Systematic temporal analysis of transcriptomes using TrendCatcher identifies early and persistent neutrophil activation as an early hallmark of severe COVID-19 Studying temporal gene expression shifts during disease progression provides important insights into the biological mechanisms that distinguish adaptive and maladaptive responses. Existing tools for the analysis of time course transcriptomic data are not designed to optimally identify distinct temporal patterns when analyzing dynamic differentially expressed genes (DDEGs). Moreover, there is a lack of methods to assess and visualize the temporal progression of biological pathways mapped from time course transcriptomic datasets. In this study, we developed an open-source R package TrendCatcher (https://github.com/jaleesr/TrendCatcher), which applies the smoothing spline ANOVA model and break point searching strategy to identify and visualize distinct dynamic transcriptional gene signatures and biological processes from longitudinal datasets. We used TrendCatcher to perform a systematic temporal analysis of COVID-19 peripheral blood transcriptomes, including bulk RNA-seq and scRNA-seq time course data. TrendCatcher uncovered the early and persistent activation of neutrophils and coagulation pathways as well as impaired type I interferon (IFN-I) signaling in circulating cells as a hallmark of patients who progressed to severe COVID-19, whereas no such patterns were identified in individuals receiving SARS- CoV-2 vaccinations or patients with mild COVID-19. These results underscore the importance of systematic temporal analysis to identify early biomarkers and possible pathogenic therapeutic targets.
A general framework to learn tertiary structure for protein sequence characterization During the past five years, deep-learning algorithms have enabled ground-breaking progress towards the prediction of tertiary structure from a protein sequence. Very recently, we developed SAdLSA, a new computational algorithm for protein sequence comparison via deep-learning of protein structural alignments. SAdLSA shows significant improvement over established sequence alignment methods. In this contribution, we show that SAdLSA provides a general machine-learning framework for structurally characterizing protein sequences. By aligning a protein sequence against itself, SAdLSA generates a fold distogram for the input sequence, including challenging cases whose structural folds were not present in the training set. About 70% of the predicted distograms are statistically significant. Although at present the accuracy of the intra-sequence distogram predicted by SAdLSA self-alignment is not as good as deep-learning algorithms specifically trained for distogram prediction, it is remarkable that the prediction of single protein structures is encoded by an algorithm that learns ensembles of pairwise structural comparisons, without being explicitly trained to recognize individual structural folds. As such, SAdLSA can not only predict protein folds for individual sequences, but also detects subtle, yet significant, structural relationships between multiple protein sequences using the same deep-learning neural network. The former reduces to a special case in this general framework for protein sequence annotation.
Differences in gait stability and acceleration characteristics between healthy young and older females Our aim was to evaluate differences in gait acceleration intensity, variability and stability of feet and trunk between older females and young females using inertial sensors. Twenty older females (OF; mean age 68.4, SD 4.1 years) and eighteen young females (YF; mean age 22.3, SD 1.7 years) were asked to walk straight for 100 meters at their preferred speed, while wearing inertial sensors on heels and lower back. We calculated spatiotemporal measures, foot and trunk acceleration characteristics and their variability, as well as trunk stability using the local divergence exponent (LDE). Two-way analysis of variance (including the factors foot and age), Students t-test, and Mann-Whitney U test were used to compare statistical differences of measures between groups. Cohens d effects were calculated for each variable. Foot maximum vertical acceleration and amplitude, trunk-foot vertical acceleration attenuation, as well as their variability were significantly smaller in OF than in YF. In contrast, trunk mediolateral acceleration amplitude, maximum vertical acceleration, and amplitude, as well as their variability were significantly larger in OF than in YF. Moreover, OF showed lower stability (i.e., higher LDE values) in mediolateral acceleration, mediolateral and vertical angular velocity of the trunk. Even though we measured healthy older females, these participants showed lower vertical foot accelerations with higher vertical trunk acceleration, lower trunk-foot vertical acceleration attenuation, less gait stability, and more variability of the trunk, and hence, were more likely to fall. These findings suggest that instrumented gait measurements may help for early detection of changes or impairments in gait performance, even before this can be observed by clinical eye or gait speed. XRN2-mediated regulation of let-7 microRNAs is of critical pathophysiological significance in Humans MicroRNAs are critical regulators of diverse developmental and physiological processes, and they themselves get regulated both at the level of biogenesis and turnover. We demonstrate that the ribonuclease XRN2 can degrade the mature forms of certain let-7 family members in multiple human cancer cell lines, without affecting their precursors. XRN2 depletion results in a reduction in the expression of a number of oncogenes, and diminishes the proliferative and metastatic potential of cancer cells. The clinical relevance of these observations is also verified in tumour transcriptomics data from public RNA-sequencing datasets, where XRN2 mRNA expression is inversely correlated with the levels of a large number of miRNAs, including let-7 members, and high XRN2 mRNA levels are associated with poor survival in hepatocellular carcinoma, lung adenocarcinoma, and glioblastoma. We demonstrate that the miRNA is released by an as-yet unidentified proteinaceous  miRNA release factor from the grasp of Argonaute before its degradation. Our analyses of the patient-derived transcriptomics data also show that XRN2, via its regulation of let-7, affects multiple pathways in a consistent manner across epithelial and glial cell lineages, and thus, is of critical pathophysiological significance. The cell growth cycle: resource allocation and subcellular pattern formation in budding yeast. Metabolic oscillation percolate throughout cellular physiology. The transcriptome oscillates between gene cohorts encoding for biosynthesis and growth, and for catabolism and stress response. However, long protein half-lives dampen effects on protein abundance, and the function of periodic transcription remains elusive. To test three prevailing hypotheses, we performed RNA-seq analysis during a dynamic state of the system, just preceding a bifurcation of system dynamics to a longer period. A few enzymes with short protein half-live and high transcript abundance amplitude could play a direct role in metabolic dynamics (hypothesis H1), e.g., carbonic anhydrase, sulfate uptake and the glyoxylate cycle. Substantial changes in the relative duration of expression of the antagonistic cohorts precede the bifurcation, supporting the idea of a function in cellular resource allocation (H2). The pulse-width modulation model, a mathematical formulation of this idea, explains the dependence of the cycle period on the culture growth rate. This pulse-like model of cell growth provides a first theoretical framework, where the phenomenon is understood as a mechanism of cellular resource allocation and protein homeostasis. The universal temporal program of transcription encodes the spatial structure of the cell, and we further suggest a function in pattern formation of the growing cell (H3). Adolescent Alcohol Binge-Drinking induces delayed appearance of behavioral defects in mice Adolescence is a developmental period characterized by significant changes in brain architecture and behavior. The immaturity of the adolescent brain is associated with heightened vulnerability to exogenous agents, including alcohol. Alcohol is the most consumed drug among teenagers, and binge-drinking during adolescence is a major public health concern. Studies have suggested that adolescent alcohol exposure (AAE) may interfere with the maturation of frontal brain regions and lead to long-lasting behavioral consequences. In this study, we used a mouse model of AAE in which adolescent mice reach high blood alcohol concentration after voluntary binge-drinking. In order to assess short- and long-term consequences of AAE, a battery of behavioral tests was performed during late adolescence and during adulthood. We showed that AAE had no short-term effect on young mice behavior but rather increased anxiety- and depressive-like behaviors, as well as alcohol consumption during adulthood. Moreover, alcohol binge-drinking during adolescence dramatically decreased recognition memory performances and behavioral flexibility in both adult males and females. Furthermore, we showed that voluntary consumption of alcohol during adolescence did not trigger any major activation of the innate immune system in the prefrontal cortex (PFC). Together, our data suggest that voluntary alcohol binge-drinking in adolescent mice induces a delayed appearance of behavioral impairments in adulthood. Pathfinder: A gamified measure to integrate general cognitive ability into the biological, medical, and behavioural sciences Genome-wide association (GWA) studies have uncovered DNA variants associated with individual differences in general cognitive ability (g), but these are far from capturing heritability estimates obtained from twin studies. A major barrier to finding more of this  missing heritability is assessment - the use of diverse measures across GWA studies as well as time and cost of assessment. In a series of four studies, we created a 15-minute (40-item), online, gamified measure of g that is highly reliable (alpha = .78; two-week test-retest reliability = .88), psychometrically valid and scalable; we called this new measure Pathfinder. In a fifth study, we administered this measure to 4,751 young adults from the Twins Early Development Study. This novel g measure, which also yields reliable verbal and nonverbal scores, correlated substantially with standard measures of g collected at previous ages (r ranging from .42 at age 7 to .57 at age 16). Pathfinder showed substantial twin heritability (.57, 95% CIs = .43, .68) and SNP heritability (.37, 95% CIs = .04, .70). A polygenic score computed from GWA studies of five cognitive and educational traits accounted for 12% of the variation in g, the strongest DNA-based prediction of g to date. Widespread use of this engaging new measure will advance research not only in genomics but throughout the biological, medical, and behavioural sciences. Metabolic reconstitution by a gnotobiotic microbiota varies over the circadian cycle The capacity of the intestinal microbiota to degrade otherwise indigestible diet components is known to greatly improve the recovery of energy from food. This has led to the hypothesis that increased digestive efficiency may underlie the contribution of the microbiome to obesity. OligoMM12-colonized gnotobiotic mice have a consistently higher fat-mass than germ-free or fully colonized counterparts. We therefore investigated their food intake, digestion efficiency, energy expenditure and respiratory quotient using a novel isolator-housed metabolic cage system which allows long-term measurements without contamination risk. This demonstrated that microbiota- released calories are perfectly balanced by decreased food intake in fully colonized versus gnotobiotic OligoMM12 and germ-free mice fed a standard chow diet, i.e., microbiota-released calories can in fact be well-integrated into appetite control. We also observed no significant difference in energy expenditure per gram lean mass between the different microbiota groups, suggesting that cumulative very small differences in energy balance, or altered energy storage must underlie fat accumulation in OligoMM12 mice. Consistent with altered energy storage, major differences were observed in the type of respiratory substrates used in metabolism over the circadian cycle: in germ-free mice the respiratory exchange ratio was consistently lower than that of fully colonized mice at all times of day, indicative of more reliance on fat and less on glucose metabolism. Intriguingly the RER of OligoMM12-colonized gnotobiotic mice phenocopied fully colonized mice during the dark (active/eating) phase but phenocopied germ-free mice during the light (fasting/resting) phase. Further, OligoMM12-colonized mice showed a germ-free-like drop in liver glycogen storage during the light cycle and both liver and plasma metabolomes of OligoMM12 mice clustered closely with germ-free mice. This implies the existence of microbiota functions that are required to maintain normal host metabolism during the resting/fasting phase of circadian cycle, and which are absent in the OligoMM12 consortium. The relative speed of the glucorticoid stress response varies independently of scope and is predicted by environmental variability and longevity across birds. The acute glucocorticoid response is a key mediator of the coordinated vertebrate response to unpredictable challenges. Rapid glucocorticoid increases initiate changes that allow animals to cope with stressors. The scope of the glucocorticoid response -- defined here as the absolute increase in glucocorticoids -- is associated with individual differences in performance and varies across species with environment and life history. In addition to varying in scope, responses can differ enormously in speed; however, relatively little is known about whether speed and absolute glucocorticoid levels covary, how selection shapes speed, or what aspects of speed are important. We used corticosterone samples collected at 5 time points from 1,750 individuals of 60 species of birds to ask i) how the speed and scope of the glucocorticoid response covary and ii) whether variation in absolute or relative speed is predicted by environmental context or life history. As predicted by a recent model, faster absolute glucocorticoid responses were strongly associated with a larger scope. Despite this covariation, the relative speed of the glucocorticoid response (standardized within species) varied independently of absolute scope, suggesting that selection could operate on both features independently. Species with faster relative glucocorticoid responses lived in locations with more variable temperature and had shorter lifespans. Our results suggest that rapid changes associated with the speed of the glucocorticoid response, such as those occurring through non-genomic receptors, might be an important determinant of coping ability and we emphasize the need for studies designed to measure speed independently of absolute glucocorticoid levels. Population-level variation of enhancer expression identifies novel disease mechanisms in the human brain Identification of risk variants for neuropsychiatric diseases within enhancers underscores the importance of understanding the population-level variation of enhancers in the human brain. Besides regulating tissue- and cell-type-specific transcription of target genes, enhancers themselves can be transcribed. We expanded the catalog of known human brain transcribed enhancers by an order of magnitude by generating and jointly analyzing large-scale cell-type-specific transcriptome and regulome data. Examination of the transcriptome in 1,382 brain samples in two independent cohorts identified robust expression of transcribed enhancers. We explored gene-enhancer coordination and found that enhancer-linked genes are strongly implicated in neuropsychiatric disease. We identified significant expression quantitative trait loci (eQTL) for 25,958 enhancers which mediate 6.8% of schizophrenia heritability, mostly independent from standard gene eQTL. Inclusion of enhancer eQTL in transcriptome-wide association studies enhanced functional interpretation of disease loci. Overall, our study characterizes the enhancer-gene regulome and genetic mechanisms in the human cortex in both healthy and disease states. 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. High expression of VRT2 increases the number of rudimentary basal spikelets in wheat Spikelets are the fundamental building blocks of Poaceae inflorescences and their development and branching patterns determine the various inflorescence architectures and grain yield of grasses. In wheat, the central spikelets produce the most and largest grains, while spikelet size gradually decreases acro- and basipetally, giving rise to the characteristic lanceolate shape of wheat spikes. The acropetal gradient correlates with the developmental age of spikelets, however the basal spikelets are developed first and the cause of their small size and rudimentary development is unclear. Here, we adapted G&T-seq, a low-input transcriptomics approach, to characterise gene expression profiles within spatial sections of individual spikes before and after the establishment of the lanceolate shape. We observed larger differences in gene expression profiles between the apical, central and basal sections of a single spike than between any section belonging to consecutive developmental timepoints. We found that SVP MADS-box transcription factors, including VRT-A2, are expressed highest in the basal section of the wheat spike and display the opposite expression gradient to flowering E-class SEP1 genes. Based on multi-year field trials and transgenic lines, we show that higher expression of VRT-A2 in the basal sections of the spike is associated with increased numbers of rudimentary basal spikelets. Our results, supported by computational modelling, suggest that the delayed transition of basal spikelets from vegetative to floral developmental programmes results in the lanceolate shape of wheat spikes. This study highlights the value of spatially resolved transcriptomics to gain new insights into developmental genetics pathways of grass inflorescences.

One sentence summaryLarge transcriptional gradients exist within a wheat spike and are associated with rudimentary basal spikelet development, resulting in the characteristic lanceolate shape of wheat spikes. Quantifying isolation-by-resistance and connectivity in dendritic ecological networks Statistical methods that quantify individual movements have limited applicability within dendritic ecological networks (DENs), to include riverscapes. We promote an approach herein by deriving an analytical framework (=DO_SCPLOWISTC_SCPLOWNO_SCPLOWETC_SCPLOW and RO_SCPLOWESISTC_SCPLOWNO_SCPLOWETC_SCPLOW) that more appropriately quantifies differentiation by meshing individual DEN segments with fitted distances and annotated environmental features. We first explored the spatial arrangement of diversity in a river network by fitting pairwise distances against graph edges. We then derived effective resistance models (e.g., as a composite of an array of possible environmental covariates) by using a genetic algorithm for heuristic model selection, invoking circuit theory (CO_SCPLOWIRCUITC_SCPLOWSO_SCPLOWCAPEC_SCPLOW) to form a graph-based complement to RO_SCPLOWESISTANCEC_SCPLOWGA (a landscape ecology package). Although numerous pairwise distance metrics can be employed, we utilized genetic distances encompassing 13,218 ddRAD loci from N=762 Speckled Dace (Cyprinidae: Rhinichthys osculus) sampled at 78 Colorado River localities ({micro}=9.77/site). When distances for each locus were fitted into the network, we found intraspecific divergences due to stream reaches were greater than expected when distances alone. In fitting model-averaged  effective resistance models to the same network, we showed the manner by which a host of anthropogenic and environmental variables contribute to patterns of connectivity underlying riverscape genetic differentiation. Our framework represents a contemporary approach to deriving metapopulation/ metacommunity structure within DENs, in that it allows: (a) The extension of projections into unsampled temporal/spatial components; (b) Comparisons to be made among species and/or drainages, both of which benefit multi-species management; and (c) the quantification of locus-specific patterns, from which adaptive hypotheses could then be derived. O_QD"The intimate relation of hydrological conditions to fish life is proverbial; to be hopelessly or dangerously maladjusted to ones environment is to be a  fish out of water" (Hubbs 1941).

C_QD Structural determinants of Acid-sensing ion channel potentiation by single chain lipids Acid-sensing ion channels (ASICs) are sensitized to activation by inflammatory mediators like the polyunsaturated fatty acid (PUFA) arachidonic acid (AA). Previous work has shown that AA can potentiate ASIC currents at subsaturating proton concentrations, but the structural mechanisms of this change in gating are not understood. Here we show that PUFAs cause multiple gating changes in ASIC3 including shifting the pH dependence of activation, slowing the rate of desensitization, and increasing the current even at a saturating pH. The impact on gating depends on the nature of both the head and tail of the lipid with the head group structure primarily determining the magnitude of the effect on the channel. An N-acyl amino acid (NAAA), arachidonoyl glycine (AG), is such a strong regulator that it can act as a ligand at neutral pH. Mutation of an arginine in the outer segment of TM1 (R64) eliminated the effect of docosahexaenoic acid (DHA) even at high concentrations suggesting a potential interaction site for the lipid on the channel. Our results suggest a model where PUFAs bind to ASICs both via their tail group as well as an electrostatic interaction between the negatively charged PUFA head group and the positively charged arginine side chain. These data provide the first look at the structural features of lipids that are important for modulating ASICs and suggest a potential binding site for PUFAs on the channel.

Short SummaryArachidonic acid (AA) is a known modulator of ASICs. Bankston and Klipp examine the structural requirements for ASIC modulation by a number of lipids related to AA. Negatively charged head groups are stronger potentiators and may interact with an arginine in TM1 near the outer leaflet of the plasma membrane. Fatal neuroinvasion and SARS-CoV-2 tropism in K18-hACE2 mice is partially independent on hACE2 expression Animal models recapitulating distinctive features of severe COVID-19 are critical to enhance our understanding of SARS-CoV-2 pathogenesis. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. The precise mechanisms of lethality in this mouse model remain unclear. Here, we evaluated the spatiotemporal dynamics of SARS-CoV-2 infection for up to 14 days post-infection. Despite infection and moderate pneumonia, rapid clinical decline or death of mice was invariably associated with viral neuroinvasion and direct neuronal injury (including brain and spinal neurons). Neuroinvasion was observed as early as 4 dpi, with virus initially restricted to the olfactory bulb supporting axonal transport via the olfactory neuroepithelium as the earliest portal of entry. No evidence of viremia was detected suggesting neuroinvasion occurs independently of entry across the blood brain barrier. SARS-CoV-2 tropism was not restricted to ACE2-expressing cells (e.g., AT1 pneumocytes), and some ACE2-positive lineages were not associated with the presence of viral antigen (e.g., bronchiolar epithelium and brain capillaries). Detectable ACE2 expression was not observed in neurons, supporting overexpression of ACE2 in the nasal passages and neuroepithelium as more likely determinants of neuroinvasion in the K18-hACE2 model. Although our work incites caution in the utility of the K18-hACE2 model to study global aspects of SARS-CoV-2 pathogenesis, it underscores this model as a unique platform for exploring the mechanisms of SARS-CoV-2 neuropathogenesis that may have clinical relevance acknowledging the growing body of evidence that suggests COVID-19 may result in long-standing neurologic consequences.

IMPORTANCECOVID-19 is predominantly a respiratory disease caused by SARS-CoV-2 that has infected more than 191 million people with over 4 million fatalities (2021-07-20). The development of animal models recapitulating distinctive features of severe COVID-19 is critical to enhancing our understanding of SARS-CoV-2 pathogenesis and in the evaluation of vaccine and therapeutic efficacy. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. Here, we show lethality of this model is invariably associated with viral neuroinvasion linked with viral replication and assembly. Importantly, pneumonia albeit invariably present was generally moderate with the absence of culturable infectious virus at peak neuroinvasion. The dynamics of viral neuroinvasion and pneumonia were only partially dependent on hACE2. Overall, this study provides an in-depth sequential characterization of the K18-hACE2 model following SARS-CoV-2 infection, highlighting its significance to further study the mechanisms of SARS-CoV-2 neuropathogenesis. A humanized nanobody phage display library yields potent binders of SARS CoV-2 spike Neutralizing antibodies targeting the SARS-CoV-2 spike protein have shown a great preventative/therapeutic potential. Here, we report a rapid and efficient strategy for the development and design of SARS-CoV-2 neutralizing humanized nanobody constructs with sub-nanomolar affinities and nanomolar potencies. CryoEM-based structural analysis of the nanobodies in complex with spike revealed two distinct binding modes. The most potent nanobody, RBD-1-2G(NCATS-BL8125), tolerates the N501Y RBD mutation and remains capable of neutralizing the B.1.1.7 (Alpha) variant. Molecular dynamics simulations provide a structural basis for understanding the neutralization process of nanobodies exclusively focused on the spike-ACE2 interface with and without the N501Y mutation on RBD. A primary human airway air-lung interface (ALI) ex vivo model showed that RBD-1-2G-Fc antibody treatment was effective at reducing viral burden following WA1 and B.1.1.7 SARS-CoV-2 infections. Therefore, this presented strategy will serve as a tool to mitigate the threat of emerging SARS-CoV-2 variants. A novel two-generation approach to the population dynamics of gregarious parasitoids Parasitoids, as important natural enemies, help maintain balance in natural ecosystems. Their population dynamics is generally predicted from the number of individuals. Here, using gregarious parasitoids as models, we show that this traditional approach omits one important parameter: the mothers manipulation of offspring fertility due to the clutch size-body size- fertility correlation. As a result of this correlation, when females deliberately adjust the number of offspring laid in a host, they determine not only the number but also the body sizes and reproductive potentials of those offspring. For the first time in the model species Anaphes flavipes, we determined the parasitoids offspring fertility from clutch size. Using this, we experimentally clarified the advantage of specific clutch size combinations and we show that identical fertility in the F1 generation can lead to distinctly different fertility values in the F2 generation. Even with the same number of hosts, lower fertility in the F1 generation can cause higher fertility in the F2 generation. Based on these results, we propose a novel two-generation approach which includes the clutch size-body size-fertility correlation. Our novel approach provides a new perspective for determining the individual fitness levels of gregarious parasitoids with new options for the modelling of parasitoid population dynamics. Development of an exosomal gene signature to detect residual disease in dogs with osteosarcoma using a novel xenograft platform and machine learning Osteosarcoma has a guarded prognosis. A major hurdle in developing more effective osteosarcoma therapies is the lack of disease-specific biomarkers to predict risk, prognosis, or therapeutic response. Exosomes are secreted extracellular microvesicles emerging as powerful diagnostic tools. However, their clinical application is precluded by challenges in identifying disease-associated cargo from the vastly larger background of normal exosome cargo. We developed a method using canine osteosarcoma in mouse xenografts to distinguish tumor-derived from host-response exosomal mRNAs. The model allows for the identification of canine osteosarcoma-specific gene signatures by RNA sequencing and a species-differentiating bioinformatics pipeline. An osteosarcoma-associated signature consisting of five gene transcripts (SKA2, NEU1, PAF1, PSMG2, and NOB1) was validated in dogs with spontaneous osteosarcoma by qRT-PCR, while a machine learning model assigned dogs into healthy or disease groups. Serum/plasma exosomes were isolated from 53 dogs in distinct clinical groups ("healthy", "osteosarcoma", "other bone tumor", or "non-neoplastic disease"). Pre-treatment samples from osteosarcoma cases were used as the training set and a validation set from post-treatment samples was used for testing, classifying as "osteosarcoma-detected" or "osteosarcoma-NOT detected". Dogs in a validation set whose post-treatment samples were classified as "osteosarcoma-NOT detected" had longer remissions, up to 15 months after treatment. In conclusion, we identified a gene signature predictive of molecular remissions with potential applications in the early detection and minimal residual disease settings. These results provide proof-of-concept for our discovery platform and its utilization in future studies to inform cancer risk, diagnosis, prognosis, and therapeutic response.



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org.highwire.dtl.DTLVardef@1b612c4org.highwire.dtl.DTLVardef@8a1847org.highwire.dtl.DTLVardef@3ffd64org.highwire.dtl.DTLVardef@114df8c_HPS_FORMAT_FIGEXP  M_FIG C_FIG A potent human monoclonal antibody with pan-neutralizing activities directly dislocates S trimer of SARS-CoV-2 through binding both up and down forms of RBD The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of novel corona virus disease (COVID-19). The neutralizing monoclonal antibodies (mAbs) targeting the receptor binding domain (RBD) of SARS-CoV-2 are among the most promising strategies to prevent and treat COVID-19. However, SARS-CoV-2 variants of concern (VOCs) profoundly reduced the efficacies of most of mAbs and vaccines approved for clinical use. Herein, we demonstrated mAb 35B5 efficiently neutralizes both wild-type (WT) SARS-CoV-2 and VOCs, including B.1.617.2 (delta) variant, in vitro and in vivo. Cryo-electron microscopy (cryo-EM) revealed that 35B5 neutralizes SARS-CoV-2 by targeting a unique epitope that avoids the prevailing mutation sites on RBD identified in circulating VOCs, providing the molecular basis for its pan-neutralizing efficacy. The 35B5-binding epitope could also be exploited for the rational design of a universal SARS-CoV-2 vaccine. Single cell profiling of functionally cured Chronic Hepatitis B patients reveals the emergence of activated innate and an altered adaptive immune response in the intra-hepatic environment Hepatitis B surface antigen (HBsAg) loss or functional cure (FC), is considered the desirable therapeutic outcome for chronic hepatitis B (CHB) patients. However, the immuno-pathological biomarkers and underlying mechanisms remain unclear. Here we present a comprehensive single cell-transcriptomic atlas together with immune-phenotyping of disease-associated cell states (DACS) isolated from intra-hepatic tissue and matched PBMCs of either CHB or FC patients. We find that the intra-hepatic environment displays specific cell identities and molecular signatures that are distinct from PBMCs. FC is associated with emergence of an altered adaptive immune response marked by CD4 cytotoxic T lymphocytes (CD4-CTLs), and an activated innate response represented by liver-resident natural killer (LR-NK) cells. Overall, these findings provide novel insights into immuno-pathological cell states associated with FC that could serve as prognostic biomarkers. Beneficial effects of novel strains of Aureobasidium pullulans produced 1,3-1,6 β-glucans on non-esterified fatty acid levels in diabetic KKAy mice Obesity, metabolic syndrome, associated lipotoxicity and its cascade of events contribute to the majority of the burden related to non-communicable diseases globally. Preventive lifestyle changes aside, several beneficial effects have been reported in type II diabetes mellitus and dyslipidaemia patients with biological response modifier glucans (BRMG) produced as an exopolysaccharide by Aureobasidium pullulans. In this study, we compared two strains (AFO-202 and N-163) that produce beta glucans in alleviating lipotoxicity. This study was performed in obese diabetic mice model of KK-Ay mice, in four groups with six subjects in each group - Group 1: sacrificed on Day 0 for baseline values; Group 2: control (drinking water); Group 3: AFO-202 beta glucan--200 mg/kg/day; Group 4: N-163 beta glucan--300 mg/kg/day. The animals in groups 2-4 had the test solutions administered by gavage once daily for 28 consecutive days. Biochemical analyses were conducted of blood glucose, triglycerides, total cholesterol, LDL cholesterol, HDL cholesterol and non-esterified fatty acids (NEFA). Group 4 (N-163) had the lowest NEFA levels, as compared to the other groups, and marginally decreased triglyceride levels. The groups had no significant differences in blood glucose, HbA1c, triglycerides, or LDL and HDL cholesterol. N-163 produced by A. pullulans decreased NEFA in a diabetic mice model in 28 days. These results, although modest, warrant further in-depth research into lipotoxicity and associated inflammatory cascades in both healthy and disease affected subjects to develop novel strategies for prevention and management. Designing single-cell experiments to harvest fluctuation information while rejecting measurement noise Measurement error is a complicating factor that reduces or distorts the information contained in any experiment. This problem becomes even more serious in the context of experiments that are specifically designed to quantify single-cell gene expression heterogeneity, where important RNA and protein copy numbers are themselves subject to the inherently random fluctuations of biochemical reactions. It is not clear how measurement noise should be managed, in addition to other experiment design variables such as sampling size and frequency, to ensure that collected data will provide useful insights on gene expression mechanisms of interest. To address these fundamental single-cell experiment design challenges, we propose a computational framework that makes explicit use of measurement error modeling and Fisher Information Matrix-based criteria to decide between experimental methods. This unified approach not only quantifies how different noise characteristics affect uncertainty in parameter estimation, but also enables a systematic approach to design hybrid experiments that combine different measurement modalities. The limits of evolutionary convergence in sympatry: reproductive interference and historical constraints leading to local diversity in warning traits Mutualistic interactions between defended species represent a striking case of evolutionary convergence in sympatry, driven by the increased protection against predators brought by mimicry in warning traits. However, such convergence is often limited: sympatric defended species frequently display different or imperfectly similar warning traits. The phylogenetic distance between sympatric species may indeed prevent evolution towards the exact same signal. Moreover, warning traits are also involved in mate recognition, so that trait convergence might result in heterospecific courtship and mating. Here, we develop a mathematical model to investigate the strength and direction of evolution of warning trait in defended species with different ancestral traits. Specifically, we determine the effect of phenotypic distances between ancestral trait states of sympatric defended species and of costs of heterospecific sexual interactions on imperfect mimicry and trait divergence. Our analytical results confirm that reproductive interference and historical constraints limit the convergence of warning traits, leading to either complete divergence, or imperfect mimicry. Our model reveals that imperfect mimicry evolves only when ancestral trait values differ between species, due to historical constraints and highlights the importance of female and predator discriminations in the evolution of such imperfect mimicry. Our study thus provides new predictions on how reproductive interference interacts with historical constraints and may promote the emergence of novel warning traits, enhancing mimetic diversity. Multi-layered regulation of neuroectoderm differentiation by retinoic acid in a primitive streak-like context The formation of the primitive streak (PS) and the subsequent induction of neuroectoderm are hallmarks of gastrulation. Combining an in vitro reconstitution of this process based on mouse embryonic stem cells (mESCs) with a collection of knockouts in reporter mESC lines, we reassessed the contribution of retinoic acid (RA) signaling at early stages of neural commitment and its cross-talk with TGF{beta} and Wnt signaling inhibition. Single-cell RNA sequencing analysis captured the temporal unfolding of cell type diversification from epiblast and primitive streak-like cells up to the emergence of anterior and posterior neural fates. In conditions thought to lack RA synthesis, we discovered a hitherto unidentified residual RA production via a sensitive RA reporter. Genetic perturbations proved that the RA-degrading enzyme Cyp26a1 safeguard the developmental capabilities of the PS-like cells, limiting neural differentiation in wild type and in Chrd-/-Nog-/- or Dkk1-/- cells. Finally, the knockout of the three RAR receptors highlighted their function as negative regulators of loci critical for neural induction. Overall, we identified two mechanisms whereby components of the RA pathway can control the formation of neural progenitors in our PS-like context: a RA-dependent neural induction gated by RARs, and a receptor-mediated repression in the absence of ligand. Citation needed?Wikipedia bibliometrics during the first waveof the COVID-19 pandemic. BackgroundWith the COVID-19 pandemics outbreak, millions flocked to Wikipedia for updated information. Amid growing concerns regarding an "infodemic", ensuring the quality of information is a crucial vector of public health. Investigating if and how Wikipedia remained up to date and in line with science is key to formulating strategies to counter misinformation. Using citation analyses, we asked: which sources informed Wikipedias COVID-19-related articles before and during the pandemics first wave (January-May 2020).

ResultsWe found that coronavirus-related articles referenced trusted media sources and high-quality academic research. Moreover, despite a surge in COVID-19 preprints, Wikipedia had a clear preference for open-access studies published in respected journals and made little use of preprints. Building a timeline of English COVID-19 articles from 2001-2020 revealed a nuanced trade-off between quality and timeliness. It further showed how preexisting articles on key topics related to the virus created a framework for integrating new knowledge. Supported by a rigid sourcing policy, this "scientific infrastructure" facilitated contextualization and regulated the influx of new information. Lastly, we constructed a network of DOI-Wikipedia articles, which showed the shifting landscape of pandemic-related knowledge on Wikipedia and how academic citations create a web of shared knowledge supporting topics like COVID-19 vaccine development.

ConclusionsUnderstanding how scientific research interacts with the digital knowledge-sphere during the pandemic provides insight into how Wikipedia can facilitate access to science. It also reveals how, aided by what we term its "citizen encyclopedists", it successfully fended off COVID-19 disinformation and how this unique model may be deployed in other contexts. CryoEM of endogenous mammalian V-ATPase interacting with the TLDc protein mEAK-7 V-ATPases are rotary proton pumps that serve as signaling hubs with numerous proposed binding partners in cells. We used cryoEM combined with exhaustive focused classification to detect endogenous proteins that associate with V-ATPase from porcine kidney. A super-stoichiometric copy of subunit C was found in ~3% of complexes, while an additional ~1.6% of complexes bound mEAK-7, a protein with proposed roles in dauer formation in nematodes and mTOR signaling in mammals. High-resolution cryoEM of porcine kidney V-ATPase with recombinant mEAK-7 shows that mEAK-7s TLDc domain interacts with V-ATPases stator while its C-terminal  helix binds V-ATPases rotor. This crosslink would be expected to inhibit rotary catalysis. However, unlike inhibition of yeast V-ATPase by the TLDc protein Oxr1p, exogenous mEAK-7 does not inhibit V-ATPase and mEAK-7 overexpression in cells does not alter lysosomal or phagosomal pH. Instead, cryoEM suggests that interaction of mEAK-7 with V-ATPase is disrupted by ATP-induced rotation of the rotor. Comparison of Oxr1p and mEAK-7 binding explains this difference. Together, these results show that differences in V-ATPase binding by TLDc domain-containing proteins can lead to effects ranging from strong inhibition to formation of labile interactions that are sensitive to the enzymes activity.