Outlier detection in multimodal MRI identifies rare individual phenotypes among 20,000 brains Outliers in neuroimaging represent spurious data or the data of unusual phenotypes that deserve special attention such as clinical follow-up. Outliers have usually been detected in a supervised or semi-supervised manner for labeled neuroimaging cohorts. There has been much less work using unsupervised outlier detection on large unlabeled cohorts like the UK Biobank brain imaging dataset. Given its large sample size, rare imaging phenotypes within this unique cohort are of interest, as they are often clinically relevant and could be informative for discovering new processes. Here we developed a two-level outlier detection and screening methodology to characterize individual outliers of multiple different brain imaging phenotypes from 20,000 UK Biobank subjects. In primary screening, every subject was parameterized with an outlier score per imaging phenotype to quantitate the degree of outlierness. This approach enabled the assessment of test-retest reliability via outlier scores, which ranged from excellent reliability for ventricular volume, white matter lesion volume, and fractional anisotropy, to good reliability for mean diffusivity and cortical thickness. Resting-state functional connectivity was eliminated for individual-level outlier screening due to its low test-retest reliability of outlier scores. In secondary screening, the extreme outliers (1110 subjects) were examined individually, and those arising from data collection/processing errors were eliminated. A subgroup (108 subjects) of the remaining non-artifactual outliers were radiologically reviewed, and radiological findings were identified in 98%. This study establishes an unsupervised framework for investigating rare individual imaging phenotypes within a large neuroimaging cohort.
Movement decoding using spatio-spectral features of cortical and subcortical local field potentials The application of machine learning to intracranial signal analysis has the potential to revolutionize deep brain stimulation (DBS) by personalizing therapy to dynamic brain states, specific to symptoms and behaviors. Most decoding pipelines for movement decoding in the context of adaptive DBS are based on single channel frequency domain features, neglecting spatial information available in multichannel recordings. Such features are extracted either from DBS lead recordings in the subcortical target and/or from electrocorticography (ECoG). To optimize the simultaneous use of both types of signals, we developed a supervised online-compatible movement decoding pipeline based on multichannel and multiple site recordings. We found that adding spatial information to the model has the potential to improve decoding. In addition, we demonstrate movement decoding from spatio-spectral features derived from cortical and subcortical oscillations. We demonstrate between-patients variability of the spatial neural maps and its relationship to feature decoding performance. This application of spatial filters to decode movement from combined cortical and subcortical recordings is an important step in developing machine learning approaches for intelligent DBS systems.
Suppression of sost/sclerostin and dickkopf-1 promote intervertebral disc structure in mice Intervertebral disc (IVD) degeneration is a leading cause of low back pain and characterized by accelerated extracellular matrix breakdown and IVD height loss but there is no approved pharmacological therapeutic. Deletion of Wnt signaling receptor Lrp5 induces IVD degeneration and suggests that Wnt signaling in the IVD may be responsive to inhibition of Wnt signaling inhibitors sost(gene)/sclerostin(protein) or dickkopf-1 (dkk1). Anti-sclerostin antibody (Scl-Ab) is an FDA-approved bone therapeutic that activates Wnt signaling. We (1) determined if pharmacological neutralization of sclerostin, dkk1 or their combination stimulate Wnt signaling and promote IVD structure and (2) determined the extent of the response of the IVD to global, persistent deletion of sost. Nine-week-old C57Bl/6J female mice (n=6-7/grp) were subcutaneously injected 2x/wk for 5.5 wk with scl-Ab (25 mg/kg), dkk1-Ab (25 mg/kg), 3:1 scl-Ab/dkk1-Ab (18.75:6.25 mg/kg) or vehicle (Veh). Separately, IVD of sost KO and WT (wildtype) mice (n=8, grp) were harvested at 16 weeks of age. First, compared to vehicle, scl-Ab, dkk1-Ab and 3:1 scl-Ab/dkk1-Ab similarly increased lumbar IVD height and {beta}-catenin gene expression. Despite these similarities, scl-Ab decreased cellular stress-related heat shock protein gene expressions while neither dkk1-Ab nor scl-Ab/dkk1-Ab altered the same. Genetically and compared to WT, sost KO increased MRI-determined hydration and proteoglycan staining in the IVD. Notably, persistent deletion of sost was compensated by upregulation of dkk1, which consequently reduced the cell nuclear fraction for Wnt signaling transcription factor {beta}-catenin in whole IVD. Lastly, RNA-sequencing pathway analysis confirmed the compensatory suppression of Wnt signaling and determined a reduction of cellular stress pathways. Together, suppression of sost/sclerostin or dkk1 each promote IVD structure by stimulating Wnt signaling, but sclerostin and dkk1 may differentially regulate cellular stress pathways. Ultimately, postmenopausal women prescribed scl-Ab injections to prevent vertebral fracture may also benefit from a restoration of IVD height and health.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/449486v2_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@db2e17org.highwire.dtl.DTLVardef@1af1bbborg.highwire.dtl.DTLVardef@145cc4corg.highwire.dtl.DTLVardef@167a19e_HPS_FORMAT_FIGEXP  M_FIG C_FIG Suppression of Wnt signaling inhibitors by genetic or pharmacological approaches promotes intervertebral disc structure and hydration by Wnt signaling. However, persistent activation of Wnt signaling induces a compensatory reduction of Wnt signaling that shifts IVD cells toward a chondrocyte-like (CLC) phenotype. AF: annulus fibrosus, NC: notochordal cell, NP: nucleus pulposus, PG: proteoglycan Deep learning can predict multi-omic biomarkers from routine pathology images: A systematic large-scale study We assessed the pan-cancer predictability of multi-omic biomarkers from haematoxylin and eosin (H&E)-stained whole slide images (WSI) using deep learning (DL) throughout a systematic study. A total of 13,443 DL models predicting 4,481 multi-omic biomarkers across 32 cancer types were trained and validated. The investigated biomarkers included a broad range of genetic, transcriptomic, proteomic, and metabolic alterations. Furthermore, established markers relevant for prognosis, molecular subtypes and clinical outcomes were included. Overall, we established the general feasibility of predicting multi-omic markers directly from routine histology images with DL across solid cancer types, where 50% of the models could perform at an area under the curve (AUC) of more than 0.633 (with 25% of the models having an AUC larger than 0.711). A wide range of biomarkers were detectable from routine histology images across all investigated cancer types, with a mean AUC of at least 0.62 in almost all malignancies. Strikingly, we observed that biomarker predictability was mostly consistent and not dependent on sample size and class ratio, suggesting a degree of true predictability inherent in histomorphology. Together, the results of our study show the potential of DL to predict a multitude of biomarkers across the omics spectrum using only routine slides. This paves the way for accelerating diagnosis and developing more precise treatments for cancer patients. Cell type-specific differential expression in spatial transcriptomics Spatial transcriptomics enables spatially resolved gene expression measurements at near single-cell resolution. There is a pressing need for computational tools to enable the detection of genes that are differentially expressed (DE) within specific cell types across tissue context. We show that current approaches cannot learn cell type-specific DE due to changes in cell type composition across space and the fact that measurement units often detect transcripts from more than one cell type. Here, we introduce a statistical method, Cell type-Specific Inference of Differential Expression (C-SIDE), that identifies cell type-specific patterns of differential gene expression while accounting for localization of other cell types. We model spatial transcriptomics gene expression as an additive mixture across cell types of general log-linear cell type-specific expression functions. This approach provides a unified framework for defining and identifying gene expression changes in a wide-range of relevant contexts: changes due to pathology, anatomical regions, physical proximity to specific cell types, and cellular microenvironment. Furthermore, our approach enables statistical inference across multiple samples and replicates when such data is available. We demonstrate, through simulations and validation experiments on Slide-seq and MER-FISH datasets, that our approach accurately identifies cell type-specific differential gene expression and provides valid uncertainty quantification. Lastly, we apply our method to characterize spatially-localized tissue changes in the context of disease. In an Alzheimers mouse model Slide-seq dataset, we identify plaque-dependent patterns of cellular immune activity. We also find a putative interaction between tumor cells and myeloid immune cells in a Slide-seq tumor dataset. We make our C-SIDE method publicly available as part of the open source R package https://github.com/dmcable/spacexr. The spatial configuration of biotic interactions shapes coexistence-area relation-ships in an annual plant community The increase of species richness with area is a universal phenomenon on Earth. How-ever, this observation contrasts with our poor understanding of how these species-area relationships (SARs) emerge from the collective effects of area, spatial heterogeneity, and local interactions. By combining a structuralist approach with five years of empirical observations in a highly-diverse Mediterranean grassland, we show that spatial hetero-geneity plays a little role in the accumulation of species richness with area in our system. Instead, as we increase the sampled area more species combinations are realized, and they coexist mainly due to direct pairwise interactions rather than by changes in single-species dominance or by indirect interactions. We also identify a small set of transient species with small population sizes that are consistently found across spatial scales. These findings empirically support the importance of the architecture of species interactions together with stochastic events for driving coexistence- and species-area relationships. Conformist social learning inoculates against adverse risk aversion Given the ubiquity of potentially adverse behavioural bias owing to myopic trial-and-error learning, it seems paradoxical that improvements in decision-making performance through conformist social learning, a process widely considered to be bias amplification, still prevail in animal collective behaviour. Here we show, through model analyses and large-scale interactive behavioural experiments with 585 human subjects, that conformist influence can indeed promote favourable risk taking in repeated experience-based decision making, even though many individuals are systematically biased towards adverse risk aversion. Although strong positive feedback conferred by copying the majoritys behaviour could result in unfavourable informational cascades, our differential equation model of collective behavioural dynamics identified a key role for increasing exploration by negative feedback arising when a weak minority influence undermines the inherent behavioural bias. This  collective behavioural rescue, emerging through coordination of positive and negative feedback, highlights a benefit of collective learning in a broader range of environmental conditions than previously assumed and resolves the ostensible paradox of adaptive collective behavioural flexibility under conformist influences. 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. Beyond Spike: Identification of nine highly prevalent SARS-CoV-2-specific CD8 T-cell epitopes in a large Norwegian cohort T-cell epitopes with broad population coverage may form the basis for a new generation of SARS-CoV-2 vaccines. However, published studies on immunoprevalence are limited by small test cohorts, low frequencies of antigen-specific cells and lack of data correlating eluted HLA ligands with T-cell responsiveness. As the protective role of pre-existing cross-reactivity to homologous peptides is unclear, we aimed to identify SARS-CoV-2-specific minimal epitopes recognized by CD8 T-cells among 48 peptides eluted from prevalent HLA alleles, and an additional 84 predicted binders, in a large cohort of convalescents (n=83) and pre-pandemic control samples (n=19). We identified nine conserved SARS-CoV-2-specific epitopes restricted by four of the most prevalent HLA class I alleles in the Norwegian study cohort, to which responding CD8 T cells were detected in 70-100% of convalescents expressing the relevant HLA allele. Only two of these were derived from the Spike protein, included in current vaccines. We found a strong correlation between immunoprevalence and immunodominance. Thus, the CD8 T-cell response to SARS-CoV-2 is more focused than previously believed. Using a new algorithm, we predict that a vaccine including these epitopes could induce a T-cell response in 83% of Caucasians. High-throughput characterization of photocrosslinker-bearing ion channel variants to map residues critical for function and pharmacology Incorporation of non-canonical amino acids (ncAAs) can endow proteins with novel functionalities, such as crosslinking or fluorescence. In ion channels, the function of these variants can be studied with great precision using standard electrophysiology, but this approach is typically labor intensive and low throughput. Here, we establish a high-throughput protocol to conduct functional and pharmacological investigations of ncAA-containing hASIC1a (human acid-sensing ion channel 1a) variants in transiently transfected mammalian cells. We introduce three different photocrosslinking ncAAs into 103 positions and assess the function of the resulting 309 variants with automated patch-clamp (APC). We demonstrate that the approach is efficient and versatile, as it is amenable to assessing even complex pharmacological modulation by peptides. The data show that the acidic pocket is a major determinant for current decay and live-cell crosslinking provides insight into the hASIC1a-psalmotoxin-1 interaction. Further, we provide evidence that the protocol can be applied to other ion channels, such as P2X2 and GluA2 receptors. We therefore anticipate the approach to enable future APC-based studies of ncAA-containing ion channels in mammalian cells. Phylogenomic discordance suggests polytomies along the backbone of the large genus Solanum Premise of the studyEvolutionary studies require solid phylogenetic frameworks, but increased volumes of phylogenomic data have revealed incongruent topologies among gene trees in many organisms both between and within genomes. Some of these incongruences indicate polytomies that may remain impossible to resolve. Here we investigate the degree of gene-tree discordance in Solanum, one of the largest flowering plant genera that includes the cultivated potato, tomato, and eggplant, as well as 24 minor crop plants.

MethodsA densely sampled species-level phylogeny of Solanum is built using unpublished and publicly available Sanger sequences comprising 60% of all accepted species (742 spp.) and nine regions (ITS, waxy, and seven plastid markers). The robustness of this topology is tested by examining a full plastome dataset with 140 species and a nuclear target-capture dataset with 39 species of Solanum (Angiosperms353 probe set).

Key resultsWhile the taxonomic framework of Solanum remained stable, gene tree conflicts and discordance between phylogenetic trees generated from the target-capture and plastome datasets were observed. The latter correspond to regions with short internodal branches, and network analysis and polytomy tests suggest the backbone is composed of three polytomies found at different evolutionary depths. The strongest area of discordance, near the crown node of Solanum, could potentially represent a hard polytomy.

ConclusionsWe argue that incomplete lineage sorting due to rapid diversification is the most likely cause for these polytomies, and that embracing the uncertainty that underlies them is crucial to understand the evolution of large and rapidly radiating lineages. The evolution of stomatal traits along the trajectory towards C4 photosynthesis C4 photosynthesis optimizes plants carbon and water relations, allowing high photosynthetic rate with low stomatal conductance. Stomata have long been believed as a part of C4 syndrome. However, it remains unclear how stomata traits evolved along the path from C3 to C4. Stomatal patterning was examined in Flaveria genus, a model for studying C4 evolution. Comparative, transgenic and semi-in-vitro experiments were used to study molecular basis that underlies stomatal traits along C4 evolution. Novel results: the evolution from C3 to C4 species through intermediate species is accompanied by a stepwise rather than an abrupt change in the stomatal traits. The initial change occurs near Type II and dramatic change occurs at the C4-like species. On the road to C4, stomata become less in number but bigger in size and changes in stomatal density dominates changes in maximum stomatal conductance (gsmax). The reduction of FSTOMAGEN expression underlies altered gsmax between Flaveria species with different photosynthetic pathways and likely occurs in other C4 lineages. Our study provides insight into the pattern, mechanism and role of stomatal evolution along the road towards C4. This work highlights the stomatal traits in the current C4 evolutionary model and the co-evolution of photosynthetic pathway and stomata. Decoding regulatory specificity of human ribosomal proteins Human ribosomes, made of around 80 ribosomal proteins (RPs) and four ribosomal RNAs, have long been thought as uniform passive protein-making factories with little regulatory function. Recently, accumulating evidence showed heterogeneity of RP composition in ribosomes responsible for regulating gene expression in development and tumorigenesis. However, a comprehensive understanding of regulatory spectrum of RPs is still lacking. In this study, we conducted a systematic survey of regulatory specificity of human RPs on global gene expression. We quantified translational and transcriptional changes of gene expression upon deficiency of 75 RPs, including 44 from the large subunit (60S) and 31 from the small subunit (40S), by ribosomal profiling and RNA sequencing analysis. We showed that RP deficiency induced diverse expression changes, particularly at the translational level. RPs were subjected to co-translational regulation under ribosomal stress where deficiency of the 60S and the 40S RPs had opposite effects on the two subunits. RP deficiency perturbed expression of genes related to cell cycle, cellular metabolism, signal transduction and development. Deficiency of RPs from the 60S led to a greater repression effect on cell growth than that from the 40S by perturbing P53 signaling and cell cycle pathways. To demonstrate functional specificity of RPs, we showed that RPS8 deficiency stimulated cellular apoptosis and RPL13 or RPL18 deficiency promoted cellular senescence. We also showed that RPL11 and RPL15 played important roles in retina development and angiogenesis, respectively. Overall, our study demonstrated a widespread regulatory role of RPs in controlling cellular activity, providing an important resource which can offer novel insights into ribosome regulation in human diseases and cancer. Balancing sensitivity and specificity in preclinical research The success of scientific discovery in preclinical drug development is based on the different roles of exploration and confirmation. Exploration requires sensitivity while confirmation needs to be specific. Based on published empirical data, we simulated two preclinical research trajectories to examine their effectiveness to detect true effects while keeping animal numbers low. We compare a conventional p-value based approach with a method based on an a priori determined smallest effect size of interest (SESOI). Using a SESOI increases transition rates from exploration to confirmation and results in higher detection rates across the trajectory. Specificity in the SESOI trajectory increases if the prior probability of true effects is low. We conclude that employing a SESOI is superior to a p-value based approach. Based on our findings, we propose a reconsideration of planning and conducting preclinical experiments, especially when the prior probability of true hypotheses is low. Fine-scale adaptations to environmental variation and growth strategies drive phyllosphere Methylobacterium diversity. Methylobacterium is a prevalent bacterial genus of the phyllosphere. Despite its ubiquity, little is known about the extent to which its diversity reflects neutral processes like migration and drift, versus environmental filtering of life history strategies and adaptations. In two temperate forests, we investigated how phylogenetic diversity within Methylobacterium was structured by biogeography, seasonality, and growth strategies. Using deep, culture-independent barcoded marker gene sequencing coupled with culture-based approaches, we uncovered a considerable diversity of Methylobacterium in the phyllosphere. We cultured different subsets of Methylobacterium lineages depending upon the temperature of isolation and growth (20 {degrees}C or 30 {degrees}C), suggesting long-term adaptation to temperature. To a lesser extent than temperature adaptation, Methylobacterium diversity was also structured across large (>100km; between forests) and small geographical scales (<1.2km within forests), among host tree species, and was dynamic over seasons. By measuring growth of 79 isolates at different temperature treatments, we observed contrasting growth performances, with strong lineage- and season-dependent variations in growth strategies. Finally, we documented a progressive replacement of lineages with a high-yield growth strategy typical of cooperative, structured communities, in favor of those characterized by rapid growth, resulting in convergence and homogenization of community structure at the end of the growing season. Together our results show how Methylobacterium is phylogenetically structured into lineages with distinct growth strategies, which helps explain their differential abundance across regions, host tree species, and time. This works paves the way for further investigation of adaptive strategies and traits within a ubiquitous phyllosphere genus.

ImportanceMethylobacterium is a bacterial group tied to plants. Despite its ubiquity and importance to their hosts, little is known about the processes driving Methylobacterium community dynamics. By combining traditional culture-dependent and independent (metabarcoding) approaches, we monitored Methylobacterium diversity in two temperate forests over a growing season. On the surface of tree leaves, we discovered remarkably diverse and dynamic Methylobacterium communities over short temporal (from June to October) and spatial scales (within 1.2 km). Because we cultured different subsets of Methylobacterium diversity depending on the temperature of incubation, we suspected that these dynamics partly reflected climatic adaptation. By culturing strains in lab conditions mimicking seasonal variations, we found that diversity and environmental variations were indeed good predictors of Methylobacterium growth performances. Our findings suggest that Methylobacterium community dynamics at the surface of tree leaves results from the succession of strains with contrasted growth strategies in response to environmental variations. Robust retrieval of data stored in DNA by de Bruijn graph-based de novo strand assembly DNA data storage is a rapidly developing technology with great potential due to its high density, long-term durability, and low maintenance cost. The major technical challenges include various errors, such as the strand breaks, rearrangements, and indels that frequently arise during DNA synthesis, amplification, sequencing, and preservation. Through a de novo assembly strategy, we developed an algorithm based on the de Bruijn graph and greedy path search (DBGPS) to address these issues. DBGPS shows distinct advantages in handling DNA breaks, rearrangements, and indels. The robustness of DBGPS is demonstrated by accelerated aging, multiple independent data retrievals, deep error-prone PCR, and large data scale simulations. Remarkably, 6.8 MB of data can be retrieved accurately from a seriously corrupted sample that has been treated at 70 {degrees}C for 70 days. With DBGPS, we were able to achieve a logical density of 1.30 bits/cycle and a physical density of 295 PB/g.

One-Sentence SummaryA de Bruijn graph-based de novo assembly algorithm for DNA data storage enables fast and robust data readouts even with DNA samples that have been severely corrupted. Reconstitution of 3'-processing of mammalian pre-mRNA reveals a central role of RBBP6 The 3 ends of almost all eukaryotic mRNAs are generated in an essential two-step processing reaction, endonucleolytic cleavage of an extended precursor followed by the addition of a poly(A) tail. By reconstituting the reaction from overproduced and purified proteins, we provide a minimal list of fourteen polypeptides essential and two stimulatory for RNA processing. In a reaction depending on the polyadenylation signal AAUAAA, the reconstituted system cleaves pre-mRNA at a single preferred site corresponding to the one used in vivo. Among the proteins, Cleavage Factor I stimulates cleavage but is not essential, consistent with its prominent role in alternative polyadenylation. RBBP6 is required, structural data showing it to contact and presumably activate the endonuclease CPSF73 through its DWNN domain. The C-terminal domain of RNA polymerase II is dispensable. ATP, but not its hydrolysis, supports RNA cleavage by binding to the hClp1 subunit of cleavage factor II with submicromolar affinity. Cell-type specific circadian bioluminescence rhythms in Dbp reporter mice Circadian rhythms are endogenously generated physiological and molecular rhythms with a cycle length of about 24 h. Bioluminescent reporters have been exceptionally useful for studying circadian rhythms in numerous species. Here, we report development of a reporter mouse generated by modification of a widely expressed and highly rhythmic gene encoding D-site albumin promoter binding protein (Dbp). In this line of mice, firefly luciferase is expressed from the Dbp locus in a Cre-recombinase-dependent manner, allowing assessment of bioluminescence rhythms in specific cellular populations. A mouse line in which luciferase expression was Cre-independent was also generated. The Dbp reporter alleles do not alter Dbp gene expression rhythms in liver or circadian locomotor activity rhythms. In vivo and ex vivo studies show the utility of the reporter alleles for monitoring rhythmicity. Our studies reveal cell-type specific characteristics of rhythms among neuronal populations within the suprachiasmatic nuclei ex vivo. In vivo studies show Dbp-driven bioluminescence rhythms in the liver of Albumin-Cre;DbpKI/+ "liver reporter" mice. After a shift of the lighting schedule, locomotor activity achieved the proper phase relationship with the new lighting cycle more rapidly than hepatic bioluminescence did. As previously shown, restricting food access to the daytime altered the phase of hepatic rhythmicity. Our model allowed assessment of the rate of recovery from misalignment once animals were provided with food ad libitum. These studies confirm the previously demonstrated circadian misalignment following environmental perturbations and reveal the utility of this model for minimally invasive, longitudinal monitoring of rhythmicity from specific mouse tissues. Genetic interactions drive heterogeneity in causal variant effect sizes for gene expression and complex traits Despite the growing number of genome-wide association studies (GWAS), it remains unclear to what extent gene-by-gene and gene-by-environment interactions influence complex traits in humans. The magnitude of genetic interactions in complex traits has been difficult to quantify because GWAS are generally underpowered to detect individual interactions of small effect. Here, we develop a method to test for genetic interactions that aggregates information across all trait-associated loci. Specifically, we test whether SNPs in regions of European ancestry shared between European American and admixed African American individuals have the same causal effect sizes. We hypothesize that in African Americans, the presence of genetic interactions will drive the causal effect sizes of SNPs in regions of European ancestry to be more similar to those of SNPs in regions of African ancestry. We apply our method to two traits: gene expression in 296 African Americans and 482 European Americans in the Multi-Ethnic Study of Atherosclerosis (MESA) and low-density lipoprotein cholesterol (LDL-C) in 74K African Americans and 296K European Americans in the Million Veteran Program (MVP). We find significant evidence for genetic interactions in our analysis of gene expression; for LDL-C, we observe a similar point estimate although this is not significant, likely due to lower statistical power. These results suggest that gene-by-gene or gene-by-environment interactions modify the effect sizes of causal variants in human complex traits. METAbolomics data Balancing with Over-sampling Algorithms (META-BOA): an online resource for addressing class imbalance MotivationClass imbalance, or unequal sample sizes between classes, is an increasing concern in machine learning for metabolomic and lipidomic data mining, which can result in overfitting for the over-represented class. Numerous methods have been developed for handling class imbalance, but they are not readily accessible to users with limited computational experience. Moreover, there is no resource that enables users to easily evaluate the effect of different over-sampling algorithms.

ResultsMETAbolomics data Balancing with Over-sampling Algorithms (META-BOA) is a web-based application that enables users to select between four different methods for class balancing, followed by data visualization and classification of the sample to observe the augmentation effects. META-BOA outputs a newly balanced dataset, generating additional samples in the minority class, according to the users choice of Synthetic Minority Over-sampling Technique (SMOTE), Borderline-SMOTE (BSMOTE), Adaptive Synthetic (ADASYN), or Random Over-Sampling Examples (ROSE). META-BOA further displays both principal component analysis (PCA) and t-distributed stochastic neighbor embedding (t-SNE) visualization of data pre- and post-over-sampling. Random forest classification is utilized to compare sample classification in both the original and balanced datasets, enabling users to select the most appropriate method for their analyses.

Availability and implementationMETA-BOA is available at https://complimet.ca/meta-boa.

Supplementary InformationSupplementary material is available at Bioinformatics online. 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. A nontoxic tetrodotoxin analog, 5,6,11-trideoxytetrodotoxin, as an olfactory chemoattractant for the grass puffer Toxic puffers contain the potent neurotoxin, tetrodotoxin (TTX). Although TTX is considered to serve as a defense substance, previous behavioral studies have demonstrated that TTX acts as an attractive pheromone for some toxic puffers. To elucidate the physiological mechanism of putative pheromonal action of TTX, we examined whether grass puffers Takifugu alboplumbeus can detect TTX. Electroolfactogram (EOG) results suggest that the olfactory epithelium (OE) of grass puffers responded to a type of TTX analog (5,6,11-trideoxyTTX), although it did not respond to TTX. We also examined the attractive action of 5,6,11-trideoxyTTX on grass puffers by recording their swimming behavior under dark conditions. Grass puffers preferred to stay on the side of the aquarium where 5,6,11-trideoxyTTX was administered, and their swimming speed decreased. Additionally, odorant-induced labeling of olfactory sensory neurons by immunohistochemistry against neural activity marker (phosphorylated extracellular signal regulated kinase; pERK) revealed that labeled olfactory sensory neurons were localized in the region surrounding "islets" where there was considered as nonsensory epithelium. 5,6,11-trideoxyTTX has been known to accumulate in grass puffers, but its toxicity is much lower (almost nontoxic) than TTX. Our results suggest that toxic puffers may positively use this unknown function TTX analog as an olfactory chemoattractant. Polycomb suppresses a female gene regulatory network to ensure testicular differentiation Gonadal sex determination is controlled by the support cells of testes and ovaries. In testes, the epigenetic mechanism that maintains cellular memory to suppress female sexual differentiation remains unknown. Here, we show that Polycomb suppresses a female gene regulatory network in Sertoli cells, the specific support cells for postnatal testes. Through genetic ablation, we removed Polycomb repressive complex 1 (PRC1) from embryonic Sertoli cells after sex determination. PRC1-depleted postnatal Sertoli cells exhibited defective proliferation and cell death, leading to the degeneration of adult testes. In adult Sertoli cells, PRC1 suppressed the specific, critical genes required for granulosa cells, the support cells of ovaries, thereby inactivating the female gene regulatory network. The underlying chromatin of female genes was coated with Polycomb-mediated repressive modifications: PRC1-mediated H2AK119ub and PRC2-mediated H3K27me3. Taken together, we identify a critical mechanism centered on Polycomb that maintains the male fate in adult testes. A phenomics approach for in vitro antiviral drug discovery BackgroundThe current COVID-19 pandemic has highlighted the need for new and fast methods to identify novel or repurposed therapeutic drugs. Here we present a method for untargeted phenotypic drug screening of virus-infected cells, combining Cell Painting with antibody-based detection of viral infection in a single assay. We designed an image analysis pipeline for segmentation and classification of virus-infected and non-infected cells, followed by extraction of morphological properties.

ResultsWe show that the methodology can successfully capture virus-induced phenotypic signatures of MRC-5 human lung fibroblasts infected with Human coronavirus 229E (CoV-229E). Moreover, we demonstrate that our method can be used in phenotypic drug screening using a panel of nine host- and virus-targeting antivirals. Treatment with effective antiviral compounds reversed the morphological profile of the host cells towards a non-infected state.

ConclusionsThe method can be used in drug discovery for morphological profiling of novel antiviral compounds on both infected and non-infected cells. Exploitation of the genetic variability in the genotype of Egyptian Wheat by studding Molecular Markers, Molecular Docking and Nano Composites. Regulation of leaf and stem rust This manuscript has been withdrawn by the authors as it was submitted and made public without the full consent of all the authors. Therefore, the authors do not wish this work to be cited as reference for the project. If you have any questions, please contact the corresponding author. LPS-TLR4 pathway exaggerates alcohol-induced acute-on-chronic liver failure via provoking NETs formation Backgrounds: Intrahepatic infiltration of neutrophils is a character of alcoholic acute-on-chronic liver failure (AACLF) and neutrophil extracellular traps (NETs) are an important strategy for neutrophils to fix and kill invading microorganisms. Intestinal bacteria and the gut-liver axis have been thought to play a key role in many liver diseases also including AACLF. However, whether NETs appear in AACLF and play a role in AACLF is still unsure. Methods: WT, NE KO, and TLR4 KO mice were used to build the AACLF model, and the intestinal bacteria were eliminated at the same time and LPS was given. Then the formation of NETs and AACLF related markers were detected. Results: The serum MPO-DNA and LPS concentration was increased in AACLF patients and a correlation was revealed between these two indexes. More intrahepatic NETs formed in AACLF mice by testing MPO-DNA, Cit H3, and NE. These markers decreased with gut detergent and restored markers with gut detergent plus LPS supplement. While NETs formation failed to change with gut microbiome or combine LPS supplement in TLR4 KO mice. As we tested AACLF related characters, liver injury, intrahepatic fat deposition, inflammation, and fibrosis alleviated with depletion of NE. These related marks were also attenuated with gut sterilization by antibiotics and recovered with combined treatment with antibiotics plus LPS. But the liver injury, intrahepatic fat, fibro deposition, and liver inflammation-related markers did show a significant difference in TLR4 KO mice when they received the same treatment. Conclusion: Intestinal-derived LPS promotes NETs formation in AACLF through the TLR4 pathway and further accelerates the AACLF process by NETs.