Delineation of insula dynorphin and kappa opioid receptor circuit elements in alcohol consumption Alcohol use disorder is complex and multi-faceted, involving the engagement of multiple signaling systems across numerous brain regions to drive pathological behavior. Previous work has indicated that both the insular cortex and dynorphin (DYN)/Kappa opioid receptor (KOR) systems contribute to excessive alcohol use. More recently, we identified a microcircuit in the medial aspect of the insular cortex that signals through DYN/KOR. Here, we explored the role of insula DYN/KOR circuit elements on alcohol intake in a long-term intermittent access (IA) procedure. Using a combination of conditional knockout strategies and site-directed pharmacology, we discovered distinct and sex-specific roles for insula DYN and KOR systems in alcohol drinking and related behavior. Our findings show that insula DYN deletion blocked escalated consumption and decreased overall intake of and preference for alcohol in male and female mice. This effect was specific to alcohol in male mice, as DYN deletion did not impact their sucrose intake. In male mice, insula KOR antagonism reduced alcohol intake and preference during the early phase of IA only. Alcohol consumption as not affected by insula KOR knockout. In addition, we found that long-term IA decreased the intrinsic excitability of DYN and deep layer pyramidal neurons (DLPN) in the insula of male mice. Excitatory synaptic transmission was also impacted by IA, as it drove an increase in excitatory synaptic drive in both DYN neurons and DLPN. Combined, our findings suggest that there is a dynamic interplay between excessive alcohol consumption and insula DYN/KOR circuit elements.
The Impact of Neuron Morphology on Cortical Network Architecture It has become increasingly clear that the neurons in the cerebral cortex are not randomly interconnected. This wiring specificity can result from synapse formation mechanisms that interconnect neurons depending on their activity or genetically defined identity. Here we report that in addition to these synapse formation mechanisms, the structural composition of the neuropil provides a third prominent source by which wiring specificity emerges in cortical networks. This structurally determined wiring specificity reflects the packing density, morphological diversity and similarity of the dendritic and axonal processes. The higher these three factors are, the more recurrent the topology of the networks. Conversely, low density, diversity and similarity yield feedforward networks. These principles predict connectivity patterns from subcellular to network scales that are remarkably consistent with empirical observations from a rich body of literature. Thus, cortical network architectures reflect the specific morphological properties of their constituents to much larger degrees than previously thought.
Sablefish (Anoplopoma fimbria Pallas, 1814) plasma biochemistry and hematology reference intervals including blood cell morphology Plasma biochemistry and hematology reference intervals are integral health assessment tools in all medical fields, including aquatic animal health. As sablefish (Anoplopoma fimbria) are becoming aquaculturally and economically more important, this manuscript provides essential reference intervals (RI) for their plasma biochemistry and hematology along with reference photomicrographs of blood cells in healthy, fasted sablefish. Blood cell morphology can differ between fish species. In addition, blood cell counts and blood chemistry can vary between fish species, demographics, water conditions, seasons, diets, and culture systems, which precludes the use of RIs from other fish species. For this study, blood was collected for plasma biochemistry and hematology analysis between June 20 and July 18, 2019, from healthy, yearling sablefish, hatched and reared in captivity on a commercial diet. Overnight fast of 16-18 hours did not sufficiently reduce lipids in the blood, which led to visible lipemia and frequent rupture of blood cells during analysis. Therefore, sablefish should be fasted for 24 to 36 hours before blood is collected to reduce hematology artifacts or possible reagent interference in plasma biochemistry analysis. Lymphocytes were the most dominant leukocytes (98%), while eosinophils were rare, and basophils were not detected in sablefish. Neutrophils were very large cells with Dohle bodies. In mammals and avian species, Dohle bodies are usually signs of toxic change from inflammation, but no such association was found in these fish. In conclusion, lipemia can interfere with sablefish blood analysis, and available removal methods should be evaluated as fasting for up to 36 h might not always be feasible. Also, more studies are required to establish RI for different developmental stages and rearing conditions. T606-phosphorylation deprives the function of Kaiso as a transcription and oncogenic factor It is well known that Kaiso protein encoded by ZBTB33 gene is a transcription repressor and that Kaiso-P120ctn interaction increases the shift of Kaiso from the nucleus into the cytoplasm. However, the regulatory mechanisms of Kaiso compartmentalization are far from clear. Here, we reported that AKT1 could phosphorylate 606-threonine residue (T606) within the RSSTIP motif of Kaiso in the cytoplasm. The T606-phosphorylated Kaiso (pT606-Kaiso) could directly bind to 14-3-3 family proteins and the depletion of T606 phosphorylation by T606A mutation abolished most of the Kaiso-14-3-3 binding. In addition, the Kaiso-P120ctn interaction was essential for the pT606-Kaiso accumulation in the cytoplasm. Notably, enforced 14-3-3{sigma} (SFN) overexpression could increase the pT606-Kaiso accumulation in the cytoplasm and de-repress the transcription of Kaiso target gene CDH1. Decreased amounts of both pT606-Kaiso and CDH1 proteins were frequently observed in human gastric cancer tissues relative to paired normal controls. The mRNA levels of 14-3-3{sigma} and Kaiso target gene CDH1 were positively and significantly correlated with each other in bioinformatics analyses using publicly available RNA-seq datasets for human normal tissues (n=11688, r=0.60, p<0.001) in the GTEx project and for cancer cell lines (n=1156, r=0.41, p<0.001) in the CCLE project. Furthermore, Kaiso T606A mutant (unable to be phosphorylated) significantly increased the migration and invasion of cancer cells in vitro as well as boosted the growth of these cells in vivo. In conclusion, Kaiso could be phosphorylated by AKT1 at the T606 and the pT606-Kaiso accumulates in the cytoplasm through binding to 14-3-3/P120ctn that de-represses the expression of Kaiso target gene CDH1 in normal tissues. Decreased Kaiso phosphorylation may contribute to the development of gastrointestinal cancer. The status of Kaiso phosphorylation is a determinant factor for the role of Kaiso in the development of cancer. High performance single-cell gene regulatory network inference atscale: The Inferelator 3.0 MotivationGene regulatory networks define regulatory relationships between transcription factors and target genes within a biological system, and reconstructing them is essential for understanding cellular growth and function. Methods for inferring and reconstructing networks from genomics data have evolved rapidly over the last decade in response to advances in sequencing technology and machine learning. The scale of data collection has increased dramatically; the largest genome-wide gene expression datasets have grown from thousands of measurements to millions of single cells, and new technologies are on the horizon to increase to tens of millions of cells and above.

ResultsIn this work, we present the Inferelator 3.0, which has been significantly updated to integrate data from distinct cell types to learn context-specific regulatory networks and aggregate them into a shared regulatory network, while retaining the functionality of the previous versions. The Inferelator is able to integrate the largest single-cell datasets and learn cell-type specific gene regulatory networks. Compared to other network inference methods, the Inferelator learns new and informative Saccharomyces cerevisiae networks from single-cell gene expression data, measured by recovery of a known gold standard. We demonstrate its scaling capabilities by learning networks for multiple distinct neuronal and glial cell types in the developing Mus musculus brain at E18 from a large (1.3 million) single-cell gene expression dataset with paired single-cell chromatin accessibility data.

AvailabilityThe inferelator software is available on GitHub (https://github.com/flatironinstitute/inferelator) under the MIT license and has been released as python packages with associated documentation (https://inferelator.readthedocs.io/). Global population genomics of two subspecies of Cryptosporidium hominis during 500 years of evolution Cryptosporidiosis is a major global health problem and a primary cause of diarrhoea, particularly in young children in low- and middle-income countries (LMICs). The zoonotic Cryptosporidium parvum and anthroponotic C. hominis cause most human infections. Here, we present a comprehensive whole-genome study of C. hominis, comprising 114 isolates from 16 countries within five continents. We detect two lineages with distinct biology and demography, which diverged circa 500 years ago. We consider these lineages two subspecies and propose the names C. hominis hominis and C. hominis aquapotentis (gp60 subtype IbA10G2). In our study, C. h. hominis is almost exclusively represented by isolates from LMICs in Africa and Asia and appears to have undergone recent population contraction. In contrast, C. h. aquapotentis was found in high-income countries, mainly in Europe, North America and Oceania, and appears to be expanding. Notably, C. h. aquapotentis is associated with high rates of direct human-to-human transmission, which may explain its success in countries with well-developed environmental sanitation infrastructure. Intriguingly, we detected genomic regions of introgression following secondary contact between the subspecies. This resulted in high diversity and divergence in genomic islands of putative virulence genes (GIPVs), including muc5 (CHUDEA2_430) and a hypothetical protein (CHUDEA6_5270). This diversity is maintained by balancing selection, suggesting a coevolutionary arms race with the host. Lastly, we find that recent gene flow from C. h. aquapotentis to C. h. hominis, likely associated with increased human migration, may be driving evolution of more virulent C. hominis variants. Pore dynamics and asymmetric cargo loading in an encapsulin nanocompartment Encapsulins are protein nanocompartments that house various cargo enzymes, including a family of decameric ferritin-like proteins. Here, we study a recombinant Haliangium ochraceum encapsulin:encapsulated ferritin complex using electron cryo-microscopy and hydrogen/deuterium exchange mass spectrometry to gain insight into the structural relationship between the encapsulin shell and its protein cargo. An asymmetric single particle reconstruction reveals four encapsulated ferritin decamers in a tetrahedral arrangement within the encapsulin nanocompartment. This leads to a symmetry mismatch between the protein cargo and the icosahedral encapsulin shell. The encapsulated ferritin decamers are offset from the interior face of the encapsulin shell. Using HDX-MS, we observed dynamic behavior of the major five-fold pore in the encapsulin shell and show the pore opening via the movement of the encapsulin A-domain. These data will accelerate efforts to engineer the encapsulation of heterologous cargo proteins and to alter the permeability of the encapsulin shell via pore modifications.

TeaserCryo-EM and HDX-MS analysis of an encapsulin nanocompartment shows that the pores at the five-fold icosahedral vertex of the shell are flexible. Drug screening at single-organoid resolution via bioprinting and interferometry High-throughput drug screening is an established approach to investigate tumor biology and identify therapeutic leads. Traditional platforms for high-throughput screening use two-dimensional cultures of immortalized cell lines which do not accurately reflect the biology of human tumors. More clinically relevant model systems, such as three-dimensional tumor organoids, can be difficult to screen and scale. For example, manually seeded organoids coupled to destructive endpoint assays allow for the characterization of response to treatment, but do not capture the transitory changes and intra-sample heterogeneity underlying clinically observed resistance to therapy. We therefore developed a pipeline to generate bioprinted tumor organoids linked to label-free, real-time imaging via high-speed live cell interferometry (HSLCI) and machine learning-based quantitation of individual organoids. Bioprinting cells gives rise to 3D organoid structures that preserve tumor histology and gene expression. HSLCI imaging in tandem with machine learning-based image segmentation and organoid classification tools enables accurate, label-free parallel mass measurements for thousands of bioprinted organoids. We demonstrate that our method quantitatively identifies individual organoids as insensitive, transiently sensitive, or persistently sensitive to specific treatments. This opens new avenues for rapid, actionable therapeutic selection using automated tumor organoid screening. The compound of baicalein, wogonin, and oroxylin-A inhibiting EMT in A549 cell line via PI3K/AKT-TWIST1-glycolysis pathway Non-small cell lung cancer (NSCLC) is a worldwide disease with high morbidity and mortality, which is most derived from its metastasis. Some researches show that the epithelial-mesenchymal transition (EMT) process promotes lung cancer cells migration and invasion, leading to NSCLC metastasis. Total Flavonoid Aglycones Extract (TFAE) isolated from Scutellaria baicalensis was reported to inhibit tumor growth and induce apoptosis. In this study, we found that baicalein, wogonin, and oroxylin-A were the active compounds of TFAE. After reconstructing with these three compounds (baicalein (65.8%), wogonin (21.2%), and oroxylin-A (13.0%)), the reconstructed TFAE (reTFAE) present inhibitory effect on the EMT process of A549 cells. Then, bioinformatic technology was employed to elucidate the potential pharmacodynamic mechanism network of reTFAE. We identified the relationship between reTFAE and PI3K/Akt signaling pathways, with TWIST1 as the key protein. LY294002, the inhibitor of PI3K/Akt signaling pathway, and knock-down TWIST1 could significantly enhance the efficacy of reTFAE, with increasing expression of epithelial markers and decreasing expression of mesenchymal markers in A549 cells at the same time. Furthermore, stable isotope dimethyl-labeled proteomics technology was conducted to complement the follow-up mechanism that the EMT-inhibition process may be realized through glycolysis pathway. In conclusion, we claim that TWIST1-targeted flavonoids could provide a new strategy to inhibit EMT progress for the treatment of NSCLC. Maternal microbiota Bifidobacterium promotes placental morphogenesis, nutrient transport and fetal growth in mice The gut microbiota plays a central role in regulating host metabolism. However, while substantial progress has been made in discerning how the microbiota influences host functions post birth and beyond, little is known about how key members of the maternal gut microbiota can influence feto-placental growth. Here, using germ-free and specific-pathogen-free mice, we demonstrate that the bacterium Bifidobacterium breve UCC2003 modulates maternal body adaptations, placental structure and nutrient transporter capacity, with implications for fetal metabolism and growth. The effects of B. breve UCC2003 on feto-placental growth are mediated, in part, by changes in the maternal and placental metabolome (i.e. acetate and carnitine). Histological analysis of the placenta confirmed that Bifidobacterium modifies placental structure via changes in Igf2P0, Dlk1, Mapk1 and Mapk14 expression. Additionally, B. breve UCC2003, acting through Slc2a1 and Fatp1-4 transporters, was shown to restore fetal glycaemia and fetal growth in association with changes in the fetal hepatic transcriptome. This study provides knowledge towards a novel and safe therapeutic strategy for treating pregnancy disorders via modulation of the maternal gut microbiota. Climate change and chill accumulation: implications for tree fruit production in cold-winter regions Winter chill accumulation is critical for the productivity and profitability of perennial tree fruit systems. Several studies have quantified the impacts of global warming on chill accumulation in the warmer production regions of the world, where insufficient chill events occur and their frequency is increasing. In contrast, we focus on a region with relatively cold winters-the Pacific Northwest United States (PNW)-where insufficient chill events are currently absent, and quantify the potential for introduction of these risks under climate change. Results identified spatial variation within the PNW, with chill accumulation projected to increase in some areas but decrease in others. There was also spatiotemporal variation in the driving factors of changes to chill accumulation. Even with decreases in chill accumulations, there are likely minimal issues with insufficient chill accumulation. However, delayed chill accumulation in combination with advances in the onset of heat accumulation can potentially shift the region from one where spring phenology is primarily forcing-driven to one where the dynamic interplay between chilling and forcing processes become important. These interactions might create production risks for varieties with high chill requirements, post mid-21st-century under high emissions scenarios. Future work should focus on understanding, modeling, and projecting responses across these overlapping chilling and forcing processes. Additionally, given significant spatial differences across a relatively small geographic range, it is also critical to understand and model these dynamics at a local landscape resolution for regions such as the PNW. A Hierarchy of Biomolecular Proportional-Integral-Derivative Feedback Controllers for Robust Perfect Adaptation and Dynamic Performance Proportional-Integral-Derivative (PID) feedback controllers have been the most widely used controllers in industry for almost a century due to their good performance, simplicity, and ease of tuning. Motivated by their success in various engineering disciplines, PID controllers recently found their way into synthetic biology, where the design of feedback molecular control systems has been identified as an important goal. In this paper, we consider the mathematical realization of PID controllers via biomolecular interactions. We propose an array of topologies that offer a compromise between simplicity and high performance. We first demonstrate that different Proportional-Integral (PI) controllers exhibit different capabilities for enhancing the dynamics and reducing variance (cell-to-cell variability). Next, we introduce several derivative controllers that are realized based on incoherent feedforward loops acting in a feedback configuration. Alternatively, we show that differentiators can be realized by placing molecular integrators in a negative feedback loop--an arrangement that can then be augmented by PI components to yield PID feedback controllers. We demonstrate that the derivative component can be exploited for enhancing system stability, dramatically increasing the molecular control systems dynamic performance, and for reducing the noise effect on the output of interest. The PID controller features are established through various deterministic and stochastic analyses as well as numerical simulations. Finally, we provide an experimental demonstration using a recently developed hybrid setup, the cyberloop, where the controller is implemented in silico to control a biological genetic circuit in vivo. The large array of novel biomolecular PID controllers introduced here forms a basis for the design and construction of advanced high-performance biomolecular control systems that robustly regulate the dynamics of living systems. Estimating the fundamental niche: accounting for the uneven availability of existing environmental conditions in the calibration area Studies that question important conceptual and methodological aspects of the field of ecological niche modeling (and species distribution modeling) have cast doubts on whether it is possible to estimate the fundamental niche of a species using presence-only data. The main limitation in niche estimation is that presence data come from the realized niche, which is only a subset of the fundamental niche. Most of the existing methods lack the ability to overcome this limitation and therefore fit niches that resemble the realized niche. To obtain a more accurate estimate of the fundamental niche, we propose using the geographic region that is accessible to a species (based on its dispersal ability) to determine a sampling distribution, in environmental space, from which we can quantify the likelihood of observing a particular environmental combination in a sample of presence points. We incorporate this sampling distribution into a multivariate normal model (i.e., a Mahalanobis distance model) by creating a weight function that modifies the probabilities of observing different environmental combinations in a sample of presences. This modification accounts for the uneven availability of environmental conditions. We show that the parameters of this weighted-normal model can be approximated with a maximum likelihood estimation approach; and then used to draw ellipsoids (confidence regions) that represent the fundamental niche of the species. We illustrate the application of our model with two worked examples. First, we use presence data for an invasive species and an accessible area that includes only its native range to evaluate whether the fitted model predicts confirmed establishments of the species outside its native range. Second, we use presence data for closely related species with known accessible areas to demonstrate how the different dispersal abilities of the species constrain a classic Mahalanobis distance model. Overall, we show that accounting for the distribution of environmental conditions that are accessible to a species indeed affects the estimation of the ellipsoids used to model its fundamental niche. Fatal COVID-19 and non-COVID-19 Acute Respiratory Distress Syndrome is Associated with Incomplete Alveolar Type 1 Epithelial Cell Differentiation from the Transitional State Without Fibrosis ARDS due to COVID-19 and other etiologies results from injury to the alveolar epithelial cell (AEC) barrier resulting in noncardiogenic pulmonary edema, which causes acute respiratory failure; clinical recovery requires epithelial regeneration. During physiologic regeneration in mice, AEC2s proliferate, exit the cell cycle, and transiently assume a transitional state before differentiating into AEC1s; persistence of the transitional state is associated with pulmonary fibrosis in humans. It is unknown whether transitional cells emerge and differentiate into AEC1s without fibrosis in human ARDS and why transitional cells differentiate into AEC1s during physiologic regeneration but persist in fibrosis. We hypothesized that incomplete but ongoing AEC1 differentiation from transitional cells without fibrosis may underlie persistent barrier permeability and fatal acute respiratory failure in ARDS. Immunostaining of postmortem ARDS lungs revealed abundant transitional cells in organized monolayers on alveolar septa without fibrosis. They were typically cuboidal or partially spread, sometimes flat, and occasionally expressed AEC1 markers. Immunostaining and/or interrogation of scRNAseq datasets revealed that transitional cells in mouse models of physiologic regeneration, ARDS, and fibrosis express markers of cell cycle exit but only in fibrosis express a specific senescence marker. Thus, in severe, fatal early ARDS, AEC1 differentiation from transitional cells is incomplete, underlying persistent barrier permeability and respiratory failure, but ongoing without fibrosis; senescence of transitional cells may be associated with pulmonary fibrosis. Designer Scaffolds for Interfacial Bioengineering In regenerative medicine, the healing of the interfacial zone between tissues is a major challenge, yet approaches for studying the complex microenvironment of this interface remain lacking. Here, we study these complex living interfaces by manufacturing modular "blocks" of naturally porous decellularized plant-derived scaffolds of varying shapes and sizes with a computer numerical controlled mill. We demonstrate how each scaffold can be seeded with different cell types and easily assembled in a manner akin to LEGO bricks to create an engineered tissue interface (ETI). Cells were observed to migrate across the interface formed between an empty scaffold and a scaffold pre-seeded with cells. However, when both scaffolds contained cells, only a shallow cross-over zone of cell infiltration formed at the interface. As a proof-of-concept study, we utilized ETIs to investigate the interaction between lab grown bone and connective tissues. Consistent with the above, a cross-over zone of the two distinct cell types formed at the interface between scaffolds, otherwise the populations remained distinct. Finally, we demonstrate how ETIs are biocompatible in vivo, becoming vascularized and integrated into surrounding tissue after implantation. This work creates new tissue design avenues for understanding biological processes or the development of synthetic artificial tissues. 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. Mechanical bistability of the mesoderm epithelium facilitates mesoderm invagination during Drosophila gastrulation Apical constriction driven by non-muscle myosin II ("myosin") provides a well-conserved mechanism to mediate epithelial folding. It remains unclear how contractile forces near the apical surface of a cell sheet drive out-of-the-plane bending of the sheet and whether myosin contractility is required throughout folding. By optogenetic-mediated acute inhibition of myosin, we find that during Drosophila mesoderm invagination, myosin contractility is critical to prevent tissue relaxation during the early, "priming" stage of folding but is dispensable for the actual folding step after the tissue passes through a stereotyped transitional configuration. The binary response suggests that the mesoderm is mechanically bistable during gastrulation. Combined modeling analysis and experimental measurements suggest that the observed mechanical bistability may arise from apicobasal shrinkage of the surrounding ectoderm, which promotes mesoderm invagination by facilitating a buckling transition. Our results suggest that Drosophila mesoderm invagination requires a joint action of local myosin contractility and mechanical bistability of the epithelium to trigger epithelial buckling. XAV-19, a swine glyco-humanized polyclonal antibody against SARS-CoV-2 Spike receptor-binding domain, targets multiple epitopes and broadly neutralizes variants. Amino acid substitutions and deletions in Spike protein of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants can reduce the effectiveness of monoclonal antibodies (mAbs). In contrast, heterologous polyclonal antibodies raised against S protein, through the recognition of multiple target epitopes, have the potential to maintain neutralization capacities. XAV-19 is a swine glyco-humanized polyclonal neutralizing antibody raised against the receptor binding domain (RBD) of the Wuhan-Hu-1 Spike protein of SARS-CoV-2. XAV-19 target epitopes were found distributed all over the RBD and particularly cover the receptor binding motives (RBM), in direct contact sites with the Angiotensin Converting Enzyme-2 (ACE-2). Therefore, in Spike/ACE2 interaction assays, XAV-19 showed potent neutralization capacities of the original Wuhan Spike and of the United Kingdom (Alpha/B.1.1.7) and South African (Beta/B.1.351) variants. These results were confirmed by cytopathogenic assays using Vero E6 and live virus variants including the Brazil (Gamma/P.1) and the Indian (Delta/B.1.617.2) variants. In a selective pressure study with the Beta strain on Vero E6 cells conducted over 1 month, no mutation was associated with addition of increasing doses XAV-19. The potential to reduce viral load in lungs was confirmed in a human ACE2 transduced mouse model. XAV-19 is currently evaluated in patients hospitalized for COVID-19-induced moderate pneumonia in a phase 2a-2b (NCT04453384) where safety was already demonstrated and in an ongoing 2/3 trial (NCT04928430) to evaluate the efficacy and safety of XAV-19 in patients with moderate-to-severe COVID-19. Owing to its polyclonal nature and its glyco-humanization, XAV-19 may provide a novel safe and effective therapeutic tool to mitigate the severity of coronavirus disease 2019 (Covid-19) including the different variants of concern identified so far. A generic hidden Markov model for multi-parent populations A common step in the analysis of multi-parent populations is genotype reconstruction: identifying the founder origin of haplotypes from dense marker data. This process often makes use of a probability model for the pattern of founder alleles along chromosomes, including the relative frequency of founder alleles and the probability of exchanges among them, which depend on a model for meiotic recombination and on the mating design for the population. While the precise experimental design used to generate the population may be used to derive a precise characterization of the model for exchanges among founder alleles, this can be tedious, particularly given the great variety of experimental designs that have been proposed. We describe an approximate model that can be applied for a variety of multi-parent populations. We have implemented the approach in the R/qtl2 software, and we illustrate its use in applications to publicly-available data on Diversity Outbred and Collaborative Cross mice If Research is Not the Evidence, What is it? The Lack of Research Citations in Health Vlogs Doctor-influencers have the knowledge needed to understand scientific research, and they have the social media popularity to share it with large audiences. In this article, I explore the treatment of evidence in vlogs by Egyptian doctor-influencers: how they present it and what they use instead of it. I answer the following questions: 1) How do doctor-influencers present evidence on social media? 2) If evidence is not the research, then what is it? The data was collected through in-depth interviews with 12 Egyptian doctor-influencers from different specializations; two focus groups; and a critical discourse analysis of 48 of the influencers most popular and most engaging videos. I found that the doctor-influencers cited academic research only in the videos about medical controversies, new treatments, misinformation, or common medical mistakes. In most of their videos, the Egyptian doctor-influencers scarcely referred to medical research. This is because they believe that their audiences would not understand evidence due to their low educational attainment, weak research skills, and the language barrier (as most medical research is published in English rather than Arabic). These findings highlight the challenges of communicating science in societies with a low level of education. In these settings, communicators may need to move beyond mediating research studies on social media and instead focus on simplifying, translating, and connecting evidence-based information to the cultural context. LabGym: quantification of user-defined animal behaviors using learning-based holistic assessment Quantifying animal behavior is important for many branches of biological research. Current computational tools for quantifying behaviors typically rely on a few pre-defined, simplified features to identify a behavior. However, such an approach underuses the behavioral information and restricts the tools applicability to limited behavior types or animal species. Here we report a new tool, LabGym, for quantifying animal behaviors without such limitations. Combining a novel approach for effective evaluation of animal motion with customizable convolutional recurrent networks for capturing spatiotemporal details, LabGym provides holistic behavioral assessment and accurately identify user-defined animal behaviors without restrictions on behavior types or animal species. It then calculates various parameters to provide quantitative measurements of the intensity and dynamics of each behavior. LabGym requires neither any intermediate step that causes information loss nor programming knowledge from users for post-hoc analysis. It tracks multiple animals simultaneously in various experimental settings for high-throughput and versatile analysis, and provides users a way to generate visualizable behavioral datasets that are valuable resources for research in neuroscience, behavioral science, and computer science. We demonstrate its efficacy in capturing subtle behavioral changes in animals ranging from soft-bodied invertebrates to mammals. Detection of ancestry-derived variants of modern Japanese revealed the formation process of regional gradations of the current Japanese archipelago population Modern Japanese have two major ancestral populations: the indigenous Jomon people and continental immigrants. To figure out the formation process of current Japanese population, we developed a reference-free detection method of variants derived from ancestral populations using a summary statistic, the ancestry-marker index (AMI), and identified 208,648 SNPs that appear to have been derived from the Jomon people (Jomon-derived variants). The analysis of Jomon-derived variants in 10,842 modern Japanese individuals recruited from all over Japan revealed that the admixture proportions of the Jomon people varied between prefectures. The estimated allele frequencies of genome-wide SNPs in the ancestral populations of modern Japanese suggested their phenotypic characteristics possibly for adaptation to their respective livelihoods. According to our findings, we propose a formation model of modern Japanese population; regional variations in admixture proportions of the Jomon people and continental East Asians formed genotypic and phenotypic gradations of current Japanese archipelago populations. Benchmarking of deep learning algorithms for 3D instance segmentation of confocal image datasets Segmenting three dimensional microscopy images is essential for understanding phenomena like morphogenesis, cell division, cellular growth and genetic expression patterns. Recently, deep learning (DL) pipelines have been developed which claim to provide high accuracy segmentation of cellular images and are increasingly considered as the state-of-the-art for image segmentation problems. However, it remains difficult to define their relative performances as the concurrent diversity and lack of uniform evaluation strategies makes it difficult to know how their results compare. In this paper, we first made an inventory of the available DL methods for 3 dimensional (3D) cell segmentation. We next implemented and quantitatively compared a number of representative DL pipelines, alongside a highly efficient non-DL method named MARS. The DL methods were trained on a common dataset of 3D cellular confocal microscopy images. Their segmentation accuracies were also tested in the presence of different image artifacts. A specific method for segmentation quality evaluation was adopted which isolates segmentation errors due to under/over segmentation. This is complemented with a 3D visualization strategy for interactive exploration of segmentation quality. Our analysis shows that the DL pipelines have different levels of accuracy. Two of them, which are end to end 3D and were originally designed for cell boundary detection, show high performance, and offer clear advantages in terms of adaptability to new data.

Author summaryIn recent years a number of deep learning (DL) algorithms based on computational neural networks have been developed which claim to achieve high accuracy and automatic segmentation of 3D microscopy images. Although these algorithms have received considerable attention in the literature, it is difficult to evaluate their relative performances, while it remains unclear whether they really perform better than other, more classical segmentation methods.

To clarify these issues, we performed a detailed, quantitative analysis of a number of representative DL pipelines for cell instance segmentation from 3D confocal microscopy image datasets. We developed a protocol for benchmarking the performances of such DL based segmentation pipelines using common training and test datasets, evaluation metrics and visualizations. Using this protocol, we evaluated and compared four different DL pipelines to identify their strengths and limitations. A high performance non-DL method was also included in the evaluation. We show that DL pipelines may show significant differences in their performances depending on their model architecture and pipeline components but overall show excellent adaptability to unseen data. We also show that our benchmarking protocol could be extended to a variety of segmentation pipelines and datasets. Comparative analysis of cattle breeds as satellite cell donors for cultured beef BackgroundCultured meat is a promising new field with the potential for considerable environmental and animal welfare benefits. One technological approach to cultured meat production utilises the proliferative and differentiative capacity of muscle-derived satellite cells (SCs) to produce large volumes of cultured muscle tissue from small biopsies of donor animals. Differing genotypes between cattle breeds lead to predictable phenotypic traits, resulting in breeds being favoured for their respective meat or milk production characteristics in the livestock industry. However, whilst these breeds show significant differences in muscle growth, it is unclear whether the physiological differences observed between them in vivo are reflected in differences in SC behaviour in vitro, particularly with respect to proliferation, differentiation and cellular longevity, and hence whether particular breeds might represent preferred SC donors for a cultured beef bioprocess.

ResultsComparing SCs isolated from five breeds (Belgian Blue, Holstein Friesian, Galloway, Limousin and Simmental), we found that the proliferation rates were largely unaffected by the donor breed. In contrast, potentially meaningful differences were observed in the kinetics and extent of myogenic differentiation. Furthermore, whilst differentiation dropped for all breeds with increasing population doublings (PDs), SCs from Belgian Blue and Limousin cattle showed significantly longer retention of differentiation capacity over long-term passaging.

ConclusionSCs from all breeds were able to proliferate and differentiate, although Limousin and (particularly) Belgian Blue cattle, both breeds commonly used for traditional meat production, may represent preferred donors for cultured beef production. OncoLoop: A network-based precision cancer medicine framework At present, prioritizing cancer treatments at the individual patient level remains challenging, and performing co-clinical studies using patient-derived models in real-time is often not feasible. To circumvent these challenges, we introduce OncoLoop, a precision medicine framework to predict and validate drug sensitivity in human tumors and their pre-existing high-fidelity (cognate) model(s) by leveraging perturbational profiles of clinically-relevant oncology drugs. As proof-of-concept, we applied OncoLoop to prostate cancer (PCa) using a series of genetically-engineered mouse models (GEMMs) that recapitulate a broad spectrum of disease states, including castration-resistant, metastatic, and neuroendocrine prostate cancer. Interrogation of published cohorts using Master Regulator (MR) conservation analysis revealed that most patients were represented by at least one cognate GEMM-derived tumor (GEMM-DT). Drugs predicted to invert MR activity in patients and their cognate GEMM-DTs were successfully validated, including in two cognate allografts and one cognate patient-derived xenograft (PDX). OncoLoop is a highly generalizable framework that can be extended to other cancers and potentially other diseases.

Significance StatementOncoLoop is a transcriptomic-based experimental and computational framework that can support rapid-turnaround co-clinical studies to identify and validate drugs for individual patients, which can then be readily adapted to clinical practice. This framework should be applicable in many cancer contexts for which appropriate models and drug perturbation data are available. Chimeric spike mRNA vaccines protect against Sarbecovirus challenge in mice The emergence of SARS-CoV in 2003 and SARS-CoV-2 in 2019 highlights the need to develop universal vaccination strategies against the broader Sarbecovirus subgenus. Using chimeric spike designs, we demonstrate protection against challenge from SARS-CoV, SARS-CoV-2, SARS-CoV-2 B.1.351, bat CoV (Bt-CoV) RsSHC014, and a heterologous Bt-CoV WIV-1 in vulnerable aged mice. Chimeric spike mRNAs induced high levels of broadly protective neutralizing antibodies against high-risk Sarbecoviruses. In contrast, SARS-CoV-2 mRNA vaccination not only showed a marked reduction in neutralizing titers against heterologous Sarbecoviruses, but SARS-CoV and WIV-1 challenge in mice resulted in breakthrough infection. Chimeric spike mRNA vaccines efficiently neutralized D614G, UK B.1.1.7., mink cluster five, and the South African B.1.351 variant of concern. Thus, multiplexed-chimeric spikes can prevent SARS-like zoonotic coronavirus infections with pandemic potential.

SentenceChimerized RBD, NTD, and S2 spike mRNA-LNPs protect mice against epidemic, zoonotic, and pandemic SARS-like viruses