Reviewer #2 (Public Review):

In this manuscript, the authors generated a novel transgenic C. elegans model with inducible expression and secretion of human GFP-tagged human Aβ1-42. Using this model, they investigated the role of ECM in the aggregation of Aβ. They identified collagens that regulate Aβ aggregate formation, and found the metalloproteases ADM-2 modulates ECM and assist in the removal of extracellular Aβ aggregates. The results suggest that ECM composition is critical for Aβ aggregate and removal. These data add in an interesting way to the ongoing discussion on the aggregation and clearance of amyloid through the extracellular matrix. However, some issues remain to be addressed.

1) The authors developed a novel C.elegans model for studying extracellular amyloid beta aggregation and is therefore likely to be taken up broadly by the field. However, the new model should be fully characterized. Throughout the manuscript, the only method to detect amyloid deposition was the GFP fluorescence intensity and morphology, while direct characterization of amyloid aggregates is lacking.

2) A targeted RNA interference (RNAi) screen was used to identify the key regulators of Aβ aggregation and clearance, which is one of the strengths of the study. There should be evidence that RNAi works to knockdown the specific genes. Similarly, there should be evidence indicating that ADM-2 is indeed expressed in the overexpression experiments.

3) It remains unknown whether ADM-2 directly degrades Aβ or facilitates the clearance of Aβ by remoulding the ECM. The effect of ADM-2 on ECM remodeing should be examined.

Reviewer #2 (Public Review):

During meiosis, mitotic cohesin complexes are replaced by meiosis-specific cohesins to enable a stepwise loss of sister chromatid cohesion. The identity of the cohesin complex is defined by its kleisin subunit. In the early meiotic prophase, the mitotic kleisin Scc1 is replaced by a meiotic counterpart Rec8. C. elegans expresses two additional meiotic kleisins, COH-3 and COH-4; however, how meiotic cohesin complexes differ in their loading and function has been unclear. In this paper, Castellano-Pozo and colleagues unveil their differential dynamics and functions using elegant approaches that include auxin-mediated depletion and TEV-mediated removal of meiotic kleisins. The association of COH-3/4 with chromosomes is dynamic and is under the control of two cohesin regulators, WAPL-1 and SCC-2, while REC-8 remains more stably associated. The authors established that COH-3/4 is involved in maintaining the structural integrity of chromosome axes, whereas the REC-8 cohesin is solely responsible for sister chromatid cohesion throughout meiosis. They further demonstrated the role of REC-8 in the repair of meiotic DSBs.

Overall, this solid work unequivocally establishes the distinct regulation and requirements for REC-8 and COH-3/4 cohesin complexes during C. elegans meiosis. However, as the authors acknowledged, the role of REC-8 cohesins in sister chromatid cohesion has been shown previously using genetic mutants (Crawley et al., 2016 eLife). While the authors highlighted the advantages of removing cohesin subunits in establishing their distinct requirements, many of the results were recapitulated from their previous work (e.g. rec-8; spo-11 and coh-3/4; spo-11). It might be helpful for the readers to compare the results between the two studies and point out uniquely illuminating results.

The role of REC-8 in DNA repair has also been shown in different contexts. Chromosomes fragmentation and DNA bridges are observed in rec-8; syp-1 or rec-8; syp-2 (RNAi) animals (Colaiacovo et al., 2003 Dev Cell; Crawley et al., 2016 eLife), suggesting a role of REC-8 in inter-sister repair. Persistent RAD-51 foci are also observed on asynapsed chromosomes in rec-8 mutants, suggesting a role for REC-8 in DNA repair (Cahoon et al., 2019 Genetics). The authors must cite these papers and discuss the results in the context of prior work.

Reviewer #2 (Public Review):

This manuscript tackles the important and vexing problem of mapping alleles for TB. It is a really important problem, and this paper presents the largest genetic data set. It does so by amalgamating data from multiple cohorts. The manuscript rightly points out that many studies have not produced reproducible results, and most alleles are population specific, and rarely seen in multiple studies.

1. Authors find a strong HLA associated SNP. They do conduct HLA imputation, but there is little effective fine-mapping. Authors should report which classical alleles are consistent with this allelic association (e.g. which classical alleles are in phase with it). Authors comment on DQA1-0301, but it isn't clear in the main text how significant it is. I think the authors should dig a little deeper. Imputing amino acids and assessing association might be useful. Finding classical alleles that explain the SNP associations and are seen across populations might be useful. If the authors think that the SNP might be a regulatory allele, the authors should make a case for that based on genomic annotations, eQTL analyses etc.<br /> 2. The authors comment on ancestry. Are ancestry components disease associated in any cohort? It might be interesting to demonstrate this.

Reviewer #2 (Public Review):

- Overall, the authors sought to determine whether children with autism spectrum disorder (ASD) or typical development (TD) would both benefit from a 5-day intervention designed to improve numerical problem-solving. They were particularly interested in how learning across training would be associated with pre-post intervention changes in brain activity, measured with functional magnetic resonance imaging (fMRI). They also examined whether brain-behavior associations driven by learning might be moderated by a classic cognitive inflexibility symptom in ASD ("insistence on sameness").

- The study is reasonably well-powered, uses a 5-day evidence-based intervention, and uses a multivariate correlation-based metric for examining neuroplastic changes that may be less susceptible to random variation over time than conventional mass univariate fMRI analyses.

- The study did have some weaknesses that draw into question the specific claims made based on the present set of analyses, as well as limit the generalizability of the findings to the significant proportion of individuals with ASD that are outside of the normative range of general cognitive functioning. The study also found minimal evidence for transfer between trained and untrained mathematical problems, limiting enthusiasm for the intervention itself.

- The majority of the authors' claims were rooted in the data and the team was generally able to accomplish their aims. I am sensitive to the fact that one of the main limitations I noted would have significant ethical implications-i.e. NOT offering potentially beneficial numerical training to children randomized to a sham or control group.

- I think the authors' work will represent a welcome addition to a growing corpus of studies showing similar neuropsychological test performance across several cognitive domains (e.g. learning, memory, proactive cognitive control, etc.) in ASD and TD. However, these relatively preserved cognitive functions still appear to be implemented by unique neural systems and demonstrate unique correlations to clinical symptoms in youth with ASD relative to TD, which may have implications for both educational and clinical contexts.

Reviewer #2 (Public Review):

Lindsay Fuzzell and her team of researchers have performed an extremely well-executed survey study, which captures a wide spectrum of providers who perform cervical cancer screening in the US. The researchers have captured a vast amount of demographic data in this study in attempting to determine whether cervical cancer screening continued to be reduced in the year immediately after the lockdown period caused by the COVID-19 pandemic.

The authors have uncovered some important and revealing concerns regarding the current state of cancer screening during the public health crisis caused by the COVID-19 pandemic. The most notable implication from their survey was a statistically higher reported reduction in cervical cancer screening in Internal medicine and family medicine providers as well as for community health and safety net clinics. These findings are important as they represent a large portion of primary care and a vulnerable patient population that has been shown to have worse cancer-related outcomes.

This study is more sobering information about the magnitude of ramifications of the COVID-19 pandemic on the US public health system. Decreases in cancer screening may have lasting implications for cancer-related mortality for many years to come. The implications of not going back to pre-pandemic cancer screening rates are daunting, to say the least.

The scope of this survey, the amount of data attained, and the sound methodology of the data acquisition and statistical analysis are the strengths of this study. Weaknesses are inherent to the study relying on survey answers rather than data from cervical cancer screening registries. Reporting biases are complex in surveys and answers given may not reflect the true rates of screening. The authors have also reported a disproportionate and statistically significant reduction in cervical cancer screening for Black and Asian providers. I would conclude more cautiously here with confidence intervals crossing one in both for this statistical analysis.

Overall, this is a survey study with a great magnitude, which has important implications for cancer screening and public health in the US.

Reviewer #2 (Public Review):

The authors seek to explore the mechanistic basis for enhancement binding to DNA by SsrB at lower pH. Their evidence supports the conclusions listed in the Evaluation Summary. Multiple additional conclusions are not supported by the data as described below:

1. The experiment displayed in Figure 5 is deeply flawed for multiple reasons and should be removed from the manuscript entirely. A Michaelis-Menton plot compares the initial rate of a reaction versus substrate concentration. Instead, the authors plotted the fraction of SsrB that is phosphorylated after 10 minutes at various substrate concentrations. Such a plot must reach saturation because the enzyme is limiting, whereas it is not always possible to achieve saturation in a genuine Michaelis-Menton plot. Because no reaction rates were measured, it is not possible to derive kcat values from the data. There are also at least three potential problems with the reaction conditions themselves: (i) Increasing the concentration of the phosphoramidite substrate increased ionic strength. Response regulator active sites contain many charged moieties and autophosphorylation of at least one response regulator (CheY) is inhibited by increasing ionic strength (PMID 10471801). (ii) Autophosphorylation with phosphoramidite is pH dependent because the nitrogen on the donor must be protonated to form a good leaving group (PMID 9398221). The pKa of phosphoramidite is ~8. Therefore, the fraction of phosphoramidite that is reactive (i.e., protonated) will be very different at pH 6.1 and 7.4. (iii) Response regulator autophosphorylation absolutely depends on the presence of a divalent metal ion (usually Mg2+) in the active site (PMID 2201404). There is no guarantee that the 20 mM Mg2+ included in the reaction is sufficient to saturate SsrB. Furthermore, as the authors themselves note, the amino acid at SsrB position 12 is likely to affect the affinity of Mg2+ binding. Therefore, the fraction of SsrB that is reactive (i.e. has Mg2+ bound) may differ between wildtype and the H12Q mutant, and/or between wildtype at different pHs (because the protonation state of His12 changes).

2. The data in Figures 1abcd and 3de are clearly sigmoidal rather than hyperbolic, indicating cooperativity. However, there are insufficient data points between the upper and lower bounds to accurately calculate the Hill coefficient or KD values. This limitation of the data means that comparisons of apparent Hill coefficient or KD values under different conditions cannot be the basis of credible conclusions.

3. There are hundreds of receiver domain structures in PDB. There is some variation, but to a first approximation receiver domain structures, all exhibit an (alpha/beta)5 fold. The structure of SsrB predicted by i-TASSER breaks the standard beta-2 strand into two parts, which throws off the numbering for subsequent beta strands. Given the highly conserved receiver domain fold, I am skeptical that the predicted i-TASSER structure is correct or adds any value to the manuscript. If the authors wish to retain the structure of the manuscript, then they should point out the unusual feature and the consequence of strand numbering.

4. The detailed predictions of active site structure in Supplementary Figure 5 are not physiologically relevant because Mg2+ was not included in the simulation. The presence of a divalent cation binding to Asp10 and Asp11 is likely to substantially alter interactions between Asp 10, Asp11, His12, and Lys109.

5. The authors present an AlphaFold model of an SsrB dimer, and note that His12 is at the dimer interface. However, the authors also believe that a higher-order oligomer of SsrB binds to DNA in a pH-dependent manner. Do the authors have any suggestions or informed speculation about how His12 might affect higher-order oligomerization than dimerization?

Reviewer #2 (Public Review):

This is a very interesting paper with several important findings related to the working mechanism of the cartwheel cells (CWC) in the dorsal cochlear nucleus (DCN). These cells generate spontaneous firing that is inhibited by the activation of α2-adrenergic receptors, which also enhances the synaptic strength in the cells, but the mechanisms underlying the spontaneous firing and the dual regulation by α2-adrenergic receptor activation have remained elusive. By recording these cells with the NALCN sodium-leak channel conditionally knocked, the authors discovered that both the spontaneous firing and the regulation by noradrenaline (NA) require NALCN. Mechanistically, the authors found that activation of the adrenergic receptor or GABAB receptor inhibits NALCN. Interestingly, these receptor activations also suppress the low [Ca2+] "activation" of NALCN currents, suggesting crosstalk between the pathways. The finding of such dominant contribution of the NALCN conductance to the regulation of firing by NA is somewhat surprising considering that NA is known to regulate K+ conductances in many other neurons.

The studies reveal the molecular mechanisms underlying well known regulations of the neuronal processes in the auditory pathway. The results will be important to the understanding of auditory information processing in particular, and, more generally, to the understanding of the regulation of inhibitory neurons and ion channels. The results are convincing and are clearly presented.

Reviewer #2 (Public Review):

Previous studies have shown that two hair cell transcription factors, Pou4f3 and Gfi1, are both necessary for the survival of cochlear hair cells, and that Gfi1 is regulated by Pou4f3. The authors have previously also shown that mosaic inactivation of the RNA-binding protein RBM24 leads to outer hair cell death.

In the present study, the authors show that hair cells die in Pou4f3 and Gfi1 mutant mice. They show that Gfi1 is regulated by Pou4f3. Both these observations have been published before. They then show that RBM24 is absent in Pou4f3 knockouts, but not Gfi1 knockouts. They ectopically activate RMB24 in the hair cells of Pou4f3 knockouts, but this does not rescue the hair cell death. Finally, the authors validate three RMB24 enhancers that are active in young hair cells and which have been previously shown to bind Pou4f3.

The experiments are well-executed and the data are clear. The results support the conclusions of the paper.

Much of the work in the paper has been reported before. The result that hair cell transcription factors operate in a network, with some transcription factors activating only a subset of hair cell genes, is an expected result. Since RMB24 is only one of many genes regulated directly by Pou4f3, it is not surprising that it cannot rescue the Pou4f3 knockout hair cell degeneration.

The identification of new hair cell enhancers may be of use to investigators wishing to express genes in hair cells.

In sum, this work, although carefully performed, does not shed significant new light on our understanding of hair cell development or survival.

Reviewer #2 (Public Review):

Kelly et al. strategically leverage state-of-the art scRNA-seq methods combined with unique strengths of the zebrafish larval model to identify gene expression patterns that underlie the different functional output of different neuronal circuits that converge on similar muscle groups. The results lead to the identification of ion channel and synapse associated genes that distinguish the neuronal components of a fast circuit mediating escape behavior from a rhythmic circuit mediating graded swimming.

The authors develop methods for isolation of single spinal cord neurons from 4 day post fertilization (dpf) zebrafish larvae. The 4 dpf neuronal circuits mediating escape vs. rhythmic swimming behavior have been extensively characterized allowing knowledge of the specific motor neuron and interneuron populations involved in one vs. the other circuit. (Work from the authors' research group has contributed to this strong starting point for this study.)

The transcriptomic analyses lead to the identification of clusters of cells sharing significant gene expression that distinguishes them from other clusters. Using well-known neuron subtype specific markers, the authors are able to assign a specific neuronal identity to about 2/3 of the cluster. Moreover, one other cluster results in the recognition in zebrafish of a neuronal cell type identified in the mammalian spinal cord, v0c, that they confirm to be present in zebrafish using solid markers. In addition, the results show that the zebrafish v0c population expressed markers of both cholinergic and glutamatergic neurons, while the mammalian v0c population is known to be cholinergic. (It is not clear whether the possibility that mammalian v0c neurons also express glutamatergic markers has been specifically tested, but it seems, at present, there is no evidence to suggest that might be the case.)

To zoom in on the question of molecular differences between the fast vs. rhythmic circuits, the authors focus on motor neurons as two different populations of neurons are involved in each circuit. (Along the way, they also identify markers that mark different subtypes of motor neurons.) They find that primary motor neurons (PMNs) involved in the fast circuit express a distinguishing cassette of ion channel and synapse associated genes. Moreover, the cassette of genes also is expressed by interneurons that function in the fast circuit. The results are illuminating and set the stage for many future exacting experiments.

As is true for significant work, the results open up and permit yet more rigorous and strategic analyses, running the gamut from specific molecules to behavior, of the circuit mechanisms underlying unique behaviors.

Overall, the work is carried out to high rigorous standards and the vast majority of conclusions are strongly supported by the results. However, there are a few instances of potential over-interpretation and points that could be further clarified/discussed:

1 - lines 412-414. The authors conclude that "Most importantly, and as detailed below, our scRNA seq revealed the ion channel and synaptic genes that serve to match specific neuronal function to behavior." That the authors have identified a gene cassette that distinguishes neurons of the fast escape circuit is a laudable finding. However, at this stage, to say that this gene cassette is the basis for unique circuit function and resultant behavior is a well-supported hypothesis that requires rigorous testing and not yet a solid conclusion. (Maybe that is what the authors meant, and I have misinterpreted the sentence.)

2 - lines 323-324: Given that ~ 6 hrs separates PMN from SMN birthdates (Myers et al. 1986) and that the study was done using 4dpf larval tissue, the possibility that the higher level of expression of transcription factors and RNA-biding factors in SMNs reflects "the less well differentiated state that accompanies the later birthdate of the SMns" seems unlikely.

3 - Fig 5 and Sup Fig 1:The authors mention that the unidentified cluster in the motor neuron set shares markers with non-skeletal muscle. I realize that this cluster is tangential to their focus. However, given that this cluster predominantly arises from the FACS sorted cells, it is worth considering that the cells might correspond to the pancreas.

4 - lines 113-115 and Fig. 1: The authors indicate that three clusters reflect cells that have mixed glial and neuronal cell expression. Is there any possibility that in a few instances, in the final single cell capture, that two rather than one cell were collected? (Again, not a major focus of the study but the cluster is commented on.)

Finally, as the transcriptomic information about glial cells will be of interest to many in the field, the authors are to be commended for depositng the data in congratulations to the authors for depositing the data in the publicly accessible Gene Expression Omnibus.

Reviewer #2 (Public Review):

The authors analysed functional MRI recordings of brain activity at rest, using state-of-the-art methods that reveal the diverse ways in which the information can be integrated in the brain. In this way, they found brain areas that act as (synergistic) gateways for the 'global workspace', where conscious access to information or cognition would occur, and brain areas that serve as (redundant) broadcasters from the global workspace to the rest of the brain. The results are compelling and consisting with the already assumed role of several networks and areas within the Global Neuronal Workspace framework. Thus, in a way, this work comes to stress the role of synergy and redundancy as complementary information processing modes, which fulfill different roles in the big context of information integration.

In addition, to prove that the identified high-order interactions are relevant to the phenomenon of consciousness, the same analysis was performed in subjects under anesthesia or with disorders of consciousness (DOC), showing that indeed the loss of consciousness is associated with a deficient integration of information within the gateway regions.

However, there is something confusing in the redundancy and synergy matrices shown in Figure 2. These are pair-wise matrices, where the PID was applied to identify high-order interactions between pairs of brain regions. I understand that synergy and redundancy are assessed in the way the brain areas integrate information in time, but it is still a little contradictory to speak about high-order in pairs of areas. When talking about a "synergistic core", one expects that all or most of the areas belonging to that core are simultaneously involved in some (synergistic) information processing, and I do not see this being assessed with the currently presented methodology. Similarly, if redundancy is assessed only in pairs of areas, it may be due to simple correlations between them, so it is not a high-order interaction. Perhaps it is a matter of language, or about the expectations that the word 'synergy' evokes, so a clarification about this issue is needed. Moreover, as the rest of the work is based on these 'pair-wise' redundancy and synergy matrices, it becomes a significative issue.

Reviewer #2 (Public Review):

This article is focused on investigating incremental speech processing, as it pertains to building higher-order syntactic structure. This is an important question because speech processing in general is lesser studied as compared to reading, and syntactic processes are lesser studied than lower-level sensory processes. The authors claim to shed light on the neural processes that build structured linguistic interpretations. The authors apply modern analysis techniques, and use state-of-the-art large language models in order to facilitate this investigation. They apply this to a cleverly designed experimental paradigm of EMEG data, and compare neural responses of human participants to the activation profiles in different layers of the BERT language model.

Strengths:

[1] The study aims to investigate an under-explored aspect of language processing, namely syntactic operations during speech processing

[2] The study is taking advantage of technological advancements in large language models, while also taking linguistic theory into account in building the hypothesis space

[3] The data combine EEG and MEG, which provides a valuable spatio-temporally resolved dataset

[4] The use of behavioural validation of high/low transitive was an elegant demonstration of the validity of their stimuli

Weaknesses:

[1] The manuscript is quite hard to understand, even for someone well-versed in both linguistic theory and LLMs. The questions, design, analysis approach, and conclusions are all quite dense and not easy to follow.

[2] The analyses end up seeming overly complicated when the underlying difference between sentence types is a simple categorical distinction between high and low transitivity. I am not sure why tree depth and BERT are being used to evaluate the degree to which a sentence is being processed as active or passive. If this is necessary, it would be helpful for the authors to motivate this more clearly.

[3] The main data result figures comparing BERT and the EMEG brain data are hard to evaluate because only t-values are provided, and those, only for significant clusters. It would be helpful to see the full 600 ms time course of rho values, with error bars across subjects, to really be able to evaluate it visually. This is a summary statistic that is very far away from the input data

[4] Some details are omitted or not explained clearly. For example, how was BERT masked to give word-by-word predictions? In its default form, I believe that BERT takes in a set of words before and after the keyword that it is predicting. But I assume that here the model is not allowed to see linguistic information in the future. How were the auditory stimuli recorded? Was it continuous speech or silences between each word? How was prosody controlled? Was it a natural speaker or a speech synthesiser?

It is difficult for me to fully assess the extent to which the authors achieved their aims, because I am missing important information about the setup of the experiment and the distribution of test statistics across subjects.

Reviewer #2 (Public Review):

Language skills are traditionally associated with a network of brain regions in the left hemisphere. In this intriguing study, Esteban Villar-Rodríguez and collaborators examined if atypical hemispheric lateralization for language determines the functional and structural organisation of the network for inhibitory control as well as its relationship with schizotypy and autistic spectrum traits. The results suggest that individuals who have atypical lateralisation of the language function have also an atypical (mirrored) lateralisation of the inhibitory control network, compared to the typical group (individuals with left-lateralised language function). Furthermore, the atypical organization of language production is associated with a greater white matter volume of the corpus callosum, and atypical lateralization of inhibitory control is related to a higher interhemispheric functional coupling of the IFC, suggesting a link between atypical functional lateralisation (language and inhibitory control) and structural and functional changes in the brain.

This study also provides interesting evidence on how atypical language lateralisation impacts some aspects of language behaviour (reading), i.e., atypical lateralization predicts worse reading accuracy. Furthermore, the results suggest an association between atypical lateralization and increased schizotypy and autistic traits.

The strength of this work is that it presents a collection of measurements on the same individuals (including task-related behavioural, functional and structural neuroimaging measures) to reveal if (and how) atypical language lateralisation might be associated with: (1) atypical neural organisation of other non-linguistic cognitive systems, (2) behavioural performance associated with language tasks, and finally (3) personality traits. As such the results presented in this manuscript have the potential to be informative for various disciplines. For instance, if clarifications/corrections are provided (see below), the results might provide some insight into the role of the right hemisphere for language processing in healthy individuals as well as patient populations with acquired linguistic impairment including stroke and dementia.

One important weakness of this manuscript is that several areas, including the characteristics of participants tested, and the hypotheses/predictions, are underspecified or incomplete. Furthermore, in some cases the types of analysis do not seem to be appropriate for addressing the questions of the present study and very little explanation for those choices is provided.

Reviewer #2 (Public Review):

The manuscript by Est and Murphy tested the feasibility of using brain microvascular endothelial-like cells (BMECs) derived from induced pluripotent stem cells (iPSCs) as a model for studying retinoid uptake and transport across the blood-brain barrier (BBB). Establishing this experimental model is an important step towards obtaining greater mechanistic insight into the specificity of retinol trafficking between blood and retinoid-dependent tissues. The authors validated the iPSC-derived BMECs by detecting the expression of specific protein markers for BBB. They also demonstrated that BMECs form a tight barrier when cultured in a Transwell chamber, allowing for the quantification of permeability across the cells rather than through paracellular leakage. Finally, they confirmed the expression of the transporter (STRA6), binding protein (CRBP1), and enzyme (LRAT), which are key elements of the molecular machinery involved in the cellular uptake of circulating retinol. The carefully established model of the human BBB served as an experimental platform for the authors to investigate the uptake and transcellular transport of retinol. For this purpose, they compared the kinetics and efficiency of retinoid accumulation delivered to the cell as free retinol, retinol bound to serum retinol-binding protein (RBP), or retinol-RBP in complex with transthyretin (TTR), a physiological binding partner for retinol-loaded RBP.

Although the development and thorough characterization of the experimental model of the BBB have great value and meaningfully contribute to ongoing efforts to better understand the mechanisms of retinoid homeostasis, the premise and interpretation of cellular uptake appear controversial. In particular:

1. The authors assume that there is a significant fraction of free ROL, 20% for ROH/RBP and 7% for RBP/TTR complexes (summarized in Table 1). This implies that at the physiological concentration of ROH/RBP in the plasma of 2 uM, free ROL represents 0.4 uM. However, the concentration of free ROL is limited by its poor solubility in the aqueous phase, which is around 0.06 uM (Szuts EZ, 1991, Arch Biochem Biophys). Moreover, taking into account the large concentration of other potential nonspecific carriers for lipids, it is safe to assume that there is virtually no free ROH in the plasma. There is also an important physiological reason for the limited amount of free ROL. Its rapid and nonspecific partition into cells (also observed in this study) would work against the highly specific RBP/STRA6-dependent ROH uptake pathway, undermining its physiological function.

2. The advantage of the experimental system used in this report is that it allows for the assessment of the permeability across BMECs. Interestingly, the basolateral accumulation of ROH represented only a small fraction (1 - 1.5%) of the total ROH taken up by the cells. Moreover, the overall permeability was comparable regardless of the source of ROL added at the apical side. However, a question remains: would the outcome of the experiment be different if the basolateral chamber contained an ROH acceptor (retinol-binding proteins) rather than Hank's balanced salt solution, to which the partition of ROL is limited by its water solubility? In fact, the maximum concentration of ROH on the basolateral side did not exceed 40 nM (Fig 5D and 7C), which is roughly the maximum water solubility of ROH. Thus, this experimental design limits extrapolation of the data to in vivo conditions.

3. The authors claim that transthyretin (TTR) increases BMECs permeability when compared to ROH/RBP. However, the mechanistic explanation for this phenomenon remains unclear. Do the authors imply the presence of a putative TTR receptor whose signaling could affect the efflux of ROL at the basolateral side of BMECs? TTR is an ubiquitous plasma protein. The concentration of TTR is tightly regulated and maintained between 300 - 330 mg/L. Therefore, it is questionable how TTR can serve as a signaling molecule modulating retinoid homeostasis in the brain.

4. Although overexpression of LRAT in response to increased uptake of ROH is well-documented, the postulate that TTR stimulates the expression of LRAT in an RBP-independent manner is puzzling, for the reasons mentioned in point 3. Moreover, LRAT is a highly efficient enzyme that operates under physiological conditions with substrate concentrations below the Km value. The rate of esterification is primarily limited by the intracellular transport of ROH to the ER. Therefore, without kinetic studies, it is unclear whether an increased number of LRAT copies (x2) would have a significant effect on the rate of accumulation of retinyl esters (REs).

5. The conclusion that cellular uptake of ROH is biphasic appears to be correct. However, the proposed interpretation of the mechanistic principles of this phenomenon is oversimplified. It assumes that loading CRBP1 with ROL to its capacity triggers the synthesis of REs. However, the saturation of CRBP1 with ROH is not required for REs formation. In fact, studies on CRBP1-deficient mice indicate that this protein is not necessary for the efficient esterification of ROL but rather affects the intracellular turnover of retinoids. It is likely that with increasing concentration of ROH, the specific and controlled mechanism of intracellular retinoid transport becomes saturated, allowing for spontaneous diffusion-driven partitioning of retinoids within cells.

Additional technical issues that could affect the experimental outcomes:

1. The formation of the ROH/RBP-TTR complex should be confirmed and purified using gel filtration to separate free TTR and ROH/RBP. Only fractions containing the complex should be used in the experiments. Assuming that the complex is formed with 100% efficiency is overly optimistic.

2. Reloading RBP with isotopically labeled ROH requires an additional purification step. Stripping ROL from the ROH/RBP complex with organic solvent (diethyl ether) is appropriate but relatively harsh, causing partial unfolding of a fraction of RBP. Therefore, assuming that 100% of stripped RBP remains functional and can be reloaded with ROH is inaccurate. Reloading apo-RBP with a stoichiometric amount of ROH without an additional purification step (e.g., ion exchanger) leads to an excess of free ROL and/or its nonspecific association with nonfunctional RBP fractions. Measuring absorbance at 330 nm is not sufficient proof of binding since free ROH also absorbs at the same wavelength.

Reviewer #2 (Public Review):

The authors tried to diagnose cancers and pinpoint tissues of origin using cfDNA. To achieve the goal, they developed a framework to assess methylation, CNA, and other genomic features. They established discovery and validation cohorts for systematic assessment and successfully achieved robust prediction power.

Still, there are places for improvement. The diagnostic effect can be maximized if their framework works well in early stage cancer patients. According to Table 1, about 10% of the participants are stage I. Do these cancers also perform well as compared to late stage cancers?

Can authors show a systematic comparison of their method to other previous methods to summarize what their algorithm can achieve compared to others.

Reviewer #2 (Public Review):

Ghasemahmad et al. report findings on the influence of salient vocalization playback, sex, and previous experience, on mice behaviors, and on cholinergic and dopaminergic neuromodulation within the basolateral amygdala (BLA). Specifically, the authors played back mice vocalizations recorded during two behaviors of opposite valence (mating and restraint) and measured the behaviors and release of acetylcholine (ACh), dopamine (DA), and serotonin in the BLA triggered in response to those sounds.

Strength: The authors identified that mating and restraint sounds have a differential impact on cholinergic and dopaminergic release. In male mice, these two distinct vocalizations exert an opposite effect on the release of ACh and DA. Mating sounds elicited a decrease of Ach release and an increase of DA release. Conversely, restraint sounds induced an increase in ACh release and a trend to decrease in DA. These neurotransmission changes were different in estrus females for whom the mating vocalization resulted in an increase of both DA and ACh release.

Weaknesses: The behavioral analysis and results remain elusive, and although addressing interesting questions, the study contains major flaws, and the interpretations are overstating the findings.

Reviewer #2 (Public Review):

In the manuscript, the authors highlighted the importance of T-cell receptor (TCR) analysis and the lack of amino acid embedding methods specific to this domain. The authors proposed a novel bi-directional context-aware amino acid embedding method, catELMo, adapted from ELMo (Embeddings from Language Models), specifically designed for TCR analysis. The model is trained on TCR sequences from seven projects in the ImmunoSEQ database, instead of the generic protein sequences. They assessed the effectiveness of the proposed method in both TCR-epitope binding affinity prediction, a supervised task, and the unsupervised TCR clustering task. The results demonstrate significant performance improvements compared to existing embedding models. The authors also aimed to provide and discuss their observations on embedding model design for TCR analysis: 1) Models specifically trained on TCR sequences have better performance than models trained on general protein sequences for the TCR-related tasks; and 2) The proposed ELMo-based method outperforms TCR embedding models with BERT-based architecture. The authors also provided a comprehensive introduction and investigation of existing amino acid embedding methods. Overall, the paper is well-written and well-organized.

The work has originality and has potential prospects for immune response analysis and immunotherapy exploration. TCR-epitope pair binding plays a significant role in T cell regulation. Accurate prediction and analysis of TCR sequences are crucial for comprehending the biological foundations of binding mechanisms and advancing immunotherapy approaches. The proposed embedding method presents an efficient context-aware mathematical representation for TCR sequences, enabling the capture and analysis of their structural and functional characteristics. This method serves as a valuable tool for various downstream analyses and is essential for a wide range of applications.

Reviewer #2 (Public Review):

In this project, Schmidig, Ruch and Henke examined whether word pairs that were presented during slow-wave sleep would leave a detectable memory trace 12 and 36 hours later. Such an effect was found, as participants showed a bias to categorize pseudowords according to a familiar word that they were paired with during slow-wave sleep. This behavior was not accompanied by any sign of conscious understanding of why the judgment was made, and so demonstrates that long-term memory can be formed even without conscious access to the presented content. Unconscious learning occurred when pairs were presented during troughs but not during peaks of slow-wave oscillations. Differences in brain responses to the two types of presentation schemes, and between word pairs that were later correctly- vs. incorrectly-judged, suggest a potential mechanism for how such deep-sleep learning can occur.

The results are very interesting, and they are based on solid methods and analyses. Results largely support the authors' conclusions, but I felt that there were a few points in which conclusions were not entirely convincing:

1) As a control for the critical stimuli in this study, authors used a single pseudoword simultaneously played to both ears. This control condition (CC) differs from the experimental condition (EC) in a few dimensions, among them: amount of information provided, binaural coherence and word familiarity. These differences make it hard to conclude that the higher theta and spindle power observed for EC over CC trials indicate associative binding, as claimed in the paper. Alternative explanations can be made, for instance, that they reflect word recognition, as only EC contains familiar words.

2) The entire set of EC pairs were tested both following 12 hours and following 36 hours. Exposure to the pairs during test #1 can be expected to have an effect over memory one day later, during test #2, and so differences between the tests could be at least partially driven by the additional activation and rehearsal of the material during test #1. Therefore, it is hard to draw conclusions regarding automatic memory reorganization between 12 and 36 hours after unconscious learning. Specifically, a claim is made regarding a third wave of plasticity, but we cannot be certain that the improvement found in the 36 hour test would have happened without test #1.

3) Authors claim that perceptual and conceptual processing during sleep led to increased neural complexity in troughs. However, neural complexity was not found to differ between EC and CC, nor between remembered and forgotten pairs. It is therefore not clear to me why the increased complexity that was found in troughs should be attributed to perceptual and conceptual word processing, as CC contains meaningless vowels. Moreover, from the evidence presented in this work at least, I am not sure there is room to infer causation - that the increase in HFD is driven by the stimuli - as there is no control analysis looking at HFD during troughs that did not contain stimulation.

Reviewer #2 (Public Review):

Chakraborty et al. present a comprehensive analysis of the role of the IP3R in regulating SOCE in neuronal cells starting with human neurons derived from stem cells and continuing with SH-SY5Y cells after careful characterization of the maintenance of the inhibitory role of IP3R. They also show differential effects in non-neuronal cell lines. The work is careful and the data convincing. The conclusion that IP3Rs somehow stabilize ER-PM MCS to enhance SOCE is supported by the findings especially the surprising finding that the IP3R effect does not require a functional pore but does require IP3 binding to IP3R. Overall this is a careful, well-done analysis. However, the conclusion that IP3R stabilizes ER-PM MCS is mostly inferred from the current data. The authors need to extend the finding by directly assessing the size, density, and the number of ER-PM MCS using endogenous STIM1 (there are reliable antibodies for STIM1) to confirm their conclusion that when IP3R is knocked down ER-PM MCS are smaller/less dense. Another interesting experiment that would support their conclusion is expressing tagged STIM1 and Orai1 and observing their interaction in real time after store depletion. These experiments would need to be carefully controlled to select cells with low levels of expression of STIM1-Orai1 as there are hints from their current data that high expressors would not exhibit the IP3R dependence on SOCE. So, some independent experimental evidence that IP3R knockdown is affecting ER-PM MCS and not STIM1-Orai1 interaction directly to support the presented PLA data would greatly support the final conclusion of the paper. From the PLA assay alone it is difficult to differentiate between poor direct STIM1-Orai1 interaction versus stability of ER-PM MCS.

Reviewer #2 (Public Review):

McCormick, Cleary et al., explore the question of how the nucleotide state of the tubulin heterodimer affects the interaction between adjacent tubulins.

(1) The setup of the authors' model, which attributes the dynamic properties of the growing microtubule only to the differences in interface binding affinities, is unrealistic. They excluded the influence of the nucleotide-dependent global conformational changes even in the 'Self-Acting Nucleodide' model (Fig. 1A). As the authors have found earlier, tubulin in its unassembled state may be curved irrespective of the species of the bound nucleotide (Rice et al., 2008, doi: 10.1073/pnas.0801155105), but at the growing end of microtubules, the situation could be different. Considering the recently published papers from other laboratories, it may be more appropriate to include the nucleotide-dependent change in the tubulin conformation in the Self-Acting Nucleotide model.

(2) The result that the minus end is insensitive to GDP (Fig. 2) was previously published in a paper by Tanaka-Takiguchi et al. (doi: 10.1006/jmbi.1998.1877). The exact experimental condition was different from the one used in Fig. 2, but the essential point of the finding is the same. The authors should cite the preceding work, and discuss the similarities and differences, as compared to their own results.

Reviewer #2 (Public Review):

Schmid et al present a lovely study looking at the effect of passive auditory exposure on learning a categorization task.

The authors utilize a two-alternative choice task where mice have to discriminate between upward and downward-moving frequency sweeps. Once mice learn to discriminate easy stimuli, the task is made psychometric and additional intermediate stimuli are introduced (as is standard in the literature). The authors introduce an additional two groups of animals, one that was passively exposed to the task stimuli before any behavioral shaping, and one that had passive exposure interleaved with learning. The major behavioral finding is that passive exposure to sounds improves learning speed. The authors show this in a number of ways through linear fits to the learning curves. Additionally, by breaking down performance based on the "extreme" vs "psychometric" stimuli, the authors show that passive exposure can influence responses to sounds that were not present during the initial training period. One limitation here is that the presented analysis is somewhat simplistic, does not include any detailed psychometric analysis (bias, lapse rates etc), and primarily focuses on learning speed. Ultimately though, the behavioral results are interesting and seem supported by the data.

To investigate the neural mechanisms that may underlie their behavioral findings, the authors turn to a family of artificial neural network models and evaluate the consequences of different learning algorithms and schedules, network architectures, and stimulus distributions, on the learning outcomes. The authors work through five different architectures that fail to recapitulate the primary behavior findings before settling on a final model, utilizing a combination of supervised and unsupervised learning, that was capable of reproducing the key aspects of the experiments. Ultimately, the behavioral results presented are consistent with network models that build latent representations of task-relevant features that are determined by statistical properties of the input distribution.

Reviewer #2 (Public Review):

Knowles et al. investigated the developmental roles of Erk1/2 expression in cells from the Nkx2.1-lineage, which includes the PV and SST classes of cortical inhibitory interneurons (CINs) and glial subtypes. They find that embryonic expression of Erk1/2 regulates the number of Nkx2.1-derived oligodendrocytes and astrocytes, but not CINs, observed in postnatal mice. However, Erk1/2 is necessary for the expression of SST in subset of Nkx2.1-derived CINs, which can be partially rescued by postnatal depolarization via chemogenetic stimulation with DREADDs. Finally, loss of Erk1/2 from these cells impairs activity-dependent expression of FOSB. Collectively, this revised paper demonstrates differential roles of Erk1/2 for the development of glia and neurons. Furthermore, it suggests SST CINs may be particularly vulnerable to loss of Erk1/2 signaling during both early embryonic and later postnatal developmental stages.

Strengths:<br /> This paper uses multiple transgenic mouse lines to investigate the contributions of Erk1/2 loss and over-expression and MEK overexpression for interneuron and glial development. Furthermore, they consider how Erk1/2 signaling may evolve over the course of development from embryonic to postnatal juvenile and adult stages. Thus, they investigate Erk1/2's early role in cell differentiation and its later role in activity dependent signaling. This approach to studying gene function throughout development is important but not often attempted within a single study.

The authors investigate Erk1/2 using several techniques, including immunohistochemistry, sequencing of translated genes using the Ribotag method, electrophysiology, and chemogenetic stimulation using DREADDs. Thus, they aim to apply a comprehensive battery of approaches to assay Erk1/2 signaling in Nkx2.1-derived cells throughout development.

Weaknesses:<br /> This paper describes a series of mostly separate observations that are not directly linked. The mechanisms underlying their observations and the significance of the findings are often unclear.

The authors use Erk1-/-; Erk2fl/wt; Nkx2.1Cre as "het" controls throughout the manuscript. However, there is no explanation for why this is a valid control except for a statement that they are "grossly intact", without elaboration. It is unclear why the authors did not use Nkx2.1Cre mice for their control. Figure 1 - Supplemental Figure 1 provides the only comparison between Erk1-/-; Erk2fl/wt; Nkx2.1Cre and Erk1-/-; Erk2wt/wt; Nkx2.1Cre mice. This figure shows a single example of immune staining for Erk2, but it is not obvious that Nkx2.1 control or "het control" cells even express Erk2 in this image. There is no quantification. Thus, their choice of control condition is not obviously appropriate.

Reviewer #2 (Public Review):

In "Behavioral entrainment to rhythmic auditory stimulation can be modulated by tACS depending on the electrical stimulation field properties" Cabral-Calderin and collaborators aimed to document 1) the possible advantages of personalized tACS montage over standard montage on modulating behavior; 2) the inter-individual and inter-session reliability of tACS effects on behavioral entrainment and, 3) the importance of the induced electric field properties on the inter-individual variability of tACS.

To do so, in two different sessions, they investigated how the detection of silent gaps occurring at random phases of a 2Hz- amplitude modulated sound could be enhanced with 2Hz tACS, delivered at different phase lags. In addition, they evaluated the advantage of using spatially optimized tACS montages (information-based procedure - using anatomy and functional MRI to define the target ROI and simulation to compare to a standard montage applied to all participants) on behavioral entrainment. They first show that the optimized and the standard montages have similar spatial overlap to the target ROI. While the optimized montage induced a more focal field compared to the standard montage, the latter induced the strongest electric field. Second, they show that tACS does not modify the optimal phase for gap detection (phase of the frequency-modulated sound) but modulates the strength of behavioral entrainment to the frequency-modulated sound in a phase-lag specific manner. However, and surprisingly, they report that the optimal tACS lag, and the magnitude of the phasic tACS effect were highly variable across sessions. Finally, they report that the inter-individual variability of tACS effects can be explained by the strength of the inward electric field as a function of the field focality and on how well it reached the target ROI.

The article is interesting and well-written, and the methods and approaches are state-of-the-art.

Strengths:<br /> - The information-based approach used by the authors is very strong, notably with the definition of subject-specific targets using a fMRI localizer and the simulation of electric field strength using 3 different tACS montages (only 2 montages used for the behavioral experiment).<br /> - The inter-session and inter-individual variability are well documented and discussed. This article will probably guide future studies in the field.

Weaknesses:<br /> - The addition of simultaneous EEG recording would have been beneficial to understand the relationship between tACS entrainment and the entrainment to rhythmic auditory stimulation.<br /> - It would have been interesting to develop the fact that tACS did not "overwrite" neural entrainment to the auditory stimulus. The authors try to explain this effect by mentioning that "tACS is most effective at modulating oscillatory activity at the intended frequency when its power is not too high" or "tACS imposes its own rhythm on spiking activity when tACS strength is stronger than the endogenous oscillations but it decreases rhythmic spiking when tACS strength is weaker than the endogenous oscillations". However, it is relevant to note that the oscillations in their study are by definition "not endogenous" and one can interpret their results as a clear superiority of sensory entrainment over tACS entrainment. This potential superiority should be discussed, documented, and developed.<br /> - The authors propose that "by applying tACS at the right lag relative to auditory rhythms, we can aid how the brain synchronizes to the sounds and in turn modulate behavior." This should be developed as the authors showed that the tACS lags are highly variable across sessions. According to their results, the optimal lag will vary for each tACS session and subtle changes in the montage could affect the effects.<br /> - In a related vein, it would be very useful to show the data presented in Figure 3 (panels b,d,e) for all participants to allow the reader to evaluate the quality of the data (this can be added as a supplementary figure).

Reviewer #2 (Public Review):

In their article titled "Brain mechanisms of reversible symbolic reference: a potential singularity of the human brain", van Kerkoerle et al address the timely question of whether non-human primates (rhesus macaques) possess the ability for reverse symbolic inference as observed in humans. Through an fMRI experiment in both humans and monkeys, they analyzed the bold signal in both species while observing audio-visual and visual-visual stimuli pairs that had been previously learned in a particular direction. Remarkably, the findings pertaining to humans revealed that a broad brain network exhibited increased activity in response to surprises occurring in both the learned and reverse directions. Conversely, in monkeys, the study uncovered that the brain activity within sensory areas only responded to the learned direction but failed to exhibit any discernible response to the reverse direction. These compelling results indicate that the capacity for reversible symbolic inference may be unique to humans.

In general, the manuscript is skillfully crafted and highly accessible to readers. The experimental design exhibits originality, and the analyses are tailored to effectively address the central question at hand. Although the first experiment raised a number of methodological inquiries, the subsequent second experiment thoroughly addresses these concerns and effectively replicates the initial findings, thereby significantly strengthening the overall study. Overall, this article is already of high quality and brings new insight into human cognition.

I identified three weaknesses in the manuscript:<br /> - One major issue in the study is the absence of significant results in monkeys. Indeed, authors draw conclusions regarding the lack of significant difference in activity related to surprise in the multi-demand network (MDN) in the reverse congruent versus reverse incongruent conditions. Although the results are convincing (especially with the significant interaction between congruency and canonicity), the article could be improved by including additional analyses in a priori ROI for the MDN in monkeys (as well as in humans, for comparison).<br /> - While the authors acknowledge in the discussion that the number of monkeys included in the study is considerably lower compared to humans, it would be informative to know the variability of the results among human participants.<br /> - Some details are missing in the methods.

Reviewer #2 (Public Review):

The manuscript by Bull et al investigates the relationship between metabolic features, in particular different lipoproteins and fatty acids, and colorectal cancer. They combine different data sources to analyze forward and reverse Mendelian Randomization associations in children and adults. Their results indicate that polyunsaturated fatty acids may be implicated in the risk for colorectal cancer.

Overall, the paper is well-written, and the methods used are solid. The use of different data (cohort individual data and summary stats) and stratifications strengthens the analyses. The conclusions drawn from the results are balanced and supported by the data although the novelty of the findings is modest.

Reviewer #2 (Public Review):

This study presents novel findings on the metabolic fuel preference shift regulated by PTPMT1, a target of interest, in skeletal and cardiac muscle cells.

Zheng et al. have investigated the effects of PTPMT1 Knock-out on cellular metabolic flexibility. Since the authors used several types of appropriate tissue-specific mouse models, it seems to be a broad significance at the first glance. However, most of the data lack the quantification, consequently they don't provide statistical significance. In addition, the functional data such as echocardiography shows partial and limited data.<br /> Therefore, it is only a matter of speculation that the absence of PTPMT1 inhibits glucose (pyruvate) utilization and promotes FAO.

Reviewer #2 (Public Review):

Members of the EphB family of tyrosine kinase receptors are involved in a multitude of diverse cellular functions, ranging from the control of axon growth to angiogenesis and synaptic plasticity. In order to provide these diverse functions, it is expected that these receptors interact in a cell-type-specific manner with a diverse variety of downstream signalling molecules.

The authors have used proteomics approaches to characterise some of these molecules in further detail. This molecule, myc-binding protein 2 (MYCBP2) also known as highwire, has been identified in the context of establishment of neural connectivity. Another molecule coming up on this screen was identified as FBXO45.

The authors use classical methods of co-IP to show a kinase-independent binding of MYCBP2 to EphB2. They further showed that FBXO45 within a ternary complex increased the stability of the EphB2/MYCBP2 complex.

To define the interacting domains, they used clearly designed swapping experiments to show that the extracellular and transmembrane domains are necessary and sufficient for the formation of the ternary complex.

Using a cellular contraction assay, the authors showed the necessity of MYCBP2 in mediating the cytoskeletal response of EphB2 forward signalling. Furthermore, they used the technically challenging stripe assay of alternating lanes of ephrinB-Fc and Fc to show that also in this migration-based essay MYCBP2 is required for EphB mediated differential migration pattern.

MYCBP2 in addition is necessary to stabilize EphB2, that is in the absence of MYCBP2, EphB2 is degraded in the lysosomal pathway.

Interestingly, the third protein in this complex, Fbxo45, was further characterized by overexpression of the domain of MYCBP2, known to interact with Fbxo45. Here the authors showed that this approach led to the disruption of the EphB2 / MYCBP2 complex, and also abolished the ephrinB-mediated activation of EphB2 receptors and their differential outgrowth on ephrinB2-Fc / Fc stripes.

Finally, the authors demonstrated an in vivo function of this complex using another model system, C elegans where they were able to show a genetic interaction.

Data shows in a nice set of experiments a novel level of EphB2 forward signalling where a ternary complex of this receptor with multifunctional MYCBP2 and Fbxo45 controls the activity of EphB2, allowing a further complex regulation of this important receptor. Additionally, the authors challenge pre-existing concepts of the function of MYCBP2 which might open up novel ways to think about this protein.

Of interest is this work also in terms of the development of the retinotectal projection in zebrafish where MYCBP2/highwire plays a crucial role, and thus might lead to a better understanding of patterning along the DV axis, for which it is known that EphB family members are crucial.

Overall, the experiments are classical experiments of co-immunoprecipitations, swapping experiments, collapse assays, and stripe assays which all are well carried out and are convincing.

Reviewer #2 (Public Review):

In this manuscript, Smith et al. delineated novel mechanistic insights into the structure-function relationships of the C-terminal repeat domains within the mouse DUX protein. Specifically, they identified and characterised the transcriptionally active repeat domains, and narrowed down to a critical 6aa region that is required for interacting with key transcription and chromatin regulators. The authors further showed how the DUX active repeats collaborate with the C-terminal acidic tail to facilitate chromatin opening and transcriptional activation at DUX genomic targets.

Reviewer #2 (Public Review):

In this study, Yan et al. report that a cleaved form of METTL3 (termed METTL3a) plays an essential role in regulating the assembly of the METTL3-METTL14-WTAP complex. Depletion of METTL3a leads to reduced m6A level on TMEM127, an mTOR repressor, and subsequently decreased breast cancer cell proliferation. Mechanistically, METTL3a is generated via 26S proteasome in an mTOR-dependent manner.

The manuscript follows a smooth, logical flow from one result to the next, and most of the results are clearly presented. Specifically, the molecular interaction assays are well-designed. This model represents a significant addition to the current understanding of m6A-methyltransferase complex formation.

Reviewer #2 (Public Review):

In this study, the authors utilize a compendium of public genomic data to identify transcription factors (TF) that can identify their DNA binding motifs in the presence of nuclosome-wrapped chromatin and convert the chromatin to open chromatin. This class of TFs are termed Pioneer TFs (PTFs). A major strength of the study is the concept, whose premise is that motifs bound by PTFs (assessed by ChIP-seq for the respective TFs) should be present in both "closed" nucleosome wrapped DNA regions (measured by MNase-seq) as well as open regions (measured by DNAseI-seq) because the PTFs are able to open the chromatin. Use of multiple ENCODE cell lines, including the H1 stem cell line, enabled the authors to assess if binding at motifs changes from closed to open. Typical, non-PTF TFs are expected to only bind motifs in open chromatin regions (measured by DNaseI-seq) and not in regions closed in any cell type. This study contributes to the field a validation of PTFs that are already known to have pioneering activity and presents an interesting approach to quantify PTF activity.

For this reviewer, there were a few notable limitations. One was the uncertainty regarding whether expression of the respective TFs across cell types was taken into account. This would help inform if a TF would be able to open chromatin. Another limitation was the cell types used. While understandable that these cell types were used, because of their deep epigenetic phenotyping and public availability, they are mostly transformed and do not bear close similarity to lineages in a healthy organism. Next, the methods used to identify PTFs were not made available in an easy-to-use tool for other researchers who may seek to identify PTFs in their cell type(s) of interest. Lastly, some terms used were not defined explicitly (e.g., meaning of dyads) and the language in the manuscript was often difficult to follow and contained improper English grammar.

Reviewer #2 (Public Review):

Dr. Kia Davis and colleagues present a thoughtful analysis of disruptions to cancer care during COVID-19 in the article, "Understanding disruptions in cancer care to reduce increased cancer burden: a cross-sectional study." The article is based on an online survey of 680 residents in the Siteman Cancer Center catchment area in Summer 2020. The authors aim to characterize demographic differences in cancer care disruptions. Information about the causes and distribution of care disruption can help reduce the impacts of COVID-19 and guide the recovery of programs and services. The article provides a clear and detailed assessment of factors associated with care disruption and return to care during the first six months of the pandemic.

A strength of the study is the focus on the catchment area of the cancer center during a period of dramatic change. The results would provide timely and actionable data to address emerging barriers to care and associated social or contextual factors. This information helps the Community Outreach and Engagement efforts to be responsive to community priorities despite rapidly evolving circumstances.

The analysis would benefit from greater detail in three areas. First, it would be helpful to have more information about how the outcome measures were originally developed or tested. Second, for the regression analysis, it would be helpful to show the demographic characteristics of the two strata to better understand the sample composition. Third, the authors should demonstrate that the data do not violate the assumptions for conducting logistic regression to improve confidence in the findings.

COVID-19 affected all aspects of the cancer continuum. The study reports factors associated with postponing or canceling cancer-related appointments during the pandemic. It will be of great interest to researchers and practitioners in cancer prevention and control.

Reviewer #2 (Public Review):

In this manuscript, the authors study the generation of joint torques in stick insects under external electrical excitation. The goal of this paper is to develop a model for the relationship between torque and excitation period, with a specific focus on accounting for inter-individual variances in the model. The long-term motivation for this work is to be able to generate controlled external excitation of insect muscle to create "cyborg" systems where computer-controlled electronics generate movement of living systems.

The authors performed measurements of joint torque generated from three different muscles across two excitation parameters (voltage and excitation time). The authors study the relationship between excitation parameters and muscle torque comparing a linear relationship, and a non-linear (power-law) relationship between torque and voltage. In addition, the authors also compare a hierarchical version of the model which includes inter-individual differences, with a pooled model that ignores individual differences. The authors use an information criteria metric to then identify the best model.

I believe that the methods of this paper and the findings are all sound; however, I have the following comments and questions.

Main questions:<br /> 1. It is interesting to find that inter-individual differences are important in the torque output from the joint. However, in some sense, this is what I would have expected. I am curious if these inter-individual differences can be related to any distinct differences among the insects studied: for example body mass, limb length, cross-sectional muscle area, and age all would likely influence torque. Now I am not advocating that all of the above parameters (age, size, etc) be added into a more complex model because I don't think that is necessarily the right path. However, I do think it would be beneficial to present the known information about the variance in individual size/age/etc, some of which may be unknown.

2. Line 145 states that "Models 1-2 and 2-1 most accurately predicted the posterior predictive distribution.", but is this not a typo? I thought Models 1-2 and 2-2 are the best as they are the linear and nonlinear models with hierarchical slopes.

In the paragraph starting at line 147 and the subsequent paragraph it is argued that while the nonlinear model 2-2 worked well, the linear model is still better. "The comparison of the linear model (model 1-2) with the nonlinear model (model 2-2) using the WAIC for all conditions (muscle type and applied voltage) resulted in lower values for the linear model." But certainly, both are quite close in WAIC, and my question is, might there be reasons from muscle physiology on stick insects to expect a non-linear model? While the linear model had the lowest WAIC (marginally from looking at Fig 2) without any prior assumptions about the torque-duration curve, certainly much is known about the effect of stimulation on force production, and might including that information validate the non-linear model over linear?

Alternatively, if the goal is to just model the data under 500ms stimulation because this is the relevant timescale for walking behavior (line 181) then the linear model is fine. But reading the manuscript I got the impression the goal was to best model the torque-voltage relationship, which I would think includes the full excitation range and incorporates known information from muscle physiology.

3. Fig 3 is a bit confusing as this is meant to compare the experimental data with the hierarchical model distribution. However, all the model distributions across the 10 insects look identical. I thought the point of the hierarchical model is that the slope parameter varies across individuals (isn't this what Fig 4 demonstrates?). So shouldn't the distributions and green fit lines all be different for the individuals?

I have some questions that should be clarified about the methods:<br /> 4. It is stated that 20 insects were tested, but all the plots show only 10. Is this just because the other 10 were not presented? Or were observations discarded from the other 10 insects for some reason? This is important to describe so that readers can assess the results.

5. More information should be provided about the ordering of the different excitation experiments. The methods do not describe what the time duration between excitations was, how many were performed over what time period, etc. Additionally, it looks like four different voltage amplitudes were performed which I could only observe from figures 2 and 4. It would be beneficial to describe in detail the full sequence of data collection on an insect.

6. What is the order of presentation of different voltages? It is stated that muscle fatigue should be negligible for under 50 stimulations, but the range of the 2V experiments alone was between 49-79 stimulations. So were another ~50 stimulations performed at the three other voltages? And if so was fatigue a possible issue?<br /> Also, were there "warm up" effects too where the muscle force increased with subsequent stimulations? It would be useful to provide some characterization of this.

Reviewer #2 (Public Review):

In the present study, Castano et al. discovered a chemical inhibitor that is specifically effective against the kinase activity of CDKL5 and applied it in the in vitro and the brain slice culture to reveal the acute effects of the loss of function (LOF) of CDKL5. LOF has been modeled in gene knockout mice, but these are loss-of-function models with the added developmental time effects of the absence of CDKL5 from developmental stages. The present authors' approach is the fastest timescale study to date, examining CDKL5 LOF effects in seconds to minutes.

The authors showed that chemical inhibition of CDKL5 kinase activity suppresses postsynaptically derived LTP in rat brain slice experiments, indicating that the previously controversial results of CDKL5 LOF on LTP in knockout mice and rats are possibly due to combined effects of the loss of the kinase and compensation by other factors.

The authors employed state-of-the-art methodologies and presented their data clearly and convincingly.

Reviewer #2 (Public Review):

In this work, the authors examine the antineoplastic effects of a combined treatment with the impridone ONC201/Tic10 and everolimus against ER+ breast cancer models. The combination was shown to have enhanced activity against everolimus resistant cells especially in 3D models as well as against primary cells derived from patients that have received treatment with everolimus in the past.

The authors address the important issue of drug resistance in ER+ breast cancer by using resistant cell models. Moreover, patient-derived cells were used in this work. From a molecular point of view, current mechanisms of action of ONC201/Tic10 were explored including effects on ERK/AKT pathways, integrated stress response and oxphos. Overall, this interesting work opens a venue for further exploration of imipridones in ER+ breast cancer resistant to current first- and second-line therapies.

Reviewer #2 (Public Review):

Past systems for identifying and tracking rodent vocaliztions have relied on triangulating positions using only a few high-quality ultrasonic microphones. There are also large arrays of less sensitive microphones, called acoustic cameras that don't capture the detail of the sounds, but do more accurately locate the sound in 3D space. Therefore the key innovation here is that the authors combine these two technologies by primarily using the acoustic camera to accurately find the emitter of each vocalization, and matching it to the high-resolution audio and video recordings. They show that this strategy (HyVL) is more accurate than other methods for identifying vocalizing mice and also has greater spatial precision. They go on to use this setup to make some novel and interesting observations. The technology and the study are timely, important, and have the potential to be very useful. As machine learning approaches to behavior become more widespread in use, it is easy to imagine this being incorporated and lowering entry costs for more investigators to begin looking at rodent vocalizations. I have a few comments.

1) What is the relationship of the current manuscript to this: https://www.biorxiv.org/content/10.1101/2021.10.22.464496v1 which has a number of very similar figures and presents a SLIM-only method that reportedly has lower precision than the current HyVL approach. Is this superseded by the submitted paper?

2) Can the authors provide any data showing the accuracy of their system in localizing sounds emitted from speakers as a function of position and amplitude? I am imagining that it would be relatively easy to place multiple speakers around the arena as ground truth emitting devices to quantify the capabilities of the system.

3) How is the system's performance affected by overlapping vocalizations? It might be useful to compare the accuracy of caller identification for periods where only one animal is calling at a time vs. periods where multiple animals are simultaneously calling.

4) Can the authors comment on how sound shadows cast by animals standing between the caller and a USM4 affect either the accuracy of identification or the fidelity of the vocal recording?

5) I'm a bit confused about how the algorithm uses the information from the video camera. Reading through the methods, it seems like they primarily calculate competing location estimates by the two types of microphone data and then make sure that a mouse is in close proximity to one location, discarding the call if there isn't. Why did the authors choose this procedure rather than use the tracked position of the snouts as constrained candidate locations and use the microphone data to arbitrate between them? Do they think that their tracking data are not reliable or accurate enough?

6) I guess the authors have code that we can run, but I couldn't access it. The manuscript describes the algorithms and equations that are used to calculate the location, but this doesn't really give me a feel for how it works. If you want to have the broadest impact possible, I think you would do well to make the code user-friendly (maybe it is, I don't know). In pursuit of that goal, I would suggest that the authors devote some of the paper to a guided example of how to use it.

Reviewer #2 (Public Review):

In the present study, Castano et al. discovered a chemical inhibitor that is specifically effective against the kinase activity of CDKL5 and applied it in the in vitro and the brain slice culture to reveal the acute effects of the loss of function (LOF) of CDKL5. LOF has been modeled in gene knockout mice, but these are loss-of-function models with the added developmental time effects of the absence of CDKL5 from developmental stages. The present authors' approach is the fastest timescale study to date, examining CDKL5 LOF effects in seconds to minutes.

The authors showed that chemical inhibition of CDKL5 kinase activity suppresses postsynaptically derived LTP in rat brain slice experiments, indicating that the previously controversial results of CDKL5 LOF on LTP in knockout mice and rats are possibly due to combined effects of the loss of the kinase and compensation by other factors.

The authors employed state-of-the-art methodologies and presented their data clearly and convincingly.

Reviewer #2 (Public Review):

Schmit et al. analyze and compare different strategies for the allocation of funding for insecticide-treated nets (ITNs) to reduce the global burden of malaria. They use previously published models of Plasmodium falciparum and Plasmodium vivax malaria transmission to quantify the effect of ITN distribution on clinical malaria numbers and the population at risk. The impact of different resource allocation strategies on the reduction of malaria cases or a combination of malaria cases and achieving pre-elimination is considered to determine the optimal strategy to allocate global resources to achieve malaria eradication.

Strengths:<br /> Schmit et al. use previously published models and optimization for rigorous analysis and comparison of the global impact of different funding allocation strategies for ITN distribution. This provides evidence of the effect of three different approaches: the prioritization of high-transmission settings to reduce the disease burden, the prioritization of low-transmission settings to "shrink the malaria map", and a resource allocation proportional to the disease burden.

Weaknesses:<br /> The analysis and optimization which provide the evidence for the conclusions and are thus the central part of this manuscript necessitate some simplifying assumptions which may have important practical implications for the allocation of resources to reduce the malaria burden. For example, seasonality, mosquito species-specific properties, stochasticity in low transmission settings, and changing population sizes were not included. Other challenges to the reduction or elimination of malaria such as resistance of parasites and mosquitoes or the spread of different mosquito species as well as other beneficial interventions such as indoor residual spraying, seasonal malaria chemoprevention, vaccinations, combinations of different interventions, or setting-specific interventions were also not included. Schmit et al. clearly state these limitations throughout their manuscript.

The focus of this work is on ITN distribution strategies, other interventions are not considered. It also provides a global perspective and analysis of the specific local setting (as also noted by Schmit et al.) and different interventions as well as combinations of interventions should also be taken into account for any decisions. Nonetheless, the rigorous analysis supports the authors' conclusions and provides evidence that supports the prioritization of funding of ITNs for settings with high Plasmodium falciparum transmission. Overall, this work may contribute to making evidence-based decisions regarding the optimal prioritization of funding and resources to achieve a reduction in the malaria burden.

Reviewer #2 (Public Review):

Marmor et al. mine a previously published dataset to examine whether recent reward/stimulus history influences responses in sensory (and other) cortices. Bulk L2/3 calcium activity is imaged across all of the dorsal cortex in transgenic mice trained to discriminate between two textures in a go/no-go behavior. The authors primarily focus on comparing responses to a specific stimulus given that the preceding trial was or was not rewarded. There are clear differences in activity during stimulus presentation in the barrel cortex along with other areas, as well as differences even before the second stimulus is presented. These differences only emerge after task learning. The data are of high quality and the paper is clear and easy to follow. My only major criticism is that I am not completely convinced that the observed difference in response is not due to differences in movement by the animal on the two trial types. That said, the demonstration of differences in sensory cortices is relatively novel, as most of the existing literature on trial history effect demonstrates such differences only in higher-order areas.

Major:

1a. The claim that body movements do not account for the results is in my view the greatest weakness of the paper - if the difference in response simply reflects a difference in movement, perhaps due to "excitement" in anticipation of reward after not receiving one on CR-H vs. H-H trials, then this should show up in movement analysis. The authors do a little bit of this, but to me, more is needed.

First, given the small sample size and use of non-parametric tests, you will only get p<.05 if at least 6 of the 7 mice perform in the same way. So getting p>.05 is not surprising even if there is an underlying effect. This makes it especially important to do analyses that are likely to reveal any differences; using whisker angle and overall body movement, which is poorly explained, is in my opinion insufficient. An alternative approach would be to compare movements within animals; small as the dataset is, it is feasible to do an animal-by-animal analysis, and then one could leverage the large trial count to get much greater statistical power, foregoing summary analyses that pool over only n=7.

The authors only consider a simple parametrization of movement (correlation across successive frames), and given the high variability in movement across animals, it is likely that different mice adopt different movements during the task, perhaps altering movement in specific ways. Aggregating movement across different body parts after an analysis where body parts are treated separately seems like an odd choice - perhaps it is fine, but again, supporting evidence for this is needed. As it stands, it is not clear if real differences were averaged out by combining all body parts, or what averaging actually entails.

If at all possible, I would recommend examining curvature and not just the whisker angle, since the angle being the same is not too surprising given that the stimulus is in the same place. If the animal is pressing more vigorously on CR-H trials, this should result in larger curvature changes.

Finally, the authors presumably have access to lick data. Are reaction times shorter on CR-H trials? Is lick count or lick frequency shorter?

If movement differs across trial types, it is entirely plausible that at least barrel cortex activity differences reflect differences in sensory input due to differences in whisker position/posture/etc. This would mitigate the novelty of the present results.

1b. Given the importance of this control to the story, both whisker and body movement tracking frames should be explicitly shown either in the primary paper or as a supplement. Moreover, in the methods, please elaborate on how both whisker and body tracking were performed.

2. Did streak length impact the response? For instance, in Fig. 1f "Learning", there is a 6-trial "no-go" streak; if the data are there, it would be useful to plot CR-H responses as a function of preceding unrewarded trials.

Reviewer #2 (Public Review):

In this manuscript, Franco et al show that the mitofusin 2 mutation MFN2 Q400 impaires mitochondrial fusion with normal GTPase activity. MFN2 Q400 fails to recruit Parkin and further disrupts Parkin-mediated mitophagy in cultured cardiac cells. They also generated MFN2 Q400 knock-in mice to show the development of lethal perinatal cardiomyopathy, which had an impairment in multiple metabolic pathways.

The major strength of this manuscript is the in vitro study that provides a thorough understanding in the characteristics of the MFN2 Q400 mutant in function of MFN2, and the effect on mitochondrial function. However, the in vivo MFN2 Q/Q400 knock-in mice are more troubling given the split phenotype of MFN2 Q/Q400a vs MFN2 Q/Q400n subtypes. Their main findings towards impaired metabolism in mutant hearts fail to distinguish between the two subtypes.

While the data support the conclusion that MFN2 Q400 causes cardiomyopathy, several experiments are needed to further understand mechanism. This manuscript will likely impact the field of MFN2 mutation-related diseases and show how MFN2 mutation leads to perinatal cardiomyopathy in support of previous literature.

Reviewer #2 (Public Review):

MCM8 and MCM9 together form a hexameric DNA helicase that is involved in homologous recombination (HR) for repairing DNA double-strand breaks. The authors have previously reported on the winged-helix structure of the MCM8 (Zeng et al. BBRC, 2020) and the N-terminal structure of MCM8/9 hexametric complex (MCM8/9-NTD) (Li et al. Structure, 2021). This manuscript reports the structure of a near-complete MCM8/9 complex and the conformational change of MCM8/9-NTD in the presence of its binding protein, HROB, as well as the residues important for its helicase activity.

The presented data might potentially explain how MCM8/9 works as a helicase. However, additional studies are required to conclude this point because the presented MCM8/9 structure is not a DNA-bound form and HROB is not visible in the presented structural data. Taking into these accounts, this work will be of interest to biologists studying DNA transactions.

A strength of this paper is that the authors revealed the near-complete MCM8/9 structure with 3.66A and 5.21A for the NTD and CTD, respectively (Figure 1). Additionally, the authors discovered a conformational change in the MCM8/9-NTD when HROB was included (Figure 4) and a flexible nature of MCM8/9-CTD (Figure S6 and Movie 1).

The revised version of "Structural and mechanistic insights into the MCM8/9 helicase complex" by Weng et al. includes only very minor changes in the text and incorporates two additional supplementary figures (S8 and S11) illustrating the size of MCM8/9 mutants.

In the previous version, I raised two important concerns that required addressing. 1) The presented structures exclusively depicted the unbound forms of DNA. It is crucial to elucidate the structure of a DNA-bound form. 2) The MCM8/9 activator, HROB, was not visible in the structural data. Although HROB induced a conformational change in MCM8/9-NTD, it is essential to visualize the structure of an MCM8/9-HROB complex.

The authors neither addressed nor provided new data in response to these issues. Consequently, I maintain my initial stance and have no further comments on the revised version.

Reviewer #2 (Public Review):

The authors present an important study on the potential of small extracellular vesicle (sEV)-derived RNAs as biomarkers for the early detection of colorectal cancer (CRC) and precancerous adenoma (AA). The authors provide a detailed analysis of the RNA landscape of sEVs isolated from participants, identifying differentially expressed sEV-RNAs associated with T1a stage CRC and AA compared to normal controls. The paper further categorises these sEV-RNAs into modules and constructs a 60-gene model that successfully distinguishes CRC/AA from NC samples. The authors also validate their findings using RT-qPCR and propose an optimised classifier with high specificity and sensitivity. Additionally, the authors discuss the potential of sEV-RNAs in understanding CRC carcinogenesis and suggest that a comprehensive biomarker panel combining sEV-RNAs and proteins could be promising for identifying both early and advanced CRC patients. Overall, the study provides valuable insights into the potential clinical application of sEV-RNAs in liquid biopsy for the early detection of CRC and AA.

Major strengths:<br /> 1. Comprehensive sEV RNA profiling: The study provides a valuable dataset of the whole-transcriptomic profile of circulating sEVs, including miRNA, mRNA, and lncRNA. This approach adds to the understanding of sEV-RNAs' role in CRC carcinogenesis and facilitates the discovery of potential biomarkers.

2. Detection of early-stage CRC and AA: The developed 60-gene t-SNE model successfully differentiated T1a stage CRC/AA from normal controls with high specificity and sensitivity, indicating the potential of sEV-RNAs as diagnostic markers for early-stage colorectal lesions.

3. Independent validation cohort: The study combines RNA-seq, RT-qPCR, and modelling algorithms to select and validate candidate sEV-RNAs, maximising the performance of the developed RNA signature. The comparison of different algorithms and consideration of other factors enhance the robustness of the findings.

Major weaknesses:<br /> 1. Lack of analysis on T1-only patients in the validation cohort: While the study identifies key sEV-RNAs associated with T1a stage CRC and AA, the validation cohort is only half of the patients in T1(25 out of 49). It would be better to do an analysis using only the T1 patients in the validation cohort, so the conclusion is not affected by the T2-T3 patients.

2. Lack of performance analysis across different demographic and tumor pathology factors listed in Supplementary Table 12. It's important to know if the sEV-RNAs identified in the study work better/worse in different age/sex/tumor size/Yamada subtypes etc.

Reviewer #2 (Public Review):

In this study, the authors identified the complex TOR, HOG, and CWI signaling networks-involved genes that relatively modulate the development, aflatoxin biosynthesis and pathogenicity of A. flavus by gene deletions combined with phenotypic observation.

They also analyzed the specific regulatory process and proposed that the TOR signaling pathway interacts with other signaling pathways (MAPK, CWI, calcineurin-CrzA pathway) to regulate the responses to various environmental stresses. Notably, they found that FKBP3 is involved in sclerotia and aflatoxin biosynthesis and rapamycin resistance in A. flavus, and that the conserved site K19 of FKBP3 plays a key role in regulating the aflatoxin biosynthesis. In general, there is a heavy workload task carried in this study and the findings are interesting and important for understanding or controlling aflatoxin biosynthesis. However, findings have not been deeply explored and conclusions mostly are based on parallel phenotypic observations. In addition, there are some concerns that exist surrounding the conclusions.

Reviewer #2 (Public Review):

This study by Syed et al identifies Prmt5 as a novel and broad modulator of gene expression and genome architecture during the early stages of adipogenesis. Specifically, Prmt5 is reported to be required to maintain strong insulation at TAD boundaries.

This is a logically and clearly conducted study that relies on the integration of public datasets (PCHi-C) to identify chromatin loops, with its own new genomics datasets, including Prmt5 ChIPseq and Hi-C data in control and Prmt5 kd cells. Despite showing relatively model effects of Prmt5 kd on genome architecture, the results are informative and contribute to advancing our knowledge of chromatin-linked processes during early adipogenesis.

The manuscript would benefit from incorporating ATACseq data (public or own) to better appreciate binding profiles of Prmt5 at H3K27ac sites. A more detailed analysis of these relative enrichments would also be useful, particularly if linked to a transcription factor footprint from ATAC data.

Reviewer #2 (Public Review):

The Kinesin superfamily motors mediate the transport of a wide variety of cargos which are crucial for cells to develop into unique shapes and polarities. Kinesin-3 subfamily motors are among the most conserved and critical classes of kinesin motors which were shown to be self-inhibited in a monomeric state and dimerized to activate motility along microtubules. Recent studies have shown that different members of this family are uniquely activated to undergo a transition from monomers to dimers.

Niwa and colleagues study two well-described members of the kinesin-3 superfamily, unc104 and KLP6, to uncover the mechanism of monomer to dimer transition upon activation. Their studies reveal that although both Unc104 and KLP6 are both self-inhibited monomers, their propensities for forming dimers are quite different. The authors relate this difference to a region in the molecules called CC2 which has a higher propensity for forming homodimers. Unc104 readily forms homodimers if its self-inhibited state is disabled while KLP6 does not.

The work suggests that although mechanisms for self-inhibited monomeric states are similar, variations in the kinesin-3 dimerization may present a unique form of kinesin-3 motor regulation with implications on the forms of motility functions carried out by these unique kinesin-3 motors.

Reviewer #2 (Public Review):

Yu et al. investigated the structural landscape of 'secreted in xylem' (SIX) effector (virulence and avirulence) proteins from the plant-pathogenic fungus, Fusarium oxysporum f. sp. lycopersici (Fol), with the goal of better understanding effector function and recognition by host (tomato) immune receptors. In recent years, several experimental and computational studies have shown that many effector proteins of plant-associated fungi can be assigned to one of a few major structural families. In the study by Yu et al., X-ray crystallography was used to show that two avirulence effectors of Fol, Avr1 (SIX4) and Avr3 (SIX1), which are recognized by the tomato immune receptors I and I-3, respectively, form part of a new structural family, the Fol dual-domain (FOLD) family, found across three fungal divisions. Using AlphaFold2, an ab initio structural prediction tool, the authors then predicted the structures of all proteins within the Fol SIX effector repertoire (and other effector candidates) and provided evidence that two other effectors, SIX6 and SIX13, also belong to this family.

In addition to identifying members of the FOLD family, structural prediction revealed that proteins of the Fol effector repertoire can largely be classified into a reduced set of structural families. Examples included four members of the ToxA-like family (including Avr2 (SIX3) and SIX8), as well as four members of a new family, Family 4 (including SIX5 and PSL1). Given previous studies had demonstrated that Avr2 (ToxA-like) and SIX5 (Family 4) interact and function together and that the genes encoding these proteins are divergently transcribed, and because homologues of SIX8 (ToxA-like) and PSL1 (Family 4) from another Fusarium pathogen are functionally dependent on each other and, in the case of Fol, are encoded by genes that are next to each other in the genome, the authors hypothesized that SIX8 and PSL1 may also physically interact. In line with this, co-incubation of the SIX8 and PSL1 proteins, followed by size exclusion chromatography (SEC), gave elution and gel migration profiles consistent with interaction in the form of a heterodimer. AlphaFold2-Multimer modelling then suggested that this interaction was mediated through an intermolecular disulfide bond. Such a prediction was subsequently confirmed through mutational analysis of the relevant cysteine residue in each protein in conjunction with SEC.

Finally, using a variant (homologue) of Avr1 from another Fusarium pathogen, as well as chimeric forms of this protein that integrated regions of Avr1 from Fol, Yu et al. determined through co-expression assays in Nicotiana benthamiana with the I immune receptor, as well as subsequent ion leakage assays, that the C-domain of Avr1 is recognized by the I immune receptor. Furthermore, through these assays, the authors were also able to show that surface-exposed residues in the C-domain enable Avr1 to evade recognition by a variant of the I receptor in Moneymaker tomato that does not provide resistance to Fol.

Overall, the manuscript presents a large body of work that is well supported by the data. A key strength of the manuscript is the validation (benchmarking) of protein structures predicted using AlphaFold2, which is a first for largescale effector structure prediction papers published to date. Another key strength is the use of largescale effector structure predictions to make hypotheses about functional relationships or interactions that are then tested (i.e. the SIX8-PSL1 protein interaction and recognition of Avr1 by the I immune receptor). This testing again goes above and beyond the large scale effector structure prediction papers published to date. Taken together, this showcases how experimental and computational experiments can be effectively combined to provide biologically relevant data for the plant protection and molecular plant-microbe interactions fields.

In terms of weaknesses, the manuscript could have validated the SIX8-PSL1 protein interaction with in planta experiments, such as co-immunoprecipitation assays or co-localization experiments in conjunction with confocal microscopy, to provide support for the interaction in a plant setting. However, given what is already known about the Avr2-SIX5 interaction, these additional experiments are not crucial and could instead form part of a follow-up study. With regards to the Agrobacterium tumefaciens-mediated transient expression assays involving co-expression of the Avr1 effector and I immune receptor, the authors need to make clear how many biological replicates were performed as this information is only provided for the ion leakage assay.

Reviewer #2 (Public Review):

In this manuscript, the authors address how cerebellar Purkinje cells (PC) control the firing of nuclear cells (CbN), the output stage of the cerebellar. They used patch-clamp recordings in acute cerebellar slices, and combined dynamic clamp with simulations of nuclear cell firing rate.

This article addresses one of the most fundamental unresolved question of the cerebellar physiology: how inhibitory PCs control the output stage of the cerebellum?<br /> They first described a developmental evolution of the that PC-CbN synapses. Inhibitory synaptic weights become highly variable after three weeks of age, with a group of very large PC inputs. They used dynamic clamp to examine the influence of these variable inputs on CbN firing rate. They demonstrate that while all input size affect CbN discharge, larger ones can stop them for a few milliseconds. Using a distribution of variable input size, they showed that increasing the variability of PC inputs favor CbN discharge, while increasing the magnitude of a constant inhibitory conductance decrease their firing rate. By varying the frequency of PC inputs, they suggest that CbNs faithfully transmit rate code, but larger inputs are more effective to decrease their firing rate. Finally, addressing how synchrony of variable PC inputs influence CbN discharge, dynamic clamp studies and simulations showed that input synchronization enhance firing, but driven by the total charge of the inhibitory input.

The keystone observations that PC inputs are highly variable is very interesting and convincing and open new questions about PC-CbN plasticity. More importantly the combination of dynamic clamp and simulations is a real strength of the study, allowing the authors to test many combinations of inputs in real cells and extrapolating their hypotheses in silico. Weaknesses result from the assumptions made on the construction of the distribution of inputs and the many different conditions explored. The organization of the article could be difficult to read for a non-specialist of cerebellar physiology.

Reviewer #2 (Public Review):

The authors of this paper use a "digital twin" computational model of electrophysiology to investigate the pathology of Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC) in several patients undergoing Electro-Physiological Studies (EPS) to treat Ventricular Tachycardias (VTs). The digital twin computational models are customised to the individual patient in two ways. Firstly, information on the patient's heart geometry and muscle/fibrous structure is extracted from Late Gadolium-Enhanced Magnetic Resonance Image (LGE-MRI) scans. Secondly, information from the patient's genotype is used to decide the particular electrophysiological cell model to use in the computational model. The two patient genotypes investigated include a Gene Ellusive (GE) group characterised by abnormal fibrous but normal cell electrical physiology and a palakophilin-2 (PKP2) group in which patients have abnormal fibrotic remodelling and distorted electrical conduction. The computational model predicts the locations and pathways of re-entrant circuits that cause VT. The model results are compared to previous recordings of induced VTs obtained from EPS studies.

The paper is very well written, and the modelling study is well thought out and thorough and represents an exemplar in the field. The major strengths of the paper are the use of a personalised patient model (geometry, fibrous structure and genotype) in a clinically relevant setting. Such a comprehensive personal model puts this paper at the forefront of such models in the field. The main weaknesses of the paper are more of a reflection on what is required for creating such models than on the study itself. As the authors acknowledge, the number of patients in each group is small. Additional patients would allow for statistical significance to be investigated.

The paper's authors set out to demonstrate the use of a "digital twin" computational model in the clinical setting of ARVC. The main findings of the paper were threefold. Firstly, the locations of VTs could be accurately predicted. There was a difference in the abnormal fibrous structure between the two genotype groups. Finally, there was an interplay between the fibrous structure of the heart and the cellular electrophysiology in that the fibrous remodelling was responsible for VTs in the GE group, but in the PKP2 group VTs were caused by slowed electrical conduction and altered restitution. The study successfully met the aims of the paper.

The major impact of the paper will be in demonstrating that a personalised computational model can a) be developed from available measurements (albeit at the high end of what would normally be measured clinically) and b) generate accurate results that may prove helpful in a clinical setting. Another impact is the finding in the paper that the cause of VTs may be different for the two genotypes investigated. The different interplay between fibrous and electrophysiology suggested by the modelling results may provide insights into different treatments for the different genotypes of the pathology. The authors use open-source software and have deposited all non-confidential data in publically available repositories.

Reviewer #2 (Public Review):

The mechanisms that mediate female aggression remain poorly understood. Chiu, Schretter, and colleagues, employed circuit dissection techniques to tease apart the specific roles of particular doublesex and fruitless expressing neurons in the fly Drosophila in generating a persistent aggressive state. They find that activating the fruitless positive alPg neurons, generated an aggressive state that persisted for >10min after the stimulation ended. Similarly, activating the doublesex positive pC1de neurons also generated a persistent state. Activating pC1d or pC1e individually did not induce a persistent state. Interestingly, while neural activation of alPGs and pC1d+e neurons induced persistent behavioural states it did not induce persistent activity in the neurons being activated.

The conclusions of this paper are well supported by the data, there were only a few points where clarification might help:

1) Figure 3 is a little confusing. This is a circuit behavioural epistasis experiment where the authors activate alPg with CsChrimson while inhibiting pC1d with Kir2.1. In Fig. 2 flies were separated for 10 min following stimulation which allowed for identification of a persistent state. However, in Fig 3 it appears as if flies were allowed to freely interact during and immediately post-stimulation. It is unclear why flies were not separated as in Fig. 2, which makes it difficult to compare the two results. Some discussion of this point would help. Also, from the rasters it appears as if inhibition of pC1d reduced aggression induced by alPg during the stimulation period. Is this true?

2) pC1e neurons also have recurrent connectivity with alPg neurons. It might help to also discuss the potential role of this arm of the microcircuit.

Reviewer #2 (Public Review):

Clark and Nolan's study aims to test whether the stability of grid cell firing fields is associated with better spatial behavior performance on a virtual task. Mice were trained to stop at a rewarded location along a virtual linear track. The rewarded location could be marked by distinct visual stimuli or be unmarked. When the rewarded location was unmarked, the animal had to estimate its distance run from the beginning of the trial to know where to stop. When the mouse reached the end of the virtual track, it was teleported back to the start of the virtual track.

The authors found that grid cells could fire in at least two modes. In the "virtual position" mode, grid firing fields had stable positions relative to the virtual track. In the "distance run" mode, grid fields were decoupled from the virtual cues and appeared to be located as a function of distance run on the running wheel. Importantly, on trials in which the rewarded location was unmarked, the behavioral performance of mice was better when grid cells fired in the "virtual position" mode.

This study is very timely as there is a pressing need to identify/delimitate the contribution of grid cells to spatial behaviors. More studies in which grid cell activity can be associated with navigational abilities are needed. The link proposed by Clark and Nolan between "virtual position" coding by grid cells and navigational performance is a significant step toward better understanding how grid cell activity might support behavior. It should be noted that the study by Clark and Nolan is correlative. Therefore, the effect of selective manipulations of grid cell activity on the virtual task will be needed to evaluate whether the activity of grid cells is causally linked to the behavioral performance on this task. In a previous study by the same research group, it was shown that inactivating the synaptic output of stellate cells of the medial entorhinal cortex affected mice's performance of the same virtual task (Tennant et al., 2018). Although this manipulation likely affects non-grid cells, it is still one of the most selective manipulations of grid cells that are currently available.

When interpreting the "position" and "distance" firing mode of grid cells, it is important to appreciate that the "position" code likely involves estimating distance. The visual cues on the virtual track appear to provide mainly optic flow to the animal. Thus, the animal has to estimate its position on the virtual track by estimating the distance run from the beginning of the track (or any other point in the virtual world).

It is also interesting to consider how grid cells could remain anchored to virtual cues. Recent work shows that grid cell activity spans the surface of a torus (Gardner et al., 2022). A run on the track can be mapped to a trajectory on the torus. Assuming that grid cell activity is updated primarily from self-motion cues on the track and that the grid cell period is unlikely to be an integer of the virtual track length, having stable firing fields on the virtual track likely requires a resetting mechanism taking place on each trial. The resetting means that a specific virtual track position is mapped to a constant position on the torus. Thus, the "virtual position" mode of grid cells may involve 1) a trial-by-trial resetting process anchoring the grid pattern to the virtual cues and 2) a path integration mechanism. Just like the "virtual position" mode of grid cell activity, successful behavioral performance on non-beaconed trials requires the animal to anchor its spatial behavior to VR cues.

One main conclusion of this study is that better performance on the VR task was observed when the grid cells were anchored to the reference frame that was the most behaviorally relevant.

Reviewer #2 (Public Review):

Schwarz et al. have presented a study aiming to investigate whether circulating factors in sera of subjects are able to synchronize depending on age, circadian rhythms of fibroblast. The authors used human serum taken from either old (age 70-76) or young (age 25-30) individuals to synchronise cultured fibroblasts containing a clock gene promoter driven luciferase reporter, followed by RNA sequencing to investigate whole gene expression.

This study has the potential to be very interesting, as evidence of circulating factors in sera that mediate peripheral rhythms has long been sought after. Moreover, the possibility that those factors are affected by age which could contribute to the weaken circadian rhythmicity observed with aging.

Here, the authors concluded that both old and young sera are equally competent at driving robust 24 hour oscillations, in particular for clock genes, although the cycling behaviour and nature of different genes is altered between the two groups, which is attributed to the age of the individuals. This conclusion could however be influenced by individual variabilities within and between the two age groups. The groups are relatively small, only four individual two females and two males, per group. And in addition, factors such as food intake and exercise prior to blood drawn, or/and chronotype, known to affect systemic signals, are not taken into consideration. As seen in figure 4, traces from different individuals vary heavily in terms of their patterns, which is not addressed in the text. Only analysing the summary average curve of the entire group may be masking the true data. More focus should be attributed to investigating the effects of serum from each individual and observing common patterns. Additionally, there are many potential causes of variability, instead or in addition to age, that may be contributing to the variation both, between the groups and between individuals within groups. All of this should be addressed by the authors and commented appropriately in the text.

The authors also note in the introduction that rhythms in different peripheral tissues vary in different ways with age, however the entire study is performed on only fibroblast, classified as peripheral tissue by the authors. It would be very interesting to investigate if the observed changes in fibroblast are extended or not to other cell lines from diverse organ origin. This could provide information about whether circulating circadian synchronising factors could exert their function systemically or on specific tissues. At the very least, this hypothesis should be addressed within the discussion.

In addition to the limitations indicated above I consider that the data of the study is an insufficiently analysis beyond the rhythmicity analysis. Results from the STRING and IPA analysis were merely descriptive and a more comprehensive bioinformatic analysis would provide additional information about potential molecular mechanism explaining the differential gene expression. For example, enrichment of transcription factors binding sites in those genes with different patters to pinpoint chromatin regulatory pathways.

Reviewer #2 (Public Review):

The authors investigate the transcriptional regulation of cysteine dioxygenase (CDO-1) in C. elegans and its role in maintaining cysteine homeostasis. They show that high cysteine levels activate cdo-1 transcription through the hypoxia-inducible transcription factor HIF-1. Using transcriptional and translational reporters for CDO-1, the authors propose a negative feedback pathway involving RHY-1, CYSL-1, EGL-9, and HIF-1 in regulating cysteine homeostasis.

Genetics is a notable strength of this study. The forward genetic screen, gene interaction, and epistasis analyses are beautifully designed and rigorously conducted, yielding solid and unambiguous conclusions on the genetic pathway regulating CDO-1. The writing is clear and accessible, contributing to the overall high quality of the manuscript.

Addressing the specifics of cysteine supplementation and interpretation regarding the cysteine homeostasis pathway would further clarify the paper and strengthen the study's conclusions.

First, the authors show that the supplementation of exogenous cysteine activates cdo-1p::GFP. Rather than showing data for one dose, the author may consider presenting dose-dependency results and whether cysteine activation of cdo-1 also requires HIF-1 or CYSL-1, which would be important data given the focus and major novelty of the paper in cysteine homeostasis, not the cdo-1 regulatory gene pathway. While the genetic manipulation of cdo-1 regulators yields much more striking results, the effect size of exogenous cysteine is rather small. Does this reflect a lack of extensive condition optimization or robust buffering of exogenous/dietary cysteine? Would genetic manipulation to alter intracellular cysteine or its precursors yield similar or stronger effect sizes?

Second, there remain several major questions regarding the interpretation of the cysteine homeostasis pathway. How much specificity is involved for the RHY-1/CYSL-1/EGL-9/HIF-1 pathway to control cysteine homeostasis? Is the pathway able to sense cysteine directly or indirectly through its metabolites or redox status in general? Given the very low and high physiological concentrations of intracellular cysteine and glutathione (GSH, a major reserve for cysteine), respectively, there is a surprising lack of mention and testing of GSH metabolism. In addition, what are the major similarities and differences of cysteine homeostasis pathways between C. elegans and other systems (HIF dependency, transcription vs post-transcriptional control)? These questions could be better discussed and noted with novel findings of the current study that are likely C. elegans specific or broadly conserved.

Reviewer #2 (Public Review):

In this paper Sasani, Quinlan and Harris present a new method for identifying genetic factors affecting germline mutation, which is particularly applicable to genome sequence data from mutation accumulation experiments using recombinant inbred lines. These are experiments where laboratory organisms are crossed and repeatedly inbred for many generations, to build up a substantial number of identifiable germline mutations. The authors apply their method to such data from mice, and identify two genetic factors at two separate genetic loci. Clear evidence of such factors has been difficult to obtain, so this is an important finding. They further show evidence of an epistatic interaction between these factors (meaning that they do not act independently in their effects on the germline mutation process). This is exciting because such interactions are difficult to detect and few if any other examples have been studied.

The authors present a careful comparison of their method to another similar approach, quantitative trait locus (QTL) analysis, and demonstrate that in situations such as the one analysed it has greater power to detect genetic factors with a certain magnitude of effect. They also test the statistical properties of their method using simulated data and permutation tests. Overall the analysis is rigorous and well motivated, and the methods explained clearly.

The main limitation of the approach is that it is difficult to see how it might be applied beyond the context of mutation accumulation experiments using recombinant inbred lines. This is because the signal it detects, and hence its power, is based on the number of extra accumulated mutations linked to (i.e. on the same chromosome as) the mutator allele. In germline mutation studies of wild populations the number of generations involved (and hence the total number of mutations) is typically small, or else the mutator allele becomes unlinked from the mutations it has caused (due to recombination), or is lost from the population altogether (due to chance or perhaps selection against its deleterious consequences).

Nevertheless, accumulation lines are a common and well established experimental approach to studying mutation processes in many organisms, so the new method could have wide application and impact on our understanding of this fundamental biological process.

The evidence presented for an epistatic interaction is convincing, and the authors suggest some plausible potential mechanisms for how this interaction might arise, involving the DNA repair machinery and based on previous studies of the proteins implicated. However as with all such findings, given the higher degree of complexity of the proposed model it needs to be treated with greater caution, perhaps until replicated in a separate dataset or demonstrated in follow-up experiments exploring the pathway itself.

Reviewer #2 (Public Review):

Qin, Sanbo and Zhou, Huan-Xiang created a model, SeqDYN, to predict nuclear magnetic resonance (NMR) spin relaxation spectra of intrinsically disordered proteins (IDPs), based primarily on amino acid sequence. To fit NMR data, SeqDYN uses 21 parameters, 20 that correspond to each amino acid, and a sequence correlation length for interactions. The model demonstrates that local sequence features impact the dynamics of the IDP, as SeqDYN performs better than a one residue predictor, despite having similar numbers of parameters. SeqDYN is trained using 45 IDP sequences and is retrained using both leave-one-out cross validation and five-fold cross validation, ensuring the model's robustness. While SeqDYN can provide reasonably accurate predictions in many cases, the authors note that improvements can be made by incorporating secondary structure predictions, especially for alpha-helices that exceed the correlation length of the model. The authors apply SeqDYN to study nine IDPs and a denatured ordered protein, demonstrating its predictive power. The model can be easily accessed via the website mentioned in the text.

While the conclusions of the paper are primarily supported by the data, there are some points that could be extended or clarified.

1. The authors state that the model includes 21 parameters. However, they exclude a free parameter that acts as a scaling factor and is necessary to fit the experimental data (lambda). As a result, SeqDYN does not predict the spectrum from the sequence de-novo, but requires a one parameter fitting. The authors mention that this factor is necessary due to non-sequence dependent factors such as the temperature and magnetic field strength used in the experiment. Given these considerations, would it be possible to predict what this scaling factor should be based on such factors?

2. The authors mention that the Lorentzian functional form fits the data better than a Gaussian functional form, but do not present these results.

3. The authors mention that they conducted five-fold cross validation to determine if differences between amino acid parameters are statistically significant. While two pairs are mentioned in the text, there are 190 possible pairs, and it would be informative to more rigorously examine the differences between all such pairs.

Reviewer #2 (Public Review):

Jarysta and colleagues set out to define how similar GNAI/O family members contribute to the shape and orientation of stereocilia bundles on auditory hair cells. Previous work demonstrated that loss of particular GNAI proteins, or inhibition of GNAIs by pertussis toxin, caused several defects in hair bundle morphogenesis, but open questions remained which the authors sought to address. Some of these questions include whether all phenotypes resulting from expression of pertussis toxin stemmed from GNAI inhibition; which GNAI family members are most critical for directing bundle development; whether GNAI proteins are needed for basal body movements that contribute to bundle patterning. These questions are important for understanding how tissue is patterned in response to planar cell polarity cues.

To address questions related to the GNAI family in auditory hair cell development, the authors assembled an impressive and nearly comprehensive collection of mouse models. This approach allowed for each Gnai and Gnao gene to be knocked out individually or in combination with each other. Notably, a new floxed allele was generated for Gnai3 because loss of this gene in combination with Gnai2 deletion was known to be embryonic lethal. Besides these lines, a new knockin mouse was made to conditionally express untagged pertussis toxin following cre induction from a strong promoter. The breadth and complexity involved in generating and collecting these strains makes this study unique, and likely the authoritative last word on which GNAI proteins are needed for which aspect of auditory hair bundle development.

Appropriate methods were employed by the authors to characterize auditory hair bundle morphology in each mouse line. Conclusions were carefully drawn from the data and largely based on excellent quantitative analysis. The main conclusions are that GNAI3 has the largest effect on hair bundle development. GNAI2 can compensate for GNAI3 loss in early development but incompletely in late development. The Gnai2 Gnai3 double mutant recapitulates nearly all the phenotypic effects associated with pertussis toxin expression and also reveals a role for GNAIs in early movement of the basal body. Although these results are not entirely unexpected based on earlier reports, the current results both uncover new functions and put putative functions on more solid ground.

Based on this study, loss of GNAI1 and GNAO show a slight shortening of the tallest row of stereocilia but no other significant changes to bundle shape. Antibody staining shows no change in GNAI localization in the Gnai1 knockout, suggesting that little to no protein is found in hair cells. One caveat to this interpretation is that the antibody, while proposed to cross-react with GNAI1, is not clearly shown to immunolabel GNAI1. More than anything, this reservation mostly serves to illustrate how challenging it is to nail down every last detail. In turn, the comprehensive nature of the current study seems all the more impressive.

Reviewer #2 (Public Review):

Aw et al presents a new stability-guided fine-mapping method by extending the previously proposed PICS method. They applied their stability-based method to fine-map cis-eQTLs in the GEUVADIS dataset and compared it against what they call residualization-based method. They evaluated the performance of the proposed method using publicly available functional annotations and claimed the variants identified by their proposed stability-based method are more enriched for these functional annotations.

While the reviewer acknowledges the contribution of the present work, there are a couple of major concerns as described below.

Major:

1. It is critical to evaluate the proposed method in simulation settings, where we know which variants are truly causal. While I acknowledge their empirical approach using the functional annotations, a more unbiased, comprehensive evaluation in simulations would be necessary to assess its performance against the existing methods.

2. Also, simulations would be required to assess how the method is sensitive to different parameters, e.g., LD threshold, resampling number, or number of potential sets.

3. Given the previous studies have identified multiple putative causal variants in both GWAS and eQTL, I think it's better to model multiple causal variants in any modern fine-mapping methods. At least, a simulation to assess its impact would be appreciated.

4. Relatedly, I wonder what fraction of non-matching variants are due to the lack of multiple causal variant modeling.

5. I wonder if you can combine the stability-based and the residualization-based approach, i.e., using the residualized phenotypes for the stability-based approach. Would that further improve the accuracy or not?

6. The authors state that confounding in cohorts with diverse ancestries poses potential difficulties in identifying the correct causal variants. However, I don't see that they directly address whether the stability approach is mitigating this. It is hard to say whether the stability approach is helping beyond what simpler post-hoc QC (e.g., thresholding) can do.

7. For non-matching variants, I wonder what the difference of posterior probabilities is between the stable and top variants in each method. If the difference is small, maybe it is due to noise rather than signal.

8. It's a bit surprising that you observed matching variants with (stable) posterior probability ~ 0 (SFig. 1). What are the interpretations for these variants? Do you observe functional enrichment even for low posterior probability matching variants?

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Reviewer #2 (Public Review):

This manuscript reports on an important study that aims to identify symptom trajectories for the early detection of pancreatic cancer. The study's findings are based on the analysis of two complementary data sources: structured data obtained from the Danish National Patient Registry and unstructured information extracted from the free-text sections of patient notes. The researchers successfully identified various symptoms and disease trajectories that are strongly associated with pancreatic cancer, with compelling evidence from both data sources. Additionally, the study provides a detailed comparison and contrast of the results obtained from each data source, adding valuable insights into the strengths and limitations of each method.

Strengths:

The work is well motivated by the urgent need for early detection of pancreatic cancer, which is often difficult due to the lack of effective (computational) methods. The manuscript is generally well-written and includes relevant studies, providing a comprehensive overview of the current state of the field.

One of the unique contributions of this work is its use of both structured registry data and unstructured clinical notes to leverage complementary information. This approach enables a more nuanced and comprehensive understanding of the disease symptom trajectories, which is critical for improving early disease diagnosis and prognosis.

The methodology employed in this study is sound and robust, and the authors have candidly discussed its limitations. The results are significant and highlight previously unknown insights into symptom disease trajectories, which have important implications for the management of pancreatic cancer.

Overall, this is a well-designed and executed study that makes an important contribution to the field of cancer/informatics research, and it should be of great interest to both researchers and clinicians.

Weaknesses:

To complement the results in Figure 1, I'd also suggest that the authors compile a list of the most common (known) symptoms of pancreatic cancer as a reference. In other words, not only can you compare results found from the two sources but also compare them with existing knowledge. This is something you discussed partly in lines 245 but including this early as part of the results in Figure 1 would be more informative.

In terms of the text mining evaluation results, providing information on recall errors would be beneficial to better understand the performance of the method. Additionally, line 144 mentions 53 words, but it is still not clear to me what these words refer to. Could you please clarify this point or provide more context?

The disparities between Figure 2A and 2B are noteworthy, from very different initial symptoms to the proportion of short median survival dates (<=90 days), with much more pronounced differences than those observed in Figure 1 comparing two data sources. The highlighted trajectories are almost completely different. Should this be expected? I was hoping to see at least some overlap between the two results.

All trajectories shown in Figure 2 include three symptoms. Is this by design? Could there be meaningful trajectories with different numbers of symptoms (e.g. 4 or more)?

Considering those patients with both clinical notes and registry data, it may be beneficial to merge their symptoms to generate more informative trajectories.

Given that results from two sources are being compared in Figures 1 and 2, have you considered calculating the top 20 most significant symptoms from the registry data as well?

While there is a discussion related to cardiovascular diseases, I noticed no mention of cataracts or gonarthrosis, which were found to be prevalent among patients with short survival in Figure 2.

Ultimately, the goal of this research is to improve the early detection and prognosis of pancreatic cancer, thus it is important to discuss how the findings of this work could be applied in practice towards this goal (e.g. used by disease prediction algorithms?)

Reviewer #2 (Public Review):

The manuscript "Nation-wide mammography screening participation in Denmark during the COVID-19 pandemic: An observational study" aims at assessing the impact of COVID-19 on the participation to the breast cancer national screening program in Denmark.

Using a cohort of almost one million women, the authors used ageneralised linear model to estimate the prevalence ratios of participation to the screening program within 3, 6, and 12 months since the start of the pandemic.

The high quality of the data used represents the strongest point of the study, which provided a strong, reliable basis on which conduct the analysis. Some limitations are related to the way the date of invitation (to the screening program) is handled, the vaccination status of the cohort of interest (information not available) and the transferability of the study to other countries, for different countries handled the pandemic in different ways.

The authors show that there was an overall slight decrease in screening participation despite the screening program remained open throughout the pandemic and discuss likely reasons of why that may have happened. Further, they identified that groups of women who were already characterised by low participation rates, experienced a further reduction in attending screening. Those were mostly composed by immigrants and low income individuals. They also discuss the barrier that language may have posed in relation to the distribution of guidelines form the government, as those were delivered in Danish.

In conclusion, the study indicates that social iniquity, which usually relates to disparity in screening participation, has been slightly exacerbated during the pandemic. Although the authors do not discuss in detail what the consequences of those findings can be, it would be interesting to assess (through a follow-up study) whether they will have an impact on the cancer incidence and, in particular, the staging of cancers at detection for the interested groups.

Reviewer #2 (Public Review):

In this work, Herron et al. investigated the impact of mTORC1 and CFIm on the expression of the Trim9/TRIM9 isoforms in both mouse and human. They extend upon their cTAG-PAPERCLIP method and demonstrated that systemic AAV injection of cell type-specific Cre recombinases to cTag-PABP mice is a feasible method of APA profiling. From this they show that mTORC1 hyperactivation promotes a shift towards the long Trim9 isoform, Trim9-L. They further provide evidence that the mTORC1 signalling pathway controls Trim9/TRIM9 isoform usage in both human and mouse with high mTORC1 promoting usage of the long isoform and low mTORC1 favouring the short isoform. They also show that the CFIm subunits CPSF6 and NUDT21 play a crucial role in the use of the TRIM9-S/Trim9-S isoform and demonstrate the importance of a twin UGUA motif in this PAS for its regulation by CPSF6. Additionally, they find that this twin UGUA motif is functionally present in the human BMPR1B, MOB4 and BRD4 genes and that insertion of the twin UGUA motif into a heterologous PAS is enough to confer regulation by both CPSF6 and mTORC1. Critically, the position of the twin UGUA motif directs preferential cleavage and polyadenylation to generate an isoform, such that it's presence can result in the use of a short isoform (TRIM9) or a long isoform (BMPR1B, MOB4 and BRD4). The work expands upon the known cis-regulatory motifs for CPSF6 and provides further evidence of a connection between the mTORC1 signalling pathway and CPSF6-mediated alternative polyadenylation. The mechanistic connection between TORC1 signalling and CPSF6 function is, however, still opaque. An experiment probing the connection between TORC1 signalling and the nuclear-cytoplasmic shuttling of CPSF6 with its activity (regulating APA) would significantly strengthen the study. Most conclusions are well supported by the presented data.

Reviewer #2 (Public Review):

Hoang, Tsutsumi et al provide a comprehensive functional mapping of cerebellar climbing fiber responses in Lobule Crus II. The study derives from analysis of a dataset originally published in Tsutsumi et al eLife 2019, using two photon Ca2+ imaging throughout the learning of a Go/No-go reward-driven licking behavior. Each recording session yielded data from a ~two-hundred micron patch of tissue, with neurons spatially localized relative the "zebrin" banding pattern of the cerebellar cortex as reported by an aldolaceC-tdTomato transgenic line. In the present work, complex spike times were extracted at higher temporal resolution using subframe raster line-scan timing information, and then decomposed at the trial-averaged population level using tensor component analysis.

The central conclusion is that the entirety of crus II climbing fiber responses decomposes into just a few patterns that capture key features of the behavior. Some of these patterns strengthen with learning, i.e., feature climbing fiber spiking that increases in frequency, while others decay with learning, i.e., feature climbing fiber responses that are prominent only in novice animals. These different climbing fiber activity components are in some cases associated with either positive or negative aldolace-C compartments of crus II. Finally, synchronization is concentrated among cells contributing to the same tensor components, and synchrony levels increase or decrease for different components over learning.

The analysis therefore suggests that distinct principles of climbing fiber function can be present simultaneously in distinct cerebellar modules (and, according to the TCA cell weightings, potentially simultaneously in individual climbing fibers). This conclusion is contrary to the implied dichotomy in the literature that climbing fibers either function as "error signals" or as "timing signals" in a particular behavioral context or cerebellar region. The authors speculate that resolution of this dichotomy could result from the biophysics of the inferior olive, in which flexibly coupled oscillators might self-organize into a low dimensional decomposition of task dynamics. Relatedly, the authors speculate that changes in synchronization that contrast between different components could serve to either regulate instructive signal dimensionality or climbing fiber timing functions, depending on each component's functional contribution. From a theoretical standpoint, this is a helpful new direction. The framework is more agnostic to the details of the activity profiles of any specific group of climbing fibers, but more attuned to the systems-level distribution of activity profiles and how these might collectively serve a behavior.

A valuable feature of the study is the simultaneous analysis of many imaging fields spanning 17 subjects and the entire dorsal surface of crus II. This bypasses some of the recurring interpretational issues with climbing fiber recordings that stem from their spatial organization across the cerebellar surface with often abrupt transitions at compartmental boundaries. By decomposing responses across many compartments simultaneously (at the trial-averaged level), the authors provide a quantitative estimate of the diversity of response patterns and their distribution across space and cells. It's worth noting that this approach is also a double-edged sword, as the trial-averaged decomposition does not depend on single-trial correlations between neurons, thus strictly speaking leaving it an open question whether apparently similar climbing fiber patterns present in distant imaging fields exhibit correlated variability either across trials or across learning.

The data convincingly show that several dominant tensor components explain a large amount of climbing fiber variance across crus II. The authors speculate that this reflects an olivary decomposition of task dynamics. Due to the nature of the analysis - TCA applied over an entire dataset - there is not a clear test of this hypothesis in the present manuscript.

The authors also present the interesting and compelling result that different CF response patterns undergo opposite learned changes in synchronization. They speculate that different trajectories of synchronization, specifically, increases for TC1 (hit) and decreases for TC2 (false alarm), could reflect different functional uses of TC1 and TC2, although it is difficult to assess the likelihood of this being true based on the data and analyses presented.

Reviewer #2 (Public Review):

In this study, the authors set out to investigate factors that have been neglected in existing mathematical models for the paradoxical activation (PA) of RAF by pharmacological inhibitors. The PA phenomenon is well known and is thought to be an important factor in limiting the effectiveness of RAF inhibitors. The authors primarily use mathematical models, first to examine the importance of conformational autoinhibition of RAF monomers, and later to investigate the potential role played by binding of 14-3-3 proteins to either autoinhibited monomers or active dimers. The authors develop several model variants containing different candidate mechanisms and generate analytical solutions that demonstrate under which parameter conditions PA may occur within these models. The use of analytical solutions is a strong point of the paper, as it allows evaluation of the models independently of specific parameter values. This analysis suggests that conformational autoinhibition is a very strong contributor to paradoxical activation, as models that include this mechanism show substantially larger concentration ranges under which RAF is activated by inhibitors. Fitting the parameters of the model to a published dataset on multiple inhibitors further suggests that conformational activation is important, as models containing this mechanism can fit the dataset with significantly lower error. Another interesting observation is that the different types of RAF inhibitors (1, 1.5, 2) fit the data with parameter values that are reasonably similar within each type. A moderate weakness in this analysis is that all of these observations provide indirect evidence for the importance of conformational autoinhibition. A direct test of whether PA is reduced when conformational autoinhibition is removed would be more compelling, but such a test could be difficult to set up experimentally.

The authors then perform an analysis of how 14-3-3 binding to either autoinhibited monomers or active dimers might enhance PA. A new model is constructed that contains these binding events in the context of conformational activation, but without negative cooperativity or dimer potentiation included, for the sake of limiting complexity. These models implicate monomer binding, but not dimer binding as a contributor to PA. They follow up on this model result by overexpressing 14-3-3 proteins in two RAS-mutant cell lines, which leads to both higher baseline ERK phosphorylation and to a wider range of inhibitor-induced PA, as predicted by the model. A cell-based RAF dimerization assay also shows higher dimerization effects when 14-3-3 plasmids are transfected as well. This experimental evidence provides strong support for the model, although one drawback, which is noted by the authors in the discussion, is that 14-3-3 overexpression could potentially exert effects on RAF activity through pleiotropic effects other than the binding actions included in the model.

Overall, this study makes a strong contribution to understanding the paradoxical effects of RAF inhibitors on the RAS/ERK signaling pathway, which remains a significant problem in the use of targeted inhibitors for cancer. Demonstrating that both conformational activation and 14-3-3 binding strongly contribute to the PA effect is an important step forward, as it establishes that these mechanisms should not be overlooked when designing strategies to use Raf inhibitors.

Reviewer #2 (Public Review):

This is a descriptive paper in the field of metascience, which documents levels of accessibility and reproducible research practices in the field of cardiovascular science. As such, it does not make a theoretical contribution, but it argues, first, that there is a problem for this field, and second, it provides a baseline against which the impact of future initiatives to improve reproducibility can be assessed. The study was pre-registered and the methods and data are clearly documented. This kind of study is extremely labour-intensive and represents a great deal of work.

I have a major concern about the analysis. It is stated that to be fully reproducible, publications must include sufficient resources (materials, methods, data and analysis scripts). But how about cases where materials are not required to reproduce the work? In line 128-129 it is noted that the materials criterion was omitted for meta-analyses, but what about other types of study where materials may be either described adequately in the text, readily available (eg published questionnaires), or impossible to share (e.g. experimental animals).

To see how valid these concerns might be, I looked at the first 4 papers in the deposited 'EmpricalResearchOnly.csv' file. Two had been coded as 'No Materials availability statement' and for two the value was blank.<br /> Study 1 used registry data and was coded as missing a Materials statement. The only materials that I could think might be useful to have might be 'standardized case report forms' that were referred to. But the authors did note that the Registry methods were fully documented elsewhere (I am not sure if that is the case).<br /> Study 2 was a short surgical case report - for this one the Materials field was left blank by the coder.<br /> Study 3 was a meta-analysis; the Materials field was blank by the coder<br /> Study 4 was again coded as lacking a Material statement. It presented a model predicting outcome for cardiac arrhythmias. The definitions of the predictor variables were provided in supplementary materials. I am not clear what other materials might be needed.<br /> These four cases suggest to me that it is rather misleading to treat lack of a Materials statement as contributing to an index of irreproducibility. Certainly, there are many studies where this is the case, but it will vary from study to study depending on the nature of the research. Indeed, this may also be true for other components of the irreproducibility index: for instance, in a case study, there may be no analysis script because no statistical analysis was done. And in some papers, the raw data may all be present in the text already - that may be less common, but it is likely to be so for case studies, for instance.

A related point concerns the criteria for selecting papers for screening: it was surprising that the requirement for studies to have empirical data was not imposed at the outset: it should be possible to screen these out early on by specifying 'publication type'; instead, they were included and that means that the numbers used for the actual analysis are well below 400. The large number of non-empirical papers is not of particular relevance for the research questions considered here. In the Discussion, the authors expressed surprise at the large number of non-emprical papers they found; I felt it would have been reasonable for them to depart from their preregistered plan on discovering this, and to review further papers to bring the number up to 400, restricting consideration to empirical papers only - also excluding case reports, which pose their own problems in this kind of analysis.

A more minor point is that some of the analyses could be dropped. The analysis of authorship by country had too few cases for many countries to allow for sensible analysis.

Overall, my concern is that the analysis presented here may create a backlash against metascientific analyses like this because it appears unfair on authors to use a metric based on criteria that may not apply to their study. I am strongly in favour of open, reproducible science, and agree it is important to document the state of the science for different disciplines. But what this study demonstrates to me is that if you are going to evaluate papers as to whether they include things like materials/data/ availability statements, then you need to have a N/A option. Unfortunately, I suspect it may not be possible to rely on authors' self-evaluation of N/A and that means that metascientists doing an evaluation would need to read enough of the paper to judge whether such a statement should apply.

Reviewer #2 (Public Review):

The authors undertook a review of studies describing the effects of the COVID-19 pandemic on breast cancer screening in countries across the world. The major strengths of the study are its breadth and the rigour of the literature search and review. The volume of studies included, and their different contexts and designs, make it challenging to summarize succinctly and the authors have done a good job. The weakness of this review, or any like it, is that we have limited data to explain the findings which a likely a complex mix of societal, structural, and personal reasons. The importance of the findings lies in the consistency of the overall trend and what the implications of potential delayed/missed breast cancer screening are and how far into the future these implications will reach.

Reviewer #2 (Public Review):

The submitted manuscript deals with the intricate and complex network among different members of the p53 family with a specific focus on TAp73alpha and TAp73 gamma. The authors provide in vitro and in vivo evidence on the oncogenic role of TAp73 gamma which opposes the tumor suppressor activity of TAp73 alpha. Mice carrying exon 11 loss which is the molecular event leading to the switch to TAp73 gamma, are obese when compared to their counterparts. Interestingly, the authors propose that obesity in E11 mice relies on TAp73 gamma-induced aberrant expression of Leptin. The strength of the reported findings resides mainly in the combination of in vitro and in vivo approaches, while its weaknesses are related to the validation of reported findings in human tumoral contexts.

Reviewer #2 (Public Review):

Machold and colleagues develop and describe an intersectional genetic mouse (Id2Cre:Dlx5/6FlpE) that allows for the targeting of a cortical interneuron subpopulation predominantly consisting of the neurogliaform cell subtype (NGFCs). The strategy is a modification of that previously published by the authors (Id2cre:Nkx2-1Flpo; Valero et al., 2021) in which a subset of deep layer 6 NGFCs with distinct embryonic origins were targeted. Conversely, using the NDNF transgenic mouse lines previous studies, including those from the Rudy laboratory, have clearly shown the prevalence of NGFCs in the outermost cortical Layer 1 region. Thus, the Id2Cre:Dlx5/6FlpE mouse poses an advantage over these previous approaches permitting the targeting of NGFCs in Layers 2-5. NGFCs in these regions have been hitherto difficult to study in an expedited manner.

The manuscript is of the resource/toolbox type and the authors are thorough in their description of the distribution and molecular characteristics of the ID2 neurons labelled by this intersectional approach. Furthermore, the authors perform a series of in vivo experiments. These entail the identification of NGFCs, the assessment of their influence on other neuronal populations, and the ability to delineate their activity during various network and behavioral states. Indeed, the authors reveal an activity pattern that is unique to NGFCs across epochs of specific network states. Therefore, this clearly demonstrates the applicability of the ID2Cre:Dlx5/6Flpe mouse to study the role of L2-5 NGFCs in a whole brain setting and these in vivo experiments constitute a major strength of the current study.

However, as with many transgenic mice, they are not always perfect, and the authors are very transparent regarding the additional, albeit a relatively smaller number of reported non-NGFCs particularly those of the CCK IN subtype. Indeed, clear morpho-functional divergence is revealed by the authors between these ID2 IN subpopulations. Furthermore, it is possible that this variability may differ across varying cortical regions. Thus, careful consideration of this caveat is necessary when using this mouse for future in vitro and in vivo studies. Related to this matter is a concern regarding the framing of the manuscript. The authors term the ID2 mixed population as the "4th group" since they do not express PV, SST, and VIP. One could argue this is a matter of semantics but to combine IN types that display distinct morphological and physiological properties into a single "group" based on one molecular feature is not consistent with that proposed by the widely accepted Petilla terminology (Ascoli et al., 2008).

Of interest to many who investigate cortical INs is the ability to genetically target specific subtypes during development. To this end, a potential and welcome addition to the manuscript would be an analysis (perhaps restricted to distribution/molecular characterization) highlighting whether the Id2cre:Dlx5/6Flpe strategy allows genetic access to layer 2-5 NGFCs during postnatal development following maternal tamoxifen administration.

Regardless, the experiments in the current study are, in general, well performed and clearly presented with the authors' conclusions supported by the results. Thus, it is clear that further refinements to genetic strategies are obviously required to exclusively target NGFCs throughout the cortical depth. Nevertheless, in the interim, the approach described in this current manuscript will be of use to the neuroscience community and help to further unravel the physiological role of this relatively understudied neuronal subtype.

Reviewer #2 (Public Review):

Pinheiro et al unravel the role of a new scavenger receptor in tubular morphogenesis. To do so they use the Drosophila respiratory network, the tracheal system. Here, the apical extracellular matrix (aECM) and the apical cytoskeleton are essential players in tube length regulation. A few years ago, a feedback mechanism between the aECM and the underlying cells was proposed (Ozturk-Çolak et al., eLife 2016), by which the aECM and the apical F-actin could regulate levels of phosphorylated Src protein to ensure proper tube morphogenesis. However, the connection between the aECM and the cells had not been found. In this manuscript, that Emp, a Drosophila scavenger receptor homologous to human CD36, could fulfill such a role. The authors show that Emp localizes in apical epithelial membranes and shows cargo selectivity for LDLr-domain-containing proteins. They show that emp mutant embryos fail to internalize the luminal chitin deacetylases Serp and Verm at the final stages of airway maturation and die at hatching with liquid-filled airways and over-elongated tracheal tubes with increased levels of the apical proteins Crb, DE-cad and phosphorylated Src (p-Src). Overexpression or loss of the Emp cargo protein Serp leads to abnormal apical accumulations of Emp and perturbations in p-Src levels. They propose a model linking aECM with cell elongation and open new lines of research in downstream signalling effectors.

Strengths:<br /> The finding of a novel receptor involved in the modulation of aECM-cellular homeostasis. A solid genetic and cellular analysis was provided. The implications for a scavenger receptor function during morphogenesis and overall implications in ECM to cell interactions and downstream signalling.

Weaknesses:<br /> The authors fail to clearly show the localization of Emp at the apical membrane and its connection to apical actin structures and chitinous aECM.

Reviewer #2 (Public Review):

The study was highly interesting personally as it tries to address a very important question of light induced brain development. The study uses a very efficient model system of birds. Using in-vivo MRI and a contrast agent increases the confidence on the results but also makes the experiments more challenging. I feel that the protocol will help fellow researchers interested in such questions a lot.

Reviewer #2 (Public Review):

This is a well-conceived and interesting study that investigates how a targeted protein phosphorylation (TPP) approach could be implemented to reconstitute PKA regulation of the cardiac KCNQ1/KCNE1 (IKs) potassium channel in the absence of an A-kinase anchoring protein (AKAP9). Using a genetically encoded GFP/YFP nanobody-based system they showed distinctive modulation of cAMP-mediated IKs activity. To that aim, they used an anti-GFP nanobody to recruit either the PKA holoenzyme RIIα or Cα subunits to YFP-tagged Q1 or YFP-E1 of reconstituted IKs channel complexes in CHO and HEK cells. They showed that targeted recruitment of endogenous Cα to E1-YFP using nano-RIIα modestly enhanced PKA-mediated IKs activity, whereas tethering of either nano-RIIα or nano-Cα to Q1-YFP retained KCNQ1 in the ER and Golgi thereby reducing IKs function. Using (LC-MS/MS), they further demonstrated that compared to free Cα, Cα targeted to Q1-YFP phosphorylated KCNQ1 subunit in multiple sites. Overall, the experiments are nicely done and yield sound data. The contribution of the paper is significant because it provides knowledge about the distinctive regulation of IKs by PKA, which could be used in the future to develop potential new drugs to prevent exercise-induced sudden cardiac death.

Reviewer #2 (Public Review):

This work uses broadband NIRS to investigate metabolic and hemodynamic changes in the brains of infants watching social or non-social stimuli, with simultaneous EEG providing the reference for specialization. The authors postulate that metabolic changes and neurovascular coupling will correlate better with power in the high-frequency beta and gamma band, but this is only justified by references to adult work. I suggest to justify better this assumption at the end of the introduction line 115 and discussing why this should be the case in infants as well.

The authors test the hypothesis that metabolic, hemodynamic, and high-frequency EEG activity will show similar spatial localization. The results support the claim. The methods are sound and thoroughly described, graphics are excellent.

At the moment though, the GitHub repository for code is empty and could not be used (sentence "All code used to analyse the NIRS data and the integration of the NIRS and EEG data is available on GitHub (https://github.com/maheensiddiqui91/NIRS-EEG)" line 346.

The Discussion is appropriate, although limitations could be more elaborate, particularly concerning spatial coverage issues and the methodological improvements required for improved fNIRS spatial resolution.

Reviewer #2 (Public Review):

Qing et al conducted high-resolution single-cell RNA sequencing and spatial transcriptomic profiling to characterize the immunological state of oral mucosa tissue from non-erosive OLP and erosive OLP patients. They find that tissue from erosive OLP patients possessed greater numbers and displayed enhanced activation of CD8+ tissue-resident memory T (CD8+ Trm) cells when compared to non-erosive OLP patients. The authors also designed a cohort study that demonstrated that tissues from patients with recent bouts of erosion displayed a more activated immunological state assessed by transcriptional profiling. Finally, the authors conducted immunological assays to demonstrate greater recovery and higher activation of CD8+ Trm cells from erosive OLP patients.

The sequencing data presented in the study are of high quality and demonstrate key immunological differences between patients with non-erosive OLP and erosive OLP. The authors focused on T cells due to their strong correlation with OLP pathogenesis, but they also observe significant changes to B cell and mast cell levels in erosive OLP compared to non-erosive OLP. Further commentary on the contribution(s) of B cells and mast cells to OLP pathogenesis would be helpful to fully capture the importance of the sequencing dataset.

My major criticism of the study is that the authors argue for CD8+ Trm activity as a key mechanism for OLP pathogenesis but have presented mostly descriptive datasets. The data strongly argue for CD8+ Trm cells as a defining feature of erosive OLP, but there is no data to support their involvement in disease pathogenesis. The authors note the lack of a mouse model for OLP which represents a significant technical barrier to interrogating the role of CD8+ Trm cells in OLP pathogenesis.

Another criticism is the lack of strong findings in the analysis of CD8+ Trm cells isolated from non-erosive and erosive OLP tissues. The authors note increases in CD8+ Trm cell recovery, however, they only observe minor changes in CD8+ Trm activity upon restimulation. Analyzing the activation status or proliferative capacity of CD8+ Trm cells from non-erosive and erosive OLP could be informative and more robust measures of functional changes.

A minor criticism is the formatting of the data presented in Figure 4. The authors should clearly label each marker used in the flow cytometry experiments as well as clearly labeling y-axes for graphs 4H and 4I.

Reviewer #2 (Public Review):

This research brings togethor an impressively long timescale dataset of fin whale song vocalisations in the North Atlantic, measuring the note frequency content and inter-note intervals and thereby tracking shifts in both over time. Different time periods are covered in different regions of the north Atlantic during the course of the study. There are two principal results - the study documents a shift in the inter-note interval (INI) in an ICES eco-region termed 'Oceanic Northeast Atlantic' (although the relevance of this to fin whale populations is unclear) occuring relatively rapidly in the years 2000-2001. This shift is discontuous and appears to show an abrupt change in note intervals in most (though not all) of the songs recorded. The second key result is that this INI measure and also the peak frequency of song element termed the 'HF note' both show consistent directional change over timescales of 12 years. The INI measure begins to change back toward the value it held prior to the 2000/2001 shift, suggestive of a cyclical process of change coupled with resets. The average HF note peak frequency descended by about 5Hz during the study period but there was no evidence of abrupt shifts.

The research significance is largely in the description of these processes in a new area, similar changes in rorqual song have been examined in the Southern Ocean and Mediterranean, and the argued interpretation of these changes as evidence for cultural learning processes in song change - the debate over whether these changes have environmental causation or are due to learning processes similar to song change in humpbacks is ongoing and this study therefore contributes interesting evidence from a newly covered population.

I think the methods and analyses broadly support the claims but also that there are weaknesses in interpretation and presentation that should be addressed. I think perhaps the degree to which this is evidence of vocal learning may be a bit overplayed. Definitely there is change, but it is tricky to compare this to e.g. experimental demonstrations. For example, age-related changes in a changing post-whaling demographic scenario should at least be considered? Is there also any possibility for large-scale oceanographic variations to be included in some way - temperature shifts, for example? This could help understand the different roles of environment and learning in these processes. I think it is also important that these results be placed in a more detailed context of current knowledge of fin whale population structure in the north Atlantic - could population range shifts be a factor? The INI data show an interesting variation in the recordings from the Barents Sea and this could be discussed in the light of population structure knowledge also. It is unclear from the presentation whether the INI shift in 2000/2001 was coupled with any frequency shifts - if not, it suggests different trajectories and processes affecting these two aspects of the acoustic display.

I am not convinced the main story here is about conformity, and I think it would be a mistake to too easily reach for the humpback comparison but there are certainly questions to be asked about the 2000/2001 shift in terms of the processes that led to it.

Reviewer #2 (Public Review):

The Author's chose to limit their response to re-doing the Lhx5 immuno using the correct antibody which now displays the expected staining: Lhx5 expression is limited to the hem. They have not however presented a characterization of where the RxCre acts, although this was pointed out by other reviewers as well. It would have been useful to demonstrate the expression domain in particular with respect to the time of its initiation, to explain how it causes a phenotype close to that described for the Lhx5 knockout (Zhao et al., 1999). From the decrease of Lhx5 expression and the CR cells which arise from the hem, it appears that the RxCre does indeed act in the hem. However, the timing and spatial pattern is important to establish, as I had pointed out in my first review, "If [the expression of RxCre] it has a dorso-ventral bias in the early embryo, it could explain the regional difference in the COUPTF phenotypes."

The major interpretive criticisms I made have not been addressed even though these would have only required a re-writing and re-interpretation of the data. The revised manuscript continues to include major errors of interpretation such as the idea that Lhx2 and Lhx5 "inhibit each other", something that is unsupported since the expression domains of these two genes are mutually exclusive as is clear from the authors' own new data and the literature.Lines 355-360: "The expression of Lhx2 was comparable between the control and double-mutant mice at E11.5 (Figure 5Be-h, e'-h'). Interestingly, the expression of the Lhx2 protein was increased in the hippocampal primordium in the COUP-TF double-mutant mice at E13.5 and E14.5 (Figure 5Bm-p, m'-p', u-x, u'-x'). The upregulation of Lhx2 expression is most likely associated with the reduced expression of the Lhx5 gene"There's clearly no Lhx5 in the hippocampal primordium so how is this possible?

The authors have missed the insights from key papers that they cite, e.g. (lines 352-354) " The expression of Lhx2 was expanded ventrally into the choroid plexus in the Lhx5 null mutant mice (Zhao et al., 1999)" - this paper in fact shows there is no choroid plexus. Lhx2 appears to extend to the midline likely because the hem isn't specified. The authors would benefit from reading https://doi.org/10.1101/2022.10.25.513532 in which Lmx1a is shown to be the master regulator of the hem.<br /> A sentence like (lines 77-81) further blurs the literature: "Intriguingly, deficiency of either Lhx5 or Lhx2 results in agenesis of the hippocampus, and more particularly, these genes inhibit each other (Hébert & Fishell, 2008; Mangale et al., 2008; Roy, Gonzalez-Gomez, Pierani, Meyer, & Tole, 2014; Zhao et al., 1999), indicating that the Lhx5 and Lhx2 genes may generate an essential regulatory axis to ensure the appropriate hippocampal development"<br /> First, none of the papers they cite shows that these two factors inhibit each other. Second, the "agenesis of the hippocampus" in the Lhx2 knockout mentioned in Porter et al. (1997) was later shown to be due to a transformation of the hippocampal primordium into an EXPANDED hem (Mangale et al.) In contrast, the "agenesis of the hippocampus" in the Lhx5 mutant appears to be due to the near-complete LOSS of the hem and evidenced by the loss of its derivatives, the choroid plexus and the CR cells (Zhao et al., 1999). The fact that loss of these two factors have opposite effects on the hem (each resulting in loss of the hippocampus, one due to transformation of the hippocampal primordium into hem and the other because of a lack of hipopcampal induction) does not mean that there is an Lhx5-Lhx2 "axis" regulating hippocampal development.

I won't repeat my other comments here, but the majority of them were not addressed in any way.

In conclusion, I find it unfortunate that the authors have chosen not to use the detailed input provided by the reviewers which would have greatly improved their manuscript.

Reviewer #2 (Public Review):

Barlow and colleagues describe a role for the Na+/K+ pump in sleep/wake regulation. They discovered this role starting with a forward genetic screen in which they tested a biased sample of virus insertion fish lines for sleep phenotypes. They found an insertion in a gene they named dreammist, which is homologous to the gene FXYD1 encoding single membrane-pass modifiers of Na/K pumps. They go on to show that genetic manipulations of either FXYD1 or the Na/K pump also reduce sleep. They use pharmacology and sleep deprivation experiments to provide further evidence that the NA/K pump regulates intracellular sodium and rebound sleep. This study provides additional evidence for the important role of membrane excitability in sleep regulation (prior studies have implicated K+ channel subunits as well as a sodium leak ion channel).

The study is well done and convincing with regard to its major conclusions. I had some minor comments/questions, which they properly addressed in their revision and rebuttal.

Reviewer #2 (Public Review):

This paper presents a valuable contribution to ongoing methods for understanding and modeling structure via latent variable models for neural and behavioral data. Building on the PS-VAE model of Whiteway et al. (2021), which posited a division of latent variables into unsupervised (i.e., useful for reconstruction) and supervised (useful for predicting selected labeled features) variables, the authors propose an additional set of "constrained subspace" latent variables that are regularized toward a prespecified prior via a Cauchy-Schwarz divergence previously proposed.

The authors contend that the added CS latents aid in capturing both patterns of covariance across the data and individual-specific features that are of particular benefit in multi-animal experiments, all without requiring additional labels. They substantiate these claims with a series of computational experiments demonstrating that their CS-VAE outperforms the PS-VAE in several tasks, particularly that of capturing differences between individuals, consistency in behavioral phenotyping, and predicting correlations with neural data.

Strengths of the present work include an extensive and rigorous set of validation experiments that will be of interest to those analyzing behavioral video. Weaknesses include a lack of discussion of key theoretical ideas motivating the design of the model, including the choice of a Cauchy-Schwarz divergence, the specific form of the prior, and arguments for sorts of information the CS latents might capture and why. In addition, the model makes use of a moderate number of key hyperparameters whose effect on training outcomes are not extensively analyzed. As a result, the model may be difficult for less experienced users to apply to their own data. Finally, as with many similar VAE approaches, the lack of a ground truth against which to validate means that much of evidence provided for the model is necessarily subjective, and its appeal lies in the degree to which the discovered latent spaces appear interpretable in particular applications.

In all, this work is a valuable contribution that is likely to have appeal to those interested in applying latent space methods, particularly to multi-animal video data.

Reviewer #2 (Public Review):

The contribution of glial cells to the pathogenesis of amyotrophic lateral sclerosis (ALS) is of substantial interest and the investigators have contributed significantly to this emerging field via prior publications. In the present study, authors use a SOD1G93A mouse model to elucidate the role of astrocyte ephrinB2 signaling in ALS disease progression. Erythropoietin-producing human hepatocellular receptors (Ephs) and the Eph receptor-interacting proteins (ephrins) signaling is an important mediator of signaling between neurons and non-neuronal cells in the nervous system. Recent evidence suggests that dysregulated Eph-ephrin signaling in the mature CNS is a feature of neurodegenerative diseases. In the ALS model, upregulated Eph4A expression in motor neurons has been linked to disease pathogenesis. In the present study, authors extend previous findings to a new class of ephrinB2 ligands. Urban et al. hypothesize that upregulated ephrinB2 signaling contributes to disease pathogenesis in ALS mice. The authors successfully test this hypothesis and their results generally support their conclusion.

Major strengths of this work include a robust study design, a well-defined translational model, and complementary biochemical and experimental methods such that correlated findings are followed up by interventional studies. Authors show that ephrinB2 ligand expression is progressively upregulated in the ventral horn of the cervical and lumbar spinal cord through pre-symptomatic to end stages of the disease. This novel association was also observed in lumbar spinal cord samples from post-mortem samples of human ALS donors with a SOD1 mutation. Further, they use a lentiviral approach to drive knock-down of ephrinB2 in the central cervical region of SOD1G93A mice at the pre-symptomatic stage. Interestingly, in spite of using a non-specific promoter, authors note that the lentiviral expression was preferentially driven in astrocytes.

Since respiratory compromise is a leading cause of morbidity in the ALS population, the authors proceed to characterize the impact of ephrinB2 knockdown on diaphragm muscle output. In mice approaching the end stage of the disease, electrophysiological recordings from the diaphragm muscle show that animals in the knock-down group exhibited a ~60% larger amplitude. This functional preservation of diaphragm function was also accompanied by the preservation of diaphragm neuromuscular innervation. However, it must be noted that this cervical ephrinB2 knockdown approach had no impact on disease onset, disease duration, or animal survival. Furthermore, there was no impact of ephrinB2 knockdown on forelimb or hindlimb function.

The major limitation of the manuscript as currently written is the conclusion that the preservation of diaphragm output following ephrinB2 knockdown in SOD1 mice is mediated primarily (if not entirely) by astrocytes. The authors present convincing evidence that a reduction in ephrinB2 is observed in local astrocytes (~56% transduction) following the intraspinal injection of the lentivirus. However, the proportion of cell types assessed for transduction with the lentivirus in the spinal cord was limited to neurons, astrocytes, and oligodendrocyte lineage cells. Microglia comprise a large proportion of the glial population in the spinal grey matter and have been shown to associate closely with respiratory motor pools. This cell type, amongst the many others that comprise the ventral gray matter, have not been investigated in this study. Thus, the primary conclusion that astrocytes drive ephrinB2-mediated pathogenesis in ALS mice is largely correlative. Further, it is interesting to note that no other functional outcomes were improved in this study. The C3-C5 region of the spinal cord consists of many motor pools that innervate forelimb muscles. CMAP recordings conducted at the diaphragm are a reflection of intact motor pools. This type of assessment of neuromuscular health is hard to re-capitulate in the kind of forelimb task that is being employed to test motor function (grip strength). Thus, it would be interesting to see if CMAP recordings of forelimb muscles would capture the kind of motor function preservation observed in the diaphragm muscle.

On a similar note, the functional impact of increased CMAP amplitude has not been presented. An increase in CMAP amplitude does not necessarily translate to improved breathing function or overall ventilation. Thus, the impact of this improvement in motor output should be clearly presented to the reader. Further, to the best of my knowledge, expression of Eph (or EphB) receptors has not been explicitly shown at the phrenic motor pool. It is thus speculative at best that the mechanism that the authors suggest in preserving diaphragm function is in fact mediated through Eph-EphrinB2 signaling at the phrenic motor pool. This aspect of the study would warrant a deeper discussion. Lastly, although authors include both male and female animals in this investigation, they do not have sufficient power to evaluate sex differences. Thus, this presents another exciting future of investigation, given that ALS has a slightly higher preponderance in males as compared to females.

In summary, this study by Urban et al. provides a valuable framework for Eph-Ephrin signaling mechanisms imposing pathological changes in an ALS mouse model. The role of glial cells in ALS pathology is a very exciting and upcoming field of investigation. The current study proposes a novel astrocyte-mediated mechanism for the propagation of disease that may eventually help to identify potential therapeutic targets.

Reviewer #2 (Public Review):

This study connects prior findings on MicroRNA15/16 and Malat1 to demonstrate a functional interaction that is consequential for T cell activation and cell fate.

The study uses mice (Malat1scr/scr) with a precise genetic modification of Malat1 to specifically excise the sites of interaction with the microRNA, but sparing all other sequences, and mice with T-cell specific deletion of miR-15/16. The effects of genetic modification on in vivo T-cell responses are detected using specific mutations and shown to be T-cell intrinsic.

It is not known where in the cell the consequential interactions between MicroRNA15/16 and Malat1 take place. The authors depict in the graphical abstract Malat1 to be a nuclear lncRNA. Malat 1 is very abundant, but it is unclear if it can shuttle between the nucleus and cytoplasm. As the authors discuss future work defining where in the cell the relevant interactions take place will be important.

In addition to showing physiological phenotypic effects, the mouse models prove to be very helpful when the effects measured are small and sometimes hard to quantitate in the context of considerable variation between biological replicates (for example the results in Figure 4D).

The impact of the genetic modification on the CD28-IL2- Bcl2 axis is quantitatively small at the level of expression of individual proteins and there are likely to be additional components to this circuitry.

Reviewer #2 (Public Review):

This paper purports to unveil a mechanism controlling telomere length through SUMO modifications controlling interactions between PCNA unloader Elg1 and the CST complex that functions at telomeres. This is an extremely interesting mechanism to understand, and this paper indeed reveals some interesting genetic results, leading to a compelling model, with potential impact on the field. Overall, however, the data do not provide sufficient support for the claims. The model may be correct but it is not yet convincingly demonstrated.

The current version addressed some of the issues regarding language describing conclusions and more experimental detail has been provided. However, the authors have not provided new data supporting the model, so the overall evaluation is that the work remains inconclusive.

Reviewer #2 (Public Review):

The pear psylla Cacopsylla chinensis has two morphologically different forms, winter- and summer-forms depending on the temperatures. The authors provided solid data showing that the cold sensor CcTRPM is responsible for switching summer- to winter forms, which is in turn regulated by the miRNA miR-252. This finding is interesting and novel.

Reviewer #2 (Public Review):

This study examines the role of the Locus Coeruleus (LC)/noradrenergic (NA) system in extinction in male and female rats. The behavioural task involves three phases i) training on a discriminative procedure in which operant responding was rewarded only during the presentation of a stimulus ii) extinction iii) testing for the expression of extinction at both short (1 day) or long (7 days) delays. Targeting LC/NA cells with optogenetic in TH::Cre rats, the authors found that photoexcitation during extinction led to an increase in the expression of extinguished responding at both short and long delays. By contrast, photo inhibition was found to be without an effect.

1. In such discrimination training, Pavlovian (CS-Food) and instrumental (LeverPress-Food) contingencies are intermixed. It would therefore be very interesting if the authors provided evidence of other behavioural responses (e.g. magazine visits) during extinction training and tests.<br /> 2. In Figure 1, the authors show the behavioural data of the different groups of control animals which were later collapsed in a single control group. It would be very nice if the authors could provide the data for each step of the discrimination training.<br /> 3. Inspection of Figures 2C & 2D shows that responding in control animals is about the same at test 2 as at the end of extinction training. Therefore, could the authors provide evidence for spontaneous recovery in control animals? This is of importance given that the main conclusion of the authors is that LC stimulation during extinction training led to an increased expression of extinction memory as expressed by reduced spontaneous recovery.<br /> 4. Current evidence suggests that there are differences in LC/NA system functioning between males and females. Could the authors provide details about the allocation of male and female animals in each group?<br /> 5. The histology section in both experiments looks a bit unsatisfying. Could the authors provide more details about the number of counted cells and also their distribution along the antero-posterior extent of the LC. Could the authors also take into account the sex in such an analysis?

Reviewer #2 (Public Review):

This work aggregates data across 5 openly available stopping studies (3 at 7 tesla and 2 at 3 tesla) to evaluate activity patterns across the common contrasts of Failed Stop (FS) > Go, FS > stop success (SS), and SS > Go. Previous work has implicated a set of regions that tend to be positively active in one or more of these contrasts, including the bilateral inferior frontal gyrus, preSMA, and multiple basal ganglia structures. However, the authors argue that upon closer examination, many previous papers have not found subcortical structures to be more active on SS than FS trials, bringing into question whether they play an essential role in (successful) inhibition. In order to evaluate this with more data and power, the authors aggregate across five datasets and find many areas that are *more* active for FS than SS, specifically bilateral preSMA, caudate, GPE, thalamus, and VTA, and unilateral M1, GPi, putamen, SN, and STN. They argue that this brings into question the role of these areas in inhibition, based upon the assumption that areas involved in inhibition should be more active on successful stop than failed stop trials, not the opposite as they observed.

As an empirical result, I believe that the results are robust, but this work does not attempt a new theoretical synthesis of the neuro-cognitive mechanisms of stopping. Specifically, if these many areas are more active on failed stop than successful stop trials, and (at least some of) these areas are situated in pathways that are traditionally assumed to instantiate response inhibition like the hyperdirect pathway, then what function are these areas/pathways involved in? I believe that this work would make a larger impact if the author endeavored to synthesize these results into some kind of theoretical framework for how stopping is instantiated in the brain, even if that framework may be preliminary.

I also have one main concern about the analysis. The authors use the mean method for computing SSRT, but this has been shown to be more susceptible to distortion from RT slowing (Verbruggen, Chambers & Logan, 2013 Psych Sci), and goes against the consensus recommendation of using the integration with replacement method (Verbruggen et al., 2019). Therefore, I would strongly recommend replacing all mean SSRT estimates with estimates using the integration with replacement method.

Reviewer #2 (Public Review):

This report by Hur et al. examines simultaneous activity in the cerebellum and anterior cingulate cortex (ACC) to determine how activity in these regions is coordinated during social behavior. To accomplish this, the authors developed a recording device named the E-scope, which combines a head-mounted mini-scope for in vivo Ca2+ imaging with an extracellular recording probe (in the manuscript they use a 32-channel silicon probe). Using the E-scope, the authors find subpopulations of cerebellar neurons with social-interaction-related activity changes. The activity pattern is predominantly decreased firing in PCs and increases in DNs, which is the expected reciprocal relationship between these populations. They also find social-interaction-related activity in the ACC. The authors nicely show the absence of locomotion onset and offset activity in PCs and DNs ruling out that is movement driven. Analysis showed high correlations between cerebellar and ACC populations (namely, Soc+ACC and Soc+DN cells). The finding of correlated activity is interesting because non-motor functions of the cerebellum are relatively little explored. However, the causal relationship is far from established with the methods used, leaving it unclear if these two brain regions are similarly engaged by the behavior or if they form a pathway/loop. Overall, the data are presented clearly, and the manuscript is well written, however, the biological insight gained is rather limited.

Reviewer #2 (Public Review):

The study provides a valuable contribution by demonstrating the use of an allocentric spatial reference frame in the perception of the location of a dimly lit target in the dark. While the evidence presented in support of the authors' claims is solid and convincing, it would be beneficial for the study to address potential limitations, such as its ecological validity.

Strengths:<br /> Unlike previous research where observers were stationary during a visual-spatial perception task, this recent study expanded upon prior findings by incorporating bodily movements for the observers. This study is a valuable addition to the literature as it not only discovered that the intrinsic bias is grounded on the home base, but also identified several key characteristics through a series of follow-up experiments. The findings suggest that this "allocentric" spatial coding decays over time, requires attentional resources, can be based solely on vestibular signals, and is most effective in the horizontal direction. In general, this study is interesting, clearly presented, well-thought-out and executed. The results confirmed the conclusions and the study's comprehensive approach offers valuable insights into the nature of intrinsic bias in spatial perception.

The counter-intuitive results presented in the manuscript are intriguing and add to the study's overall appeal. Moreover, the manuscript draws an interesting parallel between human spatial navigation and that of desert ants. This comparison helps to underscore the importance of understanding spatial coding mechanisms across different species and highlights potential avenues for future research.

One aspect I particularly valued about this study was the authors' thorough description of the experimental methods. This level of detail not only highlights the rigor of the research but also enhances the reproducibility of the study, making it more accessible for future researchers.

Weaknesses:<br /> While the current study provides valuable insights into the nature of intrinsic bias in spatial perception, there is a concern regarding its ecological validity. The experimental design involved stringent precautions, such as a very dark room and a small target, to minimize the presence of depth cues. This is in contrast to the real world, where depth information is readily available from the ground and surrounding objects, aiding in our perception of space and depth. As a result, it is unclear to what extent this "allocentric" intrinsic bias is involved in our everyday spatial perception. To provide more context for the general audience, it would be beneficial for the authors to address this issue in their discussion.

The current findings on the "allocentric" coding scheme raise some intriguing questions as to why such a mechanism would be developed and how it could be beneficial. The finding that the "allocentric" coding scheme results in less accurate object localization and requires attentional resources seems counterintuitive and raises questions about its usefulness. However, this observation presents an opportunity for the manuscript to discuss the potential evolutionary advantages or trade-offs associated with this coding mechanism.

The manuscript lacks a thorough description of the data analysis process, particularly regarding the fitting of the intrinsic bias curve (e.g., the blue and gray dashed curve in Figure 3c) and the calculation of the horizontal separation between the curves. It would be beneficial for the authors to provide more detailed information on the specific function and parameters used in the fitting process and the formula used for the separation calculation to ensure the transparency and reproducibility of the study's results.

Reviewer #2 (Public Review):

This work aims at answering whether activity in the primate visual cortex is modulated by locomotion, as was reported for the mouse visual cortex. The finding that the activity in the mouse visual cortex is modulated by running has changed the concept of primary sensory cortical areas. However, it was an open question whether this modulation generalizes to primates.

To answer this fundamental question the authors established a novel paradigm in which a head-fixed marmoset was able to run on a treadmill while watching a visual stimulus on a display. In addition, eye movements and running speed were monitored continuously and extracellular neuronal activity in the primary visual cortex was recorded using high-channel-count electrode arrays. This paradigm uniquely permitted investigation of whether locomotion modulates sensory-evoked activity in the visual cortex of a marmoset. Moreover, to directly compare the responses in the marmoset visual cortex to responses in the mouse visual cortex the authors made use of a publicly-available mouse dataset from the Allen Institute. In this dataset, the mouse was also running on a treadmill and observing a set of visual stimuli on a display. The authors took extra care to have the marmoset and mouse paradigms as comparable as possible.

To characterize the visually driven activity the authors present a series of moving gratings and estimate receptive fields with sparse noise. To estimate the gain modulation by running the authors split the dataset into epochs of running and non-running which allowed them to estimate the visually evoked firing rates in both behavioral states.

Strengths:<br /> The novel paradigm of head-fixed marmosets running on a treadmill while being presented with a visual stimulus is unique and ideally tailored to answering the question that the authors aimed to answer. Moreover, the authors took extra care to ensure that the paradigm in the marmoset matched as closely as possible to the conditions in the mouse experiments such that the results can be directly compared. To directly compare their data the authors re-analyzed publicly available data from the visual cortex of mice recorded at the Allen Institute. Such a direct comparison, and reuse of existing datasets, is another strong aspect of the work. Finally, the presented new marmoset dataset appears to be of high quality, the comparison between the mouse and marmoset visual cortex is well done and the results and interpretation are straightforward.

Weaknesses:<br /> While the presented results are clear and support the main conclusion of the authors, additional analysis and experimental details could have further strengthened and clarified some aspects of the results. For example, it is known that the locomotion gain modulation varies with layer in the mouse visual cortex, with neurons in the infragranular layers expressing a diversity of modulations (Erisken et al. 2014 Current Biology). However, for the marmoset dataset, it was not reported from which cortical layer the neurons are from, leaving this point unanswered.

Nonetheless, the aim of comparing the locomotion-induced modulation of activity in primate and mouse primary visual cortex was convincingly achieved by the authors. The results shown in the figures support the conclusion that locomotion modulates the activity in primate and mouse visual cortex differently. While mice show a profound gain increase, neurons in the primate visual cortex show little modulation or even a reduction in response strength.

This work will have a strong impact on the field of visual neuroscience but also on neuroscience in general. It revives the debate of whether results obtained in the mouse model system can be simply generalized to other mammalian model systems, such as non-human primates. Based on the presented results, the comparison between the mouse and primate visual cortex is not as straightforward as previously assumed. This will likely trigger more comparative studies between mice and primates in the future, which is important and absolutely needed to advance our understanding of the mammalian brain.

Moreover, the reported finding that neurons in the primary visual cortex of marmosets do not increase their activity during running is intriguing, as it makes you wonder why neurons in the mouse visual cortex do so. The authors discuss a few ideas in the paper which can be addressed in future experiments. In this regard, it is worth noting that the authors report an interesting difference between the foveal and peripheral parts of the visual cortex in marmoset. It will be interesting to investigate these differences in more detail in future studies. Likewise, while running might be an important behavioral state for mice, other behavioral states might be more relevant for marmosets and do modulate the activity of the primate visual cortex more profoundly. Future work could leverage the opportunities that the marmoset model system offers to reveal new insights about behavioral-related modulation in the primate brain.

Reviewer #2 (Public Review):

In this study, multiple biophysical techniques were employed to investigate the activation mechanism of BTK, a multi-domain non-receptor protein kinase. Previous studies have elucidated the inhibitory effects of the SH3 and SH2 domains on the kinase and the potential activation mechanism involving the membrane-bound PIP3 inducing transient dimerization of the PH-TH domain, which binds to lipids.

The primary focus of the present study was on three new constructs: a full-length BTK construct, a construct where the PH-TH domain is connected to the kinase domain, and a construct featuring a kinase domain with a phosphomimetic at the autophosphorylation site Y551. The authors aimed to provide new insights into the autoinhibition and allosteric control of BTK.

The study reports that SAXS analysis of the full-length BTK protein construct, along with cryoEM visualization of the PH-TH domain, supports a model in which the N-terminal PH-TH domain exists in a conformational ensemble surrounding a compact/autoinhibited SH3-SH2-kinase core. This finding is interesting because it contradicts previous models proposing that each globular domain is tightly packed within the core.

Furthermore, the authors present a model for an inhibitory interaction between the N-lobe of the kinase and the PH-TH domain. This model is based on a study using a tethered complex with a longer tether than a previously reported construct where the PH-TH domain was tightly attached to the kinase domain (ref 5). The authors argue that the new structure is relevant. However, this assertion requires further explanation and discussion, particularly considering that the functional assays used to assess the impact of mutating residues within the PH-TH/kinase domain contradict the results of the previous study (ref 5).

Additionally, the study presents the structure of the kinase domain with swapped activation loops in a dimeric form, representing a previously unseen structure along the trans-phosphorylation pathway. This structure holds potential relevance. To better understand its significance, employing a structure/function approach like the one described for the PH-TH/kinase domain interface would be beneficial.

Overall, this study contributes to our understanding of the activation mechanism of BTK and sheds light on the autoinhibition and allosteric control of this protein kinase. It presents new structural insights and proposes novel models that challenge previous understandings. However, further investigation and discussion would significantly strengthen the study.

Reviewer #2 (Public Review):

The manuscript by Nishikawa et al. addresses time-dependent changes in the electron transfer energetics in the photosynthetic reaction center from Blastochloris viridis, whose time-dependent structural changes upon light illumination were recently demonstrated by time-resolved serial femtosecond crystallography (SFX) using X-ray free-electron laser (XFEL) (Dods et al., Nature, 2021). Based on the redox potential Em values of bacteriopheophytin in the electron transfer active branch (BL) by solving the linear Poisson-Boltzmann equation, the authors found that Em(HL) values in the charge-separated 5-ps structure obtained by XFEL are not clearly changed, suggesting that the P+HL- state is not stabilized owing to protein reorganization. Furthermore, chlorin ring deformation upon HL- formation, which was expected from their QM/MM calculation, is not recognized in the 5-ps XFEL structure. Then the authors concluded that the structural changes in the XFEL structures are not related to the actual time course of charge separation. They argued that their calculated changes in Em and chlorin ring deformations using the XEFL structures may reflect the experimental errors rather than the real structural changes; they mentioned this problem is due to the fact that the XFEL structures were obtained at not high resolutions (mostly at 2.8 Å). I consider that their systematic calculations may suggest a useful theoretical interpretation of the XFEL study. However, the present manuscript insists as a whole negatively that the experimental errors may hamper to provide the actual structural changes relevant to the electron transfer events. My concerns are the following two points:<br /> Is the premise of the authors for the electron transfer energetics obviously valid?<br /> Could the authors find any positive aspect(s) in the XFEL study?

The authors' argument is certainly due to their premise "Em(HL) is expected to be exclusively higher in the 5-ps and 20-ps structures than in the other XFEL structures due to the stabilization of the [PLPM]•+HL•- state by protein reorganization" as noted in the Results and Discussion (p. 12, lines 180-182); however, it is unknown whether this premise can be applied to the ps-timescale electron transfer events. The above premise is surely based on the Marcus theory, as the authors also noted in the Introduction "The anionic state formation induces not only reorganization of the protein environment (ref. 5: Marcus and Sutin, 1985) but also out-of-plane distortion of the chlorin ring (ref. 6: two of the authors, Saito and Ishikita, co-authored, 2012)"; however, it is unknown whether protein reorganization can follow the ps-timescale electron transfer events. Indeed, Dods et al. mentioned in the Nature paper (2021) "The primary electron-transfer step from SP (special pair PLPM) to BPhL (HL) occurs in 2.8 {plus minus} 0.2 ps across a distance of 10 Å by means of a two-step hopping mechanism via the monomeric BChL molecule and is more rapid than conventional Marcus theory". It was also mentioned, "By contrast, the 9 Å electron-transfer step from BPhL to QA has a single exponential decay time of 230 {plus minus} 30 ps, which is consistent with conventional Marcus theory". As for the primary electron-transfer step from PLPM to HL, Wang et al. (2007, Science 316, 747; cited as ref. 8 in the Nature paper 2021) reported, by monitoring tryptophan absorbance changes in various reaction centers in which the driving forces (namely, the Em gaps between PLPM and HL) are different, that the protein relaxation kinetics is independent of the charge separation kinetics on the picosecond timescale. On the other hand, in the EPR study cited by the authors as ref. 7 (Muh et al. (1998) Biochemistry 37, 13066), although the authors described "two distinct conformations of HL- were reported in spectroscopic studies" (p. 3, lines 44-45), it should be noted that conformation of HL- was formed by 1 or 45 s illumination prior to freezing, and hence the second-order reorganized conformations may differ from picosecond-order conformations observed by the XFEL study (Nature, 2021) and/or the transient absorption spectroscopy (Science, 2007).

Therefore, I consider there is a possibility that the authors' findings may reflect not experimental errors but the actual ps-timescale phenomena presented by the first-time XFEL study on the timescale of the primary charge-separation reactions of photosynthesis. Thus I would like to suggest that the authors reconsider the premise for the electron transfer energetics on the picosecond timescale.

In any case, to discuss the experimental errors in the XFEL study, it is better to calculate the Em(QA) changes in the 300-ps and 8-us XFEL structures, which showed distinctive structural changes even at the 2.8 Å resolution as discussed by Dods et al. Then, if the Em(QA) values are changed as expected from theoretical calculations, such calculated results may suggest a useful theoretical interpretation of the XFEL study as a positive aspect. If the Em(QA) values are not higher in the 300-ps and 8-us structures than in the other structures, it may be argued that the experimental errors would be so large that the XFEL structures are irrelevant to the electron transfer events expected from theoretical calculations.

Reviewer #2 (Public Review):

This is an interesting study with high-quality imaging and quantitative data. The authors devise a robust quantitative parameter that is easily applicable to any experimental system. The drug screen data can potentially be helpful to the wider community studying nucleolar architecture and the effects of chemotherapy drugs. Additionally, the authors find Treacle phosphorylation as a potential link between CDK9 inhibition, rDNA transcription, and nucleolar stress. Therefore I think this would be of broad interest to researchers studying transcription, CDKs, nucleolus, and chemotherapy drug mechanisms. However, the study has several weaknesses in its current form as outlined below.

1. Overall the study seems to suffer from a lack of focus. At first, it feels like a descriptive study aimed at characterizing the effect of chemotherapy drugs on the nucleolar state. But then the authors dive into the mechanism of CDK inhibition and then suddenly switch to studying biophysical properties of nucleolus using NPM1. Figure 6 does not enhance the story in any way; on the contrary, the findings from Fig. 6 are inconclusive and therefore could lead to some confusion.

2. The justification for pursuing CDK inhibitors is not clear. Some of the top hits in the screen were mTOR, PI3K, HSP90, Topoisomerases, but the authors fail to properly justify why they chose CDKi over other inhibitors.

3. In addition to poor justification, it seems like a very superficial attempt at deciphering the mechanism of CDK9i-mediated nucleolar stress. I think the most interesting part of the study is the link between CDK9, Pol I transcription, and nucleolar stress. But the data presented is not entirely convincing. There are several important controls missing as detailed below.

4. The authors did not test if inhibition of CDK7 and/or CDK12 also induces nucleolar stress. CDK7 and CDK12 are also major kinases of RNAPII CTD, just like CDK9. Importantly, there are well-established inhibitors against both these kinases. It is not clear from the text whether these inhibitors were included in the screen library.

5. In Figure 4E, the authors show that Pol I is reduced in nucleolus/on rDNA. The authors should include an orthogonal method like chromatin fractionation and/or ChIP

6. In Fig. 5D, in vitro kinase lacks important controls. The authors should include S to A mutants of Treacle S1299A/S1301A to demonstrate that CDK9 phosphorylates these two residues specifically.

7. To support their model, the authors should test if overexpression of Treacle mutants S1299A/S1301A can partially phenocopy the nucleolar stress seen upon CDK9 inhibition. This would considerably strengthen the author's claim that reduced Treacle phosphorylation leads to Pol I disassociation from rDNA and consequently leads to nucleolar stress.

8. Additionally, it would be interesting if S1299D/S1301D mutants could partially rescue CDK9 inhibition.

Reviewer #2 (Public Review):

This paper illustrates that PSCs can model myogenesis in vitro by mimicking the in vivo development of the somite and dermomyotome. The advantages of this 3D system include (1) better structural distinctions, (2) the persistence of progenitors, and (3) the spatial distribution (e.g. migration, confinement) of progenitors. The finding is important with the implication in disease modeling. Indeed the authors tried DMD model although it suffered the lack of deeper characterization.

The differentiation protocol is based on a current understanding of myogenesis and compelling. They characterized the organoids in depth (e.g. many time points and immunofluorescence). The evidence is solid, and can be improved more by rigorous analyses and descriptions as described below.

Major comments:

1. Consistency between different cell lines.<br /> I see the authors used a few different PSC lines. Since organoid efficiency differ between lines, it is important to note the consistency between lines.

2. Heterogeneity among each organoid<br /> Let's say authors get 10 organoids in one well. Are they similar to each other? Does each organoid possess similar composition of cells? To determine the heterogeneity, the authors could try either FACS or multiple sectioning of each organoid.

3. Consistency of Ach current between organoids.<br /> Related to comment 2, are the currents consistent between each organoid? How many organoids were recorded in the figures? Also, please comment if the current differ between young and aged organoids.

4. Communication between neural cells and muscle?<br /> The authors did scRNAseq, but have not gone deep analysis. I would recommend doing Receptor-ligand mapping and address if neural cells and muscle are interacting.

5. More characterization of DMD organoids.<br /> One of the key applications of muscle organoids is disease model. They have generated DMD muscle organoids, but rarely characterized except for currents. I recommend conducting immunofluorescence of DMA organoids to confirm structure change. Very intriguing to see scRNAseq of DMD organoids and align with disease etiology.

6. More characterization of engraft.<br /> Authors could measure the size of myotube between mice and human. Does PAX7+ Sattelite cell exist in engraft? To exclude cell fusion events make up the observation, I recommend to engraft in GFP+ immunodeficient mice. Could the authors comment how long engraft survive.

Reviewer #2 (Public Review):

This is the first comprehensive study aimed at assessing the impact of landscape modification on the prevalence of P. knowlesi malaria in non-human primates in Southeast Asia. This is a very important and timely topic both in terms of developing a better understanding of zoonotic disease spillover and the impact of human modification of landscape on disease prevalence.

This study uses the meta-analysis approach to incorporate the existing data sources into a new and completely independent study that answers novel research questions linked to geospatial data analysis. The challenge, however, is that neither the sampling design of previous studies nor their geospatial accuracy are intended for spatially-explicit assessments of landscape impact. On the one hand, the data collection scheme in existing studies was intentionally opportunistic and does not represent a full range of landscape conditions that would allow for inferring the linkages between landscape parameters and P. knowlesi prevalence in NHP across the region as a whole. On the other hand, the absolute majority of existing studies did not have locational precision in reporting results and thus sweeping assumptions about the landscape representation had to be made for the modeling experiment. Finally, the landscape characterization was oversimplified in this study, making it difficult to extract meaningful relationships between the NHP/human intersection on the landscape and the consequences for P. knowlesi malaria transmission and prevalence.

Despite many study limitations, the authors point to the critical importance of understanding vector dynamics in fragmented forested landscapes as the likely primary driver in enhanced malaria transmission. This is an important conclusion particularly when taken together with the emerging evidence of substantially different mosquito biting behaviors than previously reported across various geographic regions.

Another important component of this study is its recognition and focus on the value of geospatial analysis and the availability of geospatial data for understanding complex human/environment interactions to enable monitoring and forecasting potential for zoonotic disease spillover into human populations. More multi-disciplinary focus on disease modeling is of crucial importance for current and future goals of eliminating existing and preventing novel disease outbreaks.

Reviewer #2 (Public Review):

In the study conducted by Verdikt et al, the authors employed mouse Embryonic Stem Cells (ESCs) and in vitro differentiation techniques to demonstrate that exposure to cannabis, specifically Δ9-tetrahydrocannabinol (Δ9-THC), could potentially influence early embryonic development. Δ9-THC was found to augment the proliferation of naïve mouse ESCs, but not formative Epiblast-like Cells (EpiLCs). This enhanced proliferation relies on binding to the CB1 receptor. Moreover, Δ9-THC exposure was noted to boost glycolytic rates and anabolic capabilities in mESCs. The metabolic adaptations brought on by Δ9-THC exposure persisted during differentiation into Primordial Germ Cell-Like Cells (PGCLCs), even when direct exposure ceased, and correlated with a shift in their transcriptional profile. This study provides the first comprehensive molecular assessment of the effects of Δ9-THC exposure on mouse ESCs and their early derivatives. The manuscript underscores the potential ramifications of cannabis exposure on early embryonic development and pluripotent stem cells. However, it is important to note the limitations of this study: firstly, all experiments were conducted in vitro, and secondly, the study lacks analogous experiments in human models.

Reviewer #2 (Public Review):

In the manuscript entitled 'Unveiling the Domain-Specific and RAS Isoform-Specific Details of BRAF Regulation', the authors conduct a series of in vitro experiments using N-terminal and C-terminal BRAF fragments (SPR, HDX-MS, pull-down assays) to interrogate BRAF domain-specific autoinhibitory interactions and engagement by H- and KRAS GTPases. Of the three RAF isoforms, BRAF contains an extended N-terminal domain that has yet to be detected in X-ray and cryoEM reconstructions but has been proposed to interact with the KRAS hypervariable region. The investigators probe binding interactions between 4 N-terminal (NT) BRAF fragments (containing one more NT domain (BRS, RBD, and CRD)), with full-length bacterial expressed HRAS, KRAS as well as two BRAF C-terminal kinase fragments to tease out the underlying contribution of domain-specific binding events. They find, consistent with previous studies, that the BRAF BSR domain may negatively regulate RAS binding and propose that the presence of the BSR domain in BRAF provides an additional layer of autoinhibitory constraints that mediate BRAF activity in a RAS-isoform-specific manner. One of the fragments studied contains an oncogenic mutation in the kinase domain (BRAF-KDD594G). The investigators find that this mutant shows reduced interactions with an N-terminal regulatory fragment and postulate that this oncogenic BRAF mutant may promote BRAF activation by weakening autoinhibitory interactions between the N- and C-terminus.

While this manuscript sheds light on B-RAF specific autoinhibitory interactions and the identification and partial characterization of an oncogenic kinase domain (KD) mutant, several concerns exist with the vitro binding studies as they are performed using tagged-isolated bacterial expressed fragments, 'dimerized' RAS constructs, lack of relevant citations, controls, comparisons and data/error analysis. Detailed concerns are listed below.

1. Bacterial-expressed truncated BRAF constructs are used to dissect the role of individual domains in BRAF autoinhibition. Concerns exist regarding the possibility that bacterial expression of isolated domains or regions of BRAF could miss important posttranslational modifications, intra-molecular interactions, or conformational changes that may occur in the context of the full-length protein in mammalian cells. This concern is not addressed in the manuscript.

2. The experiments employ BRAF NT constructs that retain an MBP tag and RAS proteins with a GST tag. Have the investigators conducted control experiments to verify that the tags do not induce or perturb native interactions?

3. The investigators state that the GST tag on the RAS constructs was used to promote RAS dimerization, as RAS dimerization is proposed to be key for RAF activation. However, recent findings argue against the role of RAS dimers in RAF dimerization and activation (Simanshu et al, Mol. Cell 2023). Moreover, while GST can dimerize, it is unclear whether this promotes RAS dimerization as suggested. In methods for the OpenSPR experiments probing NT BRAF:RAS interactions, it is stated that "monomeric KRAS was flowed...". This terminology is a bit confusing. How was the monomeric state of KRAS determined and what was the rationale behind the experiment? Is there a difference in binding interactions between "monomeric vs dimeric KRAS"?

4. The investigators determine binding affinities between GST-HRAS and NT BRAF domains (NT2 7.5 {plus minus} 3.5; NT3 22 {plus minus} 11 nM) by SPR, and propose that the BRS domain has an inhibitory role HRAS interactions with the RAF NT. However, it is unclear whether these differences are statistically meaningful given the error.

5. It is unclear why NT1 (BSR+RBD+CRD) was not included in the HDX experiments, which makes it challenging to directly compare and determine specific contributions of each domain in the presence of HRAS. Including NT1 in the experimental design could provide a more comprehensive understanding of the interplay between the domains and their respective roles in the HRAS-BRAF interaction. Further, excluding certain domains from the constructs, such as the BSR or CRD, may overlook potential domain-domain interactions and their influence on the conformational changes induced by HRAS binding.

6. The authors perform pulldown experiments with BRAF constructs (NT1: BSR+RBD+CRD, NT2: BSR+RBD, NT3: RBD+CRD, NT4: RBD alone), in which biotinylated BRAF-KD was captured on streptavidin beads and probed for bound His/MBP-tagged BRAF NTs. Western blot results suggest that only NT1 and NT3 bind to the KD (Figure 5). However, performing a pulldown experiment with an additional construct, CRD alone, it would help to determine whether the CRD alone is sufficient for the interaction or if the presence of the RBD is required for higher affinity binding. This additional experiment would strengthen the authors' arguments and provide further insights into the mechanism of BRAF autoinhibition.

7. While the investigators state that their findings indicate that H- and KRAS differentially interact with BRAF, most of the experiments are focused on HRAS, with only a subset on KRAS. As SPR & pull-down experiments are only conducted on NT1 and NT2, evidence for RAS isoform-specific interactions is weak. It is unclear why parallel experiments were not conducted with KRAS using BRAF NT3 & NT4 constructs.

8. The investigators do not cite the AlphaFold prediction of full-length BRAF (AF-P15056-F1) or the known X-ray structure of the BRAF BRS domain. Hence, it is unclear how Alpha-Fold is used to gain new structural information, and whether it was used to predict the structure of the N-terminal regulatory or the full-length protein.

9. In HDX-MS experiments, it is unclear how the authors determine whether small differences in deuterium uptake observed for some of the peptide fragments are statistically significant, and why for some of the labeling reaction times the investigators state " {plus minus} HRAS only" for only 3 time points?

10. The investigators find that KRAS binds NT1 in SPR experiments, whereas HRAS does not. However, the pull-down assays show NT1 binding to both KRAS and HRAS. SI Fig 5 attributes this to slow association, yet both SPR (on/off rates) and equilibrium binding measurements are conducted. This data should be able to 'tease' out differences in association.

11. The model in Figure 7B highlights BSR interactions with KRAS, however, BSR interactions with the KRAS HVR (proximal to the membrane) are not shown, as supported by Terrell et al. (2019).

12. The investigators state that 'These findings demonstrate that HRAS binding to BRAF directly relieves BRAF autoinhibition by disrupting the NT1-KD interaction, providing the first in vitro evidence of RAS-mediated relief of RAF autoinhibition, the central dogma of RAS-RAF regulation. However, in Tran et al (2005) JBC, they report pull-down experiments using N-and C-terminal fragments of BRAF and state that 'BRAF also contains an N-terminal autoinhibitory domain and that the interaction of this domain with the catalytic domain was inhibited by binding to active HRAS'. This reference is not cited.

13. In Fig 2, panels A and C, it is unclear what the grey dotted line in is each plot.

14. In Fig 3, error analysis is not provided for panel E.

15. How was RAS GMPPNP loading verified?

Reviewer #2 (Public Review):

Fuentes et al. provide a detailed and thoughtful commentary on the evolutionary and behavioral implications of complex behaviors associated with a small-brained hominin, Homo naledi. Within the Rising Star Cave of South Africa, Berger et al. 2023a,b proposed evidence that Homo naledi intentionally buried their dead through complex mortuary practices and engaged in symbolic expression by engraving the cave walls in cross-hatching motifs. Two burials were identified in the Rising Star cave subsystems: Feature 1 in the Dinaledi Chamber and a feature in the Hill Antechamber. The engravings are located in the Hill Antechamber near the passageway leading into the Dinaledi chamber. The authors aimed to provide evidence for burials by (1) testing sediment samples for mineral composition from within and outside the burial feature; (2) demonstrating an interruption in the stratigraphy indicative of a "bowl-shaped" feature; (3) evaluating the anatomical coherence of the skeletal remains; (4) demonstrate matrix-supported positioning of skeletal elements; and (5) determine the compatibility of non-articulated material with decomposition and subsequent collapse. Berger et al. 2023b evaluated the engravings through high resolution photography, cross-polarization, and 3D photogrammetry. Neither article involved radiometric dating of materials. While the review by Fuentes et al. highlights important assumptions about the relationship between hominin brain size, cognition, and complex behaviors, the evidence presented by Berger et al. 2023a,b does not support the claim that Homo naledi engaged in burial practices or symbolic expression through wall engravings.

The major weaknesses for Berger et al. 2023a are as follows:

1) The mineral composition from sediment sampled from within Dinaledi Feature 1 is not different compared to the surrounding sediment, which is one rationale proposed by the authors that would lead to the conclusion of a burial pit. An effort to replicate the multivariate statistical analysis using the data provided in SI Table 1 by this reviewer failed, and thus, the results are not replicable.

2) The authors failed to provide clear visualizations or analysis that showed an unambiguous interruption in the stratigraphy surrounding the Dinaledi Feature 1.

3) Attempts 1 and 2 were applied solely to Dinaledi Feature 1, not the Hill Antechamber Feature.

4) Skeletal cohesion does suggest that the bodies were likely covered or protected by external environment. However, given the geological context, there is minimal opportunity for scavengers or other agents to scatter the skeletal remains within such an isolated location. Thus, this alone cannot solely support intentional burials as this line of evidence is subject to equifinality.

5) Similar to the preceding statement, evidence for matrix-supported elements was inconclusive at best. There was no mention of sedimentary rate or expectations for how quickly sediments would naturally bury the remains of whole bodies in the chamber compared with the rate of decomposition of buried remains.

The major weaknesses for Berger et al. 2023b are as follows:

6) While this is incredibly difficult to accomplish, dating rock art or other cave wall engravings is the only method to ensure that the etchings were created during the time of Homo naledi. Unfortunately, this was not attempted. Instead, the authors state that "This description is intended to document the discovery and provide spatial and contextual information prior to any further analyses that may require invasive sampling." Yet, the authors assign a date to the engravings in the title of the paper. Here, the authors are generating interpretations before analyses are attempted.

7) The engravings are indeed very interesting and are likely anthropogenic in origin. However, the argument that these engravings were created by Homo naledi is based on the bold assumption that "No physical or cultural evidence of any other hominin population occurs within this part of the cave system, and there is no evidence that recent humans or earlier hominins ever entered any adjacent area of the cave until surveys by human cave explorers during the last 40 years." (page 6). To assume that no other individual entered the cave system from the time of Homo naledi until 40 years ago is an unrealistic and faulty assumption. This reviewer does not discount that the engravings could have been made by Homo naledi, but the evidence must be sufficient to support this statement or provide other alternatives as working hypotheses.

As a discipline, paleoanthropology aims to understand the evolutionary history of the hominin clade through fossil remains, material culture, and, most recently, ancient DNA. The methods and approaches that we as paleoanthropologists use to understand the past often bridge both the humanities and the hard sciences to create a unique understanding of our shared history. We are only limited by the conditions in which time and attrition has erased pieces of our collective story from the earth. Thus, it is our responsibility to ensure that our interpretations of the past are supported by measurable and testable means, to the best of our ability, and that hypotheses are not presented as conclusions.

Unfortunately, this is not the case for Berger et al. 2023a,b. The work presented by the authors is imprudent and incomplete and does not meet the requirements set forth by our discipline. While it is important that scholars publish their work in a dutiful timeline, it is arguably more critical for scholars to take the necessary time to ensure the integrity and resolution of the work. The consequences for rushing publications with such a significant unsubstantiated find will likely result in perilous ramifications, as it is more difficult to correct an idea than to introduce one.

Reviewer #2 (Public Review):

Patterns scored into or painted on durable media have long been considered important markers of the cognitive capabilities of hominins. More specifically, the association of such markers with Homo sapiens has been used to argue that our evolutionary success was in part shaped by our unique ability to code, store and convey information through abstract conventions.

That singularity of association has been cast into doubt in the last decade with finds of designs apparently painted or carved by Neanderthals, and potentially by even earlier hominins. Even allowing for these developments, however, extending the capability to generate putatively abstract designs to a relatively small-brained hominin like Homo naledi is contentious. The evidential bar for such claims is necessarily high, and I don't believe that it has been cleared here.

The central issue is that the engravings themselves are not dated. As the authors themselves note, the minimum age constraint provided by U/Th on flowstone does not necessarily relate to the last occupation of the Dinaledi cave system, as the earlier ESR age on teeth does not necessarily document first use of the cave. The authors state that "At present we have no evidence limiting the time period across which H. naledi was active in the cave system". On those grounds though, assigning the age range of presently dated material within the cave system to the engravings - as the current title unambiguously does - is not justifiable.

Because we don't know when they were made, the association between the engravings and Homo naledi rests on the assertion that no humans entered and made alterations to the cave system between its last occupation by Homo naledi, and its recent scientific recording. This is argued on page 6 with the statement that "No physical or cultural evidence of any other hominin population occurs within this part of the cave system".

There is an important contrast between the quotes I have referred to in the last two paragraphs. In the earlier quote, the absence of evidence for Homo naledi in the cave system >335 ka and <241 ka is not considered evidence for their absence before or after these ages. Just because we have no evidence that Homo naledi was in the cave at 200 ka doesn't mean they weren't there, which is an argument I think most archaeologists would accept. When it comes to other kinds of humans, though - per the latter quote - the opposite approach is taken. Specifically, the present lack of physical evidence of more recent humans in the cave is considered evidence that no such humans visited the cave until its exploration by cavers 40 years ago. I don't think many archaeologists would consider that argument compelling. I can see why the authors would be drawn to make that assertion, but an absence of evidence cannot be used to argue in one way for use of the cave by Homo naledi and in another way for use of the cave by all other humans.

A second problem is with what Homo naledi might have made engravings. The authors state that "The lines appear to have been made by repeatedly and carefully passing a pointed or sharp lithic fragment or tool into the grooves". The authors then describe one rock with superficial similarities to a flake from the more recent site of Blombos to suggest that sharp-edge stones with which to make the engravings were available to Homo naledi. Blombos is considered relevant here presumably because it has evidence for Middle Stone Age engravings. The authors do not, however, demonstrate any usewear on that stone object such as might be expected if it was used to carve dolomite. Given that it is presented as the only such find in the cave system so far, this seems important.

My greater concern is that the authors did not compare the profile morphology of the Dinaledi engravings with the extensive literature on the morphology of scored lines caused by sharp-edge stone implements (e.g., Braun et al. 2016, Pante et al. 2017). I appreciate that the research group is reticent to undertake any invasive work until necessary, but non-destructive techniques could have been used to produce profiles with which to test the proposition that the engravings were made with a sharp edge stone.

One thing I noticed in this respect is that the engravings seem very wide, both in absolute terms and relative to their depth. The data I collected from the Middle Stone Age engraved ochre from Klein Kliphuis suggested average line widths typically around 0.1-0.2 mm (Mackay and Welz 2008). The engraved lines at Dinaledi appear to be much wider, perhaps 2-5 mm. This doesn't discount the possibility that the engravings in the Dinaledi system were carved with a sharp edge stone - the range of outcomes for such engravings in soft rock can be quite variable (Hodgskiss 2010) - only that detailed analysis should precede rather than follow any assertion about their mode of formation.

None of this is to say that the arguments mounted here are wrong. It should be considered possible that Homo naledi made the engravings in the Dinaledi cave system. The problem is that other explanations are not precluded.

As an example, the western end of the Dinaledi subsystem has a particular geometry to the intersection of its passages, with three dominant orientations, one vertical (which is to say, north-south), and two diagonal (Figure 1). The major lines on Panel A have one repeated vertical orientation and two repeated diagonal orientations (Figure 16), particularly in the upper area not impacted by stromatolites. The lines in both the cave system and engravings in Panel A appear to intersect at similar angles. Several of the cave features appear, superficially at least, to be replicated. In fact, scaled, rotated, and super-imposed, Figure 16 is a plausible 'mud map' of the western end of the Dinaledi system carved incrementally by people exploring the caves. A figure showing this is included here:

Of course, there are problems with this suggestion. The choice of the upper part of Panel A is selective, the similarity is superficial, and the scales are not necessarily comparable. (Note, btw, that all of those caveats hold equally well for the comparison the authors make between the unmodified rock from Dinaledi and the flake from Blombos in Figure 19). However, the point is that such a 'mud map hypothesis' is, as with the arguments mounted in this paper, both plausible and hard to prove.

Having read this paper a few times, I am intrigued by the engravings in the Dinaledi system and look forward to learning more about them as this research unfolds. Based on the evidence presently available, however, I feel that we have no robust grounds for asserting when these engravings were made, by whom they were made, or for what reason they were made.

References:

• Braun, D. R., et al. (2016). "Cut marks on bone surfaces: influences on variation in the form of traces of ancient behaviour." Interface Focus 6: 20160006.

• Hodgskiss, T. (2010). "Identifying grinding, scoring and rubbing use-wear on experimental ochre pieces." Journal of Archaeological Science 37: 3344-3358.

• Mackay, A. & A. Welz (2008). "Engraved ochre from a Middle Stone Age context at Klein Kliphuis in the Western Cape of South Africa." Journal of Archaeological Science 35: 1521-1532.

• Pante, M. C., et al. (2017). "A new high-resolution 3-D quantitative method for identifying bone surface modifications with implications for the Early Stone Age archaeological record." J Hum Evol 102: 1-11.

Reviewer #2 (Public Review):

In this study (Berger et al.), geological and fossil data from the Rising Star Cave System in South Africa are presented to provide evidence for intentional burials of Homo naledi individuals. The authors focus on describing and interpreting what they refer to as "delimited burial features." These features include two located on the floor of the Dinaledi Chamber (referred to as 'Dinaledi Features' 1 and 2) and one from the floor of the Hill Antechamber.

'Dinaledi Feature 1' consists of a collection of 108 skeletal elements recovered from sub-unit 3b deposits. These remains are believed to primarily represent the remains of a single adult individual, along with at least one additional juvenile individual. Although additional anatomical elements associated with 'Dinaledi Feature 1' are mentioned, they are not described as they remain unexcavated. The study states that the spatial arrangement of the skeletal remains is indicative of the primary burial of a fleshed body. On the other hand, 'Dinaledi Feature 2' is not extensively discussed, and its complete extent was not thoroughly investigated.

Regarding the Hill Antechamber feature, it was divided into three separate plaster jackets for removal from the excavation. Through micro-CT and medical CT scans of these plaster jackets, a total of 90 skeletal elements and 51 dental elements were identified. From these data, three individuals were identified, along with a fourth individual described as significantly younger. Individuals 1 and 2 are classified as juveniles.

I feel that there is a significant amount of missing information in the study presented here, which fails to convince me that the human remains described represent primary burials, i.e. singular events where the bodies are placed in their final resting places. Insufficient evidence is provided to differentiate between natural processes and intentional funerary practices. In my opinion, the study should include a section that distinguishes between taphonomic changes and deliberate human modifications of the remains and their context, as well as reconstruct the sequence and timeline of events surrounding death and deposition. A deliberate burial involves a complex series of changes, including decomposition of soft tissues, disruption of articulations between bones, and the sequence of skeletonization. While the geological information is detailed, the archaeothanatological reasoning (see below) is largely absent and, when presented, it lacks clarity and unambiguousness.

My main concern is that the study does not apply or cite the basic principles of archaeothanatology, which combines taphonomy, anatomy, and knowledge of human decomposition to interpret the arrangement of human bones within the Dinaledi Chamber and the Hill Antechamber. Archaeothanatology has been developed since the 1970s (see Duday et al., 1990; Boulestin and Duday, 2005; Duday and Guillon, 2006) and has been widely used by archaeologists and osteologists to reconstruct various aspects such as the original treatment of the body, associated mortuary practices, the sequence of body decomposition, and the factors influencing changes in the skeleton within the burial.

Specifically, the study lacks a description of the relative sequence of joint disarticulation during decomposition and the spatial displacement of bones. A detailed assessment of the anatomical relationships of bones, both articulated and disarticulated, as well as the direction and extent of bone displacement, is missing. For instance, while it is mentioned that "many elements are in articulation or sequential anatomical position," a comprehensive list of these articulated elements and their classification (as labile or not) is not provided.

Furthermore, the patterns described are not illustrated in sufficient detail. If Homo naledi was deliberately buried, it would be crucial to present illustrations depicting the individuals in their burial positions, as well as the representation and proportions of the larger and smaller anatomical elements for each individual. While Figure 2B provides an overall view of 'Dinaledi Feature 1,' it is challenging to determine the relationships of bones, whether articulated or disarticulated, in Figures 2C or 2D. Such information is essential to determine whether the bones are in a primary or secondary position, differentiate between collective and multiple burials, ascertain the body's stage of decomposition at the time of burial, identify postmortem and post-depositional manipulation of the body and grave (e.g., intentional removal of bodies/body parts), and establish whether burial occurred immediately after death or was delayed.

Moreover, the study does not address bone displacements within secondary voids created after the decomposition of soft tissues, nor does it provide assessments of the position of bones within or outside of the original body volume. Factors such as variations in soft tissue volume between individuals of different sizes/corpulence, and the progressive filling (i.e., sediment continually fills newly formed voids) or delayed filling (causing the 'flattening' of the ribcage and 'hyper-flexed' burials, for instance) of secondary open spaces with sediment over time should also be discussed.

In conclusion, while I acknowledge the importance of investigating potential deliberate burials in Homo naledi, I do not think that in its present form, the evidence presented in this study is as robust as it should be.

Reviewer #2 (Public Review):

The authors have addressed most of the concerns. Yet, I still think the authors should at least mention in the article the residues involved in the intra-pore lipid binding pockets for further experimental validation (not only for those residues involve in disease). This is important because the lipid-like density information usually does not come integrated into the PDB structures, so it is not easily accessible for non-structural biologists. The structural data seems solid, and the MD data supports the notion that the GJC is in a putative close state.

Reviewer #2 (Public Review):

The Xerces Blue is an iconic species, now extinct, that is a symbol for invertebrate conservation. Using genomic sequencing of century-old specimens of the Xerces Blue and its closest living relatives, the authors hypothesize about possible genetic indicators of the species' demise. Although the limited range and habitat destruction are the most likely culprits, it is possible that some natural reasons have been brewing to bring this species closer to extinction.

The importance of this study is in its generality and applicability to any other invertebrate species. The authors find that low effective population size, high inbreeding (for tens of thousands of years), and higher fraction of deleterious alleles characterize the Xerces colonies prior to extinction. These signatures can be captured from comparative genomic analysis of any target species to evaluate its population health.

It should be noted that it remains unclear if these genomic signatures are indeed predictive of extinction, or populations can bounce back given certain conditions and increase their genetic diversity somehow.

Methods are detailed and explained well, and the study could be replicated. I think this is a solid piece of work. Interested researchers can apply these methods to their chosen species and eventually, we will assemble datasets to study extinction process in many species to learn some general rules.

Several small questions/suggestions:

1) The authors reference a study concluding that Shijimiaeoides is Glaucopsyche. Their tree shows the same, confirming previous publications. And yet they still use Shijimiaeoides, which is confusing. Why not use Glaucopsyche for all these blues?

2) Plebejus argus is a species much more distant from P. melissa than Plebejus anna (anna and melissa are really very close to each other), and yet their tree shows the opposite. What is the problem? Misidentification? Errors in phylogenetic analyses?

3) Wouldn't it be nicer to show the underside of butterfly pictures that reveals the differences between xerces and others? Now, they all look blue and like one species, no real difference.

4) The authors stated that one of five xerces specimens failed to sequence, and yet they show 5 specimens in the tree. Was the extra specimen taken from GenBank?

Reviewer #2 (Public Review):

Accumulating data suggests that the presence of immune cell infiltrates in the meninges of the multiple sclerosis brain contributes to the tissue damage in the underlying cortical grey matter by the release of inflammatory and cytotoxic factors that diffuse into the brain parenchyma. However, little is known about the identity and direct and indirect effects of these mediators at a molecular level. This study addresses the vital link between an adaptive immune response in the CSF space and the molecular mechanisms of tissue damage that drive clinical progression. In this short report the authors use a spatial transcriptomics approach using Visium Gene Expression technology from 10x Genomics, to identify gene expression signatures in the meninges and the underlying brain parenchyma, and their interrelationship, in the PLP-induced EAE model of MS in the SJL mouse. MRI imaging using a high field strength (11.7T) scanner was used to identify areas of meningeal infiltration for further study. They report, as might be expected, the upregulation of genes associated with the complement cascade, immune cell infiltration, antigen presentation, and astrocyte activation. Pathway analysis revealed the presence of TNF, JAK-STAT and NFkB signaling, amongst others, close to sites of meningeal inflammation in the EAE animals, although the spatial resolution is insufficient to indicate whether this is in the meninges, grey matter, or both.

UMAP clustering illuminated a major distinct cluster of upregulated genes in the meninges and smaller clusters associated with the grey matter parenchyma underlying the infiltrates. The meningeal cluster contained genes associated with immune cell functions and interactions, cytokine production, and action. The parenchymal clusters included genes and pathways related to glial activation, but also adaptive/B-cell mediated immunity and antigen presentation. This again suggests a technical inability to resolve fully between the compartments as immune cells do not penetrate the pial surface in this model or in MS. Finally, a trajectory analysis based on distance from the meningeal gene cluster successfully demonstrated descending and ascending gradients of gene expression, in particular a decline in pathway enrichment for immune processes with distance from the meninges.

Although these results confirm what we already know about processes involved in the meninges in MS and its models and gradients of pathology in sub-pial regions, this is the first to use spatial transcriptomics to demonstrate such gradients at a molecular level in an animal model that demonstrates lymphoid like tissue development in the meninges and associated grey matter pathology. The mouse EAE model being used here does reproduce many, although not all, of the pathological features of MS and the ability to look at longer time points has been exploited well. However, this particular spatial transcriptomics technique cannot resolve at a cellular level and therefore there is a lot of overlap between gene expression signatures in the meninges and the underlying grey matter parenchyma.

The short nature of this report means that the results are presented and discussed in a vague way, without enough molecular detail to reveal much information about molecular pathogenetic mechanisms.

The trajectory analysis is a good way to explore gradients within the tissues and the authors are to be applauded for using this approach. However, the trajectory analysis does not tell us much if you only choose 2 genes that you think might be involved in the pathogenetic processes going on in the grey matter. It might be more useful to choose some genes involved in pathogenetic processes that we already know are involved in the tissue damage in the underlying grey matter in MS, for which there is already a lot of literature, or genes that respond to molecules we know are increased in MS CSF, although the animal models may be very different. Why were C3 and B2m chosen here?

Strengths:<br /> - The mouse model does exhibit many of the features of the compartmentalized immune response seen in MS, including the presence of meningeal immune cell infiltrates in the central sulcus and over the surface of the cortex, with the presence of FDC's HEVs PNAd+ vessels and CXCL13 expression, indicating the formation of lymphoid like cell aggregates. In addition, disruption of the glia limitans is seen, as in MS. Increased microglial reactivity is also present at the pial surface.<br /> - Spatial transcriptomics is the best approach to studying gradients in gene expression in both white matter and grey matter and their relationship between compartments.<br /> - It would be useful to have more discussion of how the upregulated pathways in the two compartments fit with what we know about the cellular changes occurring in both, for which presumably there is prior information from the group's previous publications.

Limitations:<br /> - EAE in the mouse is not MS and may be far removed when one considers molecular mechanisms, especially as MS is not a simple anti-myelin protein autoimmune condition. Therefore, this study could be following gene trajectories that do not exist in MS. This needs a significant amount of discussion in the manuscript if the authors suggest that it is mimicking MS.<br /> - The model does not have the cortical subpial demyelination typical of MS and it is unknown whether neuronal loss occurs in this model, which is the main feature of cytokine-mediated neurodegeneration in MS. If it does not then a whole set of genes will be missing that are involved in the neuronal response to inflammatory stimuli that may be cytotoxic.<br /> - Visium technology does not get down to single cell level and does not appear to allow resolution of the border between the meninges and the underlying grey matter.<br /> - Neuronal loss in the MS cortex is independent of demyelination and therefore not related to remyelination failure. There does not appear to be any cortical grey matter demyelination in these animals, so it is difficult to relate any of the gene changes seen here to demyelination.<br /> - No mention of how the ascending and descending patterns of gene expression may be due to the gradient of microglial activation that underlies meningeal inflammation, which is a big omission.

Reviewer #2 (Public Review):

The authors succeed in generalizing the pre-alignment procedure for their cell identification method to allow it to work effectively on data with only small subsets of cells labeled. They convincingly show that their extension accurately identifies head angle, based on finding auto fluorescent tissue and looking for a symmetric l/r axis. They demonstrate that the method works to identify known subsets of neurons with varying accuracy depending on the nature of underlying atlas data. Their approach should be a useful one for researchers wishing to identify subsets of head neurons in C. elegans, for example in whole brain recording, and the ideas might be useful elsewhere.

The authors also strive to give some general insights on what makes a good atlas. It is interesting and valuable to see (at least for this specific set of neurons) that 5-10 ideal examples are sufficient. However, some critical details would help in understanding how far their insights generalize. I believe the set of neurons in each atlas version are matched to the known set of cells in the sparse neuronal marker, however this critical detail isn't explicitly stated anywhere I can see. In addition, it is stated that some neuron positions are missing in the neuropal data and replaced with the (single) position available from the open worm atlas. It should be stated how many neurons are missing and replaced in this way (providing weaker information). It also is not explicitly stated that the putative identities for the uncertain cells (designated with Greek letters) are used to sample the neuropal data. Large numbers of openworm single positions or if uncertain cells are misidentified forcing alignment against the positions of nearby but different cells would both handicap the neuropal atlas relative to the matched florescence atlas. This is an important question since sufficient performance from an ideal neuropal atlas (subsampled) would avoid the need for building custom atlases per strain.

Reviewer #2 (Public Review):

This manuscript presents a comprehensive investigation into the role of condensin complexes in telomere segregation in fission yeast. The authors employ chromatin immunoprecipitation analysis to demonstrate the enrichment of condensin at telomeres during anaphase. They then use condensin conditional mutants to confirm that this complex plays a crucial role in sister telomere disjunction as well as the unclustering of telomeric regions from the preceding Rabl configuration. Interestingly, they show that condensin's role in telomere disjunction is unlikely related to catenation removal but rather related to the organization of telomeres in cis and/or the elimination of structural constraints or proteins that hinder separation.

The authors also investigate the regulation of condensin localization to telomeres and reveal the involvement of the shelterin subunit Taz1 in promoting condensin's association with telomeres while demonstrating that the chromatin remodeler Mit1 prevents excessive loading of condensin onto telomeres. Finally, they show that cohesin acts as a negative regulator of telomere separation, counteracting the positive effects of condensin.

Overall, the manuscript is well-executed, and the authors provide sufficient supporting evidence for their claims. There are a couple of aspects that arise from this study that when fully elucidated will lead to a mechanistic understanding of important biological processes. For instance, the exact mechanism by which Taz1 affects condensin loading or the mechanistic link between cohesin and condensin, especially in the context of their opposing roles, are exciting prospects for the future and it is possible that future work within the context of telomeres might provide valuable insights into this question.

Another crucial point emphasized by the manuscript is that the role of condensin in telomere segregation extends beyond facilitating catenation removal.

Reviewer #2 (Public Review):

Antibody-dependent enhancement (ADE) of Dengue is largely driven by cross-reactive antibodies that target the DENV fusion loop or pre-membrane protein. Screening polyclonal sera for antibodies that bind to these cross-reactive epitopes could increase the successful implementation of a safe DENV vaccine that does not lead to ADE. However, there are few reliable tools to rapidly assess the polyclonal sera for epitope targets and ADE potential. Here the authors develop a live viral tool to rapidly screen polyclonal sera for binding to fusion loop and pre-membrane epitopes. The authors performed a deep mutational scan for viable viruses with mutations in the fusion loop (FL). The authors identified two mutations functionally tolerable in insect C6/36 cells, but lead to defective replication in mammalian Vero cells. These mutant viruses, D2-FL and D2-FLM, were tested for epitope presentation with a panel of monoclonal antibodies and polyclonal sera. The D2-FL and D2-FLM viruses were not neutralized by FL-specific monoclonal antibodies demonstrating that the FL epitope has been ablated. However, neutralization data with polyclonal sera is contradictory to the claim that cross-reactive antibody responses targeting the pre-membrane and the FL epitopes wane over time.

Overall the central conclusion that the engineered viruses can predict epitopes targeted by antibodies is supported by the data and the D2-FL and D2-FLM viruses represent a valuable tool to the DENV research community.

Reviewer #2 (Public Review):

In the present study, Masson et al. provide an elegant and profound demonstration of utilization of systems genetics data to fuel discovery of actionable therapeutics. The strengths of the study are many: generation of a novel skeletal muscle genetics proteomic dataset which is paired with measures of glucose metabolism in mice, systematic utilization of these data to yield potential therapeutic molecules which target insulin resistance, cross-referencing library screens from connectivity map with an independent validation platform for muscle glucose uptake and preclinical data supporting a new mechanism for thiostrepton in alleviating muscle insulin resistance. Future studies evaluating similar integrations of omics data from genetic diversity with compound screens, as well as detailed characterization of mechanisms such as thiostrepton on muscle fibers will further inform some remaining questions. In general, the thorough nature of this study not only provides strong support for the conclusions made but additionally offers a new framework for analysis of systems-based data. I had made several comments on the prior submission, all of which have been fully addressed and incorporated.

Reviewer #2 (Public Review):

This study is carefully designed and well executed, including a comprehensive suite of endpoint measures and large sample sizes that give confidence in the results. I have a few general comments and suggestions that the authors might find helpful.

1) I found it difficult to fully grasp the experimental design, including the length of light treatment in the three different experiments (which appears to extend from 2 weeks up to 8 weeks). A graphical description of the experimental design along a timeline would be very helpful to the reader. I suggest adding the respective sample sizes to such a graphic, because this information is currently also difficult to keep track of.

2) The authors use a lot of terminology that is second nature to a chronobiologist but may be difficult for the general reader to keep track of. For example, what is the difference between "photoinducibility" and "photosensitivity"? Similarly, "vernal" and "autumnal" should be briefly explained at the outset, or maybe simply say "spring equinox" and "fall equinox."

3) What was the rationale for using only male birds in this study? The authors may want to include a brief discussion on whether the expected results for females might be similar to or different from what they found in males, and why.

4) The authors used the Bonferroni correction method to account for multiple hypothesis testing of measures of testes mass, body mass, fat score, vimentin immunoreactivity and qPCR analyses in Study 1. I don't think Bonferroni is ever appropriate for biological data: these methods assume that all variables are independent of each other, an assumption that is almost never warranted in biology. In fact, the data show clear relationships between these endpoint measures. Alternatively, one might use Benjamini-Hochberg's FDR correction or various methods for calculating the corrected alpha level.

5) The graphical interpretations of the results shown in Figure 1n and Figure 3e, along with the hypothesized working model shown in Figure S5, might best be combined into a single figure that becomes part of the Discussion. As is, I do not think these interpretative graphics (which are well done and super helpful!) are appropriate for the Results section.

Reviewer #2 (Public Review):

The authors applied existing ReadZS and the SpliZ methods, previously developed to analyze RNA process in scRNA-seq data, to Visium data to study spatial splicing and RNA processing events in tissues by Moran's I. The authors showed several example genes in mouse brain and kidney, whose processing are spatially regulated, such as Rps24, Myl6, Gng13.

The paper touches on an important question in RNA biology about how RNA processing is regulated spatially. Both experimental and computational challenges remain to address it. Despite some potentially interesting findings, most claims remain to be validated by orthogonal methods such as RNA FISH and simulations. In addition, the percentage of spatial processing events (splicing in 0.8-2.2% of detected genes, i.e. 8-17 genes and RNA processing in 1.1-5.5% of detected genomic windows, i.e. 57-161 windows) discovered is low. Does it suggest that most of RNA processing events were not spatially regulated across the tissue? Or does it question the assumption of treating spatial transcriptomics data similar to scRNA-seq data? The unique features for ST data, such as mixture of neighboring cells, different capture biases and much smaller number of spots (pseudo cells here), may have significant effects on the power of scRNA-seq based methods, but it is not discussed in the manuscript. The lack of careful evaluation and low discovery rates could limit application of the approach to other tissues and subcellular data.

Reviewer #2 (Public Review):

This manuscript by Touray, et al. provides a significant new twist to our understanding of how antigenic variation may be regulated in T. brucei. Key aspects of antigenic variation are the mutually exclusive expression of a single antigen per cell and the periodic switching from expression of one antigen isoform to another. In this manuscript, the authors show, as they have previously shown, that depletion of the nuclear phosphatidylinositol 5-phosphatase (PIP5Pase) results in a loss of mutually exclusive VSG expression. Furthermore, using ChIP-seq, the authors show that the repressor/activator protein 1 (RAP1) binds to regions upstream and downstream of VSG genes located in transcriptionally repressed expression sites and that this binding is lost in the absence of a functional PIP5Pase. Importantly, the authors decided to further investigate this link between PIP5Pase and RAP1, a protein that has previously been implicated in antigenic variation in T. brucei, and found that inactivation of PIP5Pase results in the accumulation of PI(3,4,5)P3 bound to the RAP1 N-terminus and that this binding impairs the ability of RAP1 to bind DNA. Based on these observations, the authors suggest that the levels of PI(3,4,5)P3 may determine the cellular function of RAP1, either by binding upstream of VSG genes and repressing their function, or by not binding DNA and allowing the simultaneous expression of multiple VSG genes in a single parasite.

While I find most of the data presented in this manuscript compelling, there are aspects of Figure 1 that are not clear to me. Based on Figure 1F, the authors claim that transient inactivation of PIP5Pase results in a switch from the expression of one VSG isoform to another. However, I am not exactly sure what the authors are showing in this panel, nor do the data in Figure 1F seem to be consistent with those shown in Figure 1C. Based on Figure 1F, a transient inactivation of PIP5Pase appears to result in an almost exclusive switch to a VSG located in BES12. However, based on Figure 1E, the VSG transcripts most commonly found after a transient inactivation of PIP5Pase are those from the previously active VSG (BES1) and VSGs located on chr 1 and 6 (I believe). The small font and the low resolution make it impossible to infer the location of the expressed VSG genes, nor to confirm that ALL VSG genes located in expression sites are activated, as the authors claim. Also, I was not able to access the raw ChIP-seq and RNA-seq reads. Thus, could not evaluate the quality of the sequencing data.

Reviewer #2 (Public Review):

The authors develop SPRAWL (Subcellular Patterning Ranked Analysis With Labels), a statistical framework to identify cell-type specific subcellular RNA localization from multiplexed imaging datasets. The tool is able to assign to each gene and in each annotated cell type, a score (with a p-value) that measures:<br /> - Peripheral/central localization of RNAs within the cell, based on a previous segmentation step defining cell boundaries and the centroid coordinate.<br /> - Radial/punctuate localization of RNAs within the cell

The method is applied to three multiplexed imaging datasets, identifying defined and cell-type specific patterns for several transcripts.

In the second part of the manuscript, the authors couple SPRAWL with ReadZS, a computational tool developed by the same group and recently published (Meyer et al, 2022). Starting from single-cell datasets, ReadZS is able to quantify 3'UTR length in each cell type. The authors find a subset of genes showing a positive, or negative correlation between the predicted localization and the predicted 3'UTR length across cell types.

Strengths:<br /> As the authors state in the introduction, the study of subcellular RNA localization, with the characterization of organizational principles and of molecular regulation mechanisms, is extremely relevant. The authors develop a strategy to detect statistically significant and non-random patterns of RNA sub-cellular localization in MERFISH and SeqFISH+ datasets, i.e. emerging platforms producing spatially resolved maps of hundreds of transcripts with cellular resolution.

Weaknesses:<br /> Although the method and the presented results have strengths in principle, the main weakness of the paper is that these strengths are not directly demonstrated. That is, insufficient validations are performed to show the biological significance of the results and to fully support the key claims in the manuscript by the data presented.

In particular, the authors imply that their tool is unique and not comparable to any other method. Therefore there is no comparison of SPRAWL with any other method. For example, a comparison could be made with Baysor (Petukhov, V et al. Nat Biotechnol. https://doi.org/10.1038/s41587-021-01044-w). According to the authors, this method is able to identify "small molecular neighbourhoods with stereotypical transcriptional composition" and provides a "General approach for statistical labeling of spatial data".

The authors claim that SPRAWL is able to identify spatial patterns of localization and generated relevant hypotheses to be tested, yet the manuscript contains little proof that the results have biological significance (for example association of RNAs with specific subcellular compartments) and there is no experimental validation for the results obtained applying this method.

The correlation between localization scores and 3'UTR length across cell types for certain genes is also not experimentally validated: results are based on inference from single-cell or imaging data, with no complementary experimental validation.

It is therefore very difficult to assess the biological relevance of the results produced by SPRAWL.

Reviewer #2 (Public Review):

The manuscript by Ma et al, "Two RNA-binding proteins mediate the sorting of miR223 from mitochondria into exosomes" examines the contribution of two RNA-binding proteins on the exosomal loading of miR223. The authors conclude that YBX1 and YBAP1 work in tandem to traffic and load miR223 into the exosome. The manuscript is interesting and potentially impactful. It proposes the following scenario regarding the exosomal loading of miR223: (1) YBAP1 sequesters miR223 in the mitochondria, (2) YBAP1 then transfers miR223 to YBX1, and (3) YBX1 then delivers miR223 into the early endosome for eventual secretion within an exosome. While the authors propose plausible explanations for this phenomenon, they do not specifically test them and no mechanism by which miR223 is shuttled between YBAP1 and YBX1, and the exosome is shown. Thus, the paper is missing critical mechanistic experiments that could have readily tested the speculative conclusions that it makes.

Comments:<br /> 1. The major limitation of this paper is that it fails to explore the mechanism of any of the major changes it describes. For example, the authors propose that miR223 shuttles from mitochondrially localized YBAP1 to P-body-associated YBX1 to the exosome. This needs to be tested directly and could be easily addressed by showing a transfer of miR223 from YBAP1 to YBX1 to the exosome.<br /> 2. If YBAP1 retains miR223 in mitochondria, what is the trigger for YBAP1 to release it and pass it off to YBX1? The authors speculate in their discussion that sequestration of mito-miR223 plays a "role in some structural or regulatory process, perhaps essential for mitochondrial homeostasis, controlled by the selective extraction of unwanted miRNA into RNA granules and further by secretion in exosomes...". This is readily testable by altering mitochondria dynamics and/or integrity.<br /> 3. Much of the miRNA RT-PCR analysis is presented as a ratio of exosomal/cellular. This particular analysis assumes that cellular miRNA is unaffected by treatments. For example, Figure 1a shows that the presence of exosomal miR223 is significantly reduced when YBX1 is knocked out. This analysis does not consider the possibility that YBX1-KO alters (up or down-regulates) intracellular miR223 levels. Should that be the case, the ratiometric analysis is greatly skewed by intracellular miRNA changes. It would be better to not only show the intracellular levels of the miRs but also normalize the miRNA levels to the total amount of RNA isolated or an irrelevant/unchanged miRNA.<br /> 4. In figure 1, the authors show that in YBX1-KO cells, miR223 levels are decreased in the exosome. They further suggest this is because YBX1 binds with high affinity to miR223. This binding is compared to miR190 which the authors state is not enriched in the exosome. However, no data showing that miR190 is not present in the exosome is shown. A figure showing the amount of cellular and exosomal miR223 and 190 should be shown together on the same graph.<br /> 5. Figure 2 Supplement 1 - As to determine the nucleotides responsible for interacting with YBX1, the authors made several mutations within the miR223 sequence. However, no explanation is given regarding the mutant sequences used or what the ratios mean. Mutant sequences need to be included. How do the authors conclude that UCAGU is important when the locations of the mutations are unclear? Also, the interpretation of this data would benefit from a binding affinity curve as shown in Fig 2C.<br /> 6. While the binding of miR223mut to YBX1 is reduced, there is still significant binding. Does this mean that the 5nt binding motif is not exact? Do the authors know if there are multiple nucleotide possibilities at these positions that could facilitate binding? Perhaps confirming binding "in vivo" via RIP assay would further solidify the UCAGU motif as critical for binding to YBX1.<br /> 7. Figures 2g, h - It would be nice to show that miR190mut also packages in the cell-free system. This would confirm that the sequence is responsible. Also, to confirm that the sorting of miR223 is YBX1-dependent, a cell-free reaction using cytosol and membranes from YBX1 KO cells is needed.<br /> 8. In Figure 3a, the authors show that miR223 is mitochondrially localized. Does the sequence of miR223 (WT or Mut) matter for localization? Does it matter for shuttling between YBAP1 and YBX1?<br /> 9. Supplement 3c - Is it strange that miR190 is not localized to any particular compartment? Is miR190 present ubiquitously and equally among all intracellular compartments?<br /> 10. Figure 3h - Why would the miR223 levels increase if you remove mitochondria? Does CCCP also cause miR223 upregulation? I would have thought miR223 would just be mis-localized to the cytosol.<br /> 11. Figure 3i - What is the meaning of "Urd" in the figure label? This isn't mentioned anywhere.<br /> 12. Figure 3j - The data is presented as a ratio of EV/cell. Again, this inaccurately represents the amount of miR223 in the EV. This issue is apparent when looking at Figures 3h and 3j. In 3h, CCCP causes an upregulation of intracellular miR223. As such, the presumed decrease in EV miR233 after CCCP (3j) could be an artifact due to increased levels of intracellular miR223. Both intracellular and EV levels of miRs need to be shown.<br /> 13. In Figure 4, the authors show that when overexpressed, YBX1 will pulldown YBAP1. Can the authors comment as to why none of the earlier purifications show this finding (Figure 1 for example)? Even more curious is that when YBAP1 is purified, YBX1 does not co-purify (Figure 4 supplement 1a, b).<br /> 14. Figure 4f, g - The text associated with these figures is very confusing, as is the labeling for the input. Also, what is "miR223 Fold change" in this regard? Seeing as your IgG should not have IP'd anything, normalizing to IgG can amplify noise. As such, RIP assays are typically presented as % input or fold enrichment.<br /> 15. Figure 4h - The authors show binding between miR223 and YBAP1 however it is not clear how significant this binding is. There is more than a 30-fold difference in binding affinity between miR223 and YBX1 than between miR223 and YBAP1. Even more, when comparing the EMSAs and fraction bound from figures 1 and 2 to those of Figure 4h, the binding between miR223 and YBAP1 more closely resembles that of miR190 and YBX1, which the authors state is a non-binder of YBX1. The authors will need to reconcile these discrepancies.<br /> 16. Can the authors present the Kd values for EMSA data?<br /> 17. Figure 5 - Does YBAP1-KO affect mitochondrial protein integrity or numbers?<br /> 18. Figure 6a - Are the authors using YBAP1 as their mitochondrial marker? Please include TOM20 and/or 22.<br /> 19. Figure 6b - Rab5 is an early endosome marker and may not fully represent the organelles that become MVBs. Co-localization at this point does not suggest that associating proteins will be present in the exosome, and it is possible that the authors are looking at the precursor of a recycling endosome. Even more, exosome loading does not occur at the early endosome, but instead at the MVB. Perhaps looking at markers of the late endosome such as Rab7 or ideally markers of the MVB such as M6P or CD63 would help draw an association between YBX1, YBAP1, and the exosome. Also, If the authors want to make the claim that interactions at the early endosome leads to secretion as an exosome, the authors should show that isolated EVs from Rab5Q79L-expressing cells contain miR223.<br /> 20. The mentioning of P-bodies is interesting but at no time is an association addressed. This is therefore an overly speculative conclusion. Either show an association or leave this out of the manuscript.<br /> 21. In lines 55-58, the authors make the comment "However, many of these studies used sedimentation at ~100,000 g to collect EVs, which may also collect RNP particles not enclosed within membranes which complicates the interpretation of these data." Do RNPs not dissolve when secreted? Can the authors give a reference for this statement?

Reviewer #2 (Public Review):

The authors tested TTFields' effect on TNT formation in two mesothelioma cell lines, MSTO-211H and VMAT. The MSTO-211H is a biphasic cell line with epithelioid and sarcomatoid features while VMAT only has sarcomatoid morphology. They treated their cell lines at 150 or 200 kHz either unidirectionally or bidirectionally. The experiments took place within 72 hours of plating, after which the cells will become confluent on coverslips and their TNT formation drops.

Under these experimental conditions, they found: (i) Unidirectional is more effective than bidirectional TTFields in reducing TNT formation, (ii) TNT formation was markedly reduced after 48 hours of treatment in MSTO-211H but not VMAT cells, (iii) no difference in actin polymerization or actin filament bundling after one hour of TTFields treatment, (iv) reduced TNT formation when TTFields were combined with cisplatin but not with both cisplatin and pemetrexed, (v) analysis TNT cargo transport using markers of gondolas and mitochondria did not show changes in transport velocity, and (vi) in vivo spatial transcriptomic analysis revealed EMT markers and immunogenic markers.

Reviewer #2 (Public Review):

I've read the manuscript by Shin et al with great interest. The authors describe the identification of O-GlcNAcylation of DNMT1 and the impact this modification has on the maintenance activity of DNMT1 genome-wide and that modification of S878 leads to enzyme inhibition.<br /> The manuscript is written in a clear and understandable way making it easy for the reader to understand the logic as well as the steps of the experimental approach.

The authors identify O-GlcNAcylation of DNMT1 in a number of different cell lines by combining inhibition studies and WB and further on they identify the modification sites with LC/MS, predictions, and mutational studies. I really like the experimental approach, which while being straightforward (albeit technically challenging), is powerful and well-controlled in this case to unequivocally prove the modification of DNMT1 and identify the site. However, mutation of the two identified modification sites does not remove all the O-GlcNAcylation signal associated with DNMT1, thus possibly not all the possible sites were identified. While this is not a criticism of this manuscript, it would be interesting to know what other sites are modified and the enzymatic/biological effects associated.

Also, the authors isolate the modified DNMT1 from cells using immunoprecipitation, which is indeed useful to study the changes in catalytic activity but does not provide any information if the cellular localisation of modified DNMT1 changes. Subsequently, the authors checked the impact of high glucose diet on the genome-wide DNA methylation patterns. The observed effects (Fig 4A) are very strong, almost as strong as observed with Aza treatment and therefore I wonder if LINE/IAP or other elements are getting activated (as observed with genome-wide demethylation with Aza). Do the authors see any changes in cell phenotype, slower/faster proliferation, or increased apoptosis due to the activation of mobile elements (not only ROS)? Another point is that the S878A mutant seems not to be able to fully maintain the DNA methylation (Fig 4A). Does O-GlcNAcylation recruit any additional interactors? Given that the authors immunoprecipitated DNMT1 and use it for activity assay, it is possible, that the modification attracts an additional protein factor that could in turn inhibit DNMT1 activity (as observed). Therefore, the observed kinetic effect could be indirect, while still interesting and important, the mechanism of inhibition would be different.

DNA methylation clock can be used to estimate the biological age of a tissue/cells. While not directly in the line of the manuscript, I was wondering if the DNA methylation changes in the high glucose diet would affect the methylation sites used for the DNAme clock. Meaning, would the cells/tissue epigenetically age faster when in high glucose media, and if the Ala mutant could provide resistance to that?

In discussion, the authors write that this is the first investigation of O-GlcNAcylation in relation to DNA methylation, while this is true for DNMTs, TET enzymes, that oxidise 5mC and trigger active DNA demethylation have been shown before to also be modified.

A nice and rigorous study, with important observations and connections to biological effects. It would be nice to prove that the effects are direct and not associated with other factors that could be recruited by the modification and impact the activity of DNMT1. I find it a bit surprising that phosphorylation of the target serine does not impact DNMT1 activity as well.

Reviewer #2 (Public Review):

Fuzzell et al. conducted a mixed-method study looking into the possible impact of COVID-19 on clinician perceptions of cervical cancer screening. The authors examined how the pandemic-related staffing changes might have affected the screening and abnormal results follow-up during the period October 2021 through July 2022.

They found that 80% of the clinicians experienced decreased screening during the start of the pandemic and that ≈67% reported a return to pre-pandemic levels. The general barriers for not returning to pre-pandemic levels were staffing shortages and problems with structural systems for tracking overdue patients and those in need of follow-up after abnormal screening tests.

Strengths:

There is a high focus on the consequences and the need for action to prevent the ongoing impact of COVID-19 on cervical cancer screening. Some of the actions mentioned by the authors could be the use of HPV self-sampling kits, and it is interesting to be provided knowledge on the clinicians' views on HPV self-sampling. Both are of high interest to the general population in the US. Throughout the discussion, the authors and their claims are supported by other studies.

Weaknesses:

The lack of a National representative sample, where 63% of the responding clinicians were practicing in the Northeast, affects the possibility of generalization of the results found in the study. The overrepresentation of white females is not addressed in the discussion. This composition could have affected the results, especially when the authors report a need to look at higher salaries and better childcare to maintain adequate staffing.

The conclusions are mostly supported by the data, however, some aspects of the data analysis need to be clarified.