Reviewer #3 (Public Review):

The authors critically assessed a widespread assumption that paternal biases in the number of germline mutations passed to offspring and the number of germline cell divisions have a causal link. They gather a diverse set of previously published findings that are inconsistent with this assumption, including the accumulation of maternal DNMs with age, the consistent ratio of paternal-to-maternal germline mutation (α) in humans, the range of α in mammals, and the dominance of mutational processes that are uncorrelated to cell division in human germline and somatic tissues. They then generate estimates of α based on evolutionary rates at sex chromosomes vs autosomes. They find αevo of 1-4 across the species considered, which are robust to changes/exclusion of a number of potentially confounding factors. They find an increase in αevo with generation time in mammals but not in birds. The authors consider and evaluate a model with a fixed number of early mutations for both sexes followed by post sexual differentiation stage with a paternal mutation bias.

Reviewer #3 (Public Review):

In this manuscript, Baumgartner et al investigated how cells control Rhino specific deposition on only a subset of the H3K9me3 chromatin domains to specify piRNA source loci. They identified a previously unknown protein, Kipferl, which by interacting with the chromodomain of Rhino guides and stabilizes its specific recruitment to selected piRNA source loci. Kipferl would be preferentially recruited to Guanine-rich DNA motifs. They show that in Kipferl mutant flies, Rhino nuclear subcellular localization and Rhino's chromatin occupancy changes dramatically. Then, they dissect all the domains of the Kipferl protein and show that the Rhino- and DNA-binding activities can be separated and that the 4th ZnF of Kipferl is required to interact with Rhino.

It is a very elegant genetic work (CRISPR-edited, rescue, KD, overexpression fly lines). In addition, the authors used a combination of yeast two hybrid screen, ChIP, small-RNA-seq and imaging to dissect the function of this new protein. The data in this paper are compelling. Some conclusions might be more moderate. Even if the effect of Kipfler on 80F (Rhino binding, piRNA production) is very obvious, this study also clearly demonstrates that other protagonists are required for the specific binding of Rhino to other piRNA source loci (including 42AB and 38C).

- Is Kipferl expressed early during oogenesis development? If Kipferl starts to be expressed only after the GSCs and cystoblast stage, Kipferl is probably not required to determine the specification of piRNA source loci identity but probably more for the maintenance of the specification. Could the authors discuss or comment on that?

- To perform most of their ChIP-seq analysis, the authors have divided the genome into pericentromeric heterochromatin and euchromatin based on H3K9me3 ChIP-seq data performed on ovaries. With this classification the 42AB (2R:6,256,844-6,499,214) and the 38C (2L:20148259-20227581) piRNA clusters known to be heterochromatic fall in the euchromatic part of the genome. Was there a problem with the annotation?

- Some regions exist in euchromatin that are strongly enriched in Rhino, in Kipferl and in H3K9me3 but are not producing piRNA. Does this type of region exist in heterochromatin?

- Kipferl has been identified to interact with Rhino by a yeast two-hybrid screen (Figure 2). A co-IP which is the classical method for confirming the occurrence of this intracellular Rhino-Kipferl interaction should be provided.

- Rhino is known to homodimerize and it has been reported that this homodimerization is important for its binding to H3K9me3 (Yu et al, Cell Res 2015). It is surprising not to find Rhino among the interactors that were picked up from the screen. Do the authors have any explanations or at least comments on these results?

- In Kip mutants, the delocalization of Rhino to a very large structure at the nuclear periphery is a very clear phenotype (Figure 3). All the very elegant genetic controls are provided. This particular localization of Rhino is correlated with an increase in 1.688 Satellite expression and a colocalization of Rhino and the 1.688 RNAs in the nucleus. The authors propose that this increase is consistent with an elevated Rhino occupancy at 1.688 satellites. The authors should moderate their statements in the light of the results of ChIP experiments. Rhino is maintained on these loci in Kip mutants but an increase is not very clearly observed. Couldn't it be the RNA and not the DNA of this 1.688 region traps Rhino? The same in situ experiment should be performed after an RNAse treatment. The delocalization of Rhino is lost in the Kipferl, nxf3 double mutant flies. What is the chromosomal Rhino distribution in this context? Is the increase in nascent transcripts of 1.688 satellites lost?

- The level of some Rhino dependent germline TE piRNAs is affected in Kipferl GLKD. Is there a direct correlation between TEs which lost piRNAs and those for which the level of transcripts increases (Diver, 3S18, Chimpo, HMS Beagle, flea, hobo) ?

- Figure 5E, it seems that Kipferl binding is also dependent on Rhino. All the presented loci have much less binding of Kip in Rhino -/- (The scale for the 42AB locus should be the same between the Rhino -/- and the control MTD w-sh). In addition, the distribution of Rhino in the Kipferl-sh on the 42AB is maintained but seems to be different. Could the authors discuss these points?

- It is not clear why the authors focus only on Kipferl binding sites in a Rhino mutant in the Figure 5D? Even if the authors mention in the text that "Kipferl binding sites in Rhino mutants ... often coincided with regions bound by Kipferl and Rhino in wildtype ovaries" it should be added the same analysis presented in figure 5D centered on Kipferl peaks detected in ChIP experiments in WT condition in the different genotypes.

- There is a discrepancy between the results found Figure 3A and Supp figure 3B. In the Rhino mutant the level of Kipferl protein does not seem to be affected whereas in the Rhino GLKD, there is a strong decrease of Kipferl protein. The authors completely elude this point.

- Comparing the figure 5E and the figure 6G presenting both the 80F piRNA cluster, depending of the scale and the control line that was chosen to illustrate the results we can draw different conclusions. In the figure 5E we can conclude that le level of Kipferl decreases on the 80F locus in Rhino (-/-) compared to the control MTD w-sh, whereas in the figure 6G we can conclude that the level of Kipferl is similar in the Rhino (-/-) compared to the control w1118.

- gypsy8 or RT1b are enriched in GRGG motifs and are also the ones that among Rhino-independent Kipferl enrichment are the most Rhino enriched. Are these 2 elements present in the 80F cluster? Are these two elements derepressed upon Kipferl GLKD ? Where are these two elements in the figure presenting the change in TE transcript level upon Kipferl GLKD?

Reviewer #3 (Public Review):

This is an exciting new cryoEM structure of the HOPS tethering complex, which is necessary for membrane fusion at the vacuole/lysosome in eukaryotic cells. Finally, we can visualize, at moderate resolution, the positioning of HOPS subunits with respect to each other, and predict how HOPS and its various binding partners, such as Rab GTPases and SNAREs, can interact and control fusion. A conceptual advance put forward by this structure seems to be a rigid central core of HOPS that may contribute to helping drive the efficiency of the SNARE-mediated fusion mechanism.

As exciting as this new structure is, however, the study seems to fall a bit short of its promise to explain "why tethering complexes are an essential part of the membrane fusion machinery, or how HOPS "catalyzes fusion." As such, the title is also misleading with regard to HOPS being the "lysosomal membrane fusion machinery."

Overall, the manuscript could benefit greatly, especially for a non-HOPS specialist reader, in providing more introduction and context to the complex and tethering/fusion mechanisms in general. Additionally, the examination of the structure, in light of decades of biochemistry and cell biology studies of HOPS (and homologous proteins that regulate fusion), seems superficial and suggests that deeper analyses may reveal additional insights and lead to a more detailed and impactful model for HOPS function. Moreover, are the insights gained here applicable to other tethering complexes, why or why not?

Reviewer #3 (Public Review):

PME-1 catalyzes the removal of carboxyl methylation of the PP2A catalytic subunit and negatively regulates PP2A activity. Like the PP2A methyltransferase LCMT-1, PME-1 was previously thought to act only on the PP2A core enzyme. However, in this study, the authors show that PME-1 can interact and demethylate different families of PP2A holoenzymes in vitro. They also report the cryo-EM structure of the PP2A-B56 holoenzyme in complex with PME-1. Their structure reveals that the substrate-mimicking motif of PME-1 binds to the substrate-binding pocket of B56 subunit, which tethers PME-1 to PP2A, blocks substrate-binding to PP2A, and promotes PME-1 activation and demethylation of PP2A holoenzyme. Their further mutagenesis and functional analyses indicate that cellular PME-1 function in p53 signaling is mediated by PME-1 activity towards PP2A-B56 holoenzyme. In summary, this study has provided significant insights into our understanding of PP2A regulation by PME-1, demonstrating that PME-1 not only demethylates the PP2A core enzyme, but also the holoenzyme to control cellular PP2A homeostasis.

Reviewer #3 (Public Review):

The number of identified anti-phage defense systems is increasing. However, the general understanding of how phages can overcome such bacterial defense mechanisms is a black box. Srikant et al. apply an experimental evolution approach to identify mechanisms of how phages can overcome anti-phage defense systems. As a model system, the bacteriophage T4 and its host Escherichia coli are applied to understand genome dynamics resulting in the deactivation of phage-defensive toxin-antitoxin systems.

Strengths:<br /> The application of a coevolutionary experimental design resulted in the discovery of a gene-operon: dmd-tifA. Using immunoprecipitation experiments, the interaction of TifA with ToxN was demonstrated. This interaction results in the inactivation of ToxN, which enables the phage to overcome the anti-phage defense system ToxIN.<br /> The characterization of the genomes of T4 phages that overcome the phage-defensive ToxIN revealed that the T4 genome can undergo large genomic changes. As a driving force to manipulate the T4 phage genome, the authors identified recombination events between short homologous sequences that flank the dmd-tifA operon.<br /> The discovery of TifA is well supported by data. The authors prepared several mutant strains to start the functional characterization of TifA and can show that TifA is present in several T4-like phages.

In addition, they describe T4 head protein IPIII as another antagonist of a so far unknown defense system.

In summary, the application of a coevolutionary approach to discover anti-phage defense systems is a promising technique that might be helpful to study a variety of virus-host interactions and to predict phage evolution techniques.

Weaknesses:<br /> The authors apply Illumina sequencing to characterize genome dynamics. This NGS method has the advantage of identifying point mutations in the genome. However, the identification of repetitive elements, especially their absolute quantification in the T4 genome, cannot be achieved using this method. Thus, the authors should combine Illumina Sequencing with a long-read sequencing technology to characterize the genome of T4 in more detail.

To characterize the influence of TifA during infection, T4 phage mutants are generated using a CRISPR-Cas-based technique. The preparation of these phages is unclearly described in the methods section. The authors should describe in detail whether a b-gt deficient strain was applied to prepare the mutants. Information about the used primers and cloning schemes of the Cas9 plasmid would allow the community to repeat such experiments successfully.

The discovery of TifA would benefit from additional data, e.g. structure-based predictions, that describe the protein-protein interaction TifA/ToxN in more detail.

Several publications have described that antitoxins can arise rapidly during a phage attack. The authors should address that this concept has been described before as well by citing appropriate publications.

The authors propose that accessory genomes of viruses reflect the integrated evolutionary history of the hosts they infected. However, the experimental data do not support such a claim.

Reviewer #3 (Public Review):

In their study "Membrane-mediated dimerization potentiates PIP5K lipid kinase activity", Hansen et al. aim to deepen their biochemical understanding of a fascinating self-organizing system the authors have previously been reporting on (Hansen et al., PNAS 2019), in particular, the regulation of PI(4,5)P2 lipids by the kinase PIP5K, which is itself recruited to the membrane by the PI(4,5)P2. From reconstitution studies on supported membranes investigated by TIRF microscopy, following elegant assays that have they previously developed, they conclude that PIPK5 activity is regulated by cooperative binding to and membrane-mediated dimerization of the kinase domain. Dimerization enhances the catalytic efficiency of PIP5K through a mechanism consistent with allosteric regulation and amplifies stochastic variation in the kinase reaction velocity, leading to stochastic geometry sensing that has been reported earlier.

Overall, this is a beautiful biochemical system of great general interest. Also, the findings are plausible in the light of other pattern forming systems. However, the quality of both, the writing (with partly confusing annotations, inconsistencies, and missing clarity of what is actually reported on) and the data is extremely variable, giving the whole paper a somehow immature "patchwork" impression. Not the least, error bars are missing throughout the paper, and although both the protein/membrane system and the instrumental setup seem to be sufficiently well controlled, the quantitative aspect of this study could be greatly improved.

Reviewer #3 (Public Review):

The authors describe the crystal structure of a large fragment of PKG Ib in an autoinhibited state. The structure includes both the regulatory (R) and catalytic (C) kinase domains, and shows in atomic detail how the regulatory cGMP binding domains and autoinhibitory segment bind the kinase to block its activity. A crystal structure of one of the cGMP binding domains bearing a disease-associated mutation (TAAD, Thoracic aortic aneurysms and dissections) provides an understanding of the mechanism by which the mutation leads to constitutive activation of PKG by inducing a conformation that resembles the cyclic nucleotide bound state. This interpretation is further supported by an NMR study of the mutant that reveals chemical shifts consistent with the "open" (nucleotide-bound) conformation. A structure-function study in which variants with mutations in one or both of the active sites and regulatory domain are co-expressed shows that autoinhibition occurs in cis; that is, in an intra-chain manner, rather than as part of a dimer as is likely present in the crystal. A SAXS experiment further supports this model. The authors propose a model for PKG activation, referencing the structures described here as well as prior crystal structures of the isolated kinase and regulatory domains as "snapshots" of distinct states in the autoinhibition-activation pathway. This is a careful and technically sound study that provides a first structural view of PKG autoinhibition. It also enables comparison to the related mechanism of regulation of protein kinase A, but this aspect of the manuscript could be much better developed.

Reviewer #3 (Public Review):

Carraro et al utilize systems biology approaches to decode the mechanism of action of 3-chloropiperidines (a novel class of cancer therapeutics) in cancer cell lines and build a drug-sensitivity model from the data that they evaluate using samples from The Cancer Genome Atlas and cancer cell lines. The approach provides a framework for integrating transcriptomic and open-chromatin data to better understand the mechanism of action of drugs on cancer cell types. The author's approach is of sound design, is clearly explained, and is bolstered by validation via holdout sets and analysis in new cell lines which lends the findings and approach credibility.

The major strength of this approach is the depth of information provided by performing RNA-seq and ATAC-seq on cells treated with 3-CePs at various time points, and the author's utilization of this data to perform pairwise and crosswise analyses. Their approach identified gene modules that were indicative of why one cell type was more sensitive to a particular drug compared to another. The data was then used to build a sensitivity model which could be applied to samples from The Cancer Genome Atlas, and the authors evaluated their sensitivity predictions on a set of cancer cell lines which validated the predictions.

The major drawback to this type of approach is that it relies on next-generation sequencing (somewhat costly) and requires intricate bioinformatics analyses. While I agree with the author's perspective that this approach can be applied to additional classes of drugs and cancer samples, I disagree with their view that it is efficient and versatile. However, for research teams with the means to perform both transcriptomic and open-chromatin studies, I think this integrated approach has promise for evaluating novel classes of drugs, particularly in cancer cell lines that are easy to manipulate in vitro.

While there are examples of similar frameworks being applied to drug development, this work will add to the body of literature utilizing an integrated systems biology approach for pairing drugs with specific tumor or cancer types and understanding their mechanism of action on an epigenetic level.

Reviewer #3 (Public Review):

The authors sought to identify transcriptional changes that occur in the various somatic cell populations of the adult mouse ovary during different reproductive states using single-cell RNA sequencing. The ovaries for the analysis were harvested from mice during the four stages of the normal estrus cycle (proestrus, estrus, metestrus and diestrus), from lactating or non-lactating 10 days postpartum mice, and from randomly cycling mice. They identified the major cell subtypes of the adult ovary but focused their analysis on the mesenchyme (stromal and theca) and granulosa cells. They identified novel markers for stromal, theca and granulosa cell subpopulations and validated these by RNA in situ hybridization. They used trajectory analysis to infer differentiation lineages within the stromal and granulosa cell subtypes. Finally, from their data set they identify four secreted factors that could serve as biomarkers for staging estrus cycle progression.

Strengths - This is the first study to profile ovarian somatic gonad cells at different stages of the reproductive cycle.

Weaknesses - Enthusiasm for the current manuscript is lessened because it does not employ state-of-the-art scRNA-seq analysis. For example, once general cell populations have been determined by clustering with all cells, it is best to individually re-cluster these cell populations to identify more refined and accurate subpopulations. The PC used for the initial clustering is very useful for distinguishing different general cell populations (e.g. mesenchyme vs. granulosa vs. endothelial) but may not be as useful for distinguishing biologically relevant subpopulations (e.g. stromal subpopulations). Finally, certain cell subpopulations were excluded from the trajectory analysis without justification - specifically, the mitotic and atretic granulosa cells - calling into question what conclusions can be drawn from this analysis.

Reviewer #3 (Public Review):

The authors reanalyze an existing dataset of single-cell Sperm-seq data to search for signals of transmission distortion. They develop an improved genotype imputation method and use this approach to phase donors and characterize the landscape of ancestry across each sperm genome. Using these data, the authors determined that there are no regions in any of the male donors' genomes that display a significant excess of TD. The main biological claim of the paper is that there is a strict adherence to Mendelian transmission ratios in human males.

The computational approaches for accurately phasing and reconstructing haplotypes in individually lightly sequenced gametes is a potentially useful advance that I expect may be valuable for geneticists analyzing similar datasets. The quality of software documentation and usability is high. I have concerns about the appropriateness of the comparisons selected for this approach and the algorithm does not appear particularly novel.

I have no doubt about the authors' basic conclusion that there are no strong male TD loci in the male donors examined. However, I find their statements about "strict adherence to Mendelian ratios" and many references to strong statistical power to be oversold. The power of this study is still quite limited relative to the strength of TD that we would expect to find in human populations.

Major Concerns:

There are really two distinct papers here. One is about improved imputation and crossover analysis from sperm-seq data and one is about TD. The bulk of the methodological development is a rework of the approach for genotype imputation and haplotype phasing in Sperm-seq. Yet, the major conclusions are focused on a scan for TD. I am left wondering if analyzing these data using the original method in the Bell et al paper would have produced different conclusions about either? If not, is there a systematic bias such that one would find an excess of false detections of TD? Phasing slightly more markers is not a particularly compelling link between these sections because even fairly sparsely distributed markers that are correctly phased would certainly be fine in a scan for TD within a single individual due to linkage. If this cannot be shown I wonder if this work would be better split into two manuscripts with one more technical paper describing the differences in recombination maps associated with rhapsodi and the other as a brief report stating that strong TD is probably uncommon in human males.

It is not surprising that rhapsodi outperforms Hapi since Hapi was designed for a very different quantity of samples and sequencing depths. I appreciate the authors' point that Hapi performed better than other methods in comparisons run by the Hapi authors. However, they were looking at very few gametes (10 or so, I believe). For that reason, this comparison is not appropriate to address the application to the datasets used in this paper. The authors should include an analysis comparing rhapsodi against hapcut2, PHMM and other methods that are appropriate for the full scale and sequencing depth of the data. Additionally, the original Bell paper used a phasing + HMM approach of some kind for exactly this data. Why wasn't that approach considered as a point of comparison?

With respect to the method for imputation, no comparison is made to known recombination maps nor do the authors make any comparison across the maps derived from each donor. Reporting an improved method without it motivating novel biological conclusions is not compelling in itself. I suggest the authors expand that analysis to consider these are related questions. E.g., are there males whose recombination maps differ in specific regions? Are those associated with known major chromosomal abnormalities? Is this map consistent with estimates from LD, pedigrees, Bell et al?

Most of the validations presented are based on simulated data. This is fine and has some advantages, but real data imposes challenges that these analyses do not address. My understanding is that the Bell et al. (2020) paper includes a donor with a phased diploid genome. A comparison of rhapsodi's phasing accuracy against that genome should be included.

The main biological conclusion about a "strict adherence to Mendelian expectations across sperm genomes" is an overstatement. Statistical power of this study is still limited relative to the strength of TD that would be expected within human populations. One reason is the multiple testing correction. Another is that 1000-3000 draws from a binomial distribution with expected p = 0.5 is just not sufficient to overcome binomial sampling variance. In light of this concern and the central conclusion of this paper, the authors' discussion of power is inadequate. The main text really should contain explicit discussion of the required genotype ratio skew for TD in each donor to be detected with good power. Given previous pedigree studies, it is not surprising that no significant TD was discovered that exceeded the necessary ~10% effect sizes to be detectable. Recent, much more powerful analyses in mice, Drosophila and plants, indicate that strong TD is probably uncommon and even weak effects can be detected but are uncommon.

This manuscript would benefit from a much clearer examination of statistical power and a detailed comparison of the power of this approach vs pedigree-based analyses as well as bulk gamete sequencing approaches. Although the authors are correct that all scans for TD in human genomes have been pedigree or single-cell based, more powerful alternatives are known. These are based on sequencing pools of individuals or gametes (e.g., Wei et al. 2017, Corbett-Detig et al. 2019). Each of those studies has been able to identify signatures of segregation distortion below the thresholds required for significance in this study. These and related works should be acknowledged in both the introduction and discussion. Although I appreciate that the ability to phase the genome in a single experiment may be appealing, phasing diploid genomes via hi-c omni-c is straightforward and the advantages in statistical power suggest that approaches using pools of gametes are preferable for well-powered scans for TD.

Reviewer #3 (Public Review):

The manuscript by Bae et al describes the role of a point mutation in the PH domain of Akt that changes the inhibition by the PH domain. The data underlying the manuscript appear to be done at a high technical level. The discovery that the R86A mutant has an enhanced inhibitory interface with the kinase domain is intriguing. Although this residue is not at the putative interface, it forms an electrostatic interaction with the Glu17 in the PH domain and causes a reorientation of the loop including the Y18. Analysis of Y18 and E17 mutants can reverse this effect, revealing a molecular mechanism of R86 increased inhibition.

My main concern with the manuscript is that the conclusions as currently written do not appear to be fully supported by the data. Mainly on the role of the pi-pi stacking of the 309-18 interface. This paper requires a major rewrite. There also could be additional validation data included to verify the stability and phosphorylation state of the different proteins purified.

Major concerns

1. There are concerns about the validation of the proteins used.

2. The authors note on page 9 that they analyzed the alphafold structure to look at the PhH-kinase interface.

From the analysis of the alphafold model, it does not seem appropriate for this analysis, as the alphafold predicted aligned error (taken from alphafold protein structure database, https://www.alphafold.ebi.ac.uk/entry/P31749) validation clearly shows that there is only limited predictive value of the inter-domain interfaces. I am not sure the mutant data on the predicted pi stacking interaction can be supported by alphafold here as strongly as the authors describe, as these mutants may be working through a separate mechanism. The alphafold model also appears to be templated on the 4ekk phosphorylated structure/mutant of 308 and 473, which seems to go against the authors' hypothesis that 473 phosphorylation disrupts the PH domain interface.

The best model for interpreting the Ph-kinase interface seems to be the nanobody-bound X-ray structure, and this region is disordered at F309 in this structure. While the authors' data clearly shows a role for the Y18 reorientation in changing Ph domain binding, and they also show that mutation of F309L also changes binding, they are basing their molecular model on an alphafold model with limited predictive ability for inter-domain contacts.

Reviewer #3 (Public Review):

The main goals of this study by Guan, Aflalo and colleagues were to examine the encoding scheme of populations of neurons in the posterior parietal cortex (PPC) of a person with paralysis while she attempted individual finger movements as part of a brain-computer interface task (BCI). They used these data to answer several questions:

1) Could they decode attempted finger movements from these data (building on this group's prior work decoding a variety of movements, including arm movements, from PPC)?

2) Is there evidence that the encoding scheme for these movements is similar to that of able-bodied individuals, which would argue that even after paralysis, this area is not reorganized and that the motor representations remain more or less stable after the injury?

3) Related to #2: is there beneficial remapping, such that neural correlates of attempted movements change to improve BCI performance over time?

4) Can looking at the interrelationship between different fingers' population firing rate patterns (one aspect of the encoding scheme) indicate whether the representation structure is similar to the statistics of natural finger use, a somatotopic organization (how close the fingers are to each other), or be uniformly different from one another (which would be advantageous for the BCI and connects to question #3)? Furthermore, does the best fit amongst these choices to the data change over the course of a movement, indicating a time-varying neural encoding structure or multiple overlapping processes?

The study is well-conducted and uses sound analysis methods, and is able to contribute some new knowledge related to all of the above questions. These are rare and precious data, given the relatively few people implanted with multielectrode arrays like the Utah arrays used in this study. Even more so when considering that to this reviewer's knowledge, no other group is recording from PPC, and this manuscript thus is the first look at the attempted finger moving encoding scheme in this part of human cortex .

An important caveat is that the representational similarity analysis (RDA) method and resulting representational dissimilarity matrix (RDM) that is the workhorse analysis/metric throughout the study is capturing a fairly specific question: which pairs of finger movements' neural correlates are more/less similar, and how does that pattern across the pairings compare to other datasets. There are other questions that one could ask with these data (and perhaps this group will in subsequent studies), which will provide additional information about the encoding; for example, how well does the population activity correlate with the kinematics, kinetics, and predicted sensory feedback that would accompany such movements in an able-bodied person?

What this study shows is that the RDMs from these PPC Utah array data are most similar to motor cortical RDMs based on a prior fMRI study. It's innovative to compare effectors' representational similarity across different recording modalities, but this apparent similarity should be interpreted in light of several limitations: 1) the vastly different spatial scales (voxels spanning cm that average activity of millions of neurons each versus a few mm of cortex with sparse sampling of individual neurons, 2) the vastly different temporal scales (firing rates versus blood flow), 3) that dramatically different encoding schemes and dynamics could still result in the same RDMs. As currently written, the study does not adequately caveat the relatively superficial and narrow similarity being made between these data and the prior Ejaz et al (2015) sensorimotor cortex fMRI results before except for (some) exposition in the Discussion.

Relatedly, the study would benefit from additional explanation for why the comparison is being made to able-bodied fMRI data, rather than similar intracortical neural recordings made in homologous areas of non-human primates (NHPs), which have been traditionally used as an animal model for vision-guided forelimb reaching. This group has an illustrious history of such macaque studies, which makes this omission more surprising.

A second area in which the manuscript in its current form could better set the context for its reader is in how it introduces their motivating question of "do paralyzed BCI users need to learn a fundamentally new skillset, or can they leverage their pre-injury motor repertoire". Until the Discussion, there is almost no mention of the many previous human BCI studies where high performance movement decoding was possible based on asking participants to attempt to make arm or hand movements (to just list a small number of the many such studies: Hochberg et al 2006 and 2012, Collinger et al 2013, Gilja et al 2015, Bouton et al 2016, Ajiboye*, Willett* et al 2017; Brandman et al 2018; Willett et al 2020; Flesher et al 2021). This is important; while most of these past studies examined motor (and somatosensory) cortex and not PPC (though this group's prior Aflalo*, Kellis* et al 2015 study did!), they all did show that motor representations remain at least distinct enough between movements to allow for decoding; were qualitatively similar to the able-bodied animal studies upon which that body of work was build; and could be readily engaged by the user just by attempting/imagining a movement. Thus, there was a very strong expectation going into this present study that the result would be that there would be a resemblance to able-bodied motor representational similarity. While explicitly making this connection is a meaningful contribution to the literature by the present study (and so is comparing it to different areas' representational similarity), care should be taken not to overstate the novelty of retained motor encoding schemes in people with paralysis, given the extensive prior work.

The final analyses in the manuscript are particularly interesting: they examine the representational structure as a function of a short sliding analysis window, which indicates that there is a more motoric representational structure at the start of the movement, followed by a more somatotopic structure. These analyses are a welcome expansion of the study scope to include the population dynamics, and provides clues as to the role of this activity / the computations this area is involved in throughout movement (e.g., the authors speculate the initial activity is an efference copy from motor cortex, and the later activity is a sensory-consequence model).

An interesting result in this study is that the participant did not improve performance at the task (and that the neural representations of each finger did not change to become more separable by the decoder). This was despite ample room for improvement (the performance was below 90% accuracy across 5 possible choices), at least not over 4,016 trials. The authors provide several possible explanations for this in the Discussion. Another possibility is that the nature of the task impeded learning because feedback was delayed until the end of the 1.5 second attempted movement period (at which time the participant was presented with text reporting which finger's movement was decoded). This is a very different discrete-and-delayed paradigm from the continuous control used in prior NHP BCI studies that showed motor learning (e.g., Sadtler et al 2014 and follow-ups; Vyas et al 2018 and follow-up; Ganguly & Carmena 2009 and follow-ups). It is possible that having continuous visual feedback about the BCI effector is more similar to the natural motor system (where there is consistent visual, as well as proprioceptive and somatosensory feedback about movements), and thus better engages motor adaptation/learning mechanisms.

Overall the study contributes to the state of knowledge about human PPC cortex and its neurophysiology even years after injury when a person attempts movements. The methods are sound, but are unlikely (in this reviewer's view) to be widely adopted by the community. Two specific contributions of this study are 1) that it provides an additional data point that motor representations are stable after injury, lowering the risk of BCI strategies based on PPC recording; and 2) that it starts the conversation about how to make deeper comparisons between able-bodied neural dynamics and those of people unable to make overt movements.

Reviewer #3 (Public Review):

Childhood acute myeloid leukemia (AML) is a heterogeneous disease with different outcomes for different patients, making identifying patients with different prognoses for clinical management. A variety of approaches have been used to stratify AML patients' risk, including molecular and clinical measurements to build prognostic risk scores. Previously, Chaudhary et al found that mitochondrial genome copy number per AML cell could stratify patients who would have good and poor outcomes and survival. This interesting finding suggested that mitochondrial amount and/or function alter AML disease course and suggested a further in-depth study of mitochondria in AML.

Chaudhary and colleagues follow up their preliminary study on mitochondrial genome copy number in AML with this current study by looking if the expression of specific genes encoding mitochondrial components could provide further insight into AML prognosis. The authors collected childhood AML patient samples and grouped them based on mitochondrial genome copy number. They then performed transcriptomic analysis and identified a number of nuclear-encoded mitochondrial component genes whose expression was correlated or anticorrelated with mitochondrial genome copy number and this was confirmed with targeted analysis of identified transcripts in validation cohorts. Multivariate analysis was used to identify those genes whose expression was prognostic of patient outcome. This led to the identification of three mitochondrial genes (SDHC, CLIC1, SLC25A29) whose expression was used to build a multivariate risk model for childhood AML patients. The risk model based on the expression of these genes outperformed currently used ELN risk stratification and could be combined with ELN to increase prognostic power. Lastly, the authors used publically available data from adult AML patients and found that their risk score also had prognostic power in adult AML patients as well.

Altogether, the work by Chaudhary and colleagues interestingly builds on their previous work and suggests that mitochondria may influence AML outcomes, and measuring mitochondrial parameters may help assess patient risk. Numerous exciting questions remain: what outputs of the mitochondria influence AML disease course and how? Why are some mitochondrial genes but not others correlated with mitochondrial DNA copy number in AML cells and how does this influence mitochondrial properties? Outside of predicting patient risk, can the mitochondrial phenotype of AML cells predict effective therapies? How does the mitochondrial risk model perform compared to and when utilized with other transcriptional-based risk stratification models proposed in the literature?

Reviewer #3 (Public Review):

In their previous work, the authors studied the problem of clonal life cycles evolution. Here they extended the previous work by developing a model that describes such evolution under the presence of competition between groups. The model is studied using a combination of analytical methods and numerical simulations. The results obtained are more biologically justifiable than those obtained in the linear model that neglects competition between groups.

Strengths:

- As is known from previous work, in a linear model (when the competition is absent), a typical outcome is an exponential growth in the number of groups of some life cycle, which can be considered as a natural limitation of the model. Obviously, this limitation is removed in the presented paper.

- The authors provide analytical results for some special cases of the model and compare them with those obtained in the absence of competition. In the general case of the model, when analytical progress is impossible, the authors provide the results of extensive numerical simulations. All these results allow the authors to build a clear picture of the process under study.

- The authors study the evolutionary stability of various life cycles. Specifically, it was shown that only binary fragmentation life cycles can be evolutionary stable strategies. This result holds in the linear model as well. In contrast to the linear model, more complex dynamics can be observed in the general case (like the existence of several evolutionary stable strategies).

Overall, in my opinion, the model significantly contributes to our understanding of the evolution of clonal life cycles. Moreover, it illuminates to what extent are adequate the results of simple linear models in describing the processes under consideration.

Reviewer #3 (Public Review):

In this manuscript, the authors investigated the role of glutamine metabolism in chondrocytes and in the context of inflammation. Thus, they report that chondrocytes use glutamine for their energy production and anabolic functions. Moreover, they found that removal of glutamine resulted in metabolic reprogramming and decreased inflammatory response of chondrocytes. They attributed this anti-inflammatory response to decreased NF-κB activity. Moreover, the removal of glutamine promoted autophagy. This is a very interesting study and the vast majority of the conclusions are supported by strong data.

Reviewer #3 (Public Review):

The authors present a modular computational workflow for automated sample screening and collection of cryo-EM data and demonstrate its use for screening and 3D structure determination of human mitochondrial DNA polymerase as a test sample. Despite major advances in automation of microscope operation, optimising and screening sample conditions for the acquisition of high-quality data is still a laborious task that involves human input to navigate low-, medium- and high-magnification images to identify and select specimen areas amenable to high-resolution structure determination; and subjective tuning of parameters that can result in inefficient use of high-end cryo-TEM equipment. Fully automated methods for screening and data collection are therefore needed to meet the increasing demand for access and throughput of cryo-EM. Utilising deep-learning-based object detection algorithms, the authors show that their pre-trained models can effectively detect, classify, and rank regions (grid squares and holes) of interest based on established criteria such as contamination, support film integrity, and ice thickness. A challenge for any such method is the scarcity of annotated data reflecting the broad variety across the wide range of image and sample conditions in cryo-EM, and that selection of the "best" areas may vary by particle and sample preparation conditions. To mitigate this risk, the authors provide a web interface that allows re-training of the feature models and integrates on-the-fly assessment of data quality and adjustment of data collection parameters. As such, the presented pipeline and related approaches can become a useful addition to existing automation software for cryo-EM data collection, in multi-user environments such as cryo-EM facilities. Such approaches will best strive if software and models are openly available to the cryo-EM community so that annotated data can be added or customised and the quality of the prediction methods can improve over time.

Reviewer #3 (Public Review):

In general, I find this to be an experimentally and analytically sound paper. The observation that rate information is preserved in hippocampal replay is hinted at in previous work, but to my knowledge, has not yet been explicitly quantified as the authors have done here. Thus, this work is novel and, in my opinion, an important contribution to our understanding of hippocampal network function.

The large number of control analyses strongly support the core finding of this work. I feel that the authors have very convincingly demonstrated that rate information is represented along with spatial information in replay.

While I can think of many suggestions to follow up on this work, I have no major concerns regarding the experiments, analyses, or interpretation of the manuscript.

Reviewer #3 (Public Review):

The TRPV1 receptor channel is primarily localised to sensory nerves as well as other non-neuronal tissues. It has been known for some time that TRPV1 has a role in the regulation of body temperature, as TRPV1 antagonists, being developed as analgesics, cause hyperthermia. There is a need for further mechanistic information, as the present drug discovery programme has been delayed by the inability of scientists to develop TRPV1 analgesics that act without temperature-related side effects. This manuscript is designed to investigate whether sensory nerves or smooth muscle cells are included in the mechanisms, through the study of tissue specific genetically modified mice.

This is a highly readable and concise manuscript with a relatively simple and clear take home message that advances current knowledge. However, at times the information could be more fully given.

Reviewer #3 (Public Review):

This work seeks to identify a common factor governing priority effects, including mechanism, condition, evolution, and functional consequences. It is suggested that environmental pH is the main factor that explains various aspects of priority effects across levels of biological organization. Building upon this well-studied nectar microbiome system, it is suggested that pH-mediated priority effects give rise to bacterial and yeast dominance as alternative community states. Furthermore, pH determines both the strengths and limits of priority effects through rapid evolution, with functional consequences for the host plant's reproduction. These data contribute to ongoing discussions of deterministic and stochastic drivers of community assembly processes.

Strengths:

Provides multiple lines of field and laboratory evidence to show that pH is the main factor shaping priority effects in the nectar microbiome. Field surveys characterize the distribution of microbial communities with flowers frequently dominated by either bacteria or yeast, suggesting that inhibitory priority effects explain these patterns. Microcosm experiments showed that A. nectaris (bacteria) showed negative inhibitory priority effects against M. reukaffi (yeast). Furthermore, high densities of bacteria were correlated with lower pH potentially due to bacteria-induced reduction in nectar pH. Experimental evolution showed that yeast evolved in low-pH and bacteria-conditioned treatments were less affected by priority effects as compared to ancestral yeast populations. This potentially explains the variation of bacteria-dominated flowers observed in the field, as yeast rapidly evolves resistance to bacterial priority effects. Genome sequencing further reveals that phenotypic changes in low-pH and bacteria-conditioned nectar treatments corresponded to genomic variation. Lastly, a field experiment showed that low nectar pH reduced flower visitation by hummingbirds. pH not only affected microbial priority effects but also has functional consequences for host plants.

Weaknesses:

The conclusions of this paper are generally well-supported by the data, but some aspects of the experiments and analysis need to be clarified and expanded.

The authors imply that in their field surveys flowers were frequently dominated by bacteria or yeast, but rarely together. The authors argue that the distributional patterns of bacteria and yeast are therefore indicative of alternative states. In each of the 12 sites, 96 flowers were sampled for nectar microbes. However, it's unclear to what degree the spatial proximity of flowers within each of the sampled sites biased the observed distribution patterns. Furthermore, seasonal patterns may also influence microbial distribution patterns, especially in the case of co-dominated flowers. Temperature and moisture might influence the dominance patterns of bacteria and yeast.

The authors exposed yeast to nectar treatments varying in pH levels. Using experimental evolution approaches, the authors determined that yeast grown in low pH nectar treatments were more resistant to priority effects by bacteria. The metric used to determine the bacteria's priority effect strength on yeast does not seem to take into account factors that limit growth, such as the environmental carrying capacity. In addition, yeast evolves in normal (pH =6) and low pH (3) nectar treatments, but it's unclear how resistance differs across a range of pH levels (ranging from low to high pH) and affects the cost of yeast resistance to bacteria priority effects. The cost of resistance may influence yeast life-history traits.

• With proper design, the internet can play a more proactive role
• From passive to active, sensemaking to action
• Cosmolocal production: https://clreader.net
• Web 3 technology
• Indyweb

3 Be Radically Open-Minded

Bitcoin, in spite of its unintended consequences, does demonstrate the power and potential of these kinds of systems to scale.

Process flow: Worldview, purpose, metric and finally design

Paper 1: Worldview and purpose Paper 2: practical implementation Paper 3: Design

"Specifically, when one of my classmates stated how he was struggling with the concept and another one of my classmates took the initiative to clarify it, I realized that that individual possibilities vary greatly among students."

Example of using GPT-3 for programming

fighting and honor and protection

honor by resisting dishonor

honor

enforcement

honor

honor for all regardless of gender

how far honor goes

concept

how remained honorable

honor

.

.

white ppl are dumb

honor

Haseltine, W. A. (n.d.). Birth Of The Omicron Family: BA.1, BA.2, BA.3. Each As Different As Alpha Is From Delta. Forbes. Retrieved 30 March 2022, from https://www.forbes.com/sites/williamhaseltine/2022/01/26/birth-of-the-omicron-family-ba1-ba2-ba3-each-as-different-as-alpha-is-from-delta/

Can symbol that represents one thing change over a long period of time to mean something different?

Why was the apple chosen as the representation of temptation?

A Theory of signs and symbols that deals especially with there function in both artificially constructed and natural languages.

First

Arg3: Malgré les risques environnementaux qui pèsent sur les EM, il existe des initiatives pour protéger ces espaces

• Réduction des émissions de CO2 GAS + niveau CO2 atm + température ++ océans = phytoplanctons moins utiles à l'homme Absorber 30% du CO2 généré par l'homme Produire 50% oxygène = indispensables pour la vie humaine sur terre.

Arg3: Les Etats tentent également de lutter contre les trafics illégaux

• Lutte contre la pêche illicite Selon FAO = 15 et 20 % des prises => 23 Milliards $ /an Moins de préservation du stock renouvelable = surpêche Concurrence déloyale = pecheurs + respect quotas

• Lutte contre le trafic de cocaïne 2017 - 2019: Cocaïne saisie à bord d'embarcations commerciales x3 = 73 tonnes Moyens ? Sous marins artisanaux, Ou ? Antilles = plaque tournante Quelles saisies ? 3 tonnes sous marins par police espagnole en 2019

• Lutte contre le trafic des déchets Cout traitement + législation contraignante = Etats exportent leurs déchets / filières illégales ==> Pays d'Asie et d'Afrique: ++ déchets électroniques Malaisie => FR: 43 conteneurs de plastique illégaux

Arg3: Les EM sont au coeur de tensions géopolitiques entre les Etats qui se disputent l'accès aux ressources halieutiques, hauturières et aux routes maritimes

• Mer de Chine méridionale Chine // Philippines, Vietnam, Brunei, Indonésie, Malaison "langue de boeuf" => Archipel des Spratleys + Îles Paracels Zone de trafic CMM Territorialisation , militarisation des EM Mars 2020: percussion bateau de pêche vietnamien

• Mer de Chine Orientale Chine // Japon Îles Senkaku et Diaoyu COVID19: Liaoning traverse ZEE jap

• Mer méditerranée Turquie // Grèce // Chypre // Israël // Liban EM triangulaire de 850km² = réserves de gaz ?

Arg3: les ressources énergétiques sont également exploitées dans les Mers et les Océans

• les hydrocarbures 30% hydrocarbures proviennent de gisements offshore Mer du Nord, Mer Caspienne, Golfe de Guinée, Golfe Arabo-persique, Mer de Chine méridionale

espaces inexploités: conditions extrêmes (Arctique), fonds marins profonds = ++ pression (Brésil qui se lance dans l'exploitation d'hydrocarbures au dela du plateau continental)

• les énergies renouvelables off shore Usines marémotrices: UM de la Rance (Côtes d'Armor, FR) Parcs éoliens off shore: projets aux îles de Lérons, Europe = 1er prod mondial électricité = 5000 éoliennes off shore (Mer du Nord ++)

• les avancées scientifiques possibles Bathymétrie est mal connue = couts ++ 90% des espèces marines resteraient à découvrir

Arg3: les enjeux vitaux des chokes points pour l'économie mondialisée et le CM Connecter espaces de prod°/conso° Espaces maritimes très réduits concentrent trafic maritime:

• Canaux; Suez, Panama
• Détroit, Ormuz, Gibraltar, Bab el Manbed, Bering, Malacca
• Caps: Bonne espérance, Horn

Détroit de Malacca selon Institut Supérieur d'économie marine (2017) 14M barils / jours Port Klang (Malaisie) = 12e port à conteneurs mondial "Dilemme de Malacca" selon Hu Jintao 20 - 25% du trafic mondial / an

Dépendance = ouverture permanente des passages stratégiques Mauvaise situations: insécurité, piraterie, conflits, tensions géopolitiques sinon = perturber approvisionnement marchandises + matières premières = - économie mondiale EX: 1967 -> 1974 = pas Canal de Suez (G6jours) alternative = Cap de Bonne Espérance (+ temps, +argent)

DOI: 10.1016/j.celrep.2021.110234

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What is this?

DOI: 10.7554/eLife.72345

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What is this?

it should be regarding the first amendment not second!

DOI: 10.7554/eLife.69264

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What is this?

The president

incorrect- the act being charged is "Unfurled the glad, doused it with kerosene and set it on fire"

También depende del factor de cuanto uso se le ha dado a ese motor, no solo por el incremento de desgaste significa que va a bajar su calidad.

This seems like an unreasonably high stoichiometry of Arp2/3 complexes per actin subunit; we now know that each Arp2/3 complex covers a few subunits, so there shouldn't be enough room on the filament to fit 1:1 Arp2/3 complex/actin

It should be the first amendment

Wrong, it supposed to be did the voucher program violate the establishment clause?

Cleveland

incorrect school district - school district should be Cleveland

It should be Cleveland

APA 7 3 or more authors

THIS is it - web 3 is making consumers mutiplicitous - opens marketts WITHIN games, subworlds that can be exploited / marketed to / fashion trends will sweep games, online subcultures (maybe) - people have markeable personas on and off the web, new context for targeted advertising / commerce.

Will cannabalize physical economies?

Accessorize for a zoom meeting - digital suits, etc digital costumes. Something to wear at digital concerts, in games; your Perona will not be birthed into the metaverse clothed, accessorized...

Assets will be portable across platforms.

Is this the foundational argument for the Supremacy Clause? For this example, does this mean if the states had the power to influence federal programs or policies, that the powers delegated to the federal government would be redundantly delegated?

When do state laws take effect over federal laws? How do you know when which is supreme? or vice versa?

Based on the relationship between State, banks, and General Government, is this suggesting a contradiction or non mutual relationship between the 3 in this line of argument?

This whole phrase is really confusing me? I'm not able to even figure out what any of the parts mean, could anybody help me out?

Is this suggesting that if States were allowed to tax the Federal Government, would States hold power and authority over citizens outside of their state? Would State laws apply universally?

A lot of this argument seems centered around the idea that the people, via its representatives, declared the Constitution has supreme power over states. In this, a State (and by extension, representatives of the people) is arguing the apparent supremacy of the federal gov't over the state, doesn't this contradict the argument of the Supreme Court a bit, that the will of the people was for a federal gov't to hold supreme over state?

Does Maryland grapple with the idea that the sovereignty and power of the states comes from the people in its argument that the Constitution receives its power from the states, as opposed to the people?

I don't understand what this is saying? So on the basis of Marylands contends it changes the meaning of what the Bank means in the constitution?? I'm not sure if I even read it correctly the end of the sentence isn't making sense to me. Changes the character of what instrument? Constitution?

Taxation seems to be a big pinpoint of this argument. In history we have seen many problems with "taxation without representation" or misuse of taxing in this case, but we also see problems today with people not agreeing with where the tax money goes, or especially problems with getting tax returns. Do you think taxation is going to continue being a problem?

This question is more a thought for questions. Do you think that this idea of one government have power over another government issues still stand in to days modern world? or do you think that states and governments the the US are more lacs about this issues then they where in 1819?

Is 'another government' directly referring to the state vs. the national government?

What constitutes a case of confidence? Is Marshall saying here that the national and state governments need to just have confidence in one another that there will be no abuse of power from either end? When does the Court decide a case is to be considered a case of confidence?

Kind of seperate, but do federal buildings pay taxes to the state they are in? Or to the government? Or do they pay at all? If they dont does that mean that the state tax payer does?

In the Epstein text, it says that one of the seven Supreme Court Justices, Thomas Todd, did not participate in the decision. So it was unanimous, but only among 6 of the 7. I wonder why Todd didn't participate? Does anyone know from the text or other history?

I feel like this is a tad dramatic. How would allowing Maryland to tax a government institution arrest "all the measures of the Government"? I understand that taxing the bank would likely lead to the closing of that bank - but how would it interrupt the rest of our governence?

There - opens up GIGANTIC barter economy possibilities - will shut out old middle men & create new ones - swap airline tickets / hotel reservations for concert tickets or memorabilia

incorrect: The Court held that the President's military power as Commander in Chief of the Armed Forces did not extend to labor disputes.

The president.

News ·, C. B. C. (2021, October 1). B.C. expands mask mandate in schools to include kindergarten to Grade 3 after community outcry | CBC News. CBC. https://www.cbc.ca/news/canada/british-columbia/bc-schools-masks-safety-plans-update-1.6196198

DOI: 10.1016/j.celrep.2021.109775

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What is this?

We do not need images here. you can use some kind of icon if you wish. But this is largely text. Also FYI this section might need a headline. Such as summary overview - tbd.

Now that Marshall observes the supreme law of the land to be the constitution, this makes me wonder how the Judiciary Act of 1789 was passed when it altered the original jurisdiction that was written in the constitution. Did the creators of the this act not consult or care about the constitution?

This concludes Marshall's habit of asking questions that he proceeds to answer. Are many modern day decisions written similarly? Or is this style more suited to an early justice seeking to define the role of the court, including the types of questions a Justice should be asking and answering?

Okay help me clarify this. In this phrasing saying that if Congress gives appellate jurisdiction over the constitution witch already holds original jurisdiction than that new law or rule makes no sense?

So a mandamus can only be applied to Appellate jurisdiction and not Original? Or can it be applied to both if met with the "specificity" of the original jurisdiction requirements?

I realize this is just an example he's using to prove his point, that every word of the constitution is important and that the constitution should trump other laws. However, I've never heard of either of these - A "bill of attainder" or an "ex post facto" law. Does anyone know what these are?

I'm a little confused on how this analogy fits in. Is this meaning that the bill passed should be enforced by the courts? If this is true how exactly does this fit in the argument?

I do not understand how this statement relates to what was said before. If I'm correct, the previous statements was suggesting that the supreme and inferior courts have certain jurisdiction. Are they saying that how jurisdiction is determined may change over time?

I thought the whole point of this case was to review laws or precedents within the constitution and deem whether or not they were truly viable. Doesn't appellate jurisdiction become necessary then? A higher court overturning a lower courts decision?

How can a court's opinion change? When there are different people on the court would that maybe produce a different outcome? How would you be able to be sure that things are standard?

I am confused on how the legislature fits into the court's original jurisdiction. Did the legislature have to approve each of the cases that the supreme court took? Why only for original jurisdiction and not appellate jurisdiction as well? Does this still apply today?

Where does the issue writs of mandamus come from then if not the constitution? I thought that the way judicial courts act were all centered around the constitutional law. But the way this is worded, it appears that mandamus is not in reference to the constitution.

I'm curious as to how the writers of the Constitution had not considered that something similar could occur? Why did the writers not introduce some sort of specific method where one of the branches could declare an action of another unconstitutional?

DOI: 10.1111/bph.15630

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What is this?

DOI: 10.1016/j.devcel.2021.09.005

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What is this?

I looked up the Voluntary Cessation Doctrine, but I am still unsure what it means and how it pertains to this case? I wish they would have elaborated more on it. I could be mistaken, but I believe the Doctrine deals with exceptions to mootness, however, I thought Justice Breyer said this case was not moot.

Does Lockey vs Davey involve the qustion of scholarship (of religious schools) provided from government money? Thats what I'm gathering but I'm not sure. Not familiar with the case but before I look it up I'm guessing it has to do with government funded school scholarships secular vs non secular?

How often does social media play a part into political bias? How are judges or trial members able to keep their rulings separate from the bias they're hearing in the news or headlines?

He doesn't really answer the justices question of how he doesn't see the other way of questioning as discrimination IN FAVOR of the church against other non religious people which I think is sort of telling and again why I think justice sotomayor is one of the dissenting judges. One question I have is whether or not there actually is anything in the constitution that protects discrimination in favor of religion? I always hear about it the other way around and I remember in one instance not long ago about a christian baker who refused to bake a wedding cake for a gay couple based on the argument that it violates his ability to practice his religious beliefs. The court sided with him, which to me is discrimination in favor of "religious beliefs" that was ruled by the supreme courts as justified and constitutional.

Having no prior knowledge of the Establishment Clause, I believe I've been able to glean a little of what it might say from the course of listening to this case. The application of it seems to be broken into two halves of conditionality, "endorsement" and "entanglement." Does anyone on the thread have a definition of what these two conditions mean?

This mention of Locke has been used numerous times throughout this conversation, and I have yet to understand where the meaning of this is being drawn from. Are they referring to something John Locke wrote? Is this the name of something or someone I may have missed?

DOI: 10.1016/j.cub.2021.08.049

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What is this?

DOI: 10.1016/j.cub.2021.08.049

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What is this?

DOI: 10.1016/j.cub.2021.08.049

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What is this?

polyphonic: style of musical composition employing two or more simultaneous but relatively independent melodic lines

merriam

primordial: existing in or persisting from the beginning (as of a solar system or universe)

merriam

dampness of homes in council estates in Bath. research for community advocacy. Collective action example.

he is transitioning from what he is going through to what he went through through the class. teacher seems pretty mean towards the students and a little bit aggressive

he thought he was doing well until he mispronounced ibm and learns that it was a mistake he shouldn't of made because of how the teacher was ridiculing every single student he was confused as to why the teacher was referring to objects as genders it just didn't make sense to him

feeling very scared. seems like he is regretting it a little bit?

Moderna Completes Submission of Biologics License Application to the U.S. Food and Drug Administration for its COVID-19 Vaccine | Moderna, Inc. (n.d.). Retrieved 26 August 2021, from https://investors.modernatx.com/news-releases/news-release-details/moderna-completes-submission-biologics-license-application-us/

DOI: 10.7554/eLife.44431

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What is this?

DOI: 10.7554/eLife.38911

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What is this?

DOI: 10.1016/j.neuron.2018.06.035

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What is this?

DOI: 10.7554/eLife.68755

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What is this?

DOI: 10.1016/j.celrep.2019.09.041

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Curator: @ethanbadger

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What is this?

DOI: 10.7554/eLife.35796

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Curator: @evieth

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What is this?

DOI: 10.1016/j.mod.2015.10.001

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What is this?

DOI: 10.1016/j.cub.2017.11.018

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What is this?

This list makes sense based on the definition of metadata above in the article saying that it helps organize, find and understand data. I would expect these elements to be a part of metadata because they all give information as to what you are looking at and who created it.

The word metadata sounded way more advanced than my skill level in computers. I didn't really know what the word metadata meant until reading this article. The fact that it is just data about data makes it way easier to understand. I am finding that a lot of terms that we have used so far in class seemed hard to understand but are actually simple to do once they're broken down.

I agree with this. I think we should be asking and questioning things because that is how we learn and develop our ideas and opinions. Once we start questioning all of these things we can take this new knowledge and start to make changes.

I don't believe that Google should be biasing search to its own economic interests. I find that when I am searching things that my ads are targeted to what I have looked at previously or something that Google thinks I will like. As well, some of the other ads are completely random and not related to anything I have searched. I think that Google should base its ads on equality as well as its searches so you gain accurate information and not something put up to serve their own economic interests.

I can't believe that people are still thinking this way. Suggestions such as women cannot drive or be trusted and they should stay at home and be put in their places are not ones that we should be hearing anymore. Men and women are supposed to be viewed as equal and it shocked me that these came up as autosuggestions on Google Search. That shows that there is still a ways to go to fully achieve gender equality.

It would be great if we could pull empirical evidence to support this

Testing out the annotate feature. Student 1 will highlight sections according to the prompts, as shown HERE.

For example: "This is me during interviews. I say too much and veer off topic."

This is a shortened version of the full definition to avoid vocab words we haven't defined yet

Starting off with Giacomo's slide content

Johnson, Khari. ‘AI Could Soon Write Code Based on Ordinary Language’. Wired. Accessed 21 June 2021. https://www.wired.com/story/ai-write-code-ordinary-language.

DOI: 10.1016/j.celrep.2021.109255

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DOI: 10.1016/j.celrep.2021.109255

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DOI: 10.1016/j.celrep.2021.109255

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DOI: 10.1016/j.celrep.2021.109255

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DOI: 10.7554/eLife.62196

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DOI: 10.1016/j.celrep.2021.109230

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What is this?

Reviewer #3 (Public Review):

Barone, Paul et al. present a new computational method, named T-REX, to detect changes in immune cell populations from repeated cytometry measurements (before and after infection or treatment). The proposed method is designed to detect changes in rare and common cells with particular focus on the former. T-REX detects subpopulations of cells showing marked differences in abundance between the proportion of cells from different time points (before and after infection) from a single individual. The method relies of a dimensionality reduction step using UMAP followed by a K-nearest neighbor (KNN) search to identify cells that have a large fraction (>0.95) of neighbors from one time point, indicating expansion or shrinkage of certain cell populations. Areas in the UMAP with clustered expanding or shrinking neighborhoods are labeled as hotspots. Cells in these hotspots were further characterized and enriched markers were identified using MEM, a method published earlier by the same authors. T-REX was applied to a newly collected dataset of rhinovirus infection and three publicly available datasets of SARS-CoV-2 infections, melanoma immunotherapy and AML chemotherapy. The results are presented clearly and the authors discuss in details several examples in which the cells identified by T-REX have a phenotypic profile which align with previous knowledge, indicating the relevance of the results.

Strengths:

• T-REX is based on a simple pipeline including UMAP and KNN. This is an advantage especially given the large number of cells collected. Further, the proposed approach has a key advantage since it allows the analysis of one sample at a time, which is practical if one wants to analyze a new sample. There is no need to rerun the analysis on an aggregate of a large number of samples.

• The new rhinovirus dataset is of great value to the community.

Weaknesses:

• The paper lacks a comparison to other methods for differential abundance testing. In particular, it is not clear how T-REX differs from the Differential abundance test proposed by Lun et al. (https://doi.org/10.1038/nmeth.4295). Similarly, there are no experiments or results to support the authors' initial claim that T-REX outperforms current clustering-based methods (SPADE, FLOWSOM, Phenograph,...etc.) in capturing changes in rare (<1%) cell populations.

• T-REX relies on arbitrary cutoffs (0.95 and 0.5 %) to define expansion or shrinkage in the neighborhood of each cell (0.95 and 0.5 %) rather than a formal statistical test. These cut-offs were defined based on the ability to detect tetramer positive cells in one subject only. This greatly limits the generalizability of the method.

• The authors do not motivate the use of UMAP prior to the KNN graph reconstruction. While UMAP is a clearly powerful method to visualize single cell data, the resulting embedding can potentially show distinct groups of points when the high dimensional manifold is more continuous. For this reason, KNN graphs are usually built using the high-dimensional data (or principal components).

• Given that T-REX is mainly developed to detect changes in rare cell populations, the paper lacks an assessment of the method's sensitivity. For instance, cells were subsampled equally from each time point. An assessment of the effects of this subsampling step is necessary. In general, a guide to the users indicating the limitations of T-REX will be greatly helpful.

• Given that the main aim of T-REX is to detect differences in rare cells, the rational to perform a separate analysis for CD4 positive cells is not clear. One would expect these differences to be identified also in the analysis performed using all cells.

• The paper lacks a discussion on the effects of batch effects between the different time points on the performance of T-REX.