Distinct representation of cue-outcome association by D1 and D2 neurons in the ventral striatum's olfactory tubercle Positive and negative associations acquired through olfactory experience are thought to be especially strong and long-lasting. The conserved direct olfactory sensory input to the ventral striatal olfactory tubercle (OT) and its convergence with dense dopaminergic input to the OT could underlie this privileged form of associative memory, but how this process occurs is not well understood. We imaged the activity of the two canonical types of striatal neurons, expressing D1 or D2 type dopamine receptors, in the OT at cellular resolution while mice learned odor-outcome associations ranging from aversive to rewarding. D1 and D2 neurons both responded to rewarding and aversive odors. D1 neurons in the OT robustly and bidirectionally represented odor valence, responding similarly to odors predicting similar outcomes regardless of odor identity. This valence representation persisted even in the absence of a licking response to the odors and in the absence of the outcomes, indicating a true transformation of odor sensory information by D1 OT neurons. In contrast, D2 neuronal representation of the odor-outcome associations was weaker, contingent on a licking response by the mouse, and D2 neurons were more selective for odor identity than valence. Stimulus valence coding in the OT was modality-sensitive, with separate sets of D1 neurons responding to odors and sounds predicting the same outcomes, suggesting that integration of multimodal valence information happens downstream of the OT. Our results point to distinct representation of identity and valence of odor stimuli by D1 and D2 neurons in the OT.
Using Deep Learning to Predict Human Decisions, and Cognitive Models to Explain Deep Learning Models Deep neural networks (DNN) models have the potential to provide new insights in the study of human decision making, due to their high capacity and data-driven design. While these models may be able to go beyond theory-driven models in predicting human behaviour, their opaque nature limits their ability to explain how an operation is carried out. This explainability problem remains unresolved. Here we demonstrate the use of a DNN model as an exploratory tool to identify predictable and consistent human behaviour in value-based decision making beyond the scope of theory-driven models. We then propose using theory-driven models to characterise the operation of the DNN model. We trained a DNN model to predict human decisions in a four-armed bandit task. We found that this model was more accurate than a reinforcement-learning reward-oriented model geared towards choosing the most rewarding option. This disparity in accuracy was more pronounced during times when the expected reward from all options was similar, i.e., no unambiguous good option. To investigate this disparity, we introduced a reward-oblivious model, which was trained to predict human decisions without information about the rewards obtained from each option. This model captured decision-sequence patterns made by participants (e.g., a-b-c-d). In a series of experimental offline simulations of all models we found that the general model was in line with a reward-oriented models predictions when one option was clearly better than the others.

However, when options expected rewards were similar to each other, it was in-line with the reward-oblivious models pattern completion predictions. These results indicate the contribution of predictable but task-irrelevant decision patterns to human decisions, especially when task-relevant choices are not immediately apparent. Importantly, we demonstrate how theory-driven cognitive models can be used to characterise the operation of DNNs, making them a useful explanatory tool in scientific investigation.

Author SummaryDeep neural networks (DNN) models are an extremely useful tool across multiple domains, and specifically for performing tasks that mimic and predict human behaviour. However, due to their opaque nature and high level of complexity, their ability to explain human behaviour is limited. Here we used DNN models to uncover hitherto overlooked aspects of human decision making, i.e., their reliance on predictable patterns for exploration. For this purpose, we trained a DNN model to predict human choices in a decision-making task. We then characterised this data-driven model using explicit, theory-driven cognitive models, in a set of offline experimental simulations. This relationship between explicit and data-driven approaches, where high-capacity models are used to explore beyond the scope of established models and theory-driven models are used to explain and characterise these new grounds, make DNN models a powerful scientific tool.
DeepMAPS: Single-cell biological network inference using heterogeneous graph transformer We present DeepMAPS (Deep learning-based Multi-omics Analysis Platform for Single-cell data) for biological network inference from single-cell multi-omics (scMulti-omics). DeepMAPS includes both cells and genes in a heterogeneous graph to simultaneously infer cell-cell, cell-gene, and gene-gene relations. The multi-head attention mechanism in a graph transformer considers the heterogeneous relation among cells and genes within both local and global context, making DeepMAPS robust to data noise and scale. We benchmarked DeepMAPS on 18 scMulti-omics datasets for cell clustering and biological network inference, and the results showed that our method outperformed various existing tools. We further applied DeepMAPS on lung tumor leukocyte CITE-seq data and matched diffuse small lymphocytic lymphoma scRNA-seq and scATAC-seq data. In both cases, DeepMAPS showed competitive performance in cell clustering and predicted biologically meaningful cell-cell communication pathways based on the inferred gene networks. Note that we deployed a webserver using DeepMAPS implementation equipped with multiple functions and visualizations to improve the feasibility and reproducibility of scMulti-omics data analysis. Overall, DeepMAPS represents a heterogeneous graph transformer for single-cell study and may benefit the use of scMulti-omics data in various biological systems. SARS-CoV-2 spike P681R mutation, a hallmark of the Delta variant, enhances viral fusogenicity and pathogenicity During the current SARS-CoV-2 pandemic, a variety of mutations have been accumulated in the viral genome, and currently, four variants of concerns (VOCs) are considered as the hazardous SARS-CoV-2 variants to the human society1. The newly emerging VOC, the B.1.617.2/Delta variant, closely associates with a huge COVID-19 surge in India in Spring 20212. However, its virological property remains unclear. Here, we show that the B.1.617.2/Delta variant is highly fusogenic, and notably, more pathogenic than prototypic SARS-CoV-2 in infected hamsters. The P681R mutation in the spike protein, which is highly conserved in this lineage, facilitates the spike protein cleavage and enhances viral fusogenicity. Moreover, we demonstrate that the P681R-bearing virus exhibits higher pathogenicity than the parental virus. Our data suggest that the P681R mutation is a hallmark that characterizes the virological phenotype of the B.1.617.2/Delta variant and is closely associated with enhanced pathogenicity. The spindle assembly checkpoint and the spatial activation of Polo kinase determine the duration of cell division and prevent neural stem cells tumor formation The maintenance of a restricted pool of asymmetrically dividing stem cells is essential for tissue homeostasis. This process requires the control of mitotic progression that ensures the accurate chromosome segregation. In addition, this event is coupled to the asymmetric distribution of cell fate determinants in order to prevent stem cell amplification. How this coupling is regulated remains poorly described. Here, using asymmetrically dividing Drosophila neural stem cells (NSCs), we show that Polo kinase activity levels determine the length of cell division, independent of the spindle assembly checkpoint (SAC). This event is mediated by the direct phosphorylation of Polo kinase by Aurora A at spindle poles and Aurora B kinases at centromeres. Furthermore, we show that Aurora A-dependent activation of Polo is the major event that promotes NSC polarization and together with the SAC prevents brain tumor growth. Altogether, our results show that an Aurora/Polo kinase module couples NSC mitotic progression and polarization for tissue homeostasis. Herbivore life histories are altered by drought stress in their hosts plants Drought associated with climate change can stress plants, altering their interactions with phytophagous arthropods. Dryness not only impacts cultivated plants but also their parasites, which in some cases are favoured by drought. Herbivorous arthropods feeding on drought-stressed plants typically produce bigger offspring and develop faster. However, how much responses to abiotic factors differ among populations of a species remains poorly documented. Here, we evaluate variability among populations of a major agricultural pest, the two spotted spider mite, Tetranychus urticae, in response to drought-stress. We compare key life-history parameters of twelve populations that originate from climates ranging from wet and cool Atlantic locations to medium to dry hot Mediterranean locations. We evaluated how plant drought stress affects four life history traits: development time, fecundity, sex-ratio and emigration rate in an experiment comparing well-watered and drought-stressed bean plants. Mites feeding on drought-stressed plants developed faster and attempted to leave leaves less often, and young females were more fecund. The mites from wet temperate climates exhibited greater plasticity between the two water regimes than mites originating from dryer and hot climates. Thus, climate in the area of origin influences mite response to drought. Spatial phylogenetics of Japanese ferns: Patterns, processes, and implications for conservation PremiseBiodiversity is often only measured with species richness. However, this ignores evolutionary history and is not sufficient for making conservation decisions. Here, we characterize multiple facets and drivers of biodiversity to understand how these relate to bioregions and conservation status in the ferns of Japan.

MethodsWe compiled a community dataset of 1,239 20 km x 20 km grid-cells including 672 taxa based on > 300,000 specimen records. We combined this with a phylogeny and functional traits to analyze taxonomic, phylogenetic, and functional diversity, and modeled biodiversity metrics in response to environmental factors and reproductive mode. Hierarchical clustering was used to delimit bioregions. Conservation status and threats were assessed by comparing the overlap of significantly diverse grid-cells with conservation zones and range maps of native Japanese deer.

ResultsTaxonomic richness was highest at mid-latitudes. Phylogenetic and functional diversity and phylogenetic endemism were highest in small southern islands. Relative phylogenetic and functional diversity were high at high and low latitudes, and low at mid-latitudes. Grid-cells were grouped into three (phylogenetic) or four (taxonomic) major bioregions. Temperature and apomixis were identified as drivers of biodiversity patterns. Conservation status was generally high for grid-cells with significantly high biodiversity, but the threat due to herbivory by deer was greater for taxonomic richness than other metrics.

ConclusionsOur integrative approach reveals previously undetected patterns and drivers of biodiversity in the ferns of Japan. Future conservation efforts should recognize that threats can vary by biodiversity metric and consider multiple multiple metrics when establishing conservation priorities. Game of theories: an agent-based model of how variation in contest cost-benefits determines the evolution of contest resolution rules Game-theory based models are used to understand rules that animals use to settle contests over indivisible resources. However, the empirical literature of contests indicates controversial support to models, with some species supporting different models and other species showing no support to any model. Since strategies used to resolve contests may have different associated costs, it is possible that different conditions have determined the evolution of distinct assessment strategies used by animals. We used an agent-based model to explore the importance of the following conditions: resource availability, probability of reproduction with resource, and damage costs on evolution of assessment strategies. We used self- and mutual-assessment models as a heurist framework to build agents with different assessment strategies. In our model, agents competed for resources in scenarios with different combinations of resource availability, probability of reproduction with resource, and damage costs. We found that agents following the self-assessment with damage strategy were prevalent in scenarios with no probability of reproduction without the resource, independently of other variables. We also found that agents following the non-aggressive strategy occurred in all scenarios. However, agents using the non-aggressive strategy were prevalent only in scenarios with probability of reproduction with the resource. Finally, we observed that agents using mutual-assessment occurred only in a scenario with high risk of damage, low availability of resources, and with probability of reproduction without the resource. These results indicate that agents following the self-assessment with damage and non-aggressive strategies may be able to stay at most scenarios. Reconstitution of minimal motility system based on Spiroplasma swimming by expressing two bacterial actins in synthetic minimal bacterium Motility is one of the most important features of life, but its evolutionary origin remains unknown. In this study, we focused on Spiroplasma, commensal, or parasitic bacteria. They swim by switching the helicity of a ribbon-like cytoskeleton that comprises six proteins, each of which evolved from a nucleosidase and bacterial actin called MreB. We expressed these proteins in a synthetic, non-motile minimal bacterium, JCVI-syn3.0B, whose reduced genome was computer-designed and chemically synthesized. The synthetic bacterium exhibited swimming motility with features characteristic of Spiroplasma swimming. Moreover, some combinations of the two proteins produced a helical cell shape and swimming, suggesting that the swimming originated from the differentiation and coupling of bacterial actins, and we also obtained a minimal system for motility of the synthetic bacterium.

One-Sentence SummaryThe minimal system comprised two bacterial actins that provided cell helicity and swimming to the synthetic minimal bacterium. Diverse stem-chondrichthyan oral structures and evidence for an independently acquired acanthodid dentition The teeth of sharks famously form a series of transversely-organised files with conveyor-belt replacement that are borne directly on the jaw cartilages, in contrast to the dermal plate-borne dentition of bony fishes that undergoes site-specific replacement. A major obstacle in understanding how this system evolved is the poorly understood relationships of the earliest chondrichthyans and the profusion of morphologically and terminologically diverse bones, cartilages, splints and whorls that they possess. Here we use tomographic methods to investigate mandibular structures in several early branching  acanthodian-grade stem-chondrichthyans. We show that the dentigerous jaw bones of disparate genera of ischnacanthids are united by a common construction, being growing bones with non-shedding dentition. Mandibular splints, which support the ventro-lateral edge of the Meckels cartilage in some taxa, are formed from dermal bone and may be an acanthodid synapomorphy. We demonstrate that the teeth of Acanthodopsis are borne directly on the mandibular cartilage and that this taxon is deeply nested within an edentulous radiation, representing an unexpected independent origin of teeth. Many or even all of the range of unusual oral structures may be apomorphic, but they should nonetheless be considered when building hypotheses of tooth and jaw evolution, both in chondrichthyans and more broadly. Improved radiation expression profiling in blood by sequential application of sensitive and specific gene signatures PurposeCombinations of expressed genes can discriminate radiation-exposed from normal control blood samples by machine learning based signatures (with 8 to 20% misclassification rates). These signatures can quantify therapeutically-relevant as well as accidental radiation exposures. The prodromal symptoms of Acute Radiation Syndrome (ARS) overlap those present in Influenza and Dengue Fever infections. Surprisingly, these human radiation signatures misclassified gene expression profiles of virally infected samples as false positive exposures. The present study investigates these and other confounders, and then mitigates their impact on signature accuracy.

MethodsThis study investigated recall by previous and novel radiation signatures independently derived from multiple Gene Expression Omnibus datasets on common and rare non-malignant blood disorders and blood-borne infections (thromboembolism, S. aureus bacteremia, malaria, sickle cell disease, polycythemia vera, and aplastic anemia). Normalized expression levels of signature genes are used as input to machine learning-based classifiers to predict radiation exposure in other hematological conditions.

ResultsExcept for aplastic anemia, these blood-borne disorders modify the normal baseline expression values of genes present in radiation signatures, leading to false-positive misclassification of radiation exposures in 8 to 54% of individuals. Shared changes, predominantly in DNA damage response and apoptosis-related gene transcripts in radiation and confounding hematological conditions, compromise the utility of these signatures for radiation assessment. These confounding conditions (sickle cell disease, thromboembolism, S. aureus bacteremia, malaria) induce neutrophil extracellular traps, initiated by chromatin decondensation, DNA damage response and fragmentation followed by programmed cell death. Riboviral infections (for example, Influenza or Dengue fever) have been proposed to bind and deplete host RNA binding proteins, inducing R-loops in chromatin. R-loops that collide with incoming replication forks can result in incompletely repaired DNA damage, inducing apoptosis and releasing mature virus. To mitigate the effects of confounders, we evaluated predicted radiation-positive samples with novel gene expression signatures derived from radiation-responsive transcripts encoding secreted blood plasma proteins whose expression levels are unperturbed by these conditions.

ConclusionsThis approach identifies and eliminates misclassified samples with underlying hematological or infectious conditions, leaving only samples with true radiation exposures. Diagnostic accuracy is significantly improved by selecting genes that maximize both sensitivity and specificity in the appropriate tissue using combinations of the best signatures for each of these classes of signatures. Multiplex knockout of trichome-regulating MYB duplicates in hybrid poplar using a single gRNA As the focus for CRISPR edited plants moves from proof-of-concept to real world applications, precise gene manipulation will increasingly require concurrent multiplex editing for polygenic traits. A common approach for editing across multiple sites is to design one gRNA per target; however, this complicates construct assembly and increases the possibility of off-target mutations. In this study, we utilized one gRNA to target MYB186, a known positive trichome regulator, as well as its paralogs MYB138 and MYB38 at a consensus site for mutagenesis in Populus tremula x P. alba INRA 717-1B4. Unexpected duplications of MYB186 and MYB138 resulted in a total of eight alleles for the three targeted genes in the hybrid poplar. Deep sequencing and PCR analyses confirmed editing across all eight targets in nearly all of the resultant glabrous mutants, ranging from small indels to large genomic dropouts, with no off-target activity detected at four potential sites. This highlights the effectiveness of a single gRNA targeting conserved exonic regions for multiplex editing. Additionally, cuticular wax and whole leaf analyses showed a complete absence of triterpenes in the trichomeless mutants, hinting at a previously undescribed role for the non-glandular trichomes of poplar.

ONE SENTENCE SUMMARYTargeting conserved sequences with a single gRNA allowed efficient mutagenesis of a multigene family and the recovery of trichomeless and triterpene-free poplar mutants. Elucidation of SARS-CoV-2 budding mechanisms through molecular dynamics simulations of M and E protein complexes SARS-CoV-2 and other coronaviruses pose major threats to global health, yet computational efforts to understand them have largely overlooked the process of budding, a key part of the coronavirus life cycle. When expressed together, coronavirus M and E proteins are sufficient to facilitate budding into the ER-Golgi intermediate compartment (ERGIC). To help elucidate budding, we ran atomistic molecular dynamics (MD) simulations using the Feig laboratorys refined structural models of the SARS-CoV-2 M protein dimer and E protein pentamer. Our MD simulations consisted of M protein dimers and E protein pentamers in patches of membrane. By examining where these proteins induced membrane curvature in silico, we obtained insights around how the budding process may occur. Multiple M protein dimers acted together to induce global membrane curvature through protein-lipid interactions while E protein pentamers kept the membrane planar. These results could eventually help guide development of antiviral therapeutics which inhibit coronavirus budding. Large Bi-ethnic Study of Plasma Proteome Leads to Comprehensive Mapping of cis-pQTL and Models for Proteome-wide Association Studies Improved understanding of genetic regulation of proteome can facilitate the identification of causal mechanisms for complex traits. We analyzed data on 4,657 plasma proteins from 7,213 European American (EA) and 1,871 African American (AA) individuals from the ARIC study, and further replicated findings on 467 AA individuals from the AASK study. Here we identified 2,004 proteins in EA and 1,618 in AA, with majority overlapping, which showed associations with common variants in cis-regions. Availability of AA samples led to smaller credible sets and significant number of population-specific cis-pQTLs. Elastic-net produced powerful models for protein prediction in both populations. An application of proteome-wide association studies (PWAS) to serum urate and gout, implicated several proteins, including IL1RN, revealing the promise of the drug anakinra to treat acute gout flares. Our study demonstrates the value of large and diverse ancestry study for genetic mechanisms of molecular phenotypes and their relationship with complex traits. TeamTree analysis: a new approach to evaluate scientific production Advances in science and technology depend on the work of research teams and the publication of results through peer-reviewed articles representing a growing socio-economic resource. Current methods to mine the scientific literature regarding a field of interest focus on content, but the workforce credited by authorship remains largely unexplored, and appropriate measures of scientific production are debated. Here, a new bibliometric approach named TeamTree analysis is introduced that visualizes the development and composition of the workforce driving a field. A new citation-independent measure that scales with the H index estimates impact based on publication record, genealogical ties and collaborative connections. This author-centered approach complements existing tools to mine the scientific literature and to evaluate research across disciplines. Selection towards lighter seeds in Danish grasslands over an eight-year period Time-series analysis of cover data from 236 Danish grassland sites demonstrated community selection on seed mass. Across four grassland habitat types and during an eight-year period there was significant community selection towards lighter seeds. In the analysis, the continuous seed size variable was used to group plant species into functional types. This method was chosen in order to account for the sampling process of the abundance data, and is in contrast to most other analyses of trait selection, where the community weighted mean of the traits is used as the dependent variable. Generally, little is known on the underlying causes of possible plant trait community selection in semi-natural grasslands that are not subjected to successional processes. The compound of baicalein, wogonin, and oroxylin-A inhibiting EMT in A549 cell line via PI3K/AKT-TWIST1-glycolysis pathway Non-small cell lung cancer (NSCLC) is a worldwide disease with high morbidity and mortality, which is most derived from its metastasis. Some researches show that the epithelial-mesenchymal transition (EMT) process promotes lung cancer cells migration and invasion, leading to NSCLC metastasis. Total Flavonoid Aglycones Extract (TFAE) isolated from Scutellaria baicalensis was reported to inhibit tumor growth and induce apoptosis. In this study, we found that baicalein, wogonin, and oroxylin-A were the active compounds of TFAE. After reconstructing with these three compounds (baicalein (65.8%), wogonin (21.2%), and oroxylin-A (13.0%)), the reconstructed TFAE (reTFAE) present inhibitory effect on the EMT process of A549 cells. Then, bioinformatic technology was employed to elucidate the potential pharmacodynamic mechanism network of reTFAE. We identified the relationship between reTFAE and PI3K/Akt signaling pathways, with TWIST1 as the key protein. LY294002, the inhibitor of PI3K/Akt signaling pathway, and knock-down TWIST1 could significantly enhance the efficacy of reTFAE, with increasing expression of epithelial markers and decreasing expression of mesenchymal markers in A549 cells at the same time. Furthermore, stable isotope dimethyl-labeled proteomics technology was conducted to complement the follow-up mechanism that the EMT-inhibition process may be realized through glycolysis pathway. In conclusion, we claim that TWIST1-targeted flavonoids could provide a new strategy to inhibit EMT progress for the treatment of NSCLC. Estrogen-related receptor alpha and Rplp1-dependent translation coordinately regulate starvation response and decrease NASH progression Although general translation declines during fasting, maintaining the translation of a subset or proteins is necessary for metabolic homeostasis and cell viability. Using unbiased proteome analysis of hepatic cells during starvation, we identified a novel pathway in which Esrra-mediated transcription of Rplp1-dependent translation of lysosomal proteins declined during early starvation and recovered after prolonged starvation to restore autophagy-lysosome function. Interestingly, hepatic Esrra-Rplp1-dependent translation rate of lysosomal proteins also was impaired in patients and mice with non-alcoholic steatohepatitis (NASH), and translational response to starvation was dysregulated in mice with NASH. Remarkably, activation of Esrra pharmacologically, genetically, or by alternate day fasting restored protein translation, increased expression of lysosomal proteins, induced autophagy, and reduced lipotoxicity, inflammation, and fibrosis in cell culture and in vivo models of NASH. Thus, hepatic Esrra is essential for ribosome-dependent translation of lysosomal proteins during starvation, and prevention of lipotoxicity and progression in NASH.

Lay summaryFasting for weight loss improves non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH); however, the mechanism is not well understood. Our study shows that a nuclear protein, estrogen related receptor alpha (Esrra), increases ribosome-mediated translation of autophagy and lysosome proteins during chronic starvation to maintain essential metabolic pathways for cell survival. Surprisingly, this translational pathway is impaired during NASH with reduced lysosome-autophagy activity accompanied by increased inflammation and fibrosis gene expression in the liver. Pharmacologic, genetic and dietary activation of Esrra decreases lipid-mediated toxicity in liver cells as well as inflammation and fibrosis in livers from mice with NASH. These findings suggest that the Esrra-ribosome-lysosome pathway is important for liver response to fasting and NASH and thus may be a good therapeutic target for the treatment of NASH. Comprehensive analysis of pyroptosis-associated in molecular classification, immunity and prognostic of glioma Integrative analysis was performed in the Chinese Glioma Genome Atlas and The Cancer Genome Atlas to describe the pyroptosis-associated molecular classification and prognostic signature in glioma. Pyroptosis-related genes were used for consensus clustering and to develop a prognostic signature. The immune statuses, molecular alterations and clinical features of differentially expressed genes were analyzed among different subclasses and risk groups. A lncRNA-miRNA-mRNA network was built, and drug sensitivity analysis was used to identify small molecular drugs for the identified genes. Glioma can be divided into two subclasses using 30 pyroptosis-related genes. Cluster 1 displayed high immune signatures and poor prognosis as well as high immune-related function scores. A prognostic signature based on 15 pyroptosis-related genes of the CGGA cohort can predict the overall survival of glioma and was well validated in the TCGA cohort. Cluster 1 had higher risk scores. The high-risk group had high immune cell and function scores and low DNA methylation of pyroptosis-related genes. The differences in pyroptosis-related gene mutations and somatic copy numbers were significant between the high-risk and low-risk groups. The ceRNA regulatory network uncovered the regulatory patterns of different risk groups in glioma. Nine pairs of target genes and drugs were identified. In vitro, CASP8 promotes the progression of glioma cells. Pyroptosis-related genes can reflect the molecular biological and clinical features of glioma subclasses. The established prognostic signature can predict prognosis and distinguish molecular alterations in glioma patients. Our comprehensive analyses provide valuable guidelines for improving glioma patient management and individualized therapy. GCN5L1 promotes diastolic dysfunction by inhibiting cardiac pyruvate oxidation Left ventricular diastolic dysfunction is a structural and functional condition that precedes the development of heart failure with preserved ejection fraction (HFpEF). The etiology of diastolic dysfunction includes alterations in fuel substrate metabolism that negatively impact cardiac bioenergetics, and may precipitate the eventual transition to heart failure. To date, the molecular mechanisms that regulate early changes in fuel metabolism leading to diastolic dysfunction remain unclear. In this report, we use a diet-induced obesity model and quantitative acetylproteomics in aged mice to show that inhibitory lysine acetylation of the pyruvate dehydrogenase (PDH) complex promotes energetic deficits and diastolic dysfunction in mouse hearts. Cardiomyocyte-specific deletion of the mitochondrial lysine acetylation regulatory protein GCN5L1 prevented hyperacetylation of the PDH complex subunit PDHA1, allowing aged obese mice to continue using pyruvate as a bioenergetic substrate in the heart. Our findings suggest that changes in mitochondrial protein lysine acetylation represent a key metabolic component of diastolic dysfunction that precedes the development of heart failure. Fatal COVID-19 and non-COVID-19 Acute Respiratory Distress Syndrome is Associated with Incomplete Alveolar Type 1 Epithelial Cell Differentiation from the Transitional State Without Fibrosis ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. Major transcriptomic, epigenetic and metabolic changes underly the pluripotency continuum in rabbit preimplantation embryos Despite the growing interest in the rabbit model for developmental and stem cell biology, the characterization of embryos at the molecular level is still poorly documented. We conducted a transcriptome analysis of rabbit pre-implantation embryos from E2.7 (morula stage) to E6.6 (early primitive streak stage) using bulk and single-cell RNA-sequencing. In parallel, we studied oxidative phosphorylation and glycolysis and analysed active and repressive epigenetic modifications during blastocyst formation and expansion. We generated a transcriptomic, epigenetic, and metabolic map of the pluripotency continuum in rabbit preimplantation embryos and identified novel markers of naive pluripotency that might be instrumental for deriving naive pluripotent stem cell lines. Although the rabbit is evolutionarily closer to mice than to primates, we found that the transcriptome of rabbit epiblast cells shares common features with that of humans and non-human primates.

Summary StatementRabbit preimplantation embryos share characteristics with human and monkey embryos with respect to timing of early lineage segregation and expression of marker genes for naive and primed pluripotency. Identification of differentially distributed gene expression and distinct sets of cancer-related genes identified by changes in mean and variability There is increasing evidence that changes in the variability or overall distribution of gene expression are important both in normal biology and in diseases, particularly cancer. Genes whose expression differs in variability or distribution without a difference in mean are ignored by traditional differential expression-based analyses. Using a Bayesian hierarchical model that provides tests for both differential variability and differential distribution for bulk RNA-seq data, we report here an investigation into differential variability and distribution in cancer. Analysis of eight paired tumour-normal datasets from The Cancer Genome Atlas confirms that differential variability and distribution are able to identify cancer-related genes. We further demonstrate that differential variability identifies cancer-related genes that are missed by differential expression analysis, and that differential expression and differential variability identify functionally distinct sets of genes. These results suggest that differential variability analysis may provide insights into genetic aspects of cancer that would not be revealed by differential expression, and that differential distribution analysis may allow for more comprehensive identification of cancer-related genes than analyses based on changes in mean or variability alone. Mechanisms of damage prevention, signalling, and repair impact disease tolerance The insect gut is frequently exposed to pathogenic threats and must not only clear these potential infections, but also tolerate relatively high microbe loads. In contrast to the mechanisms that eliminate pathogens, we currently know less about the mechanisms of disease tolerance. We investigated how well-described mechanisms that either prevent, signal, control, or repair damage during infection contribute to the phenotype of disease tolerance. We established enteric infections with the bacterial pathogen Pseudomonas entomophila in transgenic lines of Drosophila melanogaster fruit flies affecting dcy (a major component of the peritrophic matrix), upd3 (a cytokine-like molecule), irc (a negative regulator of reactive oxygen species) and egfr1 (epithelial growth factor receptor). Flies lacking dcy experienced the highest susceptibility, while loss of function of either irc or upd3 reduced tolerance in both sexes. The disruption of egfr1 resulted in a severe loss in tolerance in male flies but had no substantial effect on the ability of female flies to tolerate P. entomophila infection, despite carrying greater microbe loads than males. Together, our findings provide evidence for the role of damage limitation mechanisms in disease tolerance and highlight how sex differences in these mechanisms could generate sexual dimorphism in disease tolerance. Impedance scaling for gold and platinum microelectrodes ObjectiveElectrical measurement of the activity of individual neurons is a primary goal for many invasive neural electrodes. Making these "single unit" measurements requires that we fabricate electrodes small enough so that only a few neurons contribute to the signal, but not so small that the impedance of the electrode creates overwhelming noise or signal attenuation. Thus, neuroelectrode design often must strike a balance between electrode size and electrode impedance, where the impedance is often assumed to scale linearly with electrode area.

Approach and main resultsHere we study how impedance scales with neural electrode area and find that the 1 kHz impedance of Pt electrodes (but not Au electrodes) transitions from scaling with area (r-2) to scaling with perimeter (r-1) when the electrode radius falls below 10 microns. This effect can be explained by the transition from planar to spherical diffusion behavior previously reported for electrochemical microelectrodes. Significance: These results provide important intuition for designing small, single unit recording electrodes. Specifically, for materials where the impedance is dominated by a pseudo-capacitance that is associated with a diffusion limited process, the total impedance will scale with perimeter rather than area when the electrode size becomes comparable with the diffusion layer thickness. For Pt electrodes this transition occurs around 10 um radius electrodes. At even lower frequencies (1 Hz) impedance approaches a constant. This transition to r-1 scaling implies that electrodes with a pseudo-capacitance can be made smaller than one might expect before thermal noise or voltage division limits the ability to acquire high-quality single-unit recordings. Getting more out of FLAG-Tag co-immunoprecipitation mass spectrometry experiments using FAIMS. Co-immunoprecipitation of proteins coupled to mass spectrometry is critical for the understanding of protein interaction networks. In instances where a suitable antibody is not available, it is common to graft synthetic tags onto target protein sequences and allowing the use of commercially available antibodies for affinity purification. A common approach is through FLAG-Tag co-immunoprecipitation. To allow the selective elution of protein complexes, competitive displacement using a large molar excess of the tag peptides is often carried out. Yet, this creates downstream challenges for the mass spectrometry analysis due to the presence of large quantities of these peptides. Here, we demonstrate that Field Asymmetric Ion Mobility Spectrometry (FAIMS), a gas phase ion separation device prior to mass spectrometry analysis can be applied to FLAG-Tag co-immunoprecipitation experiment to increase the depth of protein coverage. By excluding these abundant tag peptides, we were able to observe deeper coverage of interacting proteins and as a result, deeper biological insights, without the need for additional sample handling or altering sample preparation protocols.