch for purely deep networks? Is it possible to build hybrid models combining rate-coded reservoirs or convnets with a network of HH neurons? Without such a hybrid approach, it is unclear why the deep learning layers are needed. In terms of plasticity, only external training procedures are implemented (backpropagation, FORCE, surrogate gradients). No local plasticity mechanism (Hebbian learning for rate-coded networks, STDP and its variants for spiking networks) seems to be implemented, apart from STP. Is it a planned feature? Appendix 8 refers to `bp.synplast.STDP()`, but it is not present in the current code (https://github.com/brainpy/BrainPy/tree/master/brainpy/_src/dyn/synplast). Spiking networks without STDP are not going to be very useful to computational neuroscientists, so this suggests that the simulator targets primarily neuro-AI, i.e. AI researchers interested in using spiking models in a machine learning approach. However, it is unclear why they would be interested in HH or Morris-Lecar models rather than simpler LIF neurons.

A second weakness of the paper concerns the demos and benchmarks used to demonstrate the versatility and performance of BrainPy, which are not sufficiently described. In Fig. 4, it is for example not explained how the reservoirs are trained (only the readout weights, or also the recurrent ones? Using BPTT only makes sense when the recurrent weights are also trained.), nor how many neurons they have, what the final performance is, etc. The comparison with NEURON, NEST, and Brian2 is hard to trust without detailed explanations. Why are different numbers of neurons used for COBA and COBAHH? How long is the simulation in each setting? Which time is measured: the total time including compilation and network creation, or just the simulation time? Are the same numerical methods used for all simulators? It would also be interesting to discuss why the only result involving TPUs (Fig 8c) shows that it is worse than the V100 GPU. What could be the reason? Are there biologically-realistic networks that would benefit from a TPU? As the support for TPUs is a major selling point of BrainPy, it would be important to investigate its usage further.

Reviewer #3 (Public Review):

In this paper, Jiahui and colleagues propose a new method for learning individual-specific functional resonance imaging (fMRI) patterns from naturalistic stimuli, extending existing hyperalignment methods. They evaluate this method - enhanced connectivity hyperalignment (CHA) - across four datasets, each comprising between nine (Raiders) and twenty (Budapest, Sraiders) participants.

The work promises to address a significant need in existing functional alignment methods: while hyperalignment and related methods have been increasingly used in the field to compare participants scanned with overlapping stimuli (or lack thereof, in the case of resting state data), their use remains largely tied to naturalistic stimuli. In this case, having non-overlapping stimuli is a significant constraint on application, as many researchers may have access to only partially overlapping stimuli or wish to compare stimuli acquired under different protocols and at different sites.

It is surprising, however, that the authors do not cite a paper that has already successfully demonstrated a functional alignment method that can address exactly this need: a connectivity-based Shared Response Model (cSRM; Nastase et al., 2020, NeuroImage). It would be relevant for the authors to consider the cSRM method in relation to their enhanced CHA method in detail. In particular, both the relative predictive performance as well as associated computational costs would be useful for researchers to understand in considering enhanced CHA for their applications.

With this in mind, I noted several current weaknesses in the paper:

First, while the enhanced CHA method is a promising update on existing CHA techniques, it is unclear why this particular six step, iterative approach was adopted. That is: why was six steps chosen over any other number? At present, it is not clear if there is an explicit loss function that the authors are minimizing over their iterations. The relative computational cost of six iterations is also likely significant, particularly compared to previous hyperalignment algorithms. A more detailed theoretical understanding of why six iterations are necessary-or if other researchers could adopt a variable number according to the characteristics of their data-would significantly improve the transferability of this method.

Second, the existing evaluations for enhanced CHA appear to be entirely based on image-derived correlations. That is, the authors compare the predicted image from CHA with the ground-truth image using correlation. While this provides promising initial evidence, correlation-based measures are often difficult to interpret given their sensitivity to image characteristics such as smoothness. Including Cronbach's alpha reliability as a baseline does not address this concern, as it is similarly an image-based statistic. It would be useful to see additional predictive experiments using frameworks such as time-segment classification, inter-subject decoding, or encoding models.

Addressing these concerns and considering cSRM as a comparison model would significantly strengthen the paper. There are also notable strengths that I would encourage the authors to further pursue. In particular, the authors have access to a unique dataset in which the same Raiders of the Lost Ark stimulus was scanned for participants within the Budapest (SRaiders) dataset as well as non-overlapping participants in the Raiders dataset. Exploring the relative performance for cross-movie prediction within a dataset as compared to a shared movie prediction across datasets is particularly interesting for methods development. I would encourage the authors to explicitly report results in this framework to highlight both this unique testing structure as well as the performance of their enhanced CHA method.

Overall, I share the authors' enthusiasm for the potential of cross-movie, cross-dataset prediction, and I believe that methods such as enhanced CHA are likely to significantly improve our ability to make these comparisons in the near future. At present, however, I find that the theoretical and experimental support for enhanced CHA is incomplete. It is therefore difficult to assess how enhanced CHA meets its goals or how successfully other researchers would be able to adopt this method in their own experiments.

Reviewer #3 (Public Review):

Summary:<br /> Variants in the UBA5 gene are associated with rare developmental and epileptic encephalopathy, DEE44. This research developed a system to assess in vivo and in vitro genotype-phenotype relationships between UBA5 allele series by humanized UBA5 fly models and biochemical activity assays. This study provides a basis for evaluating current and future individuals afflicted with this rare disease.

Strengths:<br /> The authors developed a method to measure the enzymatic reaction activity of UBA5 mutants over time by applying the UbiReal method, which can monitor each reaction step of ubiquitination in real time using fluorescence polarization. They also classified fruit fly carrying humanized UBA5 variants into groups based on phenotype. They found a correlation between biochemical UBA5 activity and phenotype severity.

Weaknesses:<br /> In the case of human DEE44, compound heterozygotes with both loss-of-function and hypomorphic forms (e.g., p.Ala371Thr, p.Asp389Gly, p.Asp389Tyr) may cause disease states. The presented models have failed to evaluate such cases.

Reviewer #3 (Public Review):

This paper seeks to characterize finger enslavement impairment after stroke-"the unwanted coactivation of non-intended fingers in individuated finger movements." In the past, three possible neuromuscular mechanisms contributing to finger enslavement were suggested: passive musculotendon properties, an intrusion of flexor bias, and a loss of complexity in finger control repertoire. To tease apart these factors, the authors simultaneously recorded all five fingertip forces using a sensitive isometric force measurement device, which allowed characterizing patterns of enslavement for all fingers in a variety of instructed tasks. This novel experimental design opened new opportunities to study finger enslavement in more detail. To analyze this multi-dimensional dataset, new metrics were introduced, and many detailed analyses were conducted. Here is a brief account of the important results as best as I can summarize them.

1. Gross finger individuation ability is lower in the paretic hand of stroke patients than in non-paretic or healthy hands. Enslavement worsens with the severity of overall stroke impairment.<br /> 2. The enslavement patterns - unintended finger forces as functions of an instructed force in a different finger - show smaller "complexity" in paretic than nonparetic hands. I.e., the directions of unintended finger forces in the paretic hand remain similar across various instructed tasks. This reduced complexity also correlates with the severity of stroke.<br /> 3. The enslavement patterns show larger magnitude differences in the paretic than non-paretic hands; i.e., the unintended fingers' forces show a larger shift when comparing two instructed force directions in a paretic finger.<br /> 4. Finger force biases exist in paretic and non-paretic hands and correlate with the severity of stroke. Biases are more pronounced in flexion than ab/adduction direction.<br /> 5. The resting hand posture does not correlate with finger force bias or enslavement patterns.<br /> 6. Finger force biases correlate with enslavement patterns in the paretic hand, but not in the non-paretic hand.<br /> 7. Flexor bias (force biases in flexor direction) does not correlate with gross individuation ability in the ab/adduction direction in the non-paretic hand, but it correlates with the ab/adduction individuation ability in the paretic hand.<br /> 8. Finger force biases do not correlate with directional differences in enslavement patterns on either hand. However, biases correlate with the magnitude of force shift in the enslavement pattern.<br /> 9. The intrusion of flexor bias (difference of finger force biases in paretic and non-paretic hands) does not correlate with directional differences in enslavement patterns in either hand, but it correlates with force shifts in enslavement patterns in both hands.<br /> 10. More principal components (in principal component analysis, PCA) are required to explain similar levels of variance of enslavement patterns in paretic than non-paretic hands.

Taken together, the authors use these results to claim that: 1) enslavement impairment is unrelated to passive biomechanical properties, and 2) loss of complexity and flexor bias both contribute to enslavement, but possibly via different mechanisms.

The first argument is supported by the result that resting hand posture does not explain gross individuation ability or enslavement patterns. Although these results are valid, biomechanical contributions are not ruled out altogether in my opinion. The experiment starts from the optimal posture in which minimal finger forces are recorded in a relaxed state, essentially an "equilibrium" posture where all forces from muscles, ligaments, and other soft tissues are balanced. However, this equilibrium posture alone does not represent potential asymmetry in passive biomechanical properties (e.g., at equilibrium, flexion may face less stiffness than extension), nor does it take into account complex interactions between muscles of the hand. A simple finger force requires the co-activation of several intrinsic and extrinsic hand muscles as well as those of the wrist, some of which may be weak, shortened, stiff, painful, etc. Even if neural activity is present, compensation from other muscles may be needed, which may lead to unintended forces in other fingers. Although my "hunch" agrees with the author's claim that neural contributions outweigh biomechanical factors in enslavement, I believe resting posture on its own cannot account for "all" biomechanical factors. Additionally, the results comparing biases in paretic and non-paretic hands (line 389) are unrelated to biomechanics. It is reasonable to believe that the passive biomechanical properties of the paretic hand are different from those of the non-paretic hand if long enough time has passed since the stroke. So biomechanical of one hand is not representative of the other hand. Even if biases in the non-paretic hand could explain those in the paretic hand, I find it hard to extend the conclusion that biomechanics is a factor.

The authors further presented detailed analyses to tease apart contributions of flexor bias and loss of complexity to enslavement. The flexor bias is straightforward to define, and its correlation with enslavement (or the absence of correlation in the non-paretic hand) is supported by the results. However, the arguments about complexity are less straightforward. Two separate definitions of complexity are used: one is the directional differences between enslavement patterns, and the other is based on the number of principal components. This is one source of confusion as to which definition is used when referring to "loss of complexity". Nonetheless, both complexities are shown to decrease with the severity of stroke. The first type of complexity is also shown to be uncorrelated to flexor bias. However, I did not find evidence among the results that directly linked complexity to enslavement. Could complexity, similar to biomechanical properties, be ruled out? This paper provides no evidence for or against the contribution of complexity to enslavement.

My last point is about the neural correlates of these characteristics. The authors frequently use the terms "low-level", "subcortical", "top-down cortical", etc. throughout the paper, while the results are exclusively at a behavioral level. This issue is also present in the abstract where the authors state that: "we aim to tease apart the contributions of lower biomechanical, subcortical constraints, and top-down cortical control to these patterns in both healthy and stroke hands"; however, the methods and the results are unrelated to neural aspects of control, and the authors only refer to other studied to link these behavioral effects to "potential" neural causes. Further, the intrusion of flexor bias is usually associated with "subcortical" neural pathways in Results. The authors have properly discussed these possible neural correlates in the Discussion, but mentioning these terms in the Results is unjustified and unsupported by the results or the methods. This paper does not provide any standalone evidence to directly link complexity or bias to their neural correlates.

Comments on the representational distance matrices (RDM):<br /> Two types of RDM were defined: "by-Finger" RDM (Fig 4A), and "by-Target Direction" RDM (Fig 4D). While I understand the by-Finger RDM and it physically makes sense to me, I cannot fully wrap my head around the by-Target RDM. I leave the interpretation of these results to the reader.

The distinction between the Euclidean and Angular distance is also vague to me. Angular distance is a valid similarity measure for the directions of two vectors and it is unrelated to the norms of vectors. However, Euclidean distance is not fully independent of the Angular distance as the authors claim; it changes with both the norms of the two vectors and the angle between them. If the angular distance is small, then Euclidian distance mostly represents norm differences, but the statement "Euclidean distances are sensitive to the length difference between two force vectors but insensitive to direction differences" is not generally correct. This issue is particularly important because the averaging of distances (see my next point) masks details of individual distance values, which hinders the interpretation of the results.

The enslavement patterns and RDMs are potentially valuable metrics, however, the way they are condensed in the final statistical analyses reduces their value. The way I understand it, all elements of the RDM matrix are averaged into a single value. This averaging masks the details of individual pairs of comparisons, which not only reduces the information resolution but also seriously hinders rigorous analysis and interpretation of the results.

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Reviewer #3 (Public Review):

In this study, the authors investigate the effects of Notch pathway inactivation on the termination of Drosophila neuroblasts at the end of development. They find that termination is delayed, while temporal patterning progression is slowed down. Forcing temporal patterning progression in a Notch pathway mutant restores correct timing of neuroblast elimination. Finally they show that Imp, an early temporal patterning factor promotes Delta expression in neuroblast lineages. This indicates that feedback loops between temporal patterning and lineage-intrinsic Notch activity fine tunes timing of early to late temporal transitions and is important to schedule NB termination at the end of development.

The study adds another layer of regulation that finetunes temporal progression in Drosophila neural stem cells. This mechanism appears to be mainly lineage intrinsic - Delta being expressed from NBs and their progeny, but also partly niche-mediated - Delta being also expressed in glia but with a minor influence. Together with a recent study (PMID: 36040415), this work suggests that Notch signaling is a key player in promoting temporal progression in various temporal patterning system. As such it is of broad interest for the neuro-developmental community.

Strengths<br /> The data are based on genetic experiments which are clearly described and mostly convincing. The study is interesting, adding another layer of regulation that finetunes temporal progression in Drosophila neural stem cells. This mechanism appears to be mainly lineage intrinsic - Delta being expressed from NBs and their progeny, but also partly niche-mediated - Delta being also expressed in glia but with a minor influence. A similar mechanism has been recently described, although in a different temporal patterning system (medulla neuroblasts of the optic lobe - PMID: 36040415). It is overall of broad interest for the neuro-developmental community.

Weaknesses<br /> The mechanisms by which Notch signaling regulates temporal patterning progression are not investigated in details. For example, it is not clear whether Notch signaling directly regulates temporal patterning genes, or whether the phenotypes observed are indirect (for example through the regulation of the cell-cycle speed). The authors could have investigated whether temporal patterning genes are directly regulated by the Notch pathway via ChIP-seq of Su(H) or the identification of potential binding sites for Su(H) in enhancers. A similar approach has been recently undertaken by the lab of Dr Xin Li, to show that Notch signaling regulates sequential expression of temporal patterning factors in optic lobes neuroblasts (PMID: 36040415), which exhibit a different temporal patterning system than central brain neuroblasts in the present study. As such, the mechanistic insights of the study are limited.

Reviewer #3 (Public Review):

Summary:<br /> In their paper, Li et al. investigate the transcriptome of satellite cells obtained from different muscle types including hindlimb, diaphragm, and extraocular muscles (EOM) from wild-type and G93A transgenic mice (end-stage ALS) in order to identify potential factors involved in the maintenance of the neuromuscular junction. The underlying hypothesis is that since EOMs are largely spared from this debilitating disease, they may secrete NMJ-protective factors. The results of their transcriptome analysis identified several axon guidance molecules including the chemokine Cxcl12, which are particularly enriched in EOM-derived satellite cells. Transduction of hindlimb-derived satellite cells with AAV encoding Cxcl12 reverted hindlimb-derived myotubes from the G93A mice into myotubes sharing phenotypic characteristics similar to those of EOM-derived satellite cells. Additionally, the authors were able to demonstrate that EOM-derived satellite cell myotube cultures are capable of enhancing axon extensions and innervation in co-culture experiments.

Strengths:<br /> The strength of the paper is that the authors successfully isolated and purified different populations of satellite cells, compared their transcriptomes, identified specific factors released by EOM-derived satellite cells, overexpressed one of these factors (the chemokine Cxcl12) by AAV-mediated transduction of hindlimb-derived satellite cells. The transduced cells were then able to support axon guidance and NMJ integrity. They also show that administration of Na butyrate to mice decreased NMJ denervation and satellite cell depletion of hind limbs. Furthermore, the addition of Na Butyrate to hindlimb-derived satellite cell myotube cultures increased Cxcl12 expression. These are impressive results providing important insights for the development of therapeutic targets to slow the loss of neuromuscular function characterizing ALS.

Weaknesses:<br /> Several important aspects have not been addressed by the authors, these include the following points which weaken the conclusions and interpretation of the results.

a) Na Butyrate was shown to extend the survival of G93A mice by Zhang et al. Na butyrate has a variety of biological effects, for example, anti-inflammatory effects inhibit mitochondrial oxidative stress, positively influence mitochondrial function, is a class I / II HDAC inhibitor, etc. What is the mechanism underlying its beneficial effects both in the context of mouse muscle function in the ALS G93A mice and in the in vitro myotube assay? Cytokine quantification as well as histone acetylation/methylation can be assessed experimentally and this is an important point that has not been appropriately investigated.

b) In the context of satellite cell characterization, on lines 151-152 the authors state that soleus muscles were excluded from further studies since they have a higher content of slow twitch fibers and are more similar to the diaphragm. This justification is not valid in the context of ALS as well as many other muscle disorders. Indeed, soleus and diaphragm muscles contain a high proportion of slow twitch fibers (up to 80% and 50% respectively) but soleus muscles are more spared than diaphragm muscles. What makes soleus muscles (and EOMs) more resistant to ALS NMJ injury? Satellite cells from soleus muscles need to be characterized in detail as well.

Furthermore, EOMs are complex muscles, containing many types of fibers and expressing different myosin heavy chain isoforms and muscle proteins. The fact that in mice both the globular layer and orbital layers of EOMs express slow myosin heavy chain isoform as well as myosin heavy chain 2X, 2A, and 2B (Zhou et al., 2010 IOVIS 51:6355-6363) also indicates that the sparing is not directly linked to the fast or slow twitch nature of the muscle fiber. This needs to be considered.

c) In the context of myotube formation from cultured satellite cells on lines 178-179 the authors stained the myotubes for myosin heavy chain. Because of the diversity of myosin heavy chain isoforms and different muscle origins of the satellite cells investigated, the isoform of myosin heavy chain expressed by the myotubes needs to be tested and described. It is not sufficient to state anti-MYH.

d) The original RNAseq results have not been deposited and while it is true that the authors have analyzed the results and described them in Figures 6 and 7 and relative supplements, the original data needs to be shown both as an xls list as a Volcano plots (q value versus log2 fold change). This will facilitate the independent interpretation of the results by the readers as some transcripts may not be listed. As presented it is rather difficult to identify which transcripts aside from Cxcl12 are commonly upregulated. Can the data be presented in a more visual way?

e) There is no section describing the statistical analysis methods used. In many figures, more than 2 groups are compared so the authors need to use an ANOVA followed by a post hoc test.

The authors have achieved their aim in showing that satellite cells derived from EOMs have a distinct transcriptome and that this may be the basis of their sparing in ALS. Furthermore, this work may help develop future therapeutic interventions for patients with ALS.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript uses a combination of evolutionary approaches and structural/dynamics observations to provide mechanistic insights into the adaptation of the Spike protein during the evolution of variants.

Strengths:<br /> Very well-written text, pleasant and well-described pictures, and didactical and clear description of the methods.<br /> The citation of relevant similar results with different approaches is of note.<br /> Comparing the calculated scores with previous experimentally obtained data is one of the strongest points of the manuscript.

Weaknesses:<br /> A longer discussion of how the 19 orthologous coronavirus sequences were chosen would be helpful, as the rest of the paper hinges on this initial choice.<br /> The 'reasonable similarity' with previously published data is not well defined, nor there was any comment about some of the residues analyzed (namely 417-484).<br /> There seem to be no replicas of the MD simulations, nor a discussion of the convergence of these simulations.<br /> A more detailed description of the equilibration and production schemes used in MD would be helpful.<br /> Moreover, there is no discussion of how the equilibration procedure is evaluated, in particular for non-experts this would be helpful in judging the reliability of the procedure.

Reviewer #3 (Public Review):

In this study, Fleck and colleagues investigate the effects of auxin exposure on Drosophila melanogaster adults, focusing their analysis on feeding behavior, fatty acid metabolism, and oogenesis. The motivation for the study is that auxin-inducible transcription systems are now being used by Drosophila researchers to drive transcription using the Gal4-UAS system as a complement to Gal80ts versions of the system. I found the study to be carefully done. This study will be of interest to researchers using the Drosophila system, especially those focusing on fatty acid metabolism or physiology. The authors might address the following minor points.

1) Auxin, actually 1-naphthaleneaceid acid here, which is a more water-soluble version of auxin (indole-3-acetic acid) is used at what I consider to be a high concentration-10 mM. The problem I have is that the authors are discussing their results in terms of potential impacts on other experimental systems. At least for C. elegans, I think this is not a reasonable extension of the current dataset. In the C. elegans system, researchers are using 1 mM auxin. The authors note that their RNA-seq results suggest a xenobiotic response. Could this apparent xenobiotic response be due to a metabolic byproduct following auxin administration at high concentrations? Figure S1 A shows that there is quite a robust transcriptional response at 1 mM auxin. It would be helpful to know what impacts might be observed at this lower concentration in which the transcriptional induction could be used in the context of biologically meaningful experiments. The recommendation would be that the authors add the 1 mM auxin data point to key elements of their analysis.

2) This reviewer was confused by the genetic nomenclature the authors use. The authors have chosen to use the designation 3.1Lsp2-Gal4 (3.1Lsp2-Gal4AID). I think this is potentially confusing because a reader might think that it is the Gal4 transcription factor that is the direct target of auxin- and TIR1-mediated protein degradation, as I initially did. Rather, it is the Gal80 repressor protein that is the direct target. The authors might consider a nomenclature that is more reflective of how this system works. It would also be helpful if the full genotypes of strains were included in each figure legend.

3) The RNA-seq dataset does not appear to be validated by RT-PCR experiments. The authors should consider validating some of the key genes shown in Figure 3 using quantitative RT-PCR experiments, potentially adding a 1 mM auxin data point.

Reviewer #3 (Public Review):

Summary of Work<br /> This paper conducts the largest GWAS study of A. thaliana in response to a viral infection. The paper identifies a 1.5 MB region in the chromosome associated with disease, including SNPs, structural variation, and transposon insertions. Studies further validate the association experimentally with a separate experimental infection procedure with several lines and specific T-DNA mutants. Finally, the paper presents a geographic analysis of the minor disease allele and the major association. The major take-home message of the paper is that structural variants and not only SNPs are important changes associated with disease susceptibility. The manuscript also makes a strong case for negative frequency-dependent selection maintaining a disease susceptibility locus at low frequency.

Strengths and Weaknesses<br /> A major strength of this manuscript is the large sample sizes, careful experimental design, and rigor in the follow-up experiments. For instance, mentioning non-infected controls and using methods to determine if geographic locus associations were due to chance. The strong result of a GWAS-detected locus is impressive given the complex interaction between plant genotypes and strains noted in the results. In addition to the follow-up experiments, the geographic analysis added important context and broadened the scope of the study beyond typical lab-based GWAS studies. I find very few weaknesses in this manuscript.

Support of Conclusions<br /> The support for the conclusions is exceptional. This is due to the massive amount of evidence for each statement and also due to the careful consideration of alternative explanations for the data.

Significance of Work<br /> This manuscript will be of great significance in plant disease research, both for its findings and its experimental approach. The study has very important implications for genetic associations with disease beyond plants.

Reviewer #3 (Public Review):

Summary:

In this study, Faress and colleagues investigated the differential contributions of Hebbian and non-hebbian plasticity to long-term memory. For this, the authors relied on in vivo optogenetic manipulations of thalamic (Th) and cortical (Ctx) inputs to the lateral amygdala (LA), a circuit whose role in associative memories is well established. The authors first begin by demonstrating that following a weak association protocol (also involving opto stimulation of the Th input) high-frequency stimulation (HFS) of the Th input induces robust conditioned responses (CR) 24 hours later. The authors then use two excitatory opsins to independently manipulate Ctx and Th inputs to the LA. They show that by delivering HFS of the Ctx input, LTP can be observed at Th-LA inputs which is accompanied by long-lasting memory effects.

Strengths:

Overall, the study addresses an important scientific question and could potentially result in a very valuable contribution to the field. The combination of in vivo electrophysiology with optogenetic manipulations of individual input sources to the LA is attractive.

Weaknesses:

While the methods employed in this study are attractive, they are also associated with major weaknesses. In particular, the manuscript lacks convincing validation and sufficient controls. Specific comments are included in the "Recommendations for the authors" section.

Reviewer #3 (Public Review):

Stout et al investigate the link between prefrontal-hippocampal (PFC-HPC) theta-band coherence and accurate decision-making in spatial decision-making tasks. Previous studies show that PFC-HPC theta coherence positively correlates with learning of these tasks and correct decisions but the nature of this relation relies on correlations that cannot show whether coherence leads, coincides, or is a consequence of decision making. To investigate more precisely this link, the authors devise a novel paradigm. In this paradigm, the rat is blocked during a delay period preceding its choice and they control on a trial-by-trial basis the level of PFC-HPC theta coherence prior to the decision by allowing the rat to access the choice point only at a time when coherence reaches above or below a threshold. The design of the paradigm is very nicely controlled thanks in particular to the trial-by-trial matching of delay period durations which is crucial for the working memory task. Moreover, the behaviour of the animal is strongly similar during high and low coherence periods which bolsters the specificity of the author's interpretation. Thanks to this approach, the authors clearly demonstrate that high theta coherence prior to choice-making is strongly predictive of better decision-making both in working memory and a cue-guided version of the task.

This novel paradigm provides an improvement in the level of experimental control to analyse the coherence/choice link but the exact interpretation of the results it yields is not entirely clear in the current manuscript. Using the PFC-HPC theta coherence during the delay period to the gate when the rat accesses the choice zone clearly separates this coherence from the behavioural decision itself. This provides convincing support for the idea that PFC-HPC theta coherence prior to the behavioural decision is related to correct decision-making and is not simply temporally coincidental or a consequence of the decision output. It does not however substantially increase the weight of evidence in favour of a causal link between theta coherence and correct decisions as suggested in the abstract ("PFC-HPC theta synchronization leads to correct choices"). Indeed, the paradigm does not de-correlate PFC-HPC theta synchronization from other neurophysiological variables such as neuromodulation, arousal, synchrony with other areas, etc that could be playing the true causal role in modulating decision-making.

The question of the link between the manuscript's findings and causal involvement of PFC-HPC dialogue is interestingly highlighted by the author's unexpected result showing that their paradigm reveals a link between theta coherence even in a sensory-driven version of the task. As the authors point out, results based on muscimol inhibition have shown that neither PFC nor HPC, nor the ventral midline thalamus, that mediates communication between the two, are involved in this task. This raises the question of why coherence between two areas is predictive of choice accuracy when neither area appears to be causally involved. The manuscript does not discuss the possibility that these results could imply that theta coherence is not in fact a good causal indicator. As an illustrative example, it could be linked for example with neuromodulation (ie dopamine, see Benchenane et al, 2010) which itself causally modifies the choice process. In this case, coherence would be an excellent predictor of accuracy (as the authors show) without implying a causally important information exchange between the two regions, since inhibiting these regions is without effect.

Altogether, this novel paradigm provides finer control to analyse the role of theta coherence in behaviour. This allows pinpointing of interesting cases in which coherence increases during correct task performance although it may have at least an indirect causal role. This opens up the possibility of interrogating when inter-area synchrony is associated with information transfer and when this information is then used to drive behavioural decisions.

Reviewer #3 (Public Review):

This is a descriptive study of membrane excitability and Na+ and K+ current amplitudes of sympathetic motor neurons in culture. The main findings of the study are that neurons isolated from aged animals show increased membrane excitability manifested as increased firing rates in response to electrical stimulation and changes in related membrane properties including depolarized resting membrane potential, increased rheobase, and spontaneous firing. By contrast, neuron cultures from young mice show little to no spontaneous firing and relatively low firing rates in response to current injection. These changes in excitability correlate with significant reductions in the magnitude of KCNQ currents in aged neurons compared to young neurons. Treating cultures with the immunosuppressive drug, rapamycin, which has known antiaging effects in model animals appears to reverse the firing rates in aged neurons and enhance KCNQ current. The authors conclude that aging promotes hyperexcitability of sympathetic motor neurons.

The electrophysiological cataloging of the neuronal properties is generally well done, and the experiments are performed using perforated patch recordings which preserve the internal constituents of neurons, providing confidence that the effects seen are not due to washout of regulators from the cells. The main weakness is that this study is a descriptive tabulation of changes in the electrophysiology of neurons in culture, and the effects shown are correlative rather than establishing causality. It is difficult to know from the data presented whether the changes in KCNQ channels are in fact directly responsible for the observed changes in membrane excitability. Furthermore, a notable omission seems to be the analysis of Ca2+ currents which have been widely linked to alterations in membrane properties in aging. As well, additional experiments in slice cultures would provide greater significance on the potential relevance of the findings for intact preparations. Finally, experiments using KCNQ blockers and activators could provide greater relevance that the observed changes in KCNQ are indeed connected to changes in membrane excitability.

Reviewer #3 (Public Review):

The six-transmembrane epithelial antigen of the prostate (STEAP) family comprises four members in metazoans. STEAP1 was identified as integral membrane protein highly upregulated on the plasma membrane of prostate cancer cells (PMID: 10588738), and it later became evident that other STEAP proteins are also over expressed in cancers, making STEAPs potential therapeutic targets (PMID: 22804687). Functionally, STEAP2-4 are ferric and cupric reductases that are important for maintaining cellular metal uptake (PMIDs: 16227996, 16609065). The cellular function of STEAP1 remains unknown, as it cannot function as an independent metalloreductase. In the last years, structural and functional data have revealed that STEAPs form trimeric assemblies and that they transport electrons from intracellular NADPH, through membrane bound FAD and heme cofactors, to extracellular metal ions (PMIDs: 23733181, 26205815, 30337524). In addition, numerous studies (including a previous study from the senior authors) have provided strong implications for a potential metalloreductase function of STEAP1 (PMIDs: 27792302, 32409586).

This new study by Chen et al. aims to further characterize the previously established electron transport chain in STEAPs in high molecular detail through a variety of assays. This is a well-performed study that provides new insights into the established mechanism of electron transport in STEAP proteins. The authors first perform a detailed spectroscopic analysis of STEAP1, and present the interesting observation that STEAP1 can receive electrons from cytochrome b5 reductase. Then, a similar spectroscopic analysis is performed on another STEAP family member, STEAP2, followed by experiments that show how reduced FAD can diffuse from STEAP2 to STEAP1 to reduce the heme of STEAP1. Finally, the cryo-EM structure of STEAP2 is presented.

Experimentally, the conclusions are appropriate and consistent with the experimental data. The observation that STEAP1 can form an electron transfer chain with cytochrome b5 reductase in vitro is an exciting finding, but its physiological relevance remains to be validated. The metalloreductase activity of STEAP1 in vitro has been described previously by the authors and by others (PMIDs: 27792302, 32409586). However, when over expressed in HEK cells, STEAP1 by itself does not display metal ion reductase activity (PMID: 16609065), and it was also found that STEAP1 over expression does not impact iron uptake and reduction in Ewing's sarcoma (cancer) cells (PMID: 22080479). Therefore, the physiological relevance of metal ion reduction by STEAP1 remains controversial. Future studies will have to elucidate if the established interaction between STEAP1 and cytochrome b5 reductase is relevant in cells.

The work will be interesting for scientists working within the STEAP field and for those working on other oxidoreductases. The spectroscopic data is robust and However, the new structural insights into STEAP2 are limited because the structure is virtually identical to the published structures of STEAP4 and STEAP1 (PMIDs: 30337524, 32409586), which is not surprising because of the high sequence similarity between the STEAP isoforms. When taken together, this study by Chen et al. strengthens and supports previously published biochemical and structural data on STEAP proteins, making an important contribution to the STEAP field.

Reviewer #3 (Public Review):

Lee, Kyungtae and colleagues have discovered and mapped out alpha-arrestin interactomes in both human and Drosophila through the affinity purification/mass spectrometry and the SAINTexpress method. Their work revealed highly confident interactomes, consisting of 390 protein-protein interactions (PPIs) between six human alpha-arrestins and 307 preproteins, as well as 740 PPIs between twelve Drosophila alpha-arrestins and 467 prey proteins.

To define and characterize these identified alpha-arrestin interactomes, the team employed a variety of widely recognized bioinformatics tools. These analyses included protein domain enrichment analysis, PANTHER for protein class enrichment, DAVID for subcellular localization analysis, COMPLEAT for the identification of functional complexes, and DIOPT to identify evolutionary conserved interactomes. Through these assessments, they not only confirmed the roles and associated functions of known alpha-arrestin interactors, such as ubiquitin ligase and protease, but also unearthed unexpected biological functions in the newly discovered interactomes. These included involvement in RNA splicing and helicase, GTPase-activating proteins, and ATP synthase.

The authors carried out further study into the role of human TXNIP in transcription and epigenetic regulation, as well as the role of ARRDC5 in osteoclast differentiation. It is particularly commendable that the authors conducted comprehensive testing of TXNIP's role in HDAC2 in gene expression and provided a compelling model while revised the manuscript. Additionally, the quantification of the immunocytochemistry data presented in Figure 6 convincingly supports the authors' hypothesis.

Overall, this study holds important value, as the newly identified alpha-arrestin interactomes are likely aiding functional studies of this protein group and advance alpha-arrestin research.

Reviewer #3 (Public Review):

Summary:<br /> The authors set out to formally contrast several theoretical models of working memory, being particularly interested in comparing the models regarding their ability to explain cueing effects at short cue durations. These benefits are traditionally attributed to the existence of a high capacity, rapidly decaying sensory storage which can be directly read out following short latency retro-cues. Based on the model fits, the authors alternatively suggest that cue-benefits arise from a freeing of working memory resources, which at short cue latencies can be utilized to encode additional sensory information into VWM.

A dynamic neural population model consisting of separate sensory and VWM populations was used to explain temporal VWM fidelity of human behavioral data collected during several working memory tasks. VWM fidelity was probed at several timepoints during encoding, while sensory information was available, and maintenance when sensory information was no longer available. Furthermore, set size and exposure durations were manipulated to disentangle contributions of sensory and visual working memory.

Overall, the model explained human memory fidelity well, accounting for set size, exposure time, retention time, error distributions, and swap errors. Crucially the model suggests that recall at short delays is due to post-cue integration of sensory information into VWM as opposed to direct readout from sensory memory. The authors formally address several alternative theories, demonstrating that models with reduced sensory persistence, direct readout from sensory memory, no set-size dependent delays in cue processing, and constant accumulation rate provide significantly worse fits to the data.

I congratulate the authors for this rigorous scientific work. I have only very few remarks that I hope the authors can clarify.

Reviewer #3 (Public Review):

The paper by Deng, Kumar, Cavalli, Klyachko describes that, unlike in other cell types, loss of Fmr1 decreases the excitability of hippocampal mossy cells due to up-regulation of Kv7 currents. They also show evidence that while muting mossy cells appears to be a compensatory mechanism, it contributes to the higher activity of the dentate gyrus, because the removal of mossy cell output alleviates the inhibition of dentate principal cells. This may be important for the patho-mechanism in Fragile X syndrome caused by the loss of Fmr1.

These experiments were carefully designed, and the results are presented ‎in a very logical, insightful, and self-explanatory way. Therefore, this paper represents strong evidence for the claims of the authors. In the current state of the manuscript, there are only a few points that need additional explanation.

One of the results, which is shown in the supplementary dataset, does not fit the main conclusions. Changes in the mEPSC frequency suggest that in addition to the proposed network effects, there are additional changes in the synaptic machinery or synapse number that are independent of the actual activity of the neurons. Since the differences of the mEPSC and sEPSC frequencies are similar and because only the latter can signal network effects, while the former is typically interpreted as a presynaptic change, it cannot be claimed that sEPSC frequency changes are due to the hypo-excitability of mossy cells.

An apparent technical issue may imply a second weak point in the interpretation of the results. Because the IPSCs in the PP stimulation experiments (Fig 8) start within a few milliseconds, it is unlikely that its first ‎components originate from the PP-GC-MC-IN feedforward inhibitory circuit. The involvement of this circuit and MCs in the Kv7-dependent excitability changes is the main implication of the results of this paper. But this feedforward inhibition requires three consecutive synaptic steps and EPSP-AP couplings, each of them lasting for at least 1ms + 2-5ms. Therefore, the inhibition via the PP-GC-MC-IN circuit can be only seen from 10-20ms after PP stimulation. The earlier components of the cPSCs should originate from other circuit elements that are not related to the rest of the paper. Therefore, more isolated measurements on the cPSC recordings are needed ‎which consider only the later phase of the IPSCs. This can be either a measurement of the decay phase or a pharmacological manipulation that selectively enhances/inhibits a specific component of the proposed circuit.

I suggest refraining from the conclusions saying "‎MCs provide at least ~51% of the excitatory drive onto interneurons in WT and ~41% in KO mice", because too many factors (eg. IN cell types, slice condition, synaptic reliability) are not accounted for in these actual numbers, and these values are not necessary for the general observation of the paper.

There are additional minor issues about the presentation of the results.

Reviewer #3 (Public Review):

Summary:

In this study, Jones et al. examine how neural activity in a primary auditory area (field L) of singing male songbirds is modulated by the presence or absence of an audience (a female conspecific). Prior work has demonstrated that the presence of an audience attenuates the responses of dopaminergic neurons to distortions of auditory feedback (DAF). Here the authors report that even in a region that is primarily considered sensory, responses to DAF are also modulated by the audience, although in a heterogeneous manner that does not readily explain previously observed attenuation. These findings address an interesting question and will potentially be important in adding to an understanding of how non-sensory factors can alter response properties of neurons even in primary sensory regions in a context dependent fashion. However, to be fully persuasive, additional analyses will be required to address how much of the apparent modulation by audience may be explained by other factors such as changes in recorded neurons or their properties over time.

Full Public Review:

In this study, Jones et al. examine how neural activity in a primary auditory area (field L) of singing male songbirds is modulated by the presence or absence of an audience (a female conspecific). They test whether activity in Field L differs between conditions in which the male is singing to a female (directed song) or alone (undirected song) and whether response to distortions of auditory feedback (DAF) differ between these conditions. Previous work has shown that in other parts of the songbird brain, sensory-motor activity can differ between directed and undirected song, and that responses to DAF are attenuated when males sing directed song versus undirected song. These prior results raise the interesting question of the extent to which such modulations of activity by the presence of an audience are already present in primary sensory areas such as Field L. This possibility is also motivated by prior work that has shown that Field L activity is not exclusively explained by auditory input, but can also be modulated by the bird's state - whether it is singing or not.

Against this background, the questions asked here are of interest for two inter-related reasons:

1) the authors address whether the presence of an audience (a female conspecific) alters activity in a primary auditory area during singing. Primary auditory areas such as Field L, and analogous mammalian thalamo-recipient cortical regions such as A1, are often thought of as responding very specifically to the features of sensory stimuli, but are also understood to be modulated by a variety of factors including the attentional and behavioral state of the animal. For audition, such modulation includes whether or not animals are vocalizing and listening to themselves or listening to playback of their own vocalizations. Cited works from Keller (2009) as well as Eliades and Wang (2008) have indicated that the act of vocalizing can modulate auditory responses to self-generated feedback in primary auditory areas relative to those arising from playback of the same sounds. Here, the question is whether responses to self-generated feedback differ between conditions of singing alone versus singing to a female audience. A demonstration that the presence of an audience matters to responses in Field L would add to a general understanding of how it is that non-auditory factors can modulate sensory responses.

2) the authors address the possible source of an audience-dependent modulation of responses to feedback perturbation in the VTA previously reported by Goldberg and colleagues (2023). In the VTA, responses to perturbations during singing are consistently attenuated when males are singing to females versus when they are singing alone, but the underlying mechanisms of this modulation are unknown. Here, the authors test the possibility that such modulation by an audience is already present at the level of Field L. The previously reported attenuation in VTA is quite striking and reflects a nice example of how neural processing can differ with varying behavioral priorities. Understanding whether this modulation of responses to DAF arises already in primary auditory areas would further a mechanistic understanding of an intriguing example of state-dependent modulation of sensory processing and behavior, and lend broad insight into related phenomena.

The authors report 1) that activity in Field L differs between directed and undirected singing at many individual recording sites, but that these changes are heterogeneous, with both increases and decreases in activity, so that there is no consistent change across the population and 2) that the responses to DAF differ between directed and undirected song, but that there is no consistent attenuation of response (as observed in the VTA) and instead heterogeneous increases and decreases in response to DAF so that there is no net change at the population level.

These findings, if firmly established, are important and of general interest. While they do not readily explain the source of the audience-dependent attenuation of auditory responses to DAF in the VTA, the demonstration of audience-dependent modulation of self-generated feedback and its disruption in a primary auditory area is an exciting result that would provide an opportunity for further investigation of how changes in social context influence brain and behavior. The manuscript is generally well written, although the presentation is terse. My main reservations about the current manuscript relate to aspects of experimental design and analysis that need to be clarified and addressed before these conclusions will be fully persuasive. There are also some places where further discussion of the findings and their relationship to prior studies would be helpful.

1. A central concern relates to whether the main reported effects associated with differences in singing directed versus undirected song reflect only those changes in conditions, versus contributions from changes in unit isolation or response properties over time. The authors record undirected song in a block in the morning and only after collecting at least 40 renditions do they later record responses during directed song over a series of repeated exposures to a female. Therefore, differences between data collected during undirected song and directed song also reflect differences between data collected initially during the morning versus later. It is unclear from methods whether any of these recordings during undirected and directed conditions are interleaved, but if this is not the case, then it is crucial to ask how stable were neural recordings with respect to unit isolation, and potential changes to response properties, over the duration of the experiments. This would be less of a concern if the results mirrored those observed in the VTA, where attenuation of responses was observed across the entire population during directed versus undirected conditions - it is hard to explain a phenomenon that is consistently observed across the population as arising from a change in which neurons and spikes are contributing to responses, or other forms of non-stationarity. However, because there are no significant differences reported at the population level in the current study, it is important to address the possibility that observed differences between conditions reflect some form of noise or drift in recorded units, rather than being entirely due to directed versus undirected singing. I have elaborated in more detail below on this concern, including places where the data seems to suggest some non-stationarity of responses, and have some suggestions for ways in which this concern might be addressed.

2. A second concern, related to this first one, has to do with the categorical definition of 'error neurons'. The authors note in their text that it could be problematic to apply categorical definitions to continuous distributions, and yet that seems to be what they then do. The authors have a metric of error sensitivity that they apply to each neuron's response to DAF in both undirected and directed conditions (the error score). They show that there is a continuous distribution of error scores (Figure 2 - figure supplement 1) across the population, with no bimodality that would be suggestive of distinct error sensitive and error-insensitive neurons. One nice feature of their analysis is that they also show the distribution of error scores computed in an analogous fashion for a period of neural activity in the song prior to DAF. This control data set makes it persuasive that there is a significant response to DAF, but also shows that there can be a broad range of error scores even when no DAF has been played, and that this range of 'noise' responses to DAF overlaps substantially with the actual responses to DAF. Despite the continuum of error scores, the authors define a subset of neurons as error responsive only if their responses to DAF exceed a specific threshold (2.5 standard deviations). One of the main conclusions of the paper is based on finding a subset of 22 neurons that exhibited error responses (by this definition) only during singing to a female and 11 neurons that exhibited error responses only when singing alone. These neurons are described as 'retuned' because they have error responses in only one condition.

The problem here is that for some, if not many, of the neurons that are categorically defined as being responsive to DAF in only one condition (directed versus undirected) there is almost certainly not a significant difference in the actual responses to DAF between conditions. This is apparent in the relevant data figure (figure 2 - figure supplement 1) and is a consequence of using a threshold to split a continuous distribution into groups defined as error responsive or not. For example, several neurons in this plot that have almost identical scores in the directed and undirected condition are counted as examples of retuning because the error scores are just a bit over 2.5 in the directed condition and just a bit under 2.5 in the undirected condition.

That this kind of categorical approach may be problematic is apparent in the control data in the plot. Despite the absence of any perturbation, there are error responsive neurons present in these data that are considered selective for directed versus undirected singing - this is an expected consequence of using a threshold on dispersed or noisy biological data. Shifting to a more stringent threshold of three standard deviations, as the authors do, does not help with this problem, as that still treats as categorically different responses that fall on either side of a line, even if only by a tiny amount. I suggest that the authors devise a measure for each neuron to test whether the responses to DAF are significantly different under the two conditions (directed versus undirected). As noted above, this measure should take into account some assessment of the stationarity of responses, as well as the distribution of responses (which, in some of the examples does not seem to be Gaussian around a mean response level, but rather highly variable across trials).

3. There are several places where further discussion of the previous literature and how the current results relate to that literature would be helpful. This includes:

3a. Some discussion of what is already known about the auditory tuning of field L, and the extent to which responses associated with distortion of feedback may reflect the frequency tuning of field L neurons versus something that might be construed as more specifically as detecting an error in perceived feedback. For example, Field L neurons have previously been characterized as having relatively simple spectro-temporal receptive fields, often with a single frequency band that is excitatory and nearby frequency bands that are inhibitory. It would be beyond the scope of this paper to directly assess the extent to which both song responses and responses to DAF are well predicted by simple STRFs that might be measured for the recorded neurons, or computed from activity during a range of vocalizations, but perhaps worth discussing whether a neuron with such frequency tuning would potentially exhibit 'error responses' of the sort described here, simply because the DAF stimulus happens to fall into the excitatory or inhibitory regions of the neuron's receptive field. While it is OK to use the term 'error responsive' in the current study, it would be good to make clear that changes in firing associated with playing DAF should be expected even for neurons that have simple auditory receptive fields (i.e. with center surround tuning to specific frequencies in a tonotopic map, as has been described for Field L) without necessarily indicating that these neurons are specifically registering any deviation or 'error' between expected feedback and experienced feedback. In this respect, there are multiple subdivisions of Field L with different tuning properties. Please specify further what criteria were used to determine recording locations and how these correspond with previously defined subdivisions.

3b. It would also be useful to discuss further previous work on differences in auditory tuning or responses between conditions when subjects are vocalizing, versus when vocalizations are played back (as in Keller, Eliades) and whether the results in the current study are similar or different. For example, this prior work has indicated that efference copy or other signals that precede vocalizations can reach and influence activity in auditory areas - with the most compelling evidence for this being the modulation of activity prior to the onset of vocalizations. Was this also observed in the current study, and to what extent might this kind of mechanism contribute to the processing of feedback distortions? With respect to this kind of efference signal, or other possibilities, can the authors provide some discussion or speculation about possible mechanisms that might be differentially engaged between conditions of singing directed versus undirected song?

3c. The previous study on DAF responses in VTA indicates enhanced responses to female calls during directed song. To what extent did the current study control for any vocalizations or other sounds produced by females during the directed singing, and could this have contributed to differences in Field L activity between conditions? This question is motivated partly by the highly variable responses in raster plots even within one condition - might some of this reflect motifs during which transient noises are produced from female calling or other movements by the male or female?

More regarding stability of recordings:

The data presented in Figure 1D illustrate some of my concerns about the stationarity of recordings. In the directed condition there are no spikes at all following the first handful of motif renditions. Were the directed and undirected recordings interleaved here? If not, could the recorded neuron simply have been lost, changed in amplitude of recorded spikes so that it was no longer counted, or reduced its responsiveness over the course of the recordings? Because the recordings of undirected and directed singing are described as occurring sequentially, it seems likely that this type of change in recorded signal could contribute to changes in measured responses over time, independently of effects due to directed versus undirected singing.

A minor issue of this example is that the raw example trace with male alone does not seem to have a corresponding set of points in the roster plot. For panel E, I also cannot find rasters that correspond to the example recordings shown at top.

Figure 2A also shows a neuron that looks like it has non-stationarity; for the alone condition without altered feedback, the main peak has no spikes for the bottom half of the rasters. For the directed condition, much of the difference between control and distorted feedback conditions seems to come from a few trials towards the bottom of the raster plot that show more and earlier firing than most other rasters.

Other more subtle examples are suggested in the figures, such as Figure 1F where responses in the alone condition seem to increase over the course of recordings. A related issue apparent in some of the raster plots is that the firing rate distributions within a given condition sometimes appear to be very non-gaussian, with some motifs during which there is a lot of activity, or apparent bursting, and others in which there is little activity. In addition to the examples above, this includes<br /> responses in Fig 1E and Fig 2F. Does anything distinguish these cases or trails? Where differences between conditions are driven by firing differences that are present on only a subset of trials, such as in Fig 2A, there is some deviation from the normal criteria for use of T-tests/Z-scores. Please consider this point and discuss any caveats and/or apply other tests (Monte Carlo? Non-parametric?) as appropriate.

These potential issues of non-stationarily, and non-Gaussian firing rate distributions in each condition, make it complicated to think about what differences in activity reflect changes from undirected to directed conditions versus these other factors.

Approaches to addressing this issue could include more specifically indicating examples in which recordings from the alone condition and directed condition are interleaved and exhibit reversible (between conditions) changes in the pattern of responses (both without DAF in comparing alone versus directed, and with DAF demonstrating differences in DAF influences between conditions). Some good interleaved examples of this sort would be very helpful to illustrate the robustness of differences between conditions. More generally, the methods and or raster plots should include some further explanation of the time periods over which recordings were made in the alone versus directed conditions, and the extent to which they are interleaved or not.

Another approach that could be used if there are not many instances of inter-leaved recordings is to try to document the stationarily or stability of unit isolation and/or responses over time. It would be most helpful when applied to recordings from a given singing condition (i.e. alone or directed) that are interleaved, but even in cases where this is not possible perhaps one could assess the stability of waveforms and unit isolation across time. For example in Figure 2 - Supplementary figure 2, the left-hand and middle examples appear to have quite good unit isolation, and might be the sorts of cases where measures of unit isolation and waveform stability could be used to argue that a gain or loss of spikes due to drift in recordings or changes to SNR and spike detection are not contributing to changes in firing patterns over time (and across conditions).

It potentially would also be informative to present the prevalence of the main effects reported in the study as a function of some measures of unit isolation, SNR, and recording stability. It would be reassuring to see that significant differences between conditions are equally or more prevalent under the conditions of greatest unit isolation and recording stability than in cases with worse SNR or stability.

One other way that the authors might be able to address my main concern would be to look at the stability of firing patterns within conditions, where differences across trials most directly indicate the potential contributions of technical or biological changes in neural activity over time that are not related to the experimental conditions.

To further address some of these issues, it would be helpful to have additional explanations in this paper (rather than by reference to Goldberg and Fee, 2010) of the criteria that were used for counting spikes, and assessing stability of recordings. All I found about this in the Goldberg and Fee, 2010 reference was that "Spikes were sorted off-line using custom Matlab software" Does this require human inspection and judgment? Is there a simple threshold, or waveform measurement used for detecting spikes from single units? Are some sort of signal to noise measures, or ISI violations used to score how well units are isolated?

For the specific examples shown in figures, it would be useful to indicate by small tick marks or otherwise which spikes were counted as single units. For example in figure 2 column B, for the condition with female, did only the 1-3 largest spikes get counted, or also the spikes of medium height?

Page 11: "Many channels on the probes recorded multi-unit activity, which were taken note of but not analyzed in this study."

What were the criteria for this? For several of the examples in the figures there are spikes of varying amplitudes and as mentioned above it would be helpful to clarify how the spikes were sorted into single units in such cases.

Categorical scores:

Page 13: "Neurons with error responses greater than 2.5 in only one condition (undirected versus directed) were considered to have retuned; neurons with error scores greater than 2.5 in both conditions were considered not to have retuned."

This definition results in cases where responses of 2.45 vs 2.55 are described as 'retuned', even if these responses are not significantly different. The figure (Figure 2 - figure supplement 1) indicates that multiple neurons that were scored as retuning had responses that fall very near the threshold in this way.

Page 13, "Our results did not fundamentally change with ... a more stringent threshold of 3..."

The stringency is not issue here, rather the categorical threshold. Retuning would be more persuasively demonstrated if the authors could provide a test of whether or not the responses for individual neurons differ significantly between conditions appropriately taking into account multiple comparisons, stability of recordings, non-Gaussian firing rate distributions across motif renditions, etc. and use this metric to report effects, rather than setting a categorical threshold.

Reviewer #3 (Public Review):

Summary:<br /> In this study, the authors used patch-clamp to characterize the implication of various voltage-gated Na+ channels in the firing properties of mouse nociceptive sensory neurons. They report that depending on the culture conditions NaV1.3, NaV1.7, and NaV1.8 have distinct contributions to action potential firing and that similar firing patterns can result from distinct relative roles of these channels. The findings may be relevant for the design of better strategies targeting NaV channels to treat pain.

Strengths:<br /> The paper addresses the important issue of understanding, from an interesting perspective, the lack of success of therapeutic strategies targeting NaV channels in the context of pain. Specifically, the authors test the hypothesis that different NaV channels contribute in a plastic manner to action potential firing, which may be the reason why it is difficult to target pain by inhibiting these channels. The experiments seem to have been properly performed and most conclusions are justified. The paper is concisely written and easy to follow.

Weaknesses:<br /> 1) The most critical issue I find in the manuscript is the claim that different combinations of NaV channels result in equivalent excitability. For example, in the Abstract it is stated that: "...we show that nociceptors can achieve equivalent excitability using different combinations of NaV1.3, NaV1.7, and NaV1.8". The gating properties of these channels are not identical, and therefore their contributions to excitability should not be the same. I think that the culprit of this issue is that the authors reach their conclusion from the comparison of the (average) firing rate determined over 1 s current stimulation in distinct conditions. However, this is not the only parameter that determines how sensory neurons convey information. For instance, the time dependence of the instantaneous frequency, the actual firing pattern, may be important too. Moreover, the use of 1 s of current stimulation might not be sufficient to characterize the firing pattern if one wants to obtain conclusions that could translate to clinical settings (i.e., sustained pain). A neuron in which NaV1.7 is the main contributor is expected to have a damping firing pattern due to cumulative channel inactivation, whereas another depending mainly on NaV1.8 is expected to display more sustained firing. This is actually seen in the results of the modelling.

2) In Fig. 1, is 100 nM TTX sufficient to inhibit all TTX-sensitive NaV currents? More common in literature values to fully inhibit these currents are between 300 to 500 nM. The currents shown as TTX-sensitive in Fig. 1D look very strange (not like the ones at Baseline DIV4-7). It seems that 100 nM TTX was not enough, leading to an underestimation of the amplitude of the TTX-sensitive currents.

3) Page 8, the authors conclude that "Inflammation caused nociceptors to become much more variable in their reliance of specific NaV subtypes". However, how did the authors ensure that all neurons tested were affected by the CFA model? It could be that the heterogeneity in neuron properties results from distinct levels of effects of CFA.

Reviewer #3 (Public Review):

Kim, Lognon et al. present an important finding on pro-locomotor effects of optogenetic activation of the A13 region, which they identify as a dopamine-containing area of the medial zona incerta that undergoes profound remodeling in terms of afferent and efferent connectivity after administration of 6-OHDA to the MFB. The authors claim to address a model of PD-related gait dysfunction, a contentious problem that can be difficult to treat with dopaminergic medication or DBS in conventional targets. They make use of an impressive array of technologies to gain insight into the role of A13 remodeling in the 6-OHDA model of PD. The evidence provided is solid and the paper is well written, but there are several general issues that reduce the value of the paper in its current form, and a number of specific, more minor ones. Also, some suggestions, that may improve the paper compared to its recent form, come to mind.

The most fundamental issue that needs to be addressed is the relation of the structural to the behavioral findings. It would be very interesting to see whether the structural heterogeneity in afferent/effects projections induced by 6-OHDA is related to the degree of symptom severity and motor improvement during A13 stimulation.

The authors provide extensive interrogation of large-scale changes in the organization of the A13 region afferent and efferent distributions. It remains unclear how many animals were included to produce Fig 4 and 5. Fig S5 suggests that only 3 animals were used, is that correct? Please provide details about the heterogeneity between animals. Please provide a table detailing how many animals were used for which experiment. Were the same animals used for several experiments?

While the authors provide evidence that photoactivation of the A13 is sufficient in driving locomotion in the OFT, this pro-locomotor effect seems to be independent of 6-OHDA-induced pathophysiology. Only in the pole test do they find that there seems to be a difference between Sham vs 6-OHDA concerning the effects of photoactivation of the A13. Because of these behavioral findings, optogenic activation of A13 may represent a gain of function rather than disease-specific rescue. This needs to be highlighted more explicitly in the title, abstract, and conclusion.

The authors claim that A13 may be a possible target for DBS to treat gait dysfunction. However, the experimental evidence provided (in particular the lack of disease-specific changes in the OFT) seems insufficient to draw such conclusions. It needs to be highlighted that optogenetic activation does not necessarily have the same effects as DBS (see the recent review from Neumann et al. in Brain: https://pubmed.ncbi.nlm.nih.gov/37450573/). This is important because ZI-DBS so far had very mixed clinical effects. The authors should provide plausible reasons for these discrepancies. Is cell-specificity, which only optogenetic interventions can achieve, necessary? Can new forms of cyclic burst DBS achieve similar specificity (Spix et al, Science 2021)? Please comment.

In a recent study, Jeon et al (Topographic connectivity and cellular profiling reveal detailed input pathways and functionally distinct cell types in the subthalamic nucleus, 2022, Cell Reports) provided evidence on the topographically graded organization of STN afferents and McElvain et al. (Specific populations of basal ganglia output neurons target distinct brain stem areas while collateralizing throughout the diencephalon, 2021, Neuron) have shown similar topographical resolution for SNr efferents. Can a similar topographical organization of efferents and afferents be derived for the A13/ ZI in total?

In conclusion, this is an interesting study that can be improved by taking into consideration the points mentioned above.

Reviewer #3 (Public Review):

The authors report on the engineering of an induced Pluripotent Stem Cell (iPSC) line that harbours a single copy of a split mNeonGreen, mNG2(1-10). This cell line is subsequently used to take endogenous protein with a smaller part of mNeonGreen, mNG2(11), enabling the complementation of mNG into a fluorescent protein that is then used to visualize the protein. The parental cell is validated and used to construct several iPSC lines with endogenously tagged proteins. These are used to visualize and quantify endogenous protein localisation during mitosis.

I see the advantage of tagging endogenous loci with small fragments, but the complementation strategy has disadvantages that deserve some attention. One potential issue is the level of the mNG2(1-10). Is it clear that the current level is saturating? Based on the data in Figure S3, the expression levels and fluorescence intensity levels show a similar dose-dependency which is reassuring, but not definitive proof that all the mNG2(11)-tagged protein is detected.

Do the authors see a difference in fluorescence intensity for homo- and heterozygous cell lines that have the same protein tagged with mNG2(11)? One would expect two-fold differences, or not?

Related to this, would it be favourable to have a homozygous line for expressing mNG2(1-10)?

The complementation seems to work well for the proteins that are tested. Would this also work for secreted (or other organelle-resident) proteins, for which the mNG2(11) tag is localised in a membrane-enclosed compartment?

The authors present a technological advance and it would be great if others could benefit from this as well by having access to the cell lines.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, the authors are trying to delineate the mechanism underlying the osteonecrosis of the femoral head.

Strengths:<br /> The authors provided compelling in vivo and in vitro data to demonstrate Col2+ cells and Osx+ cells were differentially expressed in the femoral head. Moreover, inducible knockout of β-catenin in Col2+ cells but not Osx+ cells lead to a GONFH-like phenotype including fat accumulation, subchondral bone destruction, and femoral head collapse, indicating that imbalance of osteogenic/adipogenic differentiation of Col2+ cells plays an important role in GONFH pathogenesis. Therefore, this manuscript provided mechanistic insights into osteonecrosis as well as potential therapeutic targets for disease treatment.

Weaknesses:<br /> However, additional in-depth discussion regarding the phenotype observed in mice is highly encouraged.

Reviewer #3 (Public Review):

The co-suppressive molecule CTLA-4 has a critical role in the maintenance of peripheral tolerance, primarily by Treg mediated control of the co-stimulatory molecules CD80 and CD86. As stated by the authors, previous studies have found a variety of effects of anti-CTLA-4 antibody treatment or genetic loss of CTLA-4 on B-cells. These include increased B-cell activation and antibody production, autoantibody production, impairment of B-cell production in the bone marrow and loss of peripheral B-cells. In this article Muthana et al use a CTLA-4 humanized mouse model and examine the effects of drug conjugated CTLA-4 on the immune system. They observe a transient loss of B-cells in the blood of the treated mice. They then use a range of immune interventions such as T-cell depletion and blocking antibodies to demonstrate that this effect is dependent on T-cell activation.

Since anti-CTLA-4 immunotherapy is in active clinical use exploration of its effects are welcome, this is helped by the use of a humanized CTLA-4 system which should be considered a strength of the paper. However, currently the central premise of this paper, that B-cells are depleted seems underexplored. Direct evidence of T-cell killing of B-cells is never presented, rather it is inferred from the reduced numbers of B-cells in the blood and increased apoptosis in the bone marrow. It is not made clear if B-cell numbers in the bone marrow are reduced.

Upon examining lymphoid organs it seems that the spleen is relatively unchanged while the lymph nodes have a large increase in B-cells alongside increased serum antibody levels. The paper does underline the importance of looking at the differences of multiple immune compartments and interesting phenomenon are described in each compartment. Simultaneous inhibition of B-cell lymphopoiesis and blood trafficking with strong activation and antibody production of lymphoid resident (presumably germinal center) B-cells appears to be occurring. However the current overall interpretation that B-cells are broadly depleted is perhaps too simplistic and largely ignores the lymphoid organs and serum antibodies.

Reviewer #3 (Public Review):

Summary:

Zawieja et al. aimed to identify the pacemaker cells in the lymphatic collecting vessels. Authors have used various Cre-based expression systems and optogentic tools to identify these cells. Their findings suggest these cells are lymphatic muscle cells that drive the pacemaker activity in the lymphatic collecting vessels.

Strengths:

The authors have used multiple approaches to test their hypothesis. Some findings are presented as qualitative images, while some quantitative measurements are provided.

Weaknesses:

- More quantitative measurements.<br /> - Possible mechanisms associated with the pacemaker activity.<br /> - Membrane potential measurements.

Reviewer #3 (Public Review):

Summary:<br /> DeHaro-Arbona and colleagues investigate the in vivo dynamics of Notch-dependent transcriptional activation with a focus on the role of the Mastermind (MAM) transcriptional co-activator. They use GFP and HALO-tagged versions of the CSL DNA-binding protein and MAM to visualize the complex, and Int/ParB to visualize the site of Notch-dependent E(Spl)-C transcription. They make several conclusions. First, MAM accumulates at E(Spl)-C when Notch signaling is active, just like CSL. Second, MAM recruits the CDK module of Mediator but does not initiate chromatin accessibility. Third, after signaling is turned off, MAM leaves the site quickly but CSL and chromatin accessibility are retained. Fourth, RNA pol II recruitment, Mediator recruitment, and active transcription were similar and stochastic. Fifth, ecdysone enhances the probability of transcriptional initiation.

Strengths:<br /> The conclusions are well supported by multiple lines of extensive data that are carefully executed and controlled. A major strength is the strategic combination of Drosophila genetics, imaging, and quantitative analyses to conduct compelling and easily interpretable experiments. A second major strength is the focus on MAM to gain insights into the dynamics of transcriptional activation specifically.

Weaknesses:<br /> Weaknesses are minor. There were no p-values reported for data presented in Figure S1D and no indication of how variable measurements were. In addition, the discussion of stochasticity was not integrated optimally with relevant literature.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript reports new molecular characterization of the Haemophilus influenza tripartite ATP-independent periplasmic (TRAP) transporter of N-acetylneuraminate (Neu5Ac). This membrane transporter is important for the virulence of the pathogen. H. influenza lacks Neu5Ac biosynthetic pathway and utilizes the TRAP transporter to import it. Neu5Ac is used as a nutrient source but also as a protection from the human immune response. The transporter is composed of two fused membrane subunits, HiSiaQM, and one soluble, periplasmic subunit HiSiaP. HiSiaP, by binding to the substrate Neu5Ac, changes its conformation, allowing its binding to HiSiaQM, followed by Neu5Ac and Na+ transport to the cytoplasm. The combination of structural, biophysical and biochemical approaches provides a solid basis for describing the functioning of the Haemophilus influenza Neu5Ac TRAP transporter, which is essential for the pathogen virulence.

Strengths:<br /> The paper describes the electron microscopy structure of HiSiaQM, thanks to its solubilization in L-MNG followed by the exchange to amphipol or nanodisc. In these conditions, HiSiaQM consists of a mixture of monomers and dimers, as characterized by analytical ultracentrifugation. The cryo-EM analysis shows two types of dimers: one in an antiparallel configuration, which is artifactual, and a parallel one, which may be physiologically relevant. Cryo-EM on the dimers allows high-resolution (≈ 3 Å) structure determination. The structure is the first one of a fused SiaQM, and is the first obtained without megabody. The work highlights structural elements (fusion helix, lipids) that could modulate transport. The authors checked the functionality of the purified HiSiaQM, which, after reconstitution in liposome, displays a significantly larger Neu5Ac transport activity compared to the non-fused PpSiaQM homolog. The work identifies Na+ binding sites, and the putative Neu5Ac binding site. From analytical ultracentrifugation using fluorescently labelled HiSiaP, the authors show that HiSiaP is able to interact with HiSiaQM monomer and dimer, with a low but physiologically relevant affinity. HiSiaP interaction with HiSiaQM was modelled using AlphaFold2, and discussed in view of published activity on mutants, and new transport activity assays using SiaQM and SiaP from different organisms. In conclusion, the combination of structural, biophysical and biochemical approaches provides a solid basis for describing the functioning of this TRAP fused transporter.

Weakness:<br /> This work evidences in vitro a HiSiaQM dimer, whose in vivo relevance is not ascertained. However, the authors are very careful, not to over-interpret their data, and their conclusions regarding the transporter structure and function are valid irrespective of its state of association.

Reviewer #3 (Public Review):

The potential for sexual selection and the extent of sexual dimorphism in gene expression have been studied in great detail in animals, but hardly examined in plants so far. In this context, the study by Zhao, Zhou et al. al represents a welcome addition to the literature.

Relative to the previous studies in Angiosperms, the dataset is interesting in that it focuses on reproductive rather than somatic tissues (which makes sense to investigate sexual selection), and includes more than a single developmental stage (buds + mature flowers).

Some aspects of the presentation have been improved in this new version of the manuscript. Specifically:

- the link between sex-biased and tissue-biased genes is now slightly clearer,<br /> - the limitation related to the de novo assembled transcriptome is now formally acknowledged,<br /> - the interpretation of functional categories of the genes identified is more precise,<br /> - the legends of supplementary figures have been improved<br /> - a large number of typos have been fixed.

However, overall the analyses are largely unchanged and the manuscript did not mature much in response to this first round of reviews. As I detail below, many of the relevant and constructive suggestions by the previous reviewers were not taken into account in this revision. For instance:

- Reviewer 2 made precise suggestions for trying to take into account the potential confonding factor of sex-chromosomes. This suggestion was not followed.<br /> - Reviewer 1 & 3 indicated that results were mentioned in the discussion section without having been described before. This was not fixed in this new version.<br /> - Reviewer 1 asked for a comparison between the number of de novo assembled unigenes in this transcriptome and the number of genes in other Cucurbitaceae species. I could not see this comparison reported.<br /> - Reviewer 1 pointed out that permutation tests were more appropriate, but no change was made to the manuscript.<br /> - Reviewer 3 pointed out the small sample size (both for the RNA-seq and the phylogenetic analysis), but again this limitation is not acknowledged very clearly.<br /> - Reviewer 1 & 3 pointed out that Fig 3 was hard to understand and asked for clarifications that I did not see in the text and the figure in unchanged.<br /> - Reviewer 3 suggested to combine all genes with sex-bias expression when evaluating the evolutionary rate, in addition to the analyses already done. This suggestion was not followed.<br /> - Reviewer 3 pointed out that hand-picking specific categories of genes was not statistically valid, and in fact not necessary in the present context. This was not changed.<br /> - Reviewer 1 asked for all data to be public, but I could not find in the manuscript where the link to the data on ResearchGate was provided.<br /> - Reviewers 1 & 3 pointed out that since only two tissues were compared, the claims on pleiotropy should have been toned down, but no change was made to the text.<br /> - Reviewer 1 asked for a clarification on which genes are plotted on the heatmap of Fig3C and an explanation of the color scale. No change was made.<br /> - Reviewer 1 asked for panel B in Fig 5 and 6 to be removed. They are still there. They asked for abbreviations to be explained in the legend of Fig S8. This was not done. They asked for details about coluln headers. Such detailed were not added. They asked for more recent references on line 53-56 : this was not done.

Reviewer #3 (Public Review):

The present study aims to investigate whether pain influences cortical excitability. To this end, heat pain stimuli are applied to healthy human participants. Simultaneously, TMS pulses are applied to M1 and TMS-evoked potentials (TEPs) and pain ratings are assessed after each TMS pulse. TEPs are used as measures of cortical excitability. The results show that TEP amplitudes at 45 msec (N45) after TMS pulses are higher during painful stimulation than during non-painful warm stimulation. Control experiments indicate that auditory, somatosensory, or proprioceptive effects cannot explain this effect. Considering that the N45 might reflect GABAergic activity, the results suggest that pain changes GABAergic activity. The authors conclude that TEP indices of GABAergic transmission might be useful as biomarkers of pain sensitivity.

Pain-induced cortical excitability changes is an interesting, timely, and potentially clinically relevant topic. The paradigm and the analysis are sound, the results are convincing, and the interpretation is adequate. The findings will be of interest to researchers interested in the brain mechanisms of pain.

Reviewer #3 (Public Review):

Summary:<br /> Blaeser et al. set out to explore the link between CSD and headache pain. How does an electrochemical wave in the brain parenchyma, which lacks nociceptors, result in pain and allodynia in the V1-3 distribution? Prior work had established that CSD increased the firing rate of trigeminal neurons, measured electrophysiologically at the level of the peripheral ganglion. Here, Blaeser et al. focus on the fine afferent processes of the trigeminal neurons, resolving Ca2+ activity of individual fibers within the meninges. To accomplish these experiments, the authors injected AAV encoding the Ca2+ sensitive fluorophore GCamp6s into the trigeminal ganglion, and 8 weeks later imaged fluorescence signals from the afferent terminals within the meninges through a closed cranial window. They captured activity patterns at rest, with locomotion, and in response to CSD. They found that mechanical forces due to meningeal deformations during locomotion (shearing, scaling, and Z-shifts) drove non-spreading Ca2+ signals throughout the imaging field, whereas CSD caused propagating Ca2+ signals in the trigeminal afferent fibers, moving at the expected speed of CSD (3.8 mm/min). Following CSD, there were variable changes in basal GCamp6s signals: these signals decreased in the majority of fibers, signals increased (after a 25 min delay) in other fibers, and signals remained unchanged in the remainder of fibers. Bouts of locomotion were less frequent following CSD, but when they did occur, they elicited more robust GCamp6s signals than pre-CSD. These findings advance the field, suggesting that headache pain following CSD can be explained on the basis of peripheral cranial nerve activity, without invoking central sensitization at the brain stem/thalamic level. This insight could open new pathways for targeting the parenchymal-meningeal interface to develop novel abortive or preventive migraine treatments.

Strengths:<br /> The manuscript is well-written. The studies are broadly relevant to neuroscientists and physiologists, as well as neurologists, pain clinicians, and patients with migraine with aura and acephalgic migraine. The studies are well-conceived and appear to be technically well-executed.

Weaknesses:<br /> 1) Lack of anatomic confirmation that the dura were intact in these studies: it is notoriously challenging to create a cranial window in mouse skull without disrupting or even removing the dura. It was unclear which meningeal layers were captured in the imaging plane. Did the visualized trigeminal afferents terminate in the dura, subarachnoid space, or pia (as suggested by Supplemental Fig 1, capturing a pial artery in the imaging plane)? Were z-stacks obtained, to maintain the imaging plane, or to follow visualized afferents when they migrated out of the imaging plane during meningeal deformations?<br /> 2) Findings here, from mice with chronic closed cranial windows, failed to fully replicate prior findings from rats with acute open cranial windows. While the species, differing levels of inflammation and intracranial pressure in these two preparations may contribute, as the authors suggested, the modality of measuring neuronal activity could also contribute to the discrepancy. In the present study, conclusions are based entirely on fluorescence signals from GCamp6s, whereas prior rat studies relied upon multiunit recordings/local field potentials from tungsten electrodes inserted in the trigeminal ganglion. As a family, GCamp6 fluorophores are strongly pH dependent, with decreased signal at acidic pH values (at matched Ca2+ concentration). CSD induces an impressive acidosis transient, at least in the brain parenchyma, so one wonders whether the suppression of activity reported in the wake of CSD (Figure 2) in fact reflects decreased sensitivity of the GCamp6 reporter, rather than decreased activity in the fibers. If intracellular pH in trigeminal afferent fibers acidifies in the wake of CSD, GCamp6s fluorescence may underestimate the actual neuronal activity.

Reviewer #3 (Public Review):

Summary:<br /> The study aims to elucidate the spatial dynamics of subcellular astrocytic calcium signaling. Specifically, they elucidate how subdomain activity above a certain spatial threshold (~23% of domains being active) heralds a calcium surge that also affects the astrocytic soma. Moreover, they demonstrate that processes on average are included earlier than the soma and that IP3R2 is necessary for calcium surges to occur. Finally, they associate calcium surges with slow inward currents.

Strengths:<br /> The study addresses an interesting topic that is only partially understood. The study uses multiple methods including in vivo two-photon microscopy, acute brain slices, electrophysiology, pharmacology, and knockout models. The conclusions are strengthened by the same findings in both in vivo anesthetized mice and in brain slices.

Weaknesses:<br /> The method that has been used to quantify astrocytic calcium signals only analyzes what seems to be a small proportion of the total astrocytic domain on the example micrographs, where a structure is visible in the SR101 channel (see for instance Reeves et al. J. Neurosci. 2011, demonstrating to what extent SR101 outlines an astrocyte). This would potentially heavily bias the results: from the example illustrations presented it is clear that the calcium increases in what is putatively the same astrocyte goes well beyond what is outlined with automatically placed small ROIs. The smallest astrocytic processes are an order of magnitude smaller than the resolution of optical imaging and would not be outlined by either SR101 or with the segmentation method judged by the ROIs presented in the figures. Completely ignoring these very large parts of the spatial domain of an astrocyte, in particular when making claims about a spatial threshold, seems inappropriate. Several recent methods published use pixel-by-pixel event-based approaches to define calcium signals. The data should have been analyzed using such a method within a complete astrocyte spatial domain in addition to the analyses presented. Also, the authors do not discuss how two-dimensional sampling of calcium signals from an astrocyte that has processes in three dimensions (see Bindocci et al, Science 2017) may affect the results: if subdomain activation is not homogeneously distributed in the three-dimensional space within the astrocyte territory, the assumptions and findings between a correlation between subdomain activation and somatic activation may be affected.

The experiments are performed either in anesthetized mice, or in slices. The study would have come across as much more solid and interesting if at least a small set of experiments were performed also in awake mice (for instance during spontaneous behavior), given the profound effect of anesthesia on astrocytic calcium signaling and the highly invasive nature of preparing acute brain slices. The authors mention the caveat of studying anesthetized mice but claim that the intracellular machinery should remain the same. This explanation appears a bit dismissive as the response of an astrocyte not only depends on the internal machinery of the astrocyte, but also on how the astrocyte is stimulated: for instance synaptic stimulation or sensory input likely would be dependent on brain state and concurrent neuromodulatory signaling which is absent in both experimental paradigms. The discussion would have been more balanced if these aspects were dealt with more thoroughly.

The study uses a heaviside step function to define a spatial 'threshold' for somata either being included or not in a calcium signal. However, Fig 4E and 5D showing how the method separates the signal provide little understanding for the reader. The most informative figure that could support the main finding of the study, namely a ~23% spatial threshold for astrocyte calcium surges reaching the soma, is Fig. 4G, showing the relationship between the percentage of arborizations active and the soma calcium signal. A similar plot should have been presented in Fig 5 as well. Looking at this distribution, though, it is not clear why ~23% would be a clear threshold to separate soma involvement, one can only speculate how the threshold for a soma event would influence this number. Even if the analyses in Fig. 4H and the fact that the same threshold appears in two experimental paradigms strengthen the case, the results would have been more convincing if several types of statistical modeling describing the continuous distribution of values presented in Fig. 4E (in addition to the heaviside step function) were presented.

The description of methods should have been considerably more thorough throughout. For instance which temperature the acute slice experiments were performed at, and whether slices were prepared in ice-cold solution, are crucial to know as these parameters heavily influence both astrocyte morphology and signaling. Moreover, no monitoring of physiological parameters (oxygen level, CO2, arterial blood gas analyses, temperature etc) of the in vivo anesthetized mice is mentioned. These aspects are critical to control for when working with acute in vivo two-photon microscopy of mice; the physiological parameters rapidly decay within a few hours with anesthesia and following surgery.

Reviewer #3 (Public Review):

This paper presents several eyetracking experiments measuring task-directed reading behavior where subjects read texts and answered questions. It then models the measured reading times using attention patterns derived from deep-neural network models from the natural language processing literature. Results are taken to support the theoretical claim that human reading reflects task-optimized attention allocation.

Strengths:

(1) The paper leverages modern machine learning to model a high-level behavioral task (reading comprehension). While the claim that human attention reflects optimal behavior is not new, the paper considers a substantially more high-level task in comparison to prior work. The paper leverages recent models from the NLP literature which are known to provide strong performance on such question-answering tasks, and is methodologically well grounded in the NLP literature.

(2) The modeling uses text- and question-based features in addition to DNNs, specifically evaluates relevant effects, and compares vanilla pretrained and task-finetuned models. This makes the results more transparent and helps assess the contributions of task optimization. In particular, besides fine-tuned DNNs, the role of the task is further established by directly modeling the question relevance of each word. Specifically, the claim that human reading is predicted better by task-optimized attention distributions rests on (i) a role of question relevance in influencing reading in Expts 1-2 but not 4, and (ii) the fact that fine-tuned DNNs improve prediction of gaze in Expts 1-2 but not 4.

(3) The paper conducts experiments on both L2 and L1 speakers.

Weaknesses:

(1) Under the hypothesis advanced, human reading should adapt rationally to task demands. Indeed, Experiment 1 tests questions from different types in blocks (local and global), and the paper provides evidence that this encourages the development of question-type-specific reading strategies -- indeed, this specifically motivates Experiment 2, and is confirmed indirectly in the comparison of the effects found in the two experiments ("all these results indicated that the readers developed question-type-specific strategies in Experiment 1"). On the other hand, finetuning the model on one of the two types does not seem to reproduce this differential behavior, in the sense that fit to reading data is not improved. In this sense, the model seems to have limited abilities in reproducing the observed task dependence of human reading.

The results support the conclusions well, with the weakness described above a limitation of the modeling approach chosen.

The data are likely to be useful as a benchmark in further modeling of eye-movements, an area of interest to computational research on psycholinguistics.<br /> The modeling results contribute to theoretical understanding of human reading behavior, and strengthens a line of research arguing that it reflects task-adaptive behavior.

Reviewer #3 (Public Review):

Summary:<br /> Zhang and Lauder characterized both aerobic and anaerobic metabolic energy contributions in schools and solitary fishes in the Giant danio (Devario aequipinnatus) over a wide range of water velocities. By using a highly sophisticated respirometer system, the authors measure the aerobic metabolisms by oxygen uptake rate and the non-aerobic oxygen cost as excess post-exercise oxygen consumption (EPOC). With these data, the authors model the bioenergetic cost of schools and solitary fishes. The authors found that fish schools have a J-shaped metabolism-speed curve, with reduced total energy expenditure per tail beat compared to solitary fish. Fish in schools also recovered from exercise faster than solitary fish. Finally, the authors conclude that these energetic savings may underlie the prevalence of coordinated group locomotion in fish.

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

Strengths:<br /> This work aims to understand whether animals moving through fluids (water in this case) exhibit highly coordinated group movement to reduce the cost of locomotion. By calculating the aerobic and anaerobic metabolic rates of school and solitary fishes, the authors provide direct energetic measurements that demonstrate the energy-saving benefits of coordinated group locomotion in fishes. The results of this paper show that fish schools save anaerobic energy and reduce the recovery time after peak swimming performance, suggesting that fishes can apport more energy to other fitness-related activities whether they move collectively through water.

Weaknesses:<br /> Although the paper does have strengths in principle, the weakness of the paper is the method section. There is too much irrelevant information in the methods that sometimes is hard to follow for a researcher unfamiliar with the research topic. In addition, it was hard to imagine the experimental (respirometer) system used by the authors in the experiments; therefore, it would be beneficial for the article to include a diagram/scheme of that respiratory system.

Reviewer #3 (Public Review):

Summary:<br /> This paper investigates the evolutionary aspects around a single amino acid polymorphism in an immune peptide (the antimicrobial peptide Diptericin A) of Drosophila melanogaster. This polymorphism was shown in an earlier population genetic study to be under long-term balancing selection. Using flies with different AA at this immune peptide it was found that one allelic form provides better survival of systemic infections by a bacterial pathogen, but that the alternative allele provides its carriers a longer lifespan under certain conditions (depending on the microbiota). It is suggested that these contrasting fitness effects of the two alleles contribute to balance their long-term evolutionary fate.

Strengths:<br /> The approach taken and the results presented are interesting and show the way forward for studying such polymorphisms experimentally.

Weaknesses:<br /> 1. A clear demonstration (in one experiment) that the antagonistic effect of the two selection pressures isolated is not provided.

The study is overwhelming with many experiments and countless statistical tests. The overall conclusion of the many experiments and tests suggests that "dptS69 flies survive systemic infection better, while dptS69R flies survive some opportunistic gut infections better." (line 444-446). Given the number of results, different experiments, and hundreds of tests conducted, how can we make sure that the result is not just one of many possible combinations? I suggest experimentally testing this conclusion in one experiment (one may call this the "killer-experiment") with the relevant treatments being conducted at the same time, side by side, and the appropriate statistical test being conducted by a statistical test for a treatment x genotype interaction effect.

2. The implication that the two forms of selection acting on the immune peptide are maintained by balancing selection is not supported.

The picture presented about how balancing selection is working is rather simplistic and not convincing. In particular, it is not distinguished between fluctuating selection (FL) and balancing selection (BL). BL is the result of negative frequency-dependent selection. It may act within populations (e.g. Red Queen type processes, mating types) or between populations (local adaptation). FL is a process that is sometimes suggested to produce BL, but this is only the case when selection is negative frequency dependent. In most cases, FL does not lead to BL.

The presented study is introduced with a framework of BL, but the aspects investigated are all better described as FL (as the title says: "A suite of selective pressures ..."). The two models presented in the introduction (lines 62 to 69; two pathogens, cost of resistance) are both examples for FL, not for BL.

Finally, no evidence is presented that the different selection pressures suggested to select on the different allelic forms of the immune peptide are acting to produce a pattern of negative frequency dependence.

Reviewer #3 (Public Review):

Summary:<br /> This paper applies PSMC and genomic data to test interesting questions about how life history changes impact long-term population sizes.

Strengths:<br /> This is a creative use of PSMC to test explicit a priori hypotheses about season migration and Ne. The PSMC analyses seem well done and the authors acknowledge much of the complexity of interpretation in the discussion.

Weaknesses:<br /> The authors use an average generation time for all taxa, but the citations imply generation time is known for at least some of them. Are there differences in generation time associated with migration? I am not a bird biologist, but quick googling suggests maybe this is the case (https://doi.org/10.1111/1365-2656.13983). I think it important the authors address this, as differences in generation time I believe should affect estimates of Ne and growth.

The writing could be improved, both in the introduction for readers not familiar with the system and in the clarity and focus of the discussion.

Reviewer #3 (Public Review):

Summary:<br /> The authors carried out structural and biochemical studies to investigate the multiple functions of CBC and ALYREF in RNA metabolism.

Strengths:<br /> For the structural study part, the authors successfully revealed how NCBP1 and NCBP2 subunits interact with mALYREF (residues 1-155). Their binding interface was then confirmed by biochemical assays (mutagenesis and pull-down assays) presented in this study.

Weaknesses:<br /> The authors did not provide functional data to support their proposed models. The authors should include more details regarding the workflow of their cryo-EM data processing in the figure.

Reviewer #3 (Public Review):

Summary:<br /> In their manuscript "Recovery of proteasome activity in cells pulse-treated with proteasome inhibitors is independent of DDI2", Ibtisam and Kisselev investigate proteasome recovery in HAP1 cells either WT or DDI2 KO upon inhibition of proteasome via bortezomib or carfilzomib. The authors argue that proteasome recovery is independent of DDI2 as it is independent of the novo proteasome subunit synthesis. They argue recovery is dependent on the assembly of already synthesized proteasome subunits.

Strengths:<br /> The findings are important as they provide insight into a transcriptionally-independent proteasome stress recovery that is likely applicable across distinct cellular subtypes. Comparable proteasome recovery early on (<12 hours) from proteasomal inhibition in DDI2 KO cell lines was already noted in other manuscripts, including Chen et al, suggesting that this phenomenon is applicable to other histotypes.

Weaknesses:<br /> Some of the conclusions are not adequately supported by the data and how generalizable these findings are is unclear. In particular, there is concern regarding the status of the ubiqutin-proteasome-system in the HAP1 cell line that was used for these studies. In a previously published model system, a dependency on DDI2 and NRF1 was clearly demonstrated and this pathway was critical for late (12-24 hours) proteasome recovery as well as cell viability. The model system used here (HAP1 cells) seems completely independent of DDI2 both for proteasome recovery and viability as curves are substantially overlapping. It would be important to assess how the baseline proteasome activity in HAP1 cells compare to other cell lines and model system as these cells may be largely independent of proteasome degradation and their synthetic load on the pathway very modest.

It would also be relevant to look at later time points of proteasome recovery as one would expect DDI2 to play a role later on in the recovery of proteasome. the authors may have missed that time point as cells do not appear to recover close to 100% proteasome activity by 24 hours not even when the smallest concentration of carfilzomib is used.

A critical experiment to look at de novo proteasome assembly was not carried out, leaving the data hypothetical.

Finally, the authors leverage HAP1 cells for their work and should be mindful of not generalizing findings or disputing other author's conclusions in the absence of adequate experiments to support their hypothesis.

Reviewer #3 (Public Review):

Youssef et al. have used a range of markers to identify cancer stem cells (CSCs) in patients with oral cancers. CSCs were identified in lab conditions and were often linked to the invasiveness of cancers. The authors found a combination of markers convincingly liked to known biology and found cells expressing them in the invading cancers.<br /> The major weakness of the paper is in the technical side. There isn't enough description as to how they discriminated between CSCs inside the tumour and those invading its surroundings. Similarly, the way the information is presented it is not clear why artificial intelligence was needed to enhance the accuracy of the method linking CSCs to cancer invasion (and ultimately deadly metastasis to other organs).

• for: 3 things Nora learned from her father, mutual learning, indyweb - mutual learning

• paraphrase

  • first, Nora learned what his father was learning
  • second, Nora learned what it looks like to learn and
• third, and most important, Nora learned she could be in relationship in learning, mutual learning

Reviewer #3 (Public Review):

Summary:<br /> The paper "Unveiling the signaling network of FLT3-ITD AML improves drug sensitivity prediction" reports the combination of prior knowledge signaling networks, multiparametric cell-based data on the activation status of 14 crucial proteins emblematic of the cell state downstream of FLT3 obtained under a variety of perturbation conditions and Boolean logic modeling, to gain mechanistic insight into drug resistance in acute myeloid leukemia patients carrying the internal tandem duplication in the FLT3 receptor tyrosine kinase and predict drug combinations that may reverse pharmacorresistant phenotypes. Interestingly, the utility of the approach was validated in vitro, and also using mutational and expression data from 14 patients with FLT3-ITD positive acute myeloid leukemia to generate patient-specific Boolean models.

Strengths:<br /> The model predictions were positively validated in vitro: it was predicted that the combined inhibition of JNK and FLT3, may reverse resistance to tyrosine kinase inhibitors, which was confirmed in an appropriate FLT3 cell model by comparing the effects on apoptosis and proliferation of a JNK inhibitor and midostaurin vs. midostaurin alone.

Whereas the study does have some complexity, readability is enhanced by the inclusion of a section that summarizes the study design, plus a summary figure. Availability of data as supplementary material is also a high point.

Weaknesses:<br /> Some aspects of the methodology are not properly described (for instance, no methodological description has been provided regarding the clustering procedure that led to Figs. 2C and 2D).

It is not clear in the manuscript whether the patients gave their consent to the use of their data in this study, or the approval from an ethical committee. These are very important points that should be made explicit in the main text of the paper.

The authors claim that some of the predictions of their models were later confirmed in the follow-up of some of the 14 patients, but it is not crystal clear whether the models helped the physicians to make any decisions on tailored therapeutic interventions, or if this has been just a retrospective exercise and the predictions of the models coincide with (some of) the clinical observations in a rather limited group of patients. Since the paper presents this as additional validation of the models' ability to guide personalized treatment decisions, it would be very important to clarify this point and expand the presentation of the results (comparison of observations vs. model predictions).

Reviewer #3 (Public Review):

Yin-wei Lin et al set out to visualize the inactive conformation of full length Bruton's Tyrosine Kinase (BTK), a molecule that has evaded high resolution structural studies in its full length form to this date. An open question in the field is how the Pleckstrin Homology-Tec Homology (PHTH) domain inhibits BTK activity, with multiple competing models in the field. The authors used a complimentary set of biophysical techniques combined with well thought out stabilizing mutations to obtain structural insights into BTK regulation in its full length form. They were able to crystallize the full length construct of BTK but unfortunately the PHTH was not resolved yielding the structure similar to previously obtained in the field. The investigation of the same construct by SAXS yielded an elongated structural model, consistent with previous SAXS studies. Using cryo-EM the authors obtained a low resolution model for the FL BTK with a loosely connected density assigned to the dynamic PHTH around the compact SH2-SH3-Kinase Domain (KD) core. To gain further molecular insights into PHTH-KD interactions the authors followed a previously reported strategy and generated a fusion of PHTH-KD with a longer linker, yielding a crystal structure with a novel PHTH-KD interface which they tested in biochemical assays. Lastly, Yin-wei Lin et al crystallized the BTK KD in a novel partially active state in a "face to face" dimer with kinases exchanging the activation loops, although partially disordered, being theoretically perfectly positioned for trans phosphorylation. Overall this presents a valiant effort to gain molecular insights into what clearly is a dynamic regulatory motif on BTK and is a valuable addition to the field.

I think the authors addressed all the comments that I had during the initial round of review. The only thing I can think of that would strengthen the paper is to add a supplemental figure/table with the results of unbiased SITUS fitting rather than just saying that it is close to manual fitting. Additionally, SITUS outputs not just one best solution but all the top fits and having a significant difference in cross correlation between the best fit and second best fit is usually indicative of true fit. As the authors already ran SITUS and colores they have this data and I think having a sup table with cross correlations for the top 3 fits for each of their maps would make their EM fitting more convincing and not hard to do.

Lastly, it seems like both the authors and I agree that the cryoEM reconstructions do not correspond to the reported resolutions by the FSC. This point in no way changes any of the conclusions of the paper, however, I can't help but feel guilty that some student who is not in the field will look at these EM maps in the future and think that this is how 7A reconstructions should look like. If the authors, maybe somewhere in the methods could add a sentence indicating that the FSC curves may be overly optimistic and that there are no secondary structure features present which would be expected at these resolutions, that would be great.

Reviewer #3 (Public Review):

Summary:<br /> In the manuscript "Articular cartilage corefucosylation regulates tissue resilience in osteoarthritis", the authors investigate the glycan structural changes in the context of pre-OA conditions. By mainly conducting animal experiments and glycomic analysis, this study clarified the molecular mechanism of N-glycan core fucosylation and Fut8 expression in the extracellular matrix resilience and unrecoverable cartilage degeneration. Lastly, a comprehensive glycan analysis of human OA cartilage verified the hypothesis.

Strengths:<br /> Generally, this manuscript is well structured with rigorous logic and clear language. This study is valuable and important in the early diagnosis of OA patients in the clinic, which is a great challenge nowadays.

Weaknesses:<br /> I recommend minor revisions:

1. I would suggest the authors prepare an illustrative scheme for the whole study, to explain the complex mechanism and also to summarize the results.

2. Including but not limited to Figures 2A-C, Figures 3A and C, Figure 4B, and Figures 5A and D. The texts in the above images are too small to read, I would suggest the authors remake these images.

3. The paper is generally readable, but the language could be polished a bit. Several writing errors should be realized during the careful check.

4. As several species and OA models were conducted in this study, it would be better if the authors could note the reason behind their choice for it.

Reviewer #3 (Public Review):

Summary:<br /> Hornofova et al examined interactions between the nucleolus and promyelocytic leukemia nuclear bodies (PML-NBs) termed PML-nucleolar associations (PNAs). PNAs are found in a minor subset of cells, exist within distinct morphological subcategories, and are induced by cellular stressors including genotoxic damage. A systematic pharmacological investigation identified that compounds that inhibit RNA Polymerase 1 (RNAPI) and/or topoisomerase 1 or 2A caused the greatest proportion of cells with PNA. A specific RAD51 inhibitor (R02) impacted the number of cells exhibiting PNAs and PNA morphology. Genetic double-strand break (DSB) induction within the rDNA locus also induced PNA structures that were more prevalent when non-homologous end joining (NHEJ) was inhibited.

Strengths:<br /> PNA are morphologically distinct and readily visualized. The imaging data are high quality, and rDNA is amenable to studying nuclear dynamics. Specific induction of rDNA damage is a strong addition to the non-specific pharmacological damage characterized early in the manuscript. These data nicely demonstrate that rDNA double-strand breaks undermine PNA formation. Figure 1 is a comprehensive examination and presents a compelling argument that RNAPI and/or TOP1, TOP2A inhibition promote PNA structures.

Weaknesses:<br /> The data are limited to fixed fluorescent microscopy of structures present in a minority of cells. Data are occasionally qualitative and/or based upon interpretation of dynamic events extrapolated from fixed imaging. This study would benefit from live imaging that captures PNA dynamics.

Cell cycle and cell division are not considered. Double-strand break repair is cell cycle dependent, and most experiments occur over days of treatment and recovery. It is unclear if the cultures are proliferating, or which cell cycle phase the cells are in at the time of analysis. It is also unclear if PNAs are repeatedly dissociating and reforming each cell division.

The relationship of PNA morphologies (bowl, funnel, balloon, and PML-NDS) also remains unclear. It is possible that PNAs mature/progress through the distinct morphologies, and that morphological presentation is a readout of repair or damage in the rDNA locus. However, this is not formally addressed.

An I-Ppol targeted sequence within the rDNA locus suggests 3D structural rearrangement following damage. An orthogonal approach measuring rDNA 3D architecture would benefit comprehension. Following I-Ppol induction, it is possible that cells arrest in a G1 state. This may explain why targeting NHEJ has a greater impact on the number of 53BP1 foci and should be investigated.

Conclusions: PNAs are a phenomenon of biological significance and understanding that significance is of value. More work is required to advance knowledge in this area. The authors may wish to examine the literature on APBs (Alt-associated PML-NBs), which are similar structures where telomeres associate with PML-NBs in a specific subset of cancers. It is possible that APBs and PNAs share similar biology, and prior efforts on APBs may help guide future PNA studies.

Reviewer #3 (Public Review):

Summary:<br /> The authors are interested in the relative importance of PRL versus GH and their interactive signaling in breast cancer. After examining GHR-PRLR interactions in response to ligands, they suggest that a reduction in cell surface GHR in response to PRL may be a mechanism whereby PRL can sometimes be protective against breast cancer.

Strengths:<br /> The strengths of the study include the interesting question being addressed and the application of multiple complementary techniques, including dSTORM, which is technically very challenging, especially when using double labeling. Thus, dSTORM is used to show co-clustering of GHR and PRLR, and, in response to PRL, rapid internalization of GHR and increased cell surface PRLR. Proximity ligation assays demonstrate that some GHR and PRLR are within 40 nm (≈ 4 plasma membranes) of each other and that upon ligand stimulation, they move apart. Intact receptor knockin and knockout approaches and receptor constructs without the Jak2 binding domain demonstrate a) a requirement for the PRLR for there to be PRL-driven internalization of GHR, and b) that Jak2-PRLR interactions are necessary for the stability of the GHR-PRLR colocalizations.

Weaknesses:<br /> The manuscript suffers from a lack of detail, which in places makes it difficult to evaluate the data and would make it very difficult for the results to be replicated by others. In addition, the manuscript would very much benefit from a full discussion of the limitations of the study. For example, the manuscript is written as if there is only one form of the PRLR while the anti-PRLR antibody used for dSTORM would also recognize the intermediate form and short forms 1a and 1b on the T47D cells. Given the very different roles of these other PRLR forms in breast cancer (Dufau, Vonderhaar, Clevenger, Walker and other labs), this limitation should at the very least be discussed. Similarly, the manuscript is written as if Jak2 essentially only signals through STAT5 but Jak2 is involved in multiple other signaling pathways from the multiple PRLRs, including the long form. Also, while there are papers suggesting that PRL can be protective in breast cancer, the majority of publications in this area find that PRL promotes breast cancer. How then would the authors interpret the effect of PRL on GHR in light of all those non-protective results?

Reviewer #3 (Public Review):

Summary:<br /> Feng et al. test the hypothesis that human body size constrains the perception of object affordances, whereby only objects that are smaller than the body size will be perceived as useful and manipulable parts of the environment, whereas larger objects will be perceived as "less interesting components."

To test this idea, the study employs a multi-method approach consisting of three parts:

In the first part, human observers classify a set of 24 objects that vary systematically in size (e.g., ball, piano, airplane) based on 14 different affordances (e.g., sit, throw, grasp). Based on the average agreement of ratings across participants, the authors compute the similarity of affordance profiles between all object pairs. They report evidence for two homogenous object clusters that are separated based on their size with the boundary between clusters roughly coinciding with the average human body size. In follow-up experiments, the authors show that this boundary is larger/smaller in separate groups of participants who are instructed to imagine themselves as an elephant/cat.

In the second part, the authors ask different large language models (LLMs) to provide ratings for the same set of objects and affordances and conduct equivalent analyses on the obtained data. Some, but not all, of the models produce patterns of ratings that appear to show similar boundary effects, though less pronounced and at a different boundary size than in humans.

In the third part, the authors conduct an fMRI experiment. Human observers are presented with four different objects of different sizes and asked if these objects afford a small set of specific actions. Affordances are either congruent or incongruent with objects. Contrasting brain activity on incongruent trials against brain activity on congruent trials yields significant effects in regions within the ventral and dorsal visual stream, but only for small objects and not for large objects.

The authors interpret their findings as support for their hypothesis that human body size constrains object perception. They further conclude that this effect is cognitively penetrable, and only partly relies on sensorimotor interaction with the environment (and partly on linguistic abilities).

Strengths:<br /> The authors examine an interesting and relevant question and articulate a plausible (though somewhat underspecified) hypothesis that certainly seems worth testing. Providing more detailed insights into how object affordances shape perception would be highly desirable. Their method of analyzing similarity ratings between sets of objects seems useful and the multi-method approach is quite original and interesting.

Weaknesses:<br /> The study presents several shortcomings that clearly weaken the link between the obtained evidence and the drawn conclusions. Below I outline my concerns in no particular order:

1) Even after several readings, it is not entirely clear to me what the authors are proposing and to what extent the conducted work actually speaks to this. In the introduction, the authors write that they seek to test if body size serves not merely as a reference for object manipulation but also "plays a pivotal role in shaping the representation of objects." This motivation seems rather vague motivation and it is not clear to me how it could be falsified.<br /> Similarly, in the discussion, the authors write that large objects do not receive "proper affordance representation," and are "not the range of objects with which the animal is intrinsically inclined to interact, but probably considered a less interesting component of the environment." This statement seems similarly vague and completely beyond the collected data, which did not assess object discriminability or motivational values.<br /> Overall, the lack of theoretical precision makes it difficult to judge the appropriateness of the approaches and the persuasiveness of the obtained results. This is partly due to the fact that the authors do not spell out all of their theoretical assumptions in the introduction but insert new "speculations" to motivate the corresponding parts of the results section. I would strongly suggest clarifying the theoretical rationale and explaining in more detail how the chosen experiments allow them to test falsifiable predictions.

2) The authors used only a very small set of objects and affordances in their study and they do not describe in sufficient detail how these stimuli were selected. This renders the results rather exploratory and clearly limits their potential to discover general principles of human perception. Much larger sets of objects and affordances and explicit data-driven approaches for their selection would provide a far more convincing approach and allow the authors to rule out that their results are just a consequence of the selected set of objects and actions.

3) Relatedly, the authors could be more thorough in ruling out potential alternative explanations. Object size likely correlates with other variables that could shape human similarity judgments and the estimated boundary is quite broad (depending on the method, either between 80 and 150 cm or between 105 to 130 cm). More precise estimates of the boundary and more rigorous tests of alternative explanations would add a lot to strengthen the authors' interpretation.

4) Even though the division of the set of objects into two homogenous clusters appears defensible, based on visual inspection of the results, the authors should consider using more formal analysis to justify their interpretation of the data. A variety of metrics exist for cluster analysis (e.g., variation of information, silhouette values) and solutions are typically justified by convergent evidence across different metrics. I would recommend the authors consider using a more formal approach to their cluster definition using some of those metrics.

5) While I appreciate the manipulation of imagined body size, as a way to solidify the link between body size and affordance perception, I find it unfortunate that this is implemented in a between-subjects design, as this clearly leaves open the possibility of pre-existing differences between groups. I certainly disagree with the authors' statement that their findings suggest "a causal link between body size and affordance perception."

6) The use of LLMs in the current study is not clearly motivated and I find it hard to understand what exactly the authors are trying to test through their inclusion. As noted above, I think that the authors should discuss the putative roles of conceptual knowledge, language, and sensorimotor experience already in the introduction to avoid ambiguity about the derived predictions and the chosen methodology. As it currently stands, I find it hard to discern how the presence of perceptual boundaries in LLMs could constitute evidence for affordance-based perception.

7) Along the same lines, the fMRI study also provides very limited evidence to support the authors' claims. The use of congruency effects as a way of probing affordance perception is not well motivated. What exactly can we infer from the fact a region may be more active when an object is paired with an activity that the object doesn't afford? The claim that "only the affordances of objects within the range of body size were represented in the brain" certainly seems far beyond the data.

Importantly (related to my comments under 2) above), the very small set of objects and affordances in this experiment heavily complicates any conclusions about object size being the crucial variable determining the occurrence of congruency effects.

I would also suggest providing a more comprehensive illustration of the results (including the effects of CONGRUENCY, OBJECT SIZE, and their interaction at the whole-brain level).

Overall, I consider the main conclusions of the paper to be far beyond the reported data. Articulating a clearer theoretical framework with more specific hypotheses as well as conducting more principled analyses on more comprehensive data sets could help the authors obtain stronger tests of their ideas.

Reviewer #3 (Public Review):

Summary: This study investigated the role of mTORC1 and 2 in a mouse model of developmental epilepsy which simulates epilepsy in cortical malformations. Given activation of genes such as PTEN activates TORC1, and this is considered to be excessive in cortical malformations, the authors asked whether inactivating mTORC1 and 2 would ameliorate the seizures and malformation in the mouse model. The work is highly significant because a new mouse model is used where Raptor and Rictor, which regulate mTORC1 and 2 respectively, were inactivated in one hemisphere of the cortex. The work is also significant because the deletion of both Raptor and Rictor improved the epilepsy and malformation. In the mouse model, the seizures were generalized or there were spike-wave discharges (SWD). They also examined the interictal EEG. The malformation was manifested by increased cortical thickness and soma size.

Strengths: The presentation and writing are strong. The quality of data is strong. The data support the conclusions for the most part. The results are significant: Generalized seizures and SWDs were reduced when both Torc1 and 2 were inactivated but not when one was inactivated.

Weaknesses: One of the limitations is that it is not clear whether the area of cortex where Raptor or Rictor were affected was the same in each animal. Also, it is not clear which cortical cells were measured for soma size. Another limitation is that the hippocampus was affected as well as the cortex. One does not know the role of cortex vs. hippocampus. Any discussion about that would be good to add. It would also be useful to know if Raptor and Rictor are in glia, blood vessels, etc.

Reviewer #3 (Public Review):

This manuscript analyzed resting state functional MRI metrics related to behavioral variant frontotemporal dementia (bvFTD) for associations with patterns of neurotransmitter system receptor distribution, patterns of neurotransmitter-related gene expression, and profiles of performance on neuropsychological test battery items.

The overarching goal of the work was to assess whether these analyses point to selective vulnerability of some neurotransmitter systems in the symptomatology of bvFTD. The manuscript reports that reductions in fMRI measures of local brain functional activity in bvFTD followed the distribution of specific neurotransmitter systems. No similar findings were identified for MRI-based gray matter volume measurements.

Strengths of the manuscript include its leveraging of publicly available tools for large-scale regional brain mRNA profiles and neurotransmitter receptor distributions. An additional positive step for the literature involves further development of the concept that biomarkers of disruptions to specific functionally-connected networks may guide specific treatment strategies (as a corollary to this work, related to neurotransmitter system disruption) in neurodegenerative disease.

A weakness of the manuscript is that it is not able to directly address the main literature gap described in the Introduction -- namely, whether there is specific vulnerability of certain neuronal types versus other in bvFTD, or whether broader network/region-based neurodegeneration is the driver (and happens to include some selective neurotransmitter-related disruptions). In other words, if "A" is a biomarker of bvFTD, "A" has a partial correlation with "B", and the "AB" correlation has a partial correlation with "C", it seems too far a leap to conclude that "B" (in this case, profiles/distributions of neurotransmitter systems) is the central figure in the cascade.

Reviewer #3 (Public Review):

The authors used optogenetic manipulations and electrophysiology recordings to study a causal role and the coding of superficial part of the mouse Superior Colliculus (SCs) during figure detection tasks. Authors previously reported that figure-ground perception relies on V1 activity (Kirchberger et al. 2021) and pointed out that silencing of V1 reduced the accuracy of the mice but still the performance was above the chance level. Therefore, visual information necessary in this task, could be processed via alternative pathways. In this study, authors investigated specifically SCs and used similar approach and analysis as in Kirchberger et al. 2021. Optogenetic silencing of the activity of visual neurons in SCs impaired the accuracy in all 3 versions of the figure detection task: contrast, orientation, and phase. Electrophysiology recordings revealed that SCs neurons are figure-ground modulated, but only by contrast- and orientation-based figures. They show SCs visually responsive neurons reflect behavioral performance in orientation-based figure task. The authors conclusion is that SCs is involved in figure detection task.

Overall, this study provides evidence that mouse SCs is involved in a figure detection task, and codes for task-related events. Authors heroically compared results between 3 different versions of the figure-based detection task. The logic of the study flows through the manuscript and authors prepared a detailed description of methods. However, my main concern is with 1) the amount of data used to make the key arguments, and 2) the interpretation of results. The key findings of this study (figure-ground modulations in SCs) could be a result of the visual cortical feedback in SCs during the task, or pupil diameter changes. Unfortunately, the authors did not rule out these possibilities.

Still, this study can be relevant to a general neuroscience audience, and results could be more convincing if the authors could clarify:

1) Optogenetic inactivation<br /> - The impact of laser stimulation on neural activity is not satisfactory (Supplementary Figure 1). The method seems to be insufficient to fully salience neurons. Electrophysiology control recordings of inactivation are performed in anesthetized mice, which is not a fair estimation of the effect in awake state. Therefore, it rises a major question how effective the inactivation is during the task?<br /> - Could authors provide more details if laser stimulation has an effect only on visual, or all sampled units? How many of units were recorded, and how many show positive and negative laser modulation? How local the inactivation effect is? Where was the silicon probe placed in relation to AAV expression and optical fiber position?

2) Number of sessions and units<br /> - The inactivation effect on behavior (Figure 1E) during phase-task has a significantly larger effect at 66ms after stimulus onset. How can authors explain this? Could this result be biased by one animal/session, or low number of trials for this condition? There is no information about number of trials, or sessions from individual animals. Adding a single example of animal's performance, and sessions for individual mice could clarify results in Figure 1.

- Figure 2H shows an example of neuron with an effect in the figure detection task based on phase difference, but Figure 2I/J (population response) shows there is no effect. Overall, the conclusion is that SCs neurons are not modulated by a phase-defined object. It seems that number of mice and hence units are smaller in phase-detection task comparing to two other tasks. How many of single units are modulated in each version of the task? How big is the FGM effect on single neuron response (could authors provide values in spikes/s)?

- One task is dropped from analysis which it is one of the main points of the paper: to compare responses across different versions of the figure detection task in SCs. But Figures 3-5 only focuses on two tasks, because there is not enough of data for figure-based contrast task.

3) Figure-ground modulation in SCs<br /> - How is neural activity correlated with pupil size, movement (eg. whisking, or face), or jaw movement (preparation to lick)? Can activity of FGM neurons in SCs be explained by these behavioral variables?<br /> - Could authors describe in more detail how they measure a pupil position and diameter, by showing raw data, pupil size aligned to task events?<br /> - How does pupil diameter change between tasks? Small pupil changes can affect responses of visual neurons, and this could be an explanation of FGM effect in SCs. Can authors rule out this possibility, by for example showing pupil size and changes in position at stimulus onset in different tasks?<br /> - Authors in discussion mentioned that the modulation of V1 could be transferred to SCs through the direct projection. Moreover, animals perform above chance in both inactivation experiments (V1 and SC), which could be also an effect of geniculate projections to HVAs (eg. Sincich et al. 2004). Could authors discuss different possibilities?

4) Interpretation of multisensory neurons is not clear. In Figure 5B, there is an example of neuron with two peaks of response. Authors speculate about the activity (pre-motor) but there is lack of clear measurement showing "multisensory" response of these neurons. Could these responses be related to the movement of the lick spout towards the mouth of the mouse (500 ms after the presentation of the stimulus)? Moreover, the number of "multisensory" units is very low (5 units, and 8 units).

Reviewer #3 (Public Review):

Summary:<br /> The authors set out to characterize the anatomical connectivity profile and the functional responses of chandelier cells (ChCs) in the mouse primary visual cortex. Using retrograde rabies tracing, optogenetics, and in vitro electrophysiology, they found that the primary source of input to ChCs are local layer 5 pyramidal cells, as well as long-range thalamic and cortical connections. ChCs provided input to local layer 2/3 pyramidal neurons, but did not receive reciprocal connections.

With two-photon calcium imaging recordings during passive viewing of drifting gratings, the authors showed that ChCs exhibit weakly selective visual responses, high correlations within their own population, and strong responses during periods of arousal (assessed by locomotion and pupil size). These results were replicated and extended in experiments with natural images and prediction of receptive field structure using a convolutional neural network.

Furthermore, the authors employed a learned visuomotor task in a virtual corridor to show that ChCs exhibit strong responses to mismatches between visual flow and locomotion, locomotion-related activation (similar to what was shown above), and visually-evoked suppression. They also showed the existence of two clusters of pyramidal neurons with functionally different responses - a cluster with "classically visual" responses and a cluster with locomotion- and mismatch-driven responses (the latter more correlated with ChCs). Comparing naive and trained mice, the authors found that visual responses of ChCs are suppressed following task learning, accompanied by a shortening of the axon initial segment (AIS) of pyramidal cells and an increase in the proportion of AIS contacted by ChCs. However, additional controls would be required to identify which component(s) of the experimental paradigm led to the functional and anatomical changes observed.

Finally, using a chemogenetic inactivation of ChCs, the authors propose weak connectivity to pyramidal cells (due to small effects in pyramidal cell activity). However, these results are not unequivocally supported, as the baseline activity of ChCs before inactivation is considerably lower, suggesting a potentially confounding homeostatic plasticity mechanism might already be operating.

Strengths:<br /> The authors bring a comprehensive, state-of-the-art methodology to bear, including rabies tracing, in vivo two-photon calcium imaging, in vitro electrophysiology, optogenetics and chemogenetics, and deep neural networks. Their analyses and statistical tests are sound and for the most part, support their claims. Their results are in line with previous findings and extend them to the primary visual cortex.

Weaknesses:<br /> - Some of the results (e.g. arousal-related responses) are not entirely surprising given that similar results exist in other cortical areas.

- Control analyses regarding locomotion patterns before and after learning the task (Figure 5), and additional control experiments to identify whether functional and anatomical changes following task learning were due to learning, repeated visual exposure, exposure to reward, or visuomotor experience would strengthen the claims made.

- The strength of the results of the chemogenetics experiment is impacted by the lower baseline activity of ChCs that express the KORD receptor. At present, it is not possible to exclude the presence of homeostatic plasticity in the network *before* the inactivation takes place.

Reviewer #3 (Public Review):

Summary:<br /> The study conducted by Ouasti et al. is an elegant investigation of fission yeast CAF-1, employing a diverse array of technologies to dissect its functions and their interdependence. These functions play a critical role in specifying interactions vital for DNA replication, heterochromatin maintenance, and DNA damage repair, and their dynamics involve multiple interactions. The authors have extensively utilized various in vitro and in vivo tools to validate their model and emphasize the dynamic nature of this complex.

Strengths:<br /> Their work is supported by robust experimental data from multiple techniques, including NMR and SAXS, which validate their molecular model. They conducted in vitro interactions using EMSA and isothermal microcalorimetry, in vitro histone deposition using Xenopus high-speed egg extract, and systematically generated and tested various genetic mutants for functionality in in vivo assays. They successfully delineated domain-specific functions using in vitro assays and could validate their roles to large extent using genetic mutants. One significant revelation from this study is the unfolded nature of the acidic domain, observed to fold when binding to histones. Additionally, the authors also elucidated the role of the long KER helix in mediating DNA binding and enhancing the association of CAF-1 with PCNA. The paper effectively addresses its primary objective and is strong.

Weaknesses:<br /> A few relatively minor unresolved aspects persist, which, if clarified or experimentally addressed by the authors, could further bolster the study.

1. The precise function of the WHD domain remains elusive. Its deletion does not result in DNA damage accumulation or defects in heterochromatin maintenance. This raises questions about the biological significance of this domain and whether it is dispensable. While in vitro assays revealed defects in chromatin assembly using this mutant (Figure 5), confirming these phenotypes through in vivo assays would provide additional assurance that the lack of function is not simply due to the in vitro system lacking PTMs or other regulatory factors.

2. The observation of increased Pcf2-gfp foci in pcf1-ED* cells, particularly in mono-nucleated (G2-phase) and bi-nucleated cells with septum marks (S-phase), might suggest the presence of replication stress. This could imply incomplete replication in specific regions, leading to the persistence of Caf1-ED*-PCNA factories throughout the cell cycle. To further confirm this, detecting accumulated single-stranded DNA (ssDNA) regions outside of S-phase using RPA as an ssDNA marker could be informative.

3. Moreover, considering the authors' strong assertion of histone binding defects in ED* through in vitro assays (Figure 2d and S2a), these claims could be further substantiated, especially considering that some degree of histone deposition might still persist in vivo in the ED* mutant (Figure 7d, viable though growth defective double ED*+hip1D mutants). For example, the approach, akin to the one employed in Fig. 6a (FLAG-IPs of various Pcf1-FLAG-tagged mutants), could also enable a comparison of the association of different mutants with histones and PCNA, providing a more thorough validation of their findings.

4. It would be valuable for the authors to speculate on the necessity of having disordered regions in CAF1. Specifically, exploring the overall distribution of these domains within disordered/unfolded structures could provide insightful perspectives. Additionally, it's intriguing to note that the significant disparities observed among mutants (ED*, PIP*, and KER*) in in vitro assays seem to become more generic in vivo, except for the indispensability of the WHD-domain. Could these disordered regions potentially play a crucial role in the phase separation of replication factories? Considering these questions could offer valuable insights into the underlying mechanisms at play.

Reviewer #3 (Public Review):

Light energy drives photosynthesis. However, excessive light can damage (i.e., photo-damage) and thus inactivate the photosynthetic process. A major target site of photo-damage is photosystem II (PSII). In particular, one component of PSII, the reaction center protein, D1, is very suspectable to photo-damage, however, this protein is maintained efficiently by an elaborate multi-step PSII-D1 turnover/repair cycle. Two proteases, FtsH and Deg, are known to contribute to this process, respectively, by efficient degradation of photo-damaged D1 protein processively and endoproteolytically. In this manuscript, Kato et al., propose an additional step (an early step) in the D1 degradation/repair pathway. They propose that "Tryptophan oxidation" at the N-terminus of D1 may be one of the key oxidations in the PSII repair, leading to processive degradation of D1 by FtsH. Both, their data and arguments are very compelling.

The D1 protein repair/degradation pathway in its simplest form can be defined essentially by five steps: (1) migration of damaged PSII core complex to the stroma thylakoid, (2) partial PSII disassembly of the PSII core monomer, (3) access of protease degrading damaged D1, (4) concomitant D1 synthesis, and (5) reassembly of PSII into grana thylakoid. An enormous amount of work has already been done to define and characterize these various steps. Kato et al., in this manuscript, are proposing a very early yet novel critical step in D1 protein turnover in which Tryptophan(Trp) oxidation in PSII core proteins influences D1 degradation mediated by FtsH.

Using a variety of approaches, such as mass-spectrometry (Table 1), site-directed mutagenesis (Figures 2-4), D1 degradation assays (Figures 3, and 4), and simulation modeling (Figure 5), Kato et al., provide both strong evidence and reasonable arguments that an N-terminal Trp oxidation may be likely to be a 'key' oxidative post-translational modification (OPTM) that is involved in triggering D1 degradation and thus activating the PSII repair pathway. Consequently, from their accumulated data, the authors propose a scenario in which the unraveling of the N-terminal of the D1 protein facilitated by Trp oxidation plays a critical 'recognition' role in alerting the plant that the D1 protein is photo-damaged and thus to kick start the processive degradation pathway initiated possibly by FtsH. Coincidently, Forsman and Eaton-Rye (Biochemistry 2021, 60, 1, 53-63), while working with the thermophilic cyanobacterium, Thermosynechococcus vulcanus, showed that when the N-terminal DE-loop of the D1 protein is photo-damaged a disruption of the interaction between the PsbT subunit and D1 occurs which may serve as a signal for PSII to undergo repair following photodamage. While the activation of the processive degradation pathways in Chlamydomonas versus Thermosynechococcus vulcanus have significant mechanistic differences, it's interesting to note and speculate that the stability of the N-terminal of their respective D1 proteins seems to play a critical role in 'signaling' the PSII repair system to be activated and initiate repair. But it's complicated. For instance, significant Trp oxidation also occurs on the lumen side of other PSII subunits which may also play a significant role in activating the repair processes as well. Indeed, Kato et al.,( Photosynthesis Research volume 126, pages 409-416 (2015)) proposed a two-step model whereby the primary event is disruption of a Mn-cluster in PSII on the lumen side. A secondary event is damage to D1 caused by energy that is absorbed by chlorophyll. But models adapt, change, and get updated. And the data provided by Kato et al., in this manuscript, gives us a unique glimpse/snapshot into the importance of the stability of the N-terminal during photo-damage and its role in D1-turnover. For instance, the author's use site-directed mutagenesis of Trp residues undergoing OPTM in the D1 protein coupled with their D1 degradation assays (Figure 3 and 4), provides evidence that Trp oxidation (in particular the oxidation of Trp14) in coordination with FtsH results in the degradation of D1 protein. Indeed, their D1 degradation assays coupled with the use of a ftsh mutant provide further significant support that Trp14 oxidation and FtsH activity are strongly linked. But for FstH to degrade D1 protein it needs to gain access to photo-damaged D1. FtsH access to D1 is achieved by having CP43 partially dissociate from the PSII complex. Hence, the authors also addressed the possibility that Trp oxidation may also play a role in CP43 disassembly from the PSII complex thereby giving FtsH access to D1. Using a site-directed mutagenesis approach, they showed that Trp oxidation in CP43 appeared to have little impact on the PSII repair (Supplemental Figure S6). This result shows that D1-Trp14 oxidation appears to be playing a role in D1 turnover that occurs after CP43 disassembly from the PSII complex. Alternatively, the authors cannot exclude the possibility that D1-Trp14 oxidation in some way facilitates CP43 dissociation. Further investigation is needed on this point. However, D1-Trp14 oxidation is causing an internal disruption of the D1 protein possibly at the N-terminus of the protein. Consequently, the role of Trp14 oxidation in disrupting the stability of the N-terminal domain of the D1 protein was analyzed computationally. Using a molecular dynamics approach (Figure 5), the authors attempted to create a mechanistic model to explain why when D1 protein Trp14 undergoes oxidation the N-terminal domain of D1protein becomes unraveled. Specifically, the authors propose that the interaction between D1 protein Trp14 with PsbI Ser25 becomes disrupted upon oxidation of Trp14. Consequently, the authors concluded from their molecular dynamics simulation analysis that " the increased fluctuation of the first α-helix of D1 would give a chance to recognize the photo-damaged D1 by FtsH protease". Hence, the author's experimental and computational approaches employed here develop a compelling early-stage repair model that integrates 1) Trp14 oxidation, 2) FtsH activation and 3) D1- turnover being initiated at its N-terminal domain. However, a word of caution should be emphasized here. This model is just a snapshot of the very early stages of the D1 protein turnover process. The data presented here gives us just a small glimpse into the unique relationship between Trp oxidation of the D1 protein which may trigger significant N-terminal structural changes of the D1 protein that both signals and provides an opportunity for FstH to begin protease digestion of the D1 protein. However, the authors go to great lengths in their discussion section to not overstate solely the role of Trp14 oxidation in the complicated process of D1 turnover. The authors certainly recognize that there are a lot of moving parts involved in D1 turnover. And while Trp14 oxidation is the major focus of this paper, the authors show in Supplemental Fig S4 the structural positions of various additional oxidized Trp residues in the Thermosynecoccocus vulcans PSII core proteins. Indeed, this figure shows that the majority of oxidized Trps are located on the luminal side of PSII complex clustered around the oxygen-evolving complex. So, while oxidized Trp14 may be involved in the early stages of D1 turnover certainly oxidized Trps on the lumen side are also more than likely playing a role in D1 turnover as well. To untangle this complex process will require additional research.

Nevertheless, identifying and characterizing the role of oxidative modification of tryptophan (Trp) residues, in particular, Trp14, in the PSII core provides another critical step in an already intricate multi-step process of D1 protein turnover during photo-damage.

This suggests to me that there is a lot of proprietary layer 2-3 in IOT. Is this the case?

Reviewer #3 (Public Review):

Summary:<br /> The manuscript examines an important question, namely how the brain associates events spaced in time. It uses a variety of neural methods including fiber photometry as well as area-specific and pathway-silencing methods with the exquisite dissociation of norepinephrine and dopamine. The data show that neurons in the locus coeruleus (LC) respond to auditory cue onset, offset, and shock. These responses are stronger if the cue is paired with shock in a trace procedure. Optogenetic stimulation similar to the neural response captured by fiber photometry enhances associative learning. LC terminals in the dorsal hippocampus also showed phasic responses during fear conditioning and drove dopamine and norepinephrine responses. Pharmacological methods revealed that dopamine and not norepinephrine is critical for fear learning.

Strengths:<br /> The examination of the neural signal to different tone intensities, different shock intensities, repeated tone presentation (habituation), and conditioning, offers an unprecedented account of the neural signal to non-associative and associative processes. This kind of deconstruction of the elements of conditioning offers a strong account of how the brain processes the stimuli used and their interaction during learning.

Excellent use of data acquired with fiber photometry in the optogenetic interrogation study.

The use of pharmacology to disentangle dopamine and norepinephrine was excellent.

Weaknesses:<br /> While the optogenetic study was lovely, a control using the same stimulation but delivered at different time points would have been a good addition to show how critical the neural signal at tone onset, tone offset, and shock is.

Justification for the focus on D1 receptors was lacking.

The manuscript provides convincing evidence that the neural signal is not an error-correcting one by including a predicted (by a tone) and unpredicted shock. One possibility is that perhaps the unpredicted shock could be predicted by the context. Some clarification on the behavioural procedures would help understand if indeed the unsignaled shock could be predicted by the context or not.

Reviewer #3 (Public Review):

Summary:<br /> This manuscript is a follow-up to a recent study of synaptic development based on a powerful data set that combines anterograde labeling, immunofluorescence labeling of synaptic proteins, and STORM imaging (Cell Reports 2023). Specifically, they use anti-Vglut2 label to determine the size of the presynaptic structure (which they describe as the vesicle pool size), anti-Bassoon to label a number of active zones, and anti-Homer to identify postsynaptic densities. In their previous study, they compared the detailed synaptic structure across the development of synapses made with contra-projecting vs ipsi-projecting RGCs and compared this developmental profile with a mouse model with reduced retinal waves. In this study, they produce a new analysis on the same data set in which they classify synapses into "complex" vs. "simple" and assess the number and spacing of these synapses. From these measurements, they make conclusions regarding the processes that lead to synapse competition/stabilization.

Strengths:<br /> This is a fantastic data set for describing the structural details of synapse development in a part of the brain undergoing activity-dependent synaptic rearrangements. The fact that they can differentiate eye of origin is also a plus.

Weaknesses:<br /> The lack of details provided for the classification scheme as well as the interpretation of small effect sizes limit the interpretations that can be made based on these findings.

1. The criteria to classify synapses as simple vs. complex is critical for all of the analysis in this study. Therefore this criteria for classification should be much more explicit and tested for robustness. As stated in the methods, it is based on the number of active zones which are designated by the number of Bassoon clusters associated with a Vglut2 cluster (line 697). A second part of the criteria is the size of the presynaptic terminal as assayed by "greater Vglut2 signal" (line 116). So how are these thresholds determined? For Bassoon clusters, is one voxel sufficient? Two? If it's one, how often do they see a Bassoon positive voxel with no Vglut2 cluster and therefore may represent "noise"? There is no distribution of Bassoon volumes that is provided that might be the basis for selecting this number of sites. Unfortunately, the images are not helpful. For example, does P8 WT in Figure 1B have 7 or 2? According to Figure 2C, it appears the numbers are closer to 2-4.

The Vglut volume measurements also do not seem to provide a clear criterion. Figure 2 shows that the distributions of Vglut2 cluster volumes for complex and for simple synapses are significantly overlapping.

The authors need to clarify the quantitative approach used for this classification strategy and test how sensitive the results of the study are to how robust this strategy is

2. Effect sizes are quite small and all comparisons are made on medians of distributions. This leads to an n=3 biological replicates for all comparisons. Hence this small n may lead to significant results based on ANOVAS/t-tests, but the statistical power of these effects is quite weak. To accurately represent the variance in their data, the authors should show all three data points for each category (with a SD error bar when possible). They should also include the number of synapses in each category (e.g. the numerators in Figure 1D and the denominators for Figure 1E). For other figures, there are additional statistical questions described below.

3. The authors need to add a caveat regarding their classification of synapses as "complex" vs. "simple" since this is a terminology that already exists in the field and it is not clear that these STORM images are measuring the same thing. For example, in EM studies, "complex" refers to multiple RGCs converging on the same single postsynaptic site. The authors here acknowledge that they cannot assign different AZs to different RGCs so this comparison is an assumption. In Figure 2 they argue this is a good assumption based on the finding that the Vglut column/active zone is constant and therefore each represents a single RGC. However, the authors should acknowledge that they are actually seeing quite different percentages than those in EM studies. For example, in Monavarfeshani et al, eLife 2018, there were no complex synapses found at P8. (Note this study also found many more complex vs. simple synapses in the adult - 70% vs. the 20% found in the current study - but this difference could be a developmental effect). In the future, the authors may want to take another data set in the adult dLGN to make a direct comparison based on numbers and see if their classification method for complex/simple maps onto the one that currently exists in the literature.

4. Figure 3 assays the relative distribution of simple vs. complex synapses. They found that a larger percentage of simple synapses were within 1.5 microns of complex synapses than you would expect by chance for both ipsi and contra projecting RGCs, and hence conclude that complex synapses are sites of synaptic clustering. In contrast, there was no clustering of ipsi-simple to contra-complex synapses and vice versa. The authors also argue that this clustering decreases between P4 and P8 for ipsi projecting RGCs.

This analysis needs much more rigor before any conclusions can be drawn. First, the authors need to justify the 1.5-micron criteria for clustering and how robust their results are to variations in this distance. Second, these age effects need to be tested for statistical significance with an ANOVA (all the stats presented are pairwise comparisons to means expected by random distributions at each age). Finally, the authors should consider what n's to use here - is it still grouped by biological replicate? Why not use individual synapses across mice? If they do biological replicates, then they should again show error bars for each data point in their biological replicates. And they should include the number of synapses that went into these measurements in the caption.

5. Line 211-212 - the authors conclude that the absence of clustered ipsi-simple synapses indicates a failure to stabilize (Figure 3). Yet, the link between this measurement and synapse stabilization is not clear. In particular, the conclusion that "isolated" synapses are the ones that will be eliminated seems to be countered by their finding in Figure 3D/E which shows that there is no difference in vesicle pool volume between near and far synapses. If isolated synapses are indeed the ones that fail to stabilize by P8, wouldn't you expect them to be weaker/have fewer vesicles? Also, it's hard to tell if there is an age-dependent effect since the data presented in Figures 3D/E are merged across ages.

Reviewer #3 (Public Review):

Summary:<br /> The systematic way in which path selection is parametrically investigated is the main contribution.

Strengths:<br /> The authors have developed an impressive workflow to study gait and gaze in natural terrain.

Weaknesses:<br /> 1. The training and validation data of the CNN are not explained fully making it unclear if the data tells us anything about the visual features used to guide steering.

It is not clear how or on what data the network was trained (training vs. validation vs. un-peeked test data), and justification of the choices made. There is no discussion of possible overfitting. The network could be learning just e.g. specific rock arrangements. If the network is overfitting the "features" it uses could be very artefactual, pixel-level patterns and not the kinds of "features" the human reader immediately has in mind.

2. The use of descriptive terminology should be made systematic.

Specifically, the following terms are used without giving a single, clear definition for them: path, step, step location, foot plant, foothold, future foothold, foot location, future foot location, foot position.

I think some terms are being used interchangeably. I would really highly recommend a diagrammatic cartoon sketch, showing the definitions of all these terms in a single figure, and then sticking to them in the main text.

3. More coverage of different interpretations / less interpretation in the abstract/introduction would be prudent

The authors discuss the path selection very much on the basis of energetic costs and gait stability. At least mention should be given to other plausible parameters the participants might be optimizing (or that indeed they may be just satisficing).

That is, it is taken as "given" that energetic cost is the major driver of path selection in your task, and that the relevant perception relies on internal models. Neither of these is a priori obvious nor is it as far as I can tell shown by the data (optimizing other variables, satisficing behavior, or online "direct perception" cannot be ruled out).

Reviewer #3 (Public Review):

Summary:<br /> In this study, the authors investigated the effects of targeted memory reactivation (TMR) during sleep on memory retention for artificial words with varying levels of phonotactical similarity to real words. The authors report that the high phonotactic probability (PP) words showed a more pronounced EEG alpha decrease during encoding and were more easily learned than the low PP words. Following TMR during sleep, participants who had been cued with the high PP TMR, remembered those words better than 0, whilst no such difference was found in the other conditions. Accordingly, the authors report higher EEG spindle band power during slow-wave up-states for the high PP as compared to low PP TMR trials. Overall, the authors conclude that artificial words that are easier to learn, benefit more from TMR than those which are difficult to learn.

Strengths:<br /> 1. The authors have carefully designed the artificial stimuli to investigate the effectiveness of TMR on words that are easy to learn and difficult to learn due to their levels of similarity with prior word-sound knowledge. Their approach of varying the level of phonotactic probability enables them to have better control over phonotactical familiarity than in a natural language and are thus able to disentangle which properties of word learning contribute to TMR success.

2. The use of EEG during wakeful encoding and sleep TMR sheds new light on the neural correlates of high PP vs. low PP both during wakeful encoding and cue-induced retrieval during sleep.

Weaknesses:<br /> 1. The present analyses are based on a small sample and comparisons between participants. Considering that the TMR benefits are based on changes in memory categorization between participants, it could be argued that the individuals in the high PP group were more susceptible to TMR than those in the low PP group for reasons other than the phonotactic probabilities of the stimuli (e.g., these individuals might be more attentive to sounds in the environment during sleep). While the authors acknowledge the small sample size and between-subjects comparison as a limitation, a discussion of an alternative interpretation of the data is missing.

2. While the one-tailed comparison between the high PP condition and 0 is significant, the ANOVA comparing the four conditions (between subjects: cued/non-cued, within-subjects: high/low PP) does not show a significant effect. With a non-significant interaction, I would consider it statistically inappropriate to conduct post-hoc tests comparing the conditions against each other. Furthermore, it is unclear whether the p-values reported for the t-tests have been corrected for multiple comparisons. Thus, these findings should be interpreted with caution.

3. With the assumption that the artificial words in the study have different levels of phonotactic similarity to prior word-sound knowledge, it was surprising to find that the phonotactic probabilities were calculated based on an American English lexicon whilst the participants were German speakers. While it may be the case that the between-language lexicons overlap, it would be reassuring to see some evidence of this, as the level of phonotactic probability is a key manipulation in the study.

4. Another manipulation in the study is that participants learn whether the words are linked to a monetary reward or not, however, the rationale for this manipulation is unclear. For instance, it is unclear whether the authors expect the reward to interact with the TMR effects.

Reviewer #3 (Public Review):

The present study presents a comprehensive exploration of the distinct impacts of Isoflurane and Ketamine on c-Fos expression throughout the brain. To understand the varying responses across individual brain regions to each anesthetic, the researchers employ principal component analysis (PCA) and c-Fos-based functional network analysis. The methodology employed in this research is both methodical and expansive. Notably, the utilization of a custom software package to align and analyze brain images for c-Fos positive cells stands out as an impressive addition to their approach. This innovative technique enables effective quantification of neural activity and enhances our understanding of how anesthetic drugs influence brain networks as a whole.

The primary novelty of this paper lies in the comparative analysis of two anesthetics, Ketamine and Isoflurane, and their respective impacts on brain-wide c-Fos expression. The study reveals the distinct pathways through which these anesthetics induce loss of consciousness. Ketamine primarily influences the cerebral cortex, while Isoflurane targets subcortical brain regions. This finding highlights the differing mechanisms of action employed by these two anesthetics-a top-down approach for Ketamine and a bottom-up mechanism for Isoflurane. Furthermore, this study uncovers commonly activated brain regions under both anesthetics, advancing our knowledge about the mechanisms underlying general anesthesia.

Reviewer #3 (Public Review):

Summary:<br /> The study offers a compelling molecular model for the organization of rootlets, a critical organelle that links cilia to the basal body. Striations have been observed in rootlets, but their assembly, composition, and function remain unknown. While previous research has explored rootlet structure and organization, this study delivers an unprecedented level of resolution, valuable to the centrosome and cilia field. The authors isolated rootlets from mice's eyes. They apply EM to partially purified rootlets (first negative stain, then cryoET). From these micrographs, they observed striations along the membranes along the rootlet but no regular spacing was observed.

The thickness of the sample and membranes prevented good contrast in the tomograms. Thus they further purified the rootlets using detergent, which allowed them to obtain cryoET micrographs of the rootlets with greater details. The tomograms were segmented and further processed to improve the features of the rootlet structures. From their analysis, they described 3 regular cross-striations and amorphous densities, which are connected perpendicularly to filaments along the length of the rootlets. They propose that various proteins provide the striations and rootletin forms parallel coiled coils that run along the rootlet. Overall their data provide a detailed model for the molecular organization of the rootlet.

The major strength is that this high-quality study uses state-of-the-art cryo-electron tomography, sub-tomogram averaging, and image analysis to provide a model of the molecular organization of rootlets. The micrographs are exceptional, with excellent contrast and details, which also implies the sample preparation was well optimized to provide excellent samples for cryo-ET. The manuscript is also clear and accessible.

To further validate their model, it would have been useful to identify some components in the EM maps through complementary approaches (mass spectrometry, mutants disrupting certain features, CLEM). Some potential candidates are mentioned in the discussion.

This research marks a significant step forward in our understanding of rootlets' molecular organization.

Reviewer #3 (Public Review):

Summary:<br /> The manuscript by Leanza and colleagues explores the regulation of Wnt signaling and its association with advanced glycation end products (AGEs) accumulation in postmenopausal women with type 2 diabetes (T2D). The paper provides valuable insights into the potential mechanisms underlying bone fragility in individuals with T2D. Overall, the manuscript is well-structured, and the methodology is sound. I would suggest some minor revisions to improve clarity.

Strengths:<br /> The study addresses an important and clinically relevant question concerning the mechanisms underlying bone fragility in postmenopausal women with T2D.

The study's methodology appears sound, and the inclusion of postmenopausal women with and without T2D undergoing hip arthroplasty adds to the clinical relevance of the findings. Additionally, measuring gene expression and AGEs in bone samples provides direct insights into the study's objectives.

The manuscript presents data clearly, and the results are well-organized.

Weaknesses:<br /> Title. The title could be more specific to better reflect the content of the study. Also, the abstract should concisely summarize the study's main findings, providing some figures.

Introduction: the introduction would benefit from the addition of a clearer, more focused statement of the research questions or hypotheses guiding this study.

Methods: more information is needed on the hystomorphometry analysis. Surgical samples from 8 T2D and 9 non-diabetic subjects were used for histomorphometry analysis. How did these subjects compare with the other subjects in the T2D and control groups? Were they representative? How were they selected?

Reviewer #3 (Public Review):

Summary:<br /> The manuscript introduces a new computational framework for choosing 'the best method' according to the case for getting the best possible structural prediction for the CDR-H3 loop. The authors show their strategy improves on average the accuracy of the predictions on datasets of increasing difficulty in comparison to several state-of-the-art methods. They also show the benefits of improving the structural predictions of the CDR-H3 in the evaluation of different properties that may be relevant for drug discovery and therapeutic design.

Strengths:<br /> The authors introduce a novel framework, which can be easily adapted and improved. The authors use a well-defined dataset to test their new method. A modest average accuracy gain is obtained in comparison to other state-of-the art methods for the same task while avoiding testing different prediction approaches.

Weaknesses:<br /> The accuracy gain is mainly ascribed to easy cases, while the accuracy and precision for moderate to challenging cases are comparable to other PLM methods (see Fig. 4b and Extended Data Fig. 2). That raises the question: how likely is it to be in a moderate or challenging scenario? For example, it is not clear whether the comparison to the solved X-ray structures of anti-VEGF nanobodies represents an easy or challenging case for H3-OPT. The mutant nanobodies seem not to provide any further validation as the single mutations are very far away from the CDR-H3 loop and they do not disrupt the structure in any way. Indeed, RMSD values follow the same trend in H3-OPT and IgFold predictions (Fig. 4c). A more challenging test and interesting application could be solving the structure of a designed or mutated CDR-H3 loop.

The proposed method lacks a confidence score or a warning to help guide the users in moderate to challenging cases.

The fact that AF2 outperforms H3-OPT in some particular cases (e.g. Fig. 2c and Extended Data Fig. 3) raises the question: is there still room for improvements? It is not clear how sensible is H3-OPT to the defined parameters. In the same line, bench-marking against other available prediction algorithms, such as OmegaFold, could shed light on the actual accuracy limit.

Reviewer #3 (Public Review):

The authors tried to study the role of the cylicin gene in sperm formation and male fertility. They used the Crispr/cas 9 to knockout two mouse cylicin genes, cylicin 1 and cylicin 2. They used comprehensive methods to phenotype the mouse models and discovered that the two genes, particularly cylicin 2 are essential for sperm calyx formation. They further compared the evolution of the two genes. Finally, they identified mutations of the genes in a patient. The major strengths are the high quality of data presented, and the conclusion is supported by their findings from the animal models and patients. The major weakness is that the study is rather descriptive without molecular mechanism studies, limiting its impact on the field.

Reviewer #3 (Public Review):

Summary:<br /> Combining several MD simulation techniques (NMR-constrained replica-exchange metadynamics, Markov State Model, and unbiased MD) the authors identified the aC-beta4 loop of PKA kinase as a switch crucially involved in PKA nucleotide/substrate binding cooperatively. They identified a previously unreported excited conformational state of PKA (ES2), this switch controls and characterized ES2 energetics with respect to the ground state. Based on translating the simulations into chemical shits and NMR characterizing of PKA WT and an aC-beta4 mutant, the author made a convincing case in arguing that the simulation-suggested excited state is indeed an excited state observed by NMR, thus giving the excited state conformational details.

Strengths:<br /> This work incorporates extensive simulation works, new NMR data, and in vitro biochemical analysis. It stands out in its comprehensiveness, and I think it made a great case.

Weaknesses:<br /> The manuscript is somewhat difficult to read even for kinase experts, and even harder for the layman. The difficulty partially arises from mixing technical description of the simulations with structural interpretation of the results, which is more intuitive, and partially arises from the assumption that readers are familiar with kinase architecture and its key elements (the aC helix, the APE motif etc).

Reviewer #3 (Public Review):

Summary:<br /> In this study, the authors set out to address the question of how the SNARE protein Syntaxin 17 senses autophagosome maturation by being recruited to autophagosomal membranes only once autophagosome formation and sealing is complete. The authors discover that the C-terminal region of Syntaxin 17 is essential for its sensing mechanism that involves two transmembrane domains and a positively charged region. The authors discover that the lipid PI4P is highly enriched in mature autophagosomes and that electrostatic interaction with Syntaxin 17's positively charged region with PI4P drives recruitment specifically to mature autophagosomes. The temporal basis for PI4P enrichment and Syntaxin 17 recruitment to ensure that unsealed autophagosomes do not fuse with lysosomes is a very interesting and important discovery. Overall, the data are clear and convincing, with the study providing important mechanistic insights that will be of broad interest to the autophagy field, and also to cell biologists interested in phosphoinositide lipid biology. The author's discovery also provides an opportunity for future research in which Syntaxin 17's c-terminal region could be used to target factors of interest to mature autophagosomes.

Strengths:<br /> The study combines clear and convincing cell biology data with in vitro approaches to show how Syntaxin 17 is recruited to mature autophagosomes. The authors take a methodical approach to narrow down the critical regions within Syntaxin 17 required for recruitment and use a variety of biosensors to show that PI4P is enriched on mature autophagosomes.

Weaknesses:<br /> There are no major weaknesses, overall the work is highly convincing. It would have been beneficial if the authors could have shown whether altering PI4P levels would affect Syntaxin 17 recruitment. However, this is understandably a challenging experiment to undertake and the authors outlined their various attempts to tackle this question. In addition, clear statements within the figure legends on the number of independent experimental repeats that were conducted for experiments that were quantitated are not currently present in the manuscript.

Reviewer #3 (Public Review):

Summary:<br /> The work in this manuscript builds on prior efforts by this team to understand how sterols are biosynthesized and utilized in bacteria. The study reports a new function for three genes encoded near sterol biosynthesis enzymes, suggesting the resulting proteins function as a sterol transport system. Biochemical and structural characterization of the two soluble components of the pathway establishes that both proteins can bind sterols, with a preference for 4-methylated derivatives. High-resolution x-ray structures of the apoproteins reveal hydrophobic cavities of the appropriate size to accommodate these substrates. Docking and molecular dynamics simulations confirm this observation and provide specific insights into residues involved in substrate binding.

Strengths:<br /> The manuscript is comprehensive and well-written. The annotation of a new function in a set of proteins related to bacterial sterol usage is exciting and likely to enable further study of this phenomenon - which is currently not well understood. The work also has implications for improving our understanding of lipid usage in general among bacterial organisms.

Weaknesses:<br /> The authors might consider moving some of the bioinformatics figures to the main text, given how much space is devoted to this topic in the results section.

Reviewer #3 (Public Review):

Summary:<br /> Smith-Magenis syndrome (SMS) is associated with obesity and is caused by deletion or mutations in one cope of the Rai1 gene which encodes a transcriptional regulator. Previous studies have shown that Bdnf gene expression is reduced in the hypothalamus of Rai1 heterozygous mice. This manuscript by Javed et al. further links SMS-associated obesity with reduced Bdnf gene expression in the PVH by providing three lines of evidence. First, the authors conducted proteomic analysis of hypothalamic extracts from WT and SMS (Rai1 +/-) mice and showed that several signaling cascades downstream of BDNF (e.g., PI3K-AKT and mTOR) were down regulated in SMS mice. Second, the authors found that deletion of both copies of the Rai1 gene in all BDNF-expressing cells or BDNF-expressing neurons in the PVH led to obesity, although the phenotype is more subtle than that observed in SMS mice. Third, they found that Rai1 deletion reduced excitability of PVH BDNF neurons.

Strengths:<br /> The study provides additional evidence linking BDNF deficiency to hyperphagia and obesity associated with SMS. Furthermore, the study shows that deletion of only one copy of the Rai1 gene in all BDNF-expressing cells did not cause obesity. This result indicates that BDNF deficiency only has a minor contribution to the metabolic symptoms associated with SMS patients who lose one copy of the RAI1 gene. The discovery that Rai1 is important for excitability of PVH BDNF neurons is interesting.

Weaknesses:<br /> The main mechanism underlying SMS-associated obesity remains to be identified. This limitation is discussed in this revised manuscript. The authors also address my previous concerns in this revised manuscript.

Reviewer #3 (Public Review):

Chen et al have identified a new candidate gene for high myopia, ZC3H11A, and using a knock-out mouse model, have attempted to validate it as a myopia gene and explain a potential mechanism. They identified 4 heterozygous missense variants in highly myopic teenagers. These variants are in conserved regions of the protein, but the authors provide no evidence that these specific variants affect protein function. They then created a knock-out mouse. Heterozygotes show myopia at all ages examined but increased axial length only at very early ages. Unfortunately, the authors do not address this point or examine corneal structure in these animals. They show that the mice have decreased B-wave amplitude on electroretinogram (a sign of retinal dysfunction associated with bipolar cells), and decreased expression of a bipolar cell marker, PKC. They do not address, however, whether there are fewer bipolar cells, or simply decreased expression of the marker protein. On electron microscopy, there are morphologic differences in the outer nuclear layer (where bipolar, amacrine, and horizontal cell bodies reside). Transcriptome analysis identified over 700 differentially expressed genes. The authors chose to focus on the PI3K-AKT and NF-B signaling pathways and show changes in the expression of genes and proteins in those pathways, including PI3K, AKT, IB, NF-B, TGF-1, MMP-2, and IL-6, although there is very high variability between animals. They propose that myopia may develop in these animals either as a result of visual abnormality (decreased bipolar cell function in the retina) or by alteration of NF-B signaling. These data provide an interesting new candidate variant for the development of high myopia, and provide additional data that MMP2 and IL6 have a role in myopia development, but do not support the claim of the title that myopia is caused by an inflammatory reaction.

Reviewer #3 (Public Review):

Summary:<br /> Receptor kinases (RKs) perceive extracellular signals to regulate many processes in plants. FLS2 is an RK that acts as a pattern-recognition receptor (PRR) to recognize bacterial flagellin and activate pattern-triggered immunity (PTI). PRRs such as FLS2 have been previously shown to reside within PM nanodomains, which can regulate downstream PTI signaling. In the current manuscript, Cui et al use single particle tracking to characterize the effect of previously-described phosposite mutants (FLS2-S938A/D) on the PM organization, endocytosis, and signaling functions of FLS2. The authors confirm that FLS2-S938D but not -S938A is functional for flg22-induced responses, while also demonstrating that phopshodead mutation at this site (S938A) prevents flg22-induced sorting into nanodomains and endocytosis. These results are consistent with S938 being an important phosphorylation site for FLS2 function, however, they fall short of demonstrating that membrane disorganization of FLS2-938A is responsible for downstream signaling defects.

Strengths:<br /> The authors' experiments (single particle tracking, co-localization, etc) do a good job of demonstrating how a non-functional version of FLS2 (S938A) does not alter its spatio-temporal dynamics, nanodomain organization, and endocytosis in response to flg22, suggesting that these require a functional receptor and are regulated by intracellular signaling components.

Weaknesses:<br /> The authors do not provide direct evidence that S938 phosphorylation specifically affects membrane organization, rather than FLS2 signaling more generally. All evidence is consistent with S938A being a non-functional version of FLS2, wherein an activated/functional receptor is required for all downstream events including membrane re-organization, downstream signalling, internalization, etc. Furthermore, the authors never demonstrate that this site is phosphorylated in planta in the basal or flg22-elicited state.

As written, the manuscript also has numerous scientific issues, including a misleading/incomplete description of plant immune signaling, lack of context from previous work, and extensive use of inappropriate references.

Reviewer #3 (Public Review):

The main question of this article is as follows: "To what extent does having information on brain-age improve our ability to capture declines in fluid cognition beyond knowing a person's chronological age?" This question is worthwhile, considering that there is considerable confusion in the field about the nature of brain-age.

Comments on revised version:

Thank you to the authors for addressing so many of my concerns with this revision. There are a few points that I feel still need addressing/clarifying related to 1) calculating brain cognition, 2) the inevitability of their results, and 3) their continued recommendation to use brain-age metrics.

Reviewer #3 (Public Review):

This manuscript reports a novel pedigree with four intact copies of RHO on a single chromosome which appears to lead to overexpression of rhodopsin and a corresponding autosomal dominant form of RP. The authors generate retinal organoids from patient- and control-derived cells, characterize the phenotypes of the organoids, and then attempt to 'treat' aberrant rhodopsin expression/mislocalization in the patient organoids using a small molecule called photoregulin 3 (PR3). While this novel genetic mechanism for adRP is interesting, the organoid work is not compelling. There are multiple problems related to the technical approaches, the presentation of the results, and the interpretations of the data. I will present my concerns roughly in the order in which they appear in the manuscript.

Major concerns:<br /> (1) Individual human retinal organoids in culture can show a wide range of differentiation phenotypes with respect to the expression of specific markers, percentages of given cell types, etc. For this reason, it can be very difficult to make rigorous, quantitative comparisons between 'wild-type' and 'mutant' organoids. Despite this difficulty, the author of the present manuscript frequently presents results in an impressionistic manner without quantitation. Furthermore, there is no indication that the investigator who performed the phenotypic analyses was blind with respect to the genotype. In my opinion, such blinding is essential for the analysis of phenotypes in retinal organoids.

To give an example, in lines 193-194 the authors write "we observed that while the patient organoids developing connecting cilium and the inner segments similar to control organoids, they failed to extend outer segments". Outer segments almost never form normally in human retinal organoids, even when derived from 'wild-type' cells. Thus, I consider it wholly inadequate to simply state that outer segment formation 'failed' without a rigorous, quantitative, and blinded comparison of patient and control organoids.

(2) The presentation of qPCR results in Figure 3A is very confusing. First, the authors normalize expression to that of CRX, but they don't really explain why. In lines 210-211, they write "CRX, a ubiquitously expressing photoreceptor gene maintained from development to adulthood." Several parts of this sentence are misleading or incomplete. First, CRX is not 'ubiquitously expressed' (which usually means 'in all cell types') nor is it photoreceptor-specific: CRX is expressed in rods, cones, and bipolar cells. Furthermore, CRX expression levels are not constant in photoreceptors throughout development/adulthood. So, for these reasons alone, CRX is a poor choice for the normalization of photoreceptor gene expression.

Second, the authors' interpretation of the qPCR results (lines 216-218) is very confusing. The authors appear to be saying that there is a statistically significant increase in RHO levels between D120 and D300. However, the same change is observed in both control and patient organoids and is not unexpected, since the organoids are more mature at D300. The key comparison is between control and patient organoids at D300. At this time point, there appears to be no difference between control and patient. The authors don't even point this out in the main text.

Third, the variability in the number of photoreceptor cells in individual organoids makes a whole-organoid comparison by qPCR fraught with difficulty. It seems to me that what is needed here is a comparison of RHO transcript levels in isolated rod photoreceptors.

(3) I cannot understand what the authors are comparing in the bulk RNA-seq analysis presented in the paragraph starting with line 222 and in the paragraph starting with line 306. They write "we performed bulk-RNA sequencing on 300-days-old retinal organoids (n=3 independent biological replicates). Patient retinal organoids demonstrated upregulated transcriptomic levels of RHO... comparable to the qRT-PCR data." From the wording, it suggests that they are comparing bulk RNA-seq of patients and control organoids at D300. However, this is not stated anywhere in the main text, the figure legend, or the Methods. Yet, the subsequent line "comparable to the qRT-PCR data" makes no sense, because the qPCR comparison was between patient samples at two different time points, D120 and D300, not between patient and control. Thus, the reader is left with no clear idea of what is even being compared by RNA-seq analysis.

Remarkably, the exact same lack of clarity as to what is being compared is found in the second RNA-seq analysis presented in the paragraph starting with line 306. Here the authors write "We further carried out bulk RNA-sequencing analysis to comprehensively characterize three different groups of organoids, 0.25 μM PR3-treated and vehicle-treated patient organoids and control (RC) organoids from three independent differentiation experiments. Consistent with the qRT-PCR gene expression analysis, the results showed a significant downregulation in RHO and other rod phototransduction genes." Here, the authors make it clear that they have performed RNA-seq on three types of samples: PR3-treated patient organoids, vehicle-treated patient organoids, and control organoids (presumably not treated). Yet, in the next sentence, they state "the results showed a significant downregulation in RHO", but they don't state what two of the three conditions are being compared! Although I can assume that the comparison presented in Fig. 6A is between patient vehicle-treated and PR3-treated organoids, this is nowhere explicitly stated in the manuscript.

(4) There are multiple flaws in the analysis and interpretation of the PR3 treatment results. The authors wrote (lines 289-2945) "We treated long-term cultured 300-days-old, RHO-CNV patient retinal organoids with varying concentrations of PR3 (0.1, 0.25 and 0.5 μM) for one week and assessed the effects on RHO mRNA expression and protein localization. Immunofluorescence staining of PR3-treated organoids displayed a partial rescue of RHO localization with optimal trafficking observed in the 0.25 μM PR3-treated organoids (Figure 5B). None of the organoids showed any evidence of toxicity post-treatment."

There are multiple problems here. First, the results are impressionistic and not quantitative. Second, it's not clear that the investigator was blinded with respect to the treatment condition. Third, in the sections presented, the organoids look much more disorganized in the PR3-treated conditions than in the control. In particular, the ONL looks much more poorly formed. Overall, I'd say the organoids looked considerably worse in the 0.25 and 0.5 microM conditions than in the control, but I don't know whether or not the images are representative. Without rigorously quantitative and blinded analysis, it is impossible to draw solid conclusions here. Lastly, the authors state that "none of the organoids showed any evidence of toxicity post-treatment," but do not explain what criteria were used to determine that there was no toxicity.

(5) qPCR-based quantitation of rod gene expression changes in response to PR3 treatment is not well-designed. In lines 294-297 the authors wrote "PR3 drove a significant downregulation of RHO in a dose-dependent manner. Following qRT-PCR analysis, we observed a 2-to-5 log2FC decrease in RHO expression, along with smaller decreases in other rod-specific genes including NR2E3, GNAT1 and PDE6B." I assume these analyses were performed on cDNA derived from whole organoids. There are two problems with this analysis/interpretation. First, a decrease in rod gene expression can be caused by a decrease in the number of rods in the treated organoids (e.g., by cell death) or by a decrease in the expression of rod genes within individual rods. The authors do not distinguish between these two possibilities. Second, as stated above, the percentage of cells that are rods in a given organoid can vary from organoid to organoid. So, to determine whether there is downregulation of rod gene expression, one should ideally perform the qPCR analysis on purified rods.

(6) In Figure 4B 'RM' panels, the authors show RHO staining around the somata of 'rods' but the inset images suggest that several of these cells lack both NRL and OTX2 staining in their nuclei. All rods should be positive for NRL. Conversely, the same image shows a layer of cells scleral to the cells with putative RHO somal staining which do not show somal staining, and yet they do appear to be positive for NRL and OTX2. What is going on here? The authors need to provide interpretations for these findings.

Reviewer #3 (Public Review):

Summary:<br /> In this manuscript, Rana and colleagues examined the effect of a "low impact" ampakine, an AMPA receptor allosteric modulator, on the voiding function of rats subjected to midline T9 spinal cord contusion injury. Previous studies have shown that the micturition reflex fully depends on AMPA glutaminergic signaling, and, that the glutaminergic circuits are reorganized after spinal cord injury. In chronic paraplegic rats, other circuits (no glutaminergic) become engaged in the spinal reflex mechanism controlling micturition. The authors employed continuous flow cystometry and external urethral sphincter electromyography to assess bladder function and bladder-urethral sphincter coordination in naïve rats (control) and rats subjected to spinal cord injury (SCI). In the acute phase after SCI, rats exhibit larger voids with lower frequency than naïve rats. This study shows that CX1739 improves, in a dose-dependent manner, bladder function in rats with SCI. The interval between voids and the voided volume was reduced in rats with SCI when compared to controls. In summary, this is an interesting study that describes a potential treatment for patients with SCI.

Strengths:<br /> The findings described in this manuscript are significant because neurogenic bladder predisposes patients with SCI to urinary tract infections, hydronephrosis, and kidney failure. The manuscript is clearly written. The study is technically outstanding, and the conclusions are well justified by the data.

Weaknesses:<br /> The study was conducted 5 days after spinal cord contusion when the bladder is underactive. In rats with chronic SCI, the bladder is overactive. Therefore, the therapeutic approach described here is expected to be effective only in the underactive bladder phase of SCI. The mechanism and site of action of CX1739 is not defined.

Reviewer #3 (Public Review):

Summary:<br /> Ban et al. investigated the role of ribosome biogenesis (RiBi) in epithelial-to-mesenchymal transition (EMT) and its contribution to chemoresistance in breast cancer. They used a Tri-PyMT EMT lineage-tracing model and scRNA-seq to analyze EMT status and found that RiBi was elevated during both EMT and mesenchymal-to-epithelial transition (MET) of cancer cells. They further revealed that nascent protein synthesis mediated by ERK and mTOR signaling pathways was essential for the completion of RiBi. Inhibiting excessive RiBi impaired EMT and MET capability. More importantly, combinatorial treatment with RiBi inhibitors and chemotherapy drugs reduced metastatic outgrowth of both epithelial and mesenchymal tumor cells. These results suggest that targeting the RiBi pathway may be an effective strategy for treating advanced breast cancer with EMT-related chemoresistance.

Strengths:<br /> The conclusions of this study are generally supported by the data. However, some weaknesses still exist as mentioned below.

Weaknesses:<br /> 1) The study predominantly focused on RiBi as a target for overcoming EMT-related chemoresistance. Thus, it will be necessary to provide some canonical outcomes after upregulating ribosome biogenesis, such as translation activity. I would suggest ribosome profiling or puromycin-incorporation assay, or other more suitable experiments.

2) The results were basically obtained from mice and in vitro experiments. While these results provide valuable insights, it will be valuable to validate part of the findings using some tissue samples from patients (e.g. RiBi activity) to determine the clinical relevance and potential therapeutic applications.

3) The results revealed that mTORC1 and ERK mediated RiBi activation. How about mTORC2? It will be informative to evaluate mTORC2 signaling.

4) The results also demonstrated promising synergic effects of Pol I inhibitor (BMH21) and chemotherapy drug (CTX) on chemo-resistant metastasis. How about using the inhibitors of mTORC1 together with CTX?

5) While the results demonstrate the potential efficacy of RiBi inhibitors in reducing metastatic outgrowth, other factors and mechanisms contributing to chemoresistance may exist and need further investigation. I would suggest some discussion about this aspect.

Reviewer #3 (Public Review):

Summary:

The vesicular monoamine transporter is a key component in neuronal signaling and is implicated in diseases such as Parkinson's. Understanding of monoamine processing and our ability to target that process therapeutically has been to date provided by structural modeling and extensive biochemical studies. However, structural data is required to establish these findings more firmly.

Strengths:

Dalton et al resolved a structure of VMAT2 in the presence of an important inhibitor, tetrabenazine, with the protein in detergent micelles, using cryo-EM and with the aid of domains fused to its N- and C-terminal ends. The resolution of the maps allows clear assignment of the amino acids in the core of the protein. The structure is in good agreement with a wealth of experimental and structural prediction data and provides important insights into the binding site for tetrabenazine and selectivity relative to analogous compounds.

Weaknesses:

The authors follow up their structures with molecular dynamics simulations. The simulations resulted in repositioning of the ligand, which does not seem to be well founded, and raises questions about the methodological choices made for the simulations.

Reviewer #3 (Public Review):

Churgin et. al. seeks to understand the neural substrates of individual odor preference in the Drosophila antennal lobe, using paired behavioral testing and calcium imaging from ORNs and PNs in the same flies, and testing whether ORN and PN odor responses can predict behavioral preference. The manuscript's main claims are that ORN activity in response to a panel of odors is predictive of the individual's preference for 3-octanol (3-OCT) relative to clean air, and that activity in the projection neurons is predictive of both 3-OCT vs. air preference and 3-OCT vs. 4-methylcyclohexanol (MCH). They find that the difference in density of fluorescently-tagged brp (a presynaptic marker) in two glomeruli (DC2 and DM2) trends towards predicting behavioral preference between 3-oct vs. MCH. Implementing a model of the antennal lobe based on the available connectome data, they find that glomerulus-level variation in response reminiscent of the variation that they observe can be generated by resampling variables associated with the glomeruli, such as ORN identity and glomerular synapse density.

Strengths:<br /> The authors investigate a highly significant and impactful problem of interest to all experimental biologists, nearly all of whom must often conduct their measurements in many different individuals and so have a vested interest in understanding this problem. The manuscript represents a lot of work, with challenging paired behavioral and neural measurements.

Weaknesses:<br /> The overall impression is that the authors are attempting to explain complex, highly variable behavioral output with a comparatively limited set of neural measurements. Given the degree of behavioral variability they observe within an individual (Figure 1- supp 1) which implies temporal/state/measurement variation in behavior, it's unclear that their degree of sampling can resolve true individual variability (what they call "idiosyncrasy") in neural responses, given the additional temporal/state/measurement variation in neural responses. The statistical analyses in the manuscript are underdeveloped, and it's unclear the degree to which the correlations reported have explanatory (causative) power in accounting for organismal behavior.

Reviewer #3 (Public Review):

This paper offers a fundamental advance in our understanding of communication between human sensory neurons and keratinocytes in the skin of humans. The work, which used EM and expansion microscopy, shows that axons tunnel through keratinocytes and form gap junctions along the axon as it passes by or potentially where it is ensheathed by the cell. This is a fairly remarkable arrangement and is seen both in vivo and in vitro.

The major strengths are the quality of the imaging, the use of expansion microscopy to reveal new anatomical information and the new insight the detailed work offers to our understanding of sensory neuroscience. Another major strength is that the work was done in humans, and using human cells in vitro. I think the authors have achieved their goal of thoroughly characterizing this interesting interaction between sensory neurons and keratinocytes. The obvious next step is to understand if these interactions become pathological in neuropathies.

I do think there are some weaknesses that should be addressed, and some questions that are outstanding that the authors might want to discuss. Chief amongst these is the question of what types of sensory neurons form these contacts with keratinocytes and do these change in clinical neuropathies. A more thorough discussion of these issues for future investigation would help to place the findings in the broader context of the field, in my opinion.

Reviewer #3 (Public Review):

This important body of work aims at identifying the divergent phototransduction pathways in different subtypes of melanopsin-expressing retinal ganglion cells. The authors use a combination of patch-clamp recordings of three subtypes of ipRGCs M1, M2, and M4, and their post hoc rigorous identification. The authors demonstrate that within their conditions of recordings and the choice of light stimulus recorded ipRGCs subtypes do not signal via HCN channels as previously proposed; and that M1 signal via TRPC channel, M2 signal via TRPC, or a newly identified T-Type Ca2+ channel. While the data seem to support the authors' claims that HCN channels are not involved in phototransduction pathways of ipRGCs here, the light stimulus used is different than in the previous study (Jing et al, 2018) which contradicts this claim. This opens up questions on whether this inconsistency originates in differences in light stimulus used in these studies or something else.

Reviewer #3 (Public Review):

The manuscript by Chi et al investigated the value of ctDNA for predicting the prognosis and monitoring the treatment response in mTNBC patients. They found that patients with ctDNA+, had a shorter progression-free survival (PFS) than ctDNA− patients (5.16 months vs. 9.05 months, P = 0.001) and ctDNA+ was independently associated with a shorter PFS (HR, 95%CI: 2.67, 1.2-5.96; P = 0.016) by multivariable analyses. This study provides novel insight into the mutational landscape of mTNBC and may reliably predict the prognosis and treatment response of mTNBC patients. Overall, this study is interesting and important.

Strengths<br /> This study is well designed and novel.

Weaknesses<br /> This is a single-center study. Future studies may further validate the findings in other centers.