Mutations on RBD of SARS-CoV-2 Omicron variant result in stronger binding to human ACE2 receptor The COVID-19 pandemic caused by the SARS-CoV-2 virus has led to more than 270 million infections and 5.3 million of deaths worldwide. Several major variants of SARS-CoV-2 have emerged and posed challenges in controlling the pandemic. The recently occurred Omicron variant raised serious concerns about reducing the efficacy of vaccines and neutralization antibodies due to its vast mutations. We have modelled the complex structure of the human ACE2 protein and the receptor binding domain (RBD) of Omicron Spike protein (S-protein), and conducted atomistic molecular dynamics simulations to study the binding interactions. The analysis shows that the Omicron RBD binds more strongly to the human ACE2 protein than the original strain. The mutations at the ACE2-RBD interface enhance the tight binding by increasing hydrogen bonding interaction and enlarging buried solvent accessible surface area.
Aggregation Tool for Genomic Concepts (ATGC): A deep learning framework for sparse genomic measures Deep learning has the ability to extract meaningful features from data given enough training examples. Large scale genomic data are well suited for this class of machine learning algorithms; however, for many of these data the labels are at the level of the sample instead of at the level of the individual genomic measures and features. To leverage the power of deep learning for these types of data we turn to a multiple instance learning framework, and present an easily extensible tool built with TensorFlow and Keras. We show how this tool can be applied to somatic variants (featurizing genomic position, sequence context, and read counts) on a range of artificial tasks (classification, regression, Cox regression). In addition, we confirm the model can achieve high performance on real-world problems, accurately classifying samples according to whether they contain a specific variant (hotspot or tumor suppressor), groups of variants (tumor clonality), or a type of variant (microsatellite instability). Our results suggest this framework will lead to improvements on sample-level tasks that require aggregation of a set of genomic measures.
Citation needed? Wikipedia and 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. 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. Dynamics of SARS-CoV-2 mutations reveals regional-specificity and similar trends of N501 and High-Frequency mutation N501Y in different levels of control measures Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This disease has spread globally, causing more than 161.5 million cases and 3.3 million deaths to date. Surveillance and monitoring of new mutations in the virus genome are crucial to our understanding of the adaptation of SARS-CoV-2. Moreover, how the temporal dynamics of these mutations is influenced by control measures and non-pharmaceutical interventions (NPIs) is poorly understood. Using 1 058 020 SARS-CoV-2 from sequenced COVID-19 cases from 98 countries (totaling 714 country-month combinations), we perform a normalization by COVID-19 cases to calculate the relative frequency of SARS-CoV-2 mutations and explore their dynamics over time. We found 115 mutations estimated to be present in more than 3 % of global COVID-19 cases and determined three types of mutation dynamics: High-Frequency, Medium-Frequency, and Low-Frequency. Classification of mutations based on temporal dynamics enable us to examine viral adaptation and evaluate the effects of implemented control measures in virus evolution during the pandemic. We showed that Medium-Frequency mutations are characterized by high prevalence in specific regions and/or in constant competition with other mutations in several regions. Finally, taking N501Y mutation as representative of High-Frequency mutations, we showed that level of control measure stringency negatively correlates with the effective reproduction number of SARS-CoV-2 with High-Frequency or not-High-Frequency and both follows similar trends in different levels of stringency. CRISPR-based kinome-screening revealed MINK1 as a druggable player to rewire 5FU-resistance in OSCC through AKT/MDM2/p53 axis Cisplatin, 5FU and docetaxel (TPF) are the most common chemotherapy regimen used for advanced OSCC. However, many cancer patients experience relapse, continued tumor growth, and spread due to drug resistance, which leads to treatment failure and metastatic disease. Here, using a CRISPR/Cas9 based kinome knockout screening, Misshapen-like kinase 1 (MINK1) is identified as an important mediator of 5FU resistance in OSCC. Analysis of clinical samples demonstrated significantly higher MINK1 expression in the tumor tissues of chemotherapy non-responder as compared to chemotherapy responders. The nude mice and zebrafish xenograft experiments indicate that knocking out MINK1 restores 5FU mediated cell death in chemoresistant OSCC. An antibody based phosphorylation array screen revealed MINK1 as a negative regulator of p53. Mechanistically, MINK1 modulates AKT phosphorylation at Ser473, which enables p-MDM2 (Ser 166) mediated degradation of p53. We also identified lestaurtinib as a potent inhibitor of MINK1 kinase activity. The patient derived TPF resistant cell based xenograft data suggest that lestaurtinib restores 5FU sensitivity and facilitates a significant reduction of tumor burden. Overall, our study suggests that MINK1 is a major driver of 5FU resistance in OSCC. The novel combination of MINK1 inhibitor lestaurtinib and 5FU needs further clinical investigation in advanced OSCC. Effects of fine-scale population structure on the distribution of heterozygosity in a long-term study of (Antirrhinum majus) Many studies have quantified the distribution of heterozygosity and relatedness in natural populations, but surprisingly few have examined the demographic processes driving these patterns. In this study we take a novel approach by studying how population structure affects both pairwise identity and the distribution of heterozygosity in a natural population of a self-incompatible plant Antirrhinum majus. We look at a measure of the variance in heterozygosity within a population, identity disequilibrium (g2), together with FST using a panel of 91 SNPs in 22,353 individuals collected over 11 years. We find that pairwise relatedness (FST) declines rapidly over short spatial scales, and the excess variance in heterozygosity between individuals (g2) reflects significant variation in inbreeding. Additionally, we detect an excess of individuals with around half the average heterozygosity, indicating that some are due to selfing or matings between close relatives. We use two types of simulation to ask whether variation in heterozygosity is consistent with fine-scale spatial population structure. First, by simulating offspring using parents drawn from a range of spatial scales, we show that the known pollen dispersal kernel explains g2. Second, we simulate a 1000-generation pedigree using the known dispersal and spatial distribution and find that the resulting g2 is consistent with that observed from the field data. In contrast, a simulated population with uniform density underestimates g2, indicating that heterogeneous density promotes identity disequilibrium. Our study shows that heterogeneous density and leptokurtic dispersal can together explain the distribution of heterozygosity. Furthermore, our study highlights the limitations of making theoretical predictions from simulations that only assume simple density and dispersal distributions. The pH Dependence of Niclosamide Solubility, Dissolution, and Morphology Motivates Potentially Universal Mucin-Penetrating Nasal and Throat Sprays for COVID19, its Contagious Variants, and Other Respiratory Viral Infections MotivationWith the coronavirus pandemic still raging, prophylactic nasal and early treatment throat sprays could help prevent infection and reduce viral load. Niclosamide has the potential to treat a broad range of viral infections if local bioavailability is optimized as mucin-penetrating solutions as opposed to more traditional microparticle-based sprays that cannot penetrate the mucin.

ExperimentalpH-dependence of supernatant concentrations and dissolution rates of niclosamide were measured in buffered solutions by Nanodrop-UV/Vis-spectroscopy for niclosamide from different suppliers, as precipitated material, and as cosolvates. Data was compared to predictions from Henderson Hasselbalch and precipitation pH models. Optimal microscopy was used to observe the morphologies of precipitated and converted niclosamide.

ResultsSupernatant-concentrations of niclosamide increased with increasing pH, from 1.77uM at pH 3.66 to 30uM at pH 8, and more rapidly from 90uM at pH8.5 to 300uM at pH 9.1, reaching 641uM at pH 9.5. Logarithmic rates for dissolution increased by [~]3x for pHs 8.62 to 9.44. However, when precipitated from supersaturated solution, niclosamide equilibrated to much lower final supernatant concentrations, reflective of more stable polymorphs at each pH that were also apparent for niclosamide from other suppliers and cosolvates.

ConclusionsGiven niclosamides activity against COVID19, its more contagious variants, and other respiratory viral infections, these niclosamide solutions, that put the virus in lockdown, could represent universal prophylactic nasal and early treatment throat sprays. As solutions they would be the simplest and potentially most effective formulations from both an efficacy standpoint as well as manufacturing and distribution, with no cold chain. They now just need testing. Identifying and testing marker-trait associations for growth and phenology in three pine species: implications for genomic prediction In tree species, genomic prediction offers the potential to forecast mature trait values in early growth stages, if robust marker-trait associations can be identified. Here we apply a novel multispecies approach using genotypes from a new genotyping array, based on 20,795 SNPs from three closely related pine species (Pinus sylvestris, Pinus uncinata and Pinus mugo), to test for associations with growth and phenology data from a common garden study. Predictive models constructed using significantly associated SNPs were then tested and applied to an independent multisite field trial of P. sylvestris and the capability to predict trait values was evaluated. One hundred and eighteen SNPs showed significant associations with the traits in the pine species. Common SNPs (MAF > 0.05) associated with bud set were only found in genes putatively involved in growth and development, whereas those associated with growth and budburst were also located in genes putatively involved in response to environment and, to a lesser extent, reproduction. At one of the two independent sites, the model we developed produced highly significant correlations between predicted values and observed height data (YA, height 2020: r = 0.376, p < 0.001). Predicted values estimated with our budburst model were weakly but positively correlated with duration of budburst at one of the sites (GS, 2015: r = 0.204, p = 0.034; 2018: r = 0.205, p = 0.034-0.037) and negatively associated with budburst timing at the other (YA: r = -0.202, p = 0.046). Genomic prediction resulted in the selection of sets of trees whose mean height was taller than the average for each site. Our results provide tentative support for the capability of prediction models to forecast trait values in trees, while highlighting the need for caution in applying them to trees grown in different environments. Multiscale X-ray study of Bacillus subtilis biofilms reveals interlinked structural hierarchy and elemental heterogeneity Biofilms are multicellular microbial communities that encase themselves in an extracellular matrix (ECM) of secreted biopolymers and attach to surfaces and interfaces. Bacterial biofilms are detrimental in hospital and industrial settings, but they can be beneficial in agricultural contexts. An essential property of biofilms that grants them with increased survival relative to planktonic cells is phenotypic heterogeneity; the division of the biofilm population into functionally distinct subgroups of cells. Phenotypic heterogeneity in biofilms can be traced to the cellular level, however, the molecular structures and elemental distribution across whole biofilms as well as possible linkages between them remain unexplored. Mapping X-ray diffraction (XRD) across intact biofilms in time and space, we revealed the dominant structural features in Bacillus subtilis biofilms, stemming from matrix components, spores and water. By simultaneously following the X-ray fluorescence (XRF) signal of biofilms and isolated matrix components, we discovered that the ECM preferentially binds calcium ions over other metal ions, specifically, zinc, manganese and iron. These ions, remaining free to flow below macroscopic wrinkles that act as water channels, eventually accumulate and lead to sporulation. The possible link between ECM properties, regulation of metal ion distribution and sporulation across whole intact biofilms unravels the importance of molecular-level heterogeneity in shaping biofilm physiology and development.

Significance StatementBiofilms are multicellular soft microbial communities that are able to colonize synthetic surfaces as well as living organisms. To survive sudden environmental changes and efficiently share their common resources, cells in a biofilm divide into subgroups with distinct functions, leading to phenotypic heterogeneity. Here, by studying intact biofilms by synchrotron X-ray diffraction and fluorescence, we revealed correlations between biofilm macroscopic architectural heterogeneity and the spatio-temporal distribution of extracellular matrix, spores, water and metal ions. Our findings demonstrate that biofilm heterogeneity is not only affected by local genetic expression and cellular differentiation, but also by passive effects resulting from the physicochemical properties of the molecules secreted by the cells, leading to differential distribution of nutrients that propagates through macroscopic length scales. Synthetic periphyton as a model system to understand species dynamics in complex microbial freshwater communities Phototrophic biofilms, also known as periphyton, are microbial freshwater communities that drive crucial ecological processes in streams and lakes. Gaining a deep mechanistic understanding of the biological processes occurring in natural periphyton remains challenging due to the high complexity and variability of such communities. To address this challenge, we rationally developed a workflow to construct a synthetic community by co-culturing 26 phototrophic species (i.e., diatoms, green algae and cyanobacteria) that were inoculated in a successional sequence to create a periphytic biofilm on glass slides. We show that this community is diverse, stable and highly reproducible in terms of microbial composition, function and 3D spatial structure of the biofilm. We also demonstrate the ability to monitor microbial dynamics at the single species level during periphyton development and how their abundances are impacted by stressors such as increased temperature and a herbicide, singly and in combination. Overall, such a synthetic periphyton, grown under controlled conditions, can be used as a model system for theory testing through targeted manipulation. Heterogeneous interactions and polymer entropy decide organization and dynamics of chromatin domains Chromatin is known to be organized into multiple domains of varying sizes and compaction. While these domains are often imagined as static structures, they are highly dynamic and show cell-to-cell variability. Since processes such as gene regulation and DNA replication occur in the context of these domains, it is important to understand their organization, fluctuation and dynamics. To simulate chromatin domains, one requires knowledge of interaction strengths among chromatin segments. Here, we derive interaction strength parameters from experimentally known contact maps and use them to predict chromatin organization and dynamics. Taking two domains on the human chromosome as examples, we investigate its 3D organization, size/shape fluctuations, and dynamics of different segments within a domain, accounting for hydrodynamic effects. Considering different cell types, we quantify changes in interaction strengths and chromatin shape fluctuations in different epigenetic states. Perturbing the interaction strengths systematically, we further investigate how epigenetic-like changes can alter the spatio-temporal nature of the domains. Our results show that heterogeneous weak interactions are crucial in determining the organization of the domains. Computing effective stiffness and relaxation times, we investigate how perturbations in interactions affect the solid-like and liquid-like nature of chromatin domains. Quantifying dynamics of chromatin segments within a domain, we show how the competition between polymer entropy and interaction energy influence the timescales of loop formation and maintenance of stable loops. Evaluation of US state pollinator plans using 3 evidence-based policymaking frameworks After the US federal government created a national pollinator protection plan in 2015, many states followed with their own. Since their goal is to promote pollinating insect conservation, we wanted to know whether the state plans are using best practices for evidence-based science policy. In early 2019 we found and downloaded every existing, publicly available US state pollinator protection plan. We then used content analysis to assess the goals, scope, and implementation of state-level pollinator protection plans across the US. This analysis was conducted using three distinct frameworks for evidence-based policymaking: US Department of Interior Adaptive Resources Management (ARM), US Environmental Protection Agency management pollinator protection plan (MP3) guidance, and Pew Trusts Pew-MacAthur Results First Project elements of evidence-based state policymaking (PEW) framework. Then we scored them using the framework criteria, to assess whether the plans were using known best practices for evidence based policymaking. Of the 31 states with a state pollinator plan, Connecticut was the state with the lowest total score across the three evaluation frameworks. The state with the highest overall scores, across the three frameworks, was Missouri. Most states did not score highly on the majority of the frameworks. Overall, many state plans were lacking policy elements that address monitoring, evaluation, and adjustment. These missing elements impact states ability to achieve their conservation goals. Our results indicate that states can improve their pollinator conservation policies to better match evidence-based science policy guidance, regardless of which framework is used. N-VEGF, the forgotten isoform of VEGF-A, activate cellular stress survival circuits Vascular endothelial growth factor A (VEGF-A) is a secreted protein that stimulates angiogenesis in response to hypoxia. Under hypoxic conditions, a non-canonical long isoform called L-VEGF is concomitantly expressed with VEGF-A. Once translated, L-VEGF it is proteolytically cleaved to generate N-VEGF and VEGF-A. Interestingly, while VEGF-A is secreted and affects the surrounding cells, N-VEGF is mobilized to the nucleus. This suggests that N-VEGF participates in transcriptional response to hypoxia. In this study, we performed a series of complementary experiments to examine the functional role of N-VEGF. Strikingly, we found that the mere expression of N-VEGF followed by its hypoxia-independent mobilization to the nucleus was sufficient to induce key genes associated with angiogenesis, such as Hif1, VEGF-A isoforms, as well as genes associated with cell survival under hypoxia. Complementarily, when N-VEGF was genetically depleted, key hypoxia-induced genes were downregulated and cells were significantly susceptible to hypoxia-mediated apoptosis. This is the first reports of N-VEGF serving as an autoregulatory arm of VEGF-A. Further experiments will be needed to determine the role of N-VEGF in cancer and embryogenesis. Production and characterization of virus-free, CRISPR-CAR T cells capable of inducing solid tumor regression BackgroundChimeric antigen receptor (CAR) T cells traditionally harbor viral vector-based sequences that encode the CAR transgene in the genome. These T cell products have yet to show consistent anti-tumor activity in patients with solid tumors. Further, viral vector manufacturing is resource intensive, suffers from batch-to-batch variability, and includes several animal components, adding regulatory and supply chain pressures.

MethodsAnti-GD2 CAR T cells were generated using CRISPR/Cas9 within nine days using recombinant Cas9 protein and nucleic acids, without any viral vectors or animal components. The CAR was specifically targeted to the T Cell Receptor Alpha Constant gene (TRAC). T cell products were characterized at the level of the genome, transcriptome, proteome, and secretome using CHANGE-seq, scRNA-seq, spectral cytometry, and ELISA assays. Functionality was evaluated in vivo in an NSG xenograft neuroblastoma model.

ResultsIn comparison to traditional retroviral CAR T cells, virus-free CRISPR CAR (VFC-CAR) T cells exhibit TRAC-targeted genomic integration of the CAR transgene, elevation of transcriptional and protein characteristics associated with a memory phenotype, and low tonic signaling prior to infusion arising in part from the the knockout of the TCR. Upon exposure to the GD2 target antigen, anti-GD2 VFC-CAR T cells exhibited specific cytotoxicity against GD2+ cells in vitro and induced solid tumor regression in vivo, with robust homing, persistence, and low exhaustion against a human neuroblastoma xenograft model.

ConclusionsThis proof-of-principle study leveraging virus-free genome editing technology could enable flexible manufacturing of clinically relevant, high-quality CAR T cells to treat cancers, including solid tumors. Cell cycle-independent integration of stress signals promotes Non-G1/G0 quiescence entry Cellular quiescence is a non-proliferative state required for cell survival under stress and during development. In most quiescent cells, proliferation is stopped in a reversible state of low Cdk1 kinase activity; in many organisms, however, quiescent states with high Cdk1 activity can also be established through still uncharacterized stress or developmental mechanisms. Here, we used a microfluidics approach coupled to phenotypic classification by machine learning to identify stress pathways associated with starvation-triggered high-Cdk1 quiescent states in Saccharomyces cerevisiae. We found that low- and high-Cdk1 quiescent states shared a core of stress-associated processes, such as autophagy, protein aggregation, and mitochondrial upregulation, but differed in the nuclear accumulation of the stress transcription factors Xbp1, Gln3, and Sfp1. The decision between low- or high-Cdk1 quiescence was controlled by cell cycle-independent accumulation of Xbp1, which acted as a time-delayed integrator of the duration of stress stimuli. Our results show how cell cycle-independent stress-activated factors promote cellular quiescence outside of G1/G0. Long term analysis of social structure: evidence of age-based consistent associations in male Alpine ibex Despite its recognized importance for understanding the evolution of animal sociality as well as for conservation, long term analysis of social networks of animal populations is still relatively uncommon. We investigated social network dynamics in males of a gregarious mountain ungulate (Alpine ibex, Capra ibex) over ten years focusing on groups, sub-groups and individuals, exploring the dynamics of sociality over different scales. Despite the social structure changing between seasons, the Alpine ibex population was highly cohesive: fission-fusion dynamics lead almost every male in the population to associate with each other male at least once. Nevertheless, we found that male Alpine ibex showed preferential associations that were maintained across seasons and years. Age seemed to be the most important factor driving preferential associations while other characteristics, such as social status, appeared less crucial. We also found that centrality measures were influenced by age and were also related to individual physical condition. The multi-scale and long-term frame of our study helped us show that ecological constrains, such as resource availability, may play a role in shaping associations in a gregarious species, but they cannot solely explain sociality and preferential association that are likely also to be driven by life-history linked physiological and social needs. Our results highlight the importance of long-term studies based on individually recognizable subjects to help us build on our understanding of the evolution of animal sociality. High-Potency Polypeptide-based Inhibition of Enveloped-virus Glycoproteins Specific manipulation of proteins post-translationally remains difficult. Here we report results of a general approach that uses a partial sequence of a protein to efficiently modulate the expression level of the native protein. When applied to coronavirus, human immunodeficiency virus, Ebolavirus, respiratory syncytial virus and influenza virus, polypeptides containing highly conserved regions of the viral glycoproteins potently diminished expression of the respective native proteins. In the cases of coronavirus and influenza virus where multiple strains were tested, the polypeptides were equally effective against glycoproteins of other coronavirus and influenza strains with sequence identity as low as 27%, underscoring their high insensitivity to mutations. Thus, this method provides a platform for developing high-efficacy broad-spectrum anti-viral inhibitors, as well as a new way to alter expression of essentially any systems post-translationally. Royal knifefish generate powerful suction feeding through large neurocranial elevation and high epaxial muscle power Suction feeding in ray-finned fishes involves powerful buccal cavity expansion to accelerate water and food into the mouth. Previous XROMM studies in largemouth bass (Micropterus salmoides), bluegill sunfish (Lepomis macrochirus), and channel catfish (Ictalurus punctatus) have shown that more than 90% of suction power in high performance strikes comes from the axial musculature. Thus, the shape of the axial muscles and skeleton may impact suction feeding mechanics. Royal knifefish (Chitala blanci) have an unusual postcranial morphology, with a ventrally flexed vertebral column and relatively large mass of epaxial muscle. Based on their body shape, we hypothesized that royal knifefish would generate high power strikes by utilizing large neurocranial elevation, vertebral column extension, and epaxial shortening. As predicted, C. blanci generated high suction expansion power compared to the other three species studied to date (up to 160 W), which was achieved by increasing both the rate of volume change and the intraoral subambient pressure. The large epaxial muscle (25% of body mass) shortened at high velocities to produce large neurocranial elevation and vertebral extension (up to 41 deg, combined), as well as high muscle mass-specific power (up to 800 W kg-1). For the highest power strikes, axial muscles generated 95% of the power, and 64% of the axial muscle mass consisted of the epaxial muscles. The epaxial-dominated suction expansion of royal knifefish supports our hypothesis that postcranial morphology may be a strong predictor of suction feeding biomechanics.

SUMMARY STATEMENTRoyal knifefish rely on their distinct postcranial morphology--with a curved vertebral column and large dorsal body muscles--to produce large neurocranial elevation and powerful suction feeding. Genetic analysis of mitochondrial DNA copy number and associated traits identifies loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation, and reveals a causal association of mitochondrial function with mortality Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses were used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 x 10-15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 x 10-8) and mtDNA replication (p = 1.2 x 10-7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 x 10-4). Cortical encoding during word reading in bilinguals: parallel interdigitated distributed networks support convergent linguistic functioning Word reading includes a series of cognitive processes that convert low-level visual characteristics to neural representations. However, the consistency of the neural mechanisms for processing these cognitive components across different writing systems in bilinguals remains inconclusive. Here, we explored this question by employing representational similarity analysis with a semantic access task involving Chinese words, English words and Chinese pinyin. Distinct anatomical distribution patterns were detected for each type of brain representation across ideographic and alphabetic languages, resulting in 100% classification accuracy. Meanwhile, convergent cognitive components processing was found in the core language-related regions in left hemisphere, including the inferior frontal gyrus, temporal pole, superior and middle temporal gyrus, precentral gyrus and supplementary motor areas. Broadly, our findings indicated that the neural basis for word recognition of different writing systems in bilinguals was divergent in anatomical locations of neural representations for specialized processing but convergent in cognitive domains, which supported and enriched the assimilation-accommodation hypothesis.

TeaserCortical encoding linguistic processing across languages was support by parallel interdigitated distributed networks but convergent in cognitive domains. Circulating immune complexes drive immunopathology in COVID-19 A dysregulated immune response with high levels of SARS-CoV-2 specific IgG antibodies characterizes patients with severe or critical COVID-19. Although a robust IgG response is traditionally considered to be protective, excessive triggering of activating Fc-gamma-receptors (Fc{gamma}Rs) could be detrimental and cause immunopathology. Here, we document that patients who develop soluble circulating IgG immune complexes (sICs) during infection are subject to enhanced immunopathology driven by Fc{gamma}R activation. Utilizing cell-based reporter systems we provide evidence that sICs are predominantly formed prior to a specific humoral response against SARS-CoV-2. sIC formation, together with increased afucosylation of SARS-CoV-2 specific IgG eventually leads to an enhanced CD16 (Fc{gamma}RIII) activation of immune cells reaching activation levels comparable active systemic lupus erythematosus (SLE) disease. Our data suggest a vicious cycle of escalating immunopathology driven by an early formation of sICs in predisposed patients. These findings reconcile the seemingly paradoxical findings of high antiviral IgG responses and systemic immune dysregulation in severe COVID-19.

Clinical implicationsThe identification of sICs as drivers of an escalating immunopathology in predisposed patients opens new avenues regarding intervention strategies to alleviate critical COVID-19 progression.

Graphical abstract

O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=78 SRC="FIGDIR/small/449893v4_ufig1.gif" ALT="Figure 1">
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org.highwire.dtl.DTLVardef@b4616corg.highwire.dtl.DTLVardef@682d1aorg.highwire.dtl.DTLVardef@16946cborg.highwire.dtl.DTLVardef@a6ef7d_HPS_FORMAT_FIGEXP  M_FIG C_FIG A vicious cycle of immunopathology in COVID-19 patients is driven by soluble multimeric immune complexes (sICs). SARS-CoV-2 infection triggers sIC formation in prone individuals. Activation of Fc{gamma}RIII/CD16 expressing immune cells by sICs precedes a humoral response to SARS-CoV2 infection. sICs and infection add to IgG afucosylation, further enhancing Fc{gamma}RIII/CD16 activation by opsonized targets. High inflammation induces further sIC mediated immune cell activation ultimately leading to an escalating immunopathology. Integrative Modelling of Signalling Network Dynamics Identifies Cell Type-selective Therapeutic Strategies for FGFR4-driven Cancers Oncogenic FGFR4 signalling represents a potential therapeutic target in many cancer types, including triple negative breast cancer (TNBC) and hepatocellular carcinoma (HCC). However, resistance to single-agent therapy directed at FGFR4 remains a major challenge, prompting the need to identify more effective combinatorial therapeutic strategies. Here, we integrated computational network modelling and experimental validation to characterise dynamic reprogramming of the FGFR4 signalling network in TNBC following FGFR4 kinase inhibition. We found that AKT, which signals downstream of FGFR4, displayed a rapid and potent reactivation following FGFR4 targeting. Through model-based simulation and systematic prediction of the effect of co-targeting specific network nodes, we predicted, and validated experimentally, strong synergism of co-targeting FGFR4 and particular ErbB kinases or AKT, but not the upstream kinase PI3K. Further, incorporation of protein expression data from hundreds of cancer cell types enabled us to adapt our model to other diverse cellular contexts, leading to the prediction that while AKT rebound occurs frequently, it is not a general phenomenon. Instead, ERK is reactivated in a subset of cell types, including the FGFR4-driven HCC cell line Hep3B. This was subsequently corroborated, and moreover, co-targeting FGFR4 and MEK in Hep3B cells markedly enhanced inhibition of cell proliferation. Overall, these findings provide novel insights into the dynamics of drug-induced network remodelling in cancer cells, highlight the impact of protein expression heterogeneity on network response to targeted therapy and identify candidate cell type-selective combination treatments for FGFR4-driven cancer. Outer hair cell electro-mechanical power conversion Outer hair cells are the cellular motors in the mammalian inner ear responsible for sensitive high-frequency hearing. Motor function requires expression of the protein prestin in the OHC lateral membrane and mechano-electrical transduction in the apical hair bundle. In the present report, electrical power consumption and mechanical power output are determined using previously published voltage clamp data from isolated OHCs and membrane patches. Results reveal that power output by the prestin-motor complex peaks at a best frequency much higher than implied by the low-pass character of nonlinear capacitance, and much higher than the whole-cell resistive-capacitive corner frequency. High frequency power output is enabled by a -90{degrees} shift in the phase of prestin-dependent electrical charge displacement, manifested electrically as emergence of imaginary-valued nonlinear capacitance. A new method for the sampling and preservation of placental specimens in low-resource settings for the identification of P. falciparum and analysis of nucleic acids Collection, preservation, and shipment of histological specimens in low-resource settings is challenging. We present a novel method that achieved excellent preservation of placental specimens from rural Mali by using formalin fixation, ethanol dehydration, and long-term storage in a solar-powered freezer. Sample preservation success was 92%, permitting evaluation of current and past malaria infection, anemia, placental maturity, and inflammation. Using RNAscope(R) hybridization we were able to visualize cell-specific gene expression patterns in the formalin-fixed paraffin-embedded (FFPE) specimens. Additionally, our method entailed mirrored sampling from the two cut faces of a cotyledon, one for the FFPE workflows and the other for storage in RNAlater and RNA-seq. Integrated annotation and analysis of genomic features reveal new types of functional elements and large-scale epigenetic phenomena in the developing zebrafish Zebrafish, a popular model for embryonic development and for modelling human diseases, has so far lacked a systematic functional annotation programme akin to those in other animal models. To address this, we formed the international DANIO-CODE consortium and created the first central repository to store and process zebrafish developmental functional genomic data. Our Data Coordination Center (https://danio-code.zfin.org) combines a total of 1,802 sets of unpublished and reanalysed published genomics data, which we used to improve existing annotations and show its utility in experimental design. We identified over 140,000 cis-regulatory elements in development, including novel classes with distinct features dependent on their activity in time and space. We delineated the distinction between regulatory elements active during zygotic genome activation and those active during organogenesis, identifying new aspects of how they relate to each other. Finally, we matched regulatory elements and epigenomic landscapes between zebrafish and mouse and predict functional relationships between them beyond sequence similarity, extending the utility of zebrafish developmental genomics to mammals.