Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis Single-cell RNA-sequencing (RNA-seq) has become a powerful tool to study biologically significant characteristics at explicitly high resolution. However, its application on emerging data is currently limited by its intrinsic techniques. Though many methods have been proposed to analyze bulk data using single-cell profile as a reference, they are limited on the interpretability, processing speed, and data size requirement. Here, we introduce Tissue-AdaPtive autoEncoder (TAPE), a deep learning method connecting bulk RNA-seq and single-cell RNA-seq, to achieve precise prediction in short time. By constructing an interpretable decoder and training under a unique scheme, TAPE can predict cell-type fractions and cell-type-specific gene expression tissue-adaptively. Compared with existing methods on several benchmarking datasets, TAPE is more accurate (up to 40% improvement on the real bulk data) and faster. Thus, it is sensitive enough to provide biologically meaningful predictions. For example, only TAPE can predict the tendency of increasing monocytes-to-lymphocytes ratio in COVID-19 patients from mild to serious symptoms, of which estimated indices are consistent with laboratory data. More importantly, through the analysis of clinical data, TAPE shows its ability to predict cell-type-specific gene expression profiles with biological significance. Combining with single-sample gene set enrichment analysis (ssGSEA), TAPE also provides valuable clues to investigate the immune response in different virus-infected patients. We believe that TAPE will enable and accelerate the precise analysis of high-throughput clinical data in a wide range.
hECA: the cell-centric assembly of a cell atlas Single-cell omics data can characterize multifaceted features of massive cells and bring significant insights to biomedical researches. The accumulation of single-cell data provides growing resources for constructing atlases for all cells of a human organ or the whole body. The true assembly of a cell atlas should be cell-centric rather than file-centric. We proposed a unified information framework enabling seamless cell-centric data assembly and developed a human Ensemble Cell Atlas (hECA) as an instance. hECA version 1.0 assembled scRNA-seq data across multiple studies into one orchestrated data repository. It contains 1,093,299 labeled cells and metadata from 116 published human single-cell studies, covering 38 human organs and 11 systems. We invented three methods of applications based on the cell-centric assembly: "In data" cell sorting enables targeted data retrieval in the full atlas with customizable logic expressions; The "quantitative portraiture" system provides a multi-view presentation of biological entities (organs, cell types, and genes) of multiple granularities; The customizable reference creation allows users to use the cell-centric assembly to generate references for their own cell type annotations. Case studies on agile construction of user-defined sub-atlases and "in data" investigation of CAR-T off-targets in multiple organs showed the great potential of cell-centric atlas assembly.
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. Mobile elements harbouring heavy metal and bacitracin resistance cassettes are common among Listeria monocytogenes persisting on dairy farms Listeria monocytogenes is a food-borne pathogen and a resilient environmental saprophyte. Dairy farms are a reservoir of L. monocytogenes and strains can persist on farms for years. Here, we sequenced the genomes of 250 L. monocytogenes isolates to investigate the persistence and mobile genetic elements of Listeria inhabiting dairy farms. We performed a SNP-based phylogenomic analysis to identify 14 monophyletic clades of L. monocytogenes that persistent on the farms for [&ge;] 6 months. We found that prophages and other mobile genetic elements were on average more numerous among isolates in persistent than nonpersistent clades, and demonstrated that resistance genes against bacitracin, arsenic and cadmium were significantly more prevalent among isolates in persistent than nonpersistent clades. We identified a diversity of mobile elements among the 250 farm isolates, including three novel plasmids, three novel transposons and a novel prophage harbouring cadmium resistance genes. Several of the mobile elements we identified in Listeria were identical to the mobile elements of Enterococci, indicative of recent transfer between these genera. Finally, we demonstrated that the CRISPR-cas IIa system and a type II restriction-modification system were negatively associated with persistence on farms. Our findings suggest that mobile elements support the persistence of L. monocytogenes on dairy farms and that L. monocytogenes inhabiting the agroecosystem is a potential reservoir of mobile elements that may spread to the food industry.

ImportanceAnimal derived raw materials are an important source of L. monocytogenes for the food industry. Knowledge of the factors contributing to the pathogens transmission and persistence on farms are essential for designing effective strategies against the spread of the pathogen from farm to fork. An increasing body of evidence suggests that mobile genetic elements support the adaptation and persistence of L. monocytogenes in the food industry, as these elements contribute to the dissemination of genes encoding favourable phenotypes, such as resilience against biocides and thermal stress. Understanding the role of farms as a potential reservoir of these elements is needed for managing the transmission of mobile elements across the food chain. Because L. monocytogenes coinhabits the farm ecosystem with a diversity of other bacterial species, it is important to assess the degree to which genetic elements are exchanged between Listeria and other species, as such exchanges may contribute to rise the novel resistance phenotypes. Modulation of P2X4 pore closure by magnesium,potassium, and ATP The P2X4 receptor plays a prominent role in cellular responses to extracellular ATP. Through classical all-atom molecular dynamics (MD) simulations totaling 24 {micro}s we have investigated how metal-complexed ATP stabilizes the channels open state and prevents its closing. We have identified two metal-binding sites, magnesium (Mg2+) and potassium (K+), one at the intersection of the three subunits in the ectodomain (MBS1) and the second one near the ATP binding site (MBS2), similar to those characterized in Gulf coast P2X. Our data indicate that when Mg2+ and K+ ions are complexed with ATP, the channel is locked into an open state. Interestingly, irrespective of the number of bound ATP molecules, Mg2+ ions bound to the MBS2 resisted collapsing of the open state protein to a closed state by stabilizing the ATP-protein interactions. However, when Mg2+ in the MBS2 was replaced with K+ ions, as might be expected when in equilibrium with an extracellular solution, the interactions between the subunits were weakened and we found evidence of pore collapse. This collapse was apparent when fewer than two ATP were bound to MBS2 in the presence of K+. Therefore, the different capacities of common cations to stabilize the channel may underlie a mechanism governing P2X4 channel gating in physiological systems. This study provides structural insights into the differential modulation of ATP activation of P2X4 by Mg2+ and K+. Extended Graphical Lasso for Multiple Interaction Networks for High Dimensional Omics Data There has been a spate of interest in association networks in biological and medical research, for example, genetic interaction networks. In this paper, we propose a novel method, the extended joint hub graphical lasso (EDOHA), to estimate multiple related interaction networks for high dimensional omics data across multiple distinct classes. To be specific, we construct a convex penalized log likelihood optimization problem and solve it with an alternating direction method of multipliers (ADMM) algorithm. The proposed method can also be adapted to estimate interaction networks for high dimensional compositional data such as microbial interaction networks. The performance of the proposed method in the simulated studies shows that EDOHA has remarkable advantages in recognizing class-specific hubs than the existing comparable methods. We also present three applications of real datasets. Biological interpretations of our results confirm those of previous studies and offer a more comprehensive understanding of the underlying mechanism in disease.

Author summaryReconstruction of multiple association networks from high dimensional omics data is an important topic, especially in biology. Previous studies focused on estimating different networks and detecting common hubs among all classes. Integration of information over different classes of data while allowing difference in the hub nodes is also biologically plausible. Therefore, we propose a method, EDOHA, to jointly construct multiple interaction networks with capacity in finding different hub networks for each class of data. Simulation studies show the better performance over conventional methods. The method has been demonstrated in three real world data. Proinflammatory innate cytokines and metabolomic signatures predict T cell response in active COVID-19 The underlying factors contributing to the evolution of SARS-CoV-2-specific T cell responses during COVID-19 infection remain unidentified. To address this, we characterized innate and adaptive immune responses with metabolomic profiling longitudinally at three different time points (0-3, 7-9, and 14-16 days post-COVID-19 positivity) from young mildly symptomatic active COVID-19 patients infected with the ancestral virus in mid-2020. We observed that anti-RBD IgG and viral neutralization are significantly reduced against the Delta variant compared to the ancestral strain. In contrast, compared to the ancestral strain, T cell responses remain preserved against the delta and omicron variants. We determined innate immune responses during the early stage of active infection in response to TLR 3/7/8 mediated activation in PBMCs and serum metabolomic profiling. Correlation analysis indicated PBMCs-derived proinflammatory cytokines, IL-6, IL-1{beta}, and IL-23, and the abundance of plasma metabolites, pyroglutamate, itaconate, and azelaic acid, were predictive of a robust SARS-CoV-2-specific Th1 response at a later stage (two weeks after PCR positivity). These observations may contribute to designing effective vaccines and adjuvants that promote innate immune responses and metabolites to induce long-lasting anti-SARS-CoV-2 specific T cells response.

Key MessageO_LIEarly proinflammatory innate cytokine response is critical for a robust T cell response during COVID-19.
C_LIO_LIWe report a set of plasma metabolites that significantly correlate with the innate and adaptive immune responses.
C_LI

Graphical Abstract

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org.highwire.dtl.DTLVardef@1bdb656org.highwire.dtl.DTLVardef@dd23aorg.highwire.dtl.DTLVardef@164e404org.highwire.dtl.DTLVardef@b5f389_HPS_FORMAT_FIGEXP  M_FIG C_FIG Design, Mutate, Screen: High-throughput creation of genetic clocks with different period-amplitude characteristics Directed evolution has become an invaluable tool in protein engineering and has also greatly influenced the construction of synthetic gene circuits. The ability to generate diversity at precise targets for directed evolution approaches has improved vastly, allowing researchers to create large, specific mutant libraries with relative ease. Screening approaches for large mutant libraries have similarly come a long way, especially when the desired behavior can easily be tested for with static, single time-point assays. For more complex gene circuits with dynamic phenotypes that change over time, directed evolution approaches to controlling and tuning circuit behavior have been hindered by the lack of sufficiently high-throughput screening methods to isolate variants with desired characteristics. Here we utilize directed mutagenesis and multiplexed microfluidics to develop a workflow for creating, screening and tuning dynamic gene circuits that operate at the population level. Specifically, we create a mutant library of an existing oscillator, the synchronized lysis circuit, and tune its dynamics while uncovering principles regarding its behavior. Lastly, we utilize this directed evolution workflow to construct a new synchronized genetic oscillator that exhibits robust dynamics over long time scales. A thermodynamic model for water activity and redox potential in evolution and development Reactions involving water and oxygen are basic features of geological and biological processes. To understand how life interacts with its environment requires monitoring interactions with H2O and O2 at timescales relevant to not only organismal growth but also billions of years of geobiological evolution. Here, chemical transformations intrinsic to evolution and development were characterized by analyzing data from recent phylostratigraphic and proteomic studies. This two-stage analysis involves obtaining chemical metrics (carbon oxidation state and stoichiometric hydration state) from the elemental compositions of proteins followed by modeling the relative stabilities of target proteins against a proteomic background to infer thermodynamic parameters (oxygen fugacity, water activity, and virtual redox potential (Eh)). The main results of this study are a rise in carbon oxidation state of proteins spanning the time of the Great Oxidation Event, a rise in virtual redox potential that coincides with the likely emergence of aerobic metabolism, a rise in carbon oxidation state of proteins inferred from the transcriptome in late stages of Bacillus subtilis biofilm growth, and a drop in stoichiometric hydration state of the fruit fly developmental proteome at the same time as a drop in organismal water content. Stoichiometric hydration state also decreases for proteins with more recent gene ages and through stages of biofilm development, leading to predictions of higher hydration potentials at earlier time points. By building chemical representations of protein evolution and developmental proteomes, exciting new types of geobiochemical proxies can be developed. Identification of two cancer stem cell-like populations in triple-negative breast cancer xenografts Gene expression analysis at the single-cell level by next generation sequencing has revealed the existence of clonal dissemination and microheterogeneity in cancer metastasis. The current spatial analysis technologies can elucidate the heterogeneity of cell-cell interactions in situ. To reveal the regional and expressional heterogeneity in primary tumors and metastases, we performed transcriptomic analysis of microtissues dissected from a triple-negative breast cancer (TNBC) cell line MDA-MB-231 xenograft model with our automated tissue microdissection punching technology. This multiple-microtissue transcriptome analysis revealed three cancer cell-type clusters in the primary tumor and axillary lymph node metastasis, two of which were cancer stem cell (CSC)-like clusters (CD44/MYC-high, HMGA1-high). Reanalysis of public single-cell RNA-seq (scRNA-seq) datasets confirmed that the two CSC-like populations existed both in TNBC xenograft models and TNBC patients. In addition, the gene signature of the HMGA1-high CSC-like cluster has the potential to serve as a novel biomarker for diagnosis. The diversity of these multiple CSC-like populations may cause differential anticancer drug resistance, increasing the difficulty of curing this cancer. 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. Collective polymerase dynamics emerge from DNA supercoiling during transcription All biological processes ultimately come from physical interactions. The mechanical properties of DNA play a critical role in transcription. RNA polymerase can over or under twist DNA (referred to as DNA supercoiling) when it moves along a gene resulting in mechanical stresses in DNA that impact its own motion and that of other polymerases. For example, when enough supercoiling accumulates, an isolated polymerase halts and transcription stops. DNA supercoiling can also mediate non-local interactions between polymerases that shape gene expression fluctuations. Here, we construct a comprehensive model of transcription that captures how RNA polymerase motion changes the degree of DNA supercoiling which in turn feeds back into the rate at which polymerases are recruited and move along the DNA. Surprisingly, our model predicts that a group of three or more polymerases move together at a constant velocity and sustain their motion (forming what we call a polymeton) whereas one or two polymerases would have halted. We further show that accounting for the impact of DNA supercoiling on both RNA polymerase recruitment and velocity recapitulates empirical observations of gene expression fluctuations. Finally, we propose a mechanical toggle switch whereby interactions between genes are mediated by DNA twisting as opposed to proteins. Understanding the mechanical regulation of gene expression provides new insights into how endogenous genes can interact and informs the design of new forms of engineered interactions.

PACS numbers: Dynamic selective auditory attention detection using RNN and reinforcement learning The cocktail party phenomenon describes the ability of the human brain to focus auditory attention on a particular stimulus while ignoring other acoustic events. Selective auditory attention detection (SAAD) is an important issue in the development of brain-computer interface systems and cocktail party processors. This paper proposes a new dynamic attention detection system to process the temporal evolution of the input signal. The proposed dynamic SAAD is modeled as a sequential decision-making problem, which is solved by recurrent neural network (RNN) and reinforcement learning methods of Q-learning and deep Q-learning. Among different dynamic learning approaches, the evaluation results show that the deep Q-learning approach with RNN as agent provides the highest classification accuracy (94.2%) with the least detection delay. The proposed SAAD system is advantageous, in the sense that the detection of attention is performed dynamically for the sequential inputs. Also, the system has the potential to be used in scenarios, where the attention of the listener might be switched in time in the presence of various acoustic events. High-quality genome assembly of Cinnamomum burmannii (chvar. Borneol) provides insights into the natural borneol biosynthesis Cinnamomum burmannii (chvar. Borneol) is a well-known medicinal and industrial plant cultivated in the Lingnan region of China. It is the key source from organism of natural borneol (D-borneol), one of the precious and widely used Chinese herbal medicines with a variety of medicinal effects. Here, we report a high-quality chromosome-scale genome assembly of C. burmannii (chvar. Borneol) using Pacbio single-molecule sequencing and Hi-C technology. The assembled genome size was 1.14 GB with a scaffold N50 of 94.30 Mb, while 98.77% of the assembled sequences were anchored on 12 pseudochromosomes including 41549 protein-coding genes. Genomic evolution analysis revealed C. burmannii and C. micranthum shared two Lauraceae unique ancestral whole-genome duplication (WGD) events. Likewise, comparative genomic analysis showed strong collinearity between these two species. Besides, the analysis for Long Terminal Repeat Retrotransposons (LTR-RTs) indicated the outbreak of LTR-RTs insertion made a great contribution to the size difference of genomes between C. burmannii and C. micranthum. Furthermore, the candidate genes in pathway associated with natural borneol synthesis were identified on the genome and their differential expressions were analyzed in various biological tissues. We considered that several of genes in Mevalonate (MVA) Methylerythritol Phosphate (MEP) pathways or in downstream pathway have the potential to be the key factors in the biosynthesis of D-borneol. We also constructed the genome database (CAMD; http://www.cinnamomumdatabase.com/) of Cinnamomum species for a better data utilization in the future. All these results will enrich the genomic data of Lauraceae plants and facilitate genetic improvement of this commercially important plant. Plant biomechanics and resilience to environmental changes are controlled by specific lignin chemistries in each vascular cell type and morphotype The biopolymer lignin, deposited in the cell walls of vascular cells, is essential for long-distance water conduction and structural support of plants. Independently of the species, each different vascular cell type contains a conserved lignin chemistry with specific aromatic and aliphatic substitutions. Yet, the biological role of this conserved and specific lignin chemistry for each cell type remained unclear. Herein, we investigate the role of specific lignin chemistries for cellular function by producing single cell analyses on vascular cell morphotypes, all enabling sap conduction but differing in morphology. We found that specific lignin chemistries accumulate in each morphotype. Moreover, lignin accumulates dynamically, increasing in quantity and changing composition, to alter the cell wall biomechanics of each morphotype during their maturation. For similar aromatic substitution, residues with alcohol aliphatic functions increased stiffness whereas aldehydes increased flexibility. Modifying this specific lignin chemistry impairs the cell wall biomechanics of each morphotype and consequently reduces their capacity to optimally conduct water in normal conditions, and to recover from drought. Altogether, lignin chemistry is differently controlled for each sap conducting cell types during their maturation to dynamically adjust their biomechanics and hydraulic properties to adapt to developmental and environmental constraints. GPI-anchored FGF directs cytoneme-mediated bidirectional signaling to self-regulate tissue-specific dispersion How signaling proteins generate a multitude of information to organize tissue patterns is critical to understanding morphogenesis. In Drosophila, FGF produced in wing-disc cells regulates the development of the disc-associated air-sac-primordium (ASP). Here, we show that FGF is Glycosylphosphatidylinositol-anchored to the producing cell surface and that this modification both inhibits free FGF secretion and activates target-specific bidirectional FGF-FGFR signaling through cytonemes. FGF-source and recipient ASP cells extend cytonemes that present FGF and FGFR on their surfaces and reciprocally recognize each other over distance by contacting through CAM-like FGF-FGFR binding. Contact-mediated FGF-FGFR binding induces bidirectional signaling, which, in turn, promotes ASP and source cells to polarize cytonemes toward each other and reinforce signaling contacts. Subsequent un-anchoring of FGFR-bound-FGF from the source cell membrane dissociates cytoneme contacts and delivers FGF target-specifically to ASP cytonemes for paracrine functions. Thus, GPI-anchored FGF organizes both source and recipient cells and self-regulates its cytoneme-mediated tissue-specific dispersion and signaling. Embryonic exposure to cannabidiol disrupts active neural circuits, an effect increased by Δ9-tetrahydrocannabinol and involving CB1R and CB2R in zebrafish In the light of legislative changes and the widespread use of cannabis as a recreational and medicinal drug, delayed effects of cannabis upon brief exposure during embryonic development are of high interest as early pregnancies often go undetected. Here, zebrafish embryos were exposed to cannabidiol (CBD) and {Delta}-9-tetrahydrocannabinol l (THC) until the end of gastrulation (1-10 hours post-fertilization) and analyzed later in development (4-5 days post-fertilization). In order to measure neural activity, we implemented CaMPARI (Calcium-Modulated Photoactivatable Ratiometric Integrator) and optimized the protocol for a 96-well format complemented by locomotor analysis. Our results revealed that neural activity was decreased by CBD more than THC. At higher doses, both cannabinoids could dramatically reduce neural activity and locomotor activity. Interestingly, the decrease was more pronounced when CBD and THC were combined. At the receptor level, CBD-mediated reduction of locomotor activity was partially prevented using cannabinoid type 1 and 2 receptor inhibitors. Overall, we report that CBD toxicity occurs via two cannabinoid receptors and is synergistically enhanced by THC exposure to negatively impact neural activity late in larval development. Future studies are warranted to reveal other cannabinoids and receptors involved in this pathway to understand the subsequent health implications of cannabis consumption on fetal development. Feline tooth resorption findings from a questionnaire survey on 8115 Finnish cats and a case-control study for a more defined population drawn from the survey Tooth resorption (TR) is one of the most common dental diseases in cats. It is a painful disease characterised by progressive dental destruction, which eventually results in loss of teeth. The aetiology of the disease remains unclear, but associations with old age, breed, other oral and dental diseases, and certain environmental factors have been suspected. We collected health and environmental information of 8115 Finnish cats from 41 breeds through an online survey for cat owners to study TR in Finland with an observational study. The frequency of TR that the owner reported as veterinarian-diagnosed was 3.9% in the entire data (316/8115) and 15% in cats that the owner reported as having veterinarian-diagnosed oral or dental disease (316/2070). We determined the risk factors and breed variation of feline TR by logistic regression with the entire data and a case-control study in a more defined population drawn from the entire data. In the entire data, we defined those cats that the owners had reported as being diagnosed with TR by a veterinarian as TR-cats and compared them to all other cats. In the case-control study, we included only cats with owner-reported veterinarian-diagnosed oral and dental diseases. We defined cats with TR-diagnosis made under sedation as TR-cases. Other veterinarian-diagnosed TR-cats were excluded. Cats with other oral and dental diseases were used as controls. The model with the entire population included 308 TR-cats compared with 7508 cats, and the case-control study included 198 TR-cats and 1683 controls. Although the diagnoses were reportedly made by a veterinarian, the owner answered the survey and might have understood, remembered, or interpreted the diagnoses in a way that could affect the results. The results indicated an increasing risk of TR with age. Dental calculus, gingivitis, and periodontitis were potential risk factors for TR. These findings and the interaction between dental calculus and gingivitis suggest that inflammatory changes caused by dental calculus increase the risk of TR. Keeping food available constantly was a potential protective factor. We found that Cornish Rex, European, and Ragdoll breeds were at higher risk for TR. The observed differences between breeds highlight a genetic contribution. ConVarT: a search engine for orthologous variants and functional inference of human genetic variants The availability of genetic variants, together with phenotypic annotations from model organisms, facilitates comparing these variants with equivalent variants in humans. However, existing databases and search tools do not make it easy to scan for equivalent variants, namely "matching variants" (MatchVars) between humans and other organisms. Therefore, we developed an integrated search engine called ConVarT (http://www.convart.org/) for matching variants between humans, mice, and C. elegans. ConVarT incorporates annotations (including phenotypic and pathogenic) into variants, and these previously unexploited phenotypic MatchVars from mice and C. elegans can give clues about the functional consequence of human genetic variants. Our analysis shows that many phenotypic variants in different genes from mice and C. elegans, so far, have no counterparts in humans, and thus, can be useful resources when evaluating a relationship between a new human mutation and a disease. Frequency modulated timer regulates mammalian hibernation Mammalian hibernators decrease basal metabolism and body temperature (Tb) to minimize energy expenditure in harsh seasons. During hibernation, Tb drops to low temperature (<10 {degrees}C) and remains constant for days, known as deep torpor in small mammalian hibernators. Spontaneous interbout arousals interrupt torpor bouts, when Tb recovers to euthermic state ~37 {degrees}C. Torpor-interbout arousal event repeats during several months of hibernation. However, little is known about mechanisms governing Tb fluctuation across torpor-interbout arousal cycles during hibernation. Recent improvement in data-logging techniques enables us to monitor Tb for more than hundred days with high precision, opening up new avenues for quantitative analysis to address the principle governing Tb fluctuation. Here, we analyzed Tb fluctuation across torpor-interbout arousal cycle of Syrian hamster, which can hibernate in response to chronic cold and short photoperiod under a laboratory condition, using generalized harmonic analysis and discovered a model with frequency modulation quantitatively reproducing Tb fluctuation. This analysis also identified an unexpectedly longer period of 120-430 days as the period that modulates another period of several days, generating Tb fluctuation for Syrian hamster. We propose that concerted action of two endogenous periods governs torpor-interbout arousal cycles during hibernation. Lowland plant arrival in alpine ecosystems facilitates a decrease in soil carbon content under experimental climate warming Climate warming is releasing carbon from soils around the world1-3, constituting a positive climate feedback. Warming is also causing species to expand their ranges into new ecosystems4-9. Yet, in most ecosystems, whether range expanding species will amplify or buffer expected soil carbon loss is unknown10. Here we used two whole-community transplant experiments and a follow-up glasshouse experiment to determine whether the establishment of herbaceous lowland plants in alpine ecosystems influences soil carbon content under warming. We found that warming (transplantation to low elevation) led to a negligible decrease in alpine soil carbon content, but its effects became significant and 52% {+/-} 31% (mean {+/-} 95% CIs) larger after lowland plants were introduced at low density into the ecosystem. We present evidence that decreases in soil carbon content likely occurred via lowland plants increasing rates of root exudation, soil microbial respiration and CO2 release under warming. Our findings suggest that warming-induced range expansions of herbaceous plants have the potential to alter climate feedbacks from this system, and that plant range expansions among herbaceous communities may be an overlooked mediator of warming effects on carbon dynamics. Variation in female songbird state determines signal strength needed to evoke copulation It is the female response to male signals that determines courtship success. In most songbirds, females control reproduction via the copulation solicitation display (CSD), an innate, stereotyped posture produced in direct response to male displays. Because CSD can be elicited in the absence of males by the presentation of recorded song, CSD production enables investigations into the effects of underlying signal features and behavioral state on female mating preferences. Using computer vision to quantify CSD trajectory in female brown-headed cowbirds (Molothrus ater), we show that both song quality and a females internal state predict CSD production, as well as the onset latency and duration of the display. We also show that CSD can be produced in a graded fashion based on both signal strength and internal state. These results emphasize the importance of underlying receiver state in determining behavioral responses and suggest that female responsiveness acts in conjunction with male signal strength to determine the efficacy of male courtship. In vitro evolution of uracil glycosylase towards DnaKJ and GroEL binding evolves different misfolded states Natural evolution is driven by random mutations that improve fitness. In vitro evolution mimics this process, however, on a short time-scale and is driven by the given bait. Here, we used directed in vitro evolution of a random library of Uracil glycosylase (eUNG) displayed on yeast surface to select for binding to chaperones GroEL, DnaK+DnaJ+ATP (DnaKJ) or E.coli cell extract (CE). Using binding to the eUNG inhibitor Ugi as probe for native foldedess, the CE selected population was further divided to Ugi binders (+U) (native) or non-binders (-U). We found that GroEL, DnaKJ and CE-U select and enrich for mutations causing eUNG to misfold, with the three being enriched in mutations in buried and conserved positions, with a tendency to increase positive charge. Still, each selection, as well as CE+U and natural evolution of eUNG has its own trajectory. While GroEL and CE-U selected for mutants highly sensitive to protease cleavage, DnaKJ selected for partially structured misfolded species with a tendency to refold, making them less sensitive to proteases. CE+U selected for more neutral mutations than natural evolution. In a more general context, our results show that GroEL has a higher tendency to purge promiscuous misfolded protein mutants from the system, while DnaKJ binds mutants misfolding-prone species that are, upon chaperone release, more likely to natively refold. CE-U shares some of the properties of GroEL and DnaKJ selected populations, while harboring also unique properties, explained by the existence of additional chaperones in CE, such as Tig, HtpG and ClpB. OrganoID: a versatile deep learning platform for tracking and analysis of single-organoid dynamics Organoids have immense potential as ex vivo disease models for drug discovery and personalized drug screening. Dynamic changes in individual organoid morphology, number, and size can indicate important drug responses, however these metrics are difficult and labor-intensive to obtain for high-throughput image datasets. Here, we present OrganoID, a robust image analysis platform that automatically recognizes, labels, and tracks single organoids, pixel-by-pixel, in brightfield and phase-contrast microscopy experiments. The platform was trained on images of pancreatic cancer organoids and validated on separate images of pancreatic, lung, colon, and adenoid cystic carcinoma organoids, which showed excellent agreement with manual measurements of organoid count (96%) and size (95%) without any parameter adjustments. Single-organoid tracking accuracy remained above 89% over a four-day time-lapse microscopy study. Automated single-organoid morphology analysis of a chemotherapy dose-response experiment identified decreased organoid circularity as an important morphological feature reflecting drug response. OrganoID enables straightforward, detailed, and accurate image analysis to accelerate the use of organoids in high-throughput, data-intensive biomedical applications. Ex vivo anticoagulants affect the mechanical properties of human blood platelets with implications for in vitro high-throughput functional mechanophenotyping. Inherited platelet disorders affecting the human platelet cytoskeleton result in increased bleeding risk. However, deciphering their impact on cytoskeleton-dependent intrinsic biomechanics of platelets remains challenging and represents an unmet need from a diagnostic and prognostic perspective. It is currently unclear whether ex vivo anticoagulants used for the collection of peripheral blood impact the mechanophenotype of cellular components of blood. Using unbiased, high-throughput functional mechanophenotyping of single human platelets by deformability cytometry, we found that ex vivo anticoagulants are a critical pre-analytical variable that differentially influences platelet deformation, their size and functional response to agonists by altering the cytoskeleton. We applied our findings to characterize the functional mechanophenotype of platelets from a patient with Myosin Heavy Chain 9 (MYH9) related macrothrombocytopenia. Our data suggest that platelets from MYH9 p.E1841K mutation in humans affecting platelet non-muscle myosin heavy chain IIa (NMMHC-IIA) are biomechanically less deformable in comparison to platelets from healthy individuals. Erythropoietin supplementation ameliorates the immunological and hematological deficiencies of lysinuric protein intolerance in mice SLC7A7 encodes for y+LAT1, a cationic amino acid transporter expressed on the basolateral membrane of epithelial cells and macrophages. Mutations in human SLC7A7 cause lysinuric protein intolerance (LPI), a rare autosomal disorder with a variety of clinical symptoms. Citrulline and a low protein diet are widely used to treat the main symptoms of LPI; however, the hematological and immunological abnormalities in LPI remain poorly understood and difficult to manage by established treatments. Here, we show that erythropoietin levels are significantly diminished in mice lacking Slc7a7, which reduces the number of erythroblast precursors, resulting in mature red blood cells with a smaller mean corpuscular volume. Ex vivo analysis demonstrated that erythrocytes from Slc7a7-deficient mice were phagocytosed more by bone marrow-derived macrophages. Gene expression analysis of sorted red pulp macrophages (RPMs) from Slc7a7-deficient mice indicated that this cell population had higher erythrophagocytic activity, but preserved heme catabolic activity. The increase in erythrophagocytosis resulted in iron accumulation in macrophages and tissues, and ultimately led to RPM apoptosis. Surprisingly, ablation of Slc7a7 in myeloid cells failed to trigger tissue iron accumulation or changes in the RPM population, indicating that the expression of this gene in macrophages is not key for the development of iron accumulation in tissue. Finally, restoration of serum erythropoietin levels in Slc7a7-deficient mice re-established normal erythropoiesis and erythrophagocytosis and prevented the accumulation of iron in tissues. Thus, erythropoietin has a fundamental role in the immune-hematological alterations of LPI in mice, revealing a new crucial role for this hormone in this disease.