Human cortical areas are sparsely connected: Combining histology with diffusion MRI to estimate the absolute number of axons The tracts between cortical areas are conceived as playing a central role in cortical information processing, but their actual numbers have never been determined in humans. Here we estimate the absolute number of axons linking cortical areas from a whole-cortex diffusion-MRI (dMRI) connectome, calibrated using the histologically-measured callosal fiber density. Median connectivity is estimated as ~6200 axons between cortical areas within-hemisphere and ~1300 axons inter-hemispherically, with axons connecting functionally-related areas surprisingly sparse. For example, we estimate that <5% of the axons in the trunk of the arcuate and superior longitudinal fasciculi connect Wernickes and Brocas areas. These results suggest that detailed information is transmitted between cortical areas either via linkage of the dense local connections or via rare, extraordinarily privileged long-range connections.
In Vivo Multi-Day Calcium Imaging of CA1 Hippocampus in Freely Moving Rats Reveals a High Preponderance of Place Cells with Consistent Place Fields Calcium imaging using GCaMP indicators and miniature microscopes has been used to image cellular populations during long timescales and in different task phases, as well as to determine neuronal circuit topology and organization. Because the hippocampus (HPC) is essential for tasks of memory, spatial navigation, and learning, calcium imaging of large populations of HPC neurons can provide new insight on cell changes over time during these tasks. All reported HPC in vivo calcium imaging experiments have been done in mouse. However, rats have many behavioral and physiological experimental advantages over mice. In this paper, we present the first (to our knowledge) in vivo calcium imaging from CA1 hippocampus in freely moving male rats. Using the UCLA Miniscope, we demonstrate that, in rat, hundreds of cells can be visualized and held across weeks. We show that calcium events in these cells are highly correlated with periods of movement, with few calcium events occurring during periods without movement. We additionally show that an extremely large percent of cells recorded during a navigational task are place cells (77.3{+/-}5.0%, surpassing the percent seen during mouse calcium imaging), and that these cells enable accurate decoding of animal position and can be held over days with consistent place fields in a consistent spatial map. A detailed protocol is included, and implications of these advancements on in vivo imaging and place field literature are discussed.

Significance statementIn vivo calcium imaging in freely moving animals allows the visualization of cellular activity across days. In this paper, we present the first in vivo Ca2+ recording from CA1 hippocampus in freely moving rats. We demonstrate that hundreds of cells can be visualized and held across weeks, and that calcium activity corresponds to periods of movement. We show that a high percentage (77.3{+/-}5.0%) of imaged cells are place cells, and that these place cells enable accurate decoding and can be held stably over days with little change in field location. Because the hippocampus is essential for many tasks involving memory, navigation, and learning, imaging of large populations of HPC neurons can shed new insight on cellular activity changes and organization.
TeamTree analysis: a new approach to evaluate scientific production Advances in science and technology depend on the work of research teams and the publication of results through peer-reviewed articles representing a growing socio-economic resource. Current methods to mine the scientific literature regarding a field of interest focus on content, but the workforce credited by authorship remains largely unexplored, and appropriate measures of scientific production are debated. Here, a new bibliometric approach named TeamTree analysis is introduced that visualizes the development and composition of the workforce driving a field. A new citation-independent measure that scales with the H index estimates impact based on publication record, genealogical ties and collaborative connections. This author-centered approach complements existing tools to mine the scientific literature and to evaluate research across disciplines. Getting to know each other: PPIMem, a novel approach for predicting transmembrane protein-protein complexes Because of their considerable number and diversity, membrane proteins and their macromolecular complexes represent the functional units of cells. Their quaternary structure may be stabilized by interactions between the -helices of different proteins in the hydrophobic region of the cell membrane. Membrane proteins also represent potential pharmacological targets par excellence for various diseases. Unfortunately, their experimental 3D structure and that of their complexes with intramembrane interacting partners are scarce due to technical difficulties. To overcome this key problem, we devised PPIMem, a computational approach for the specific prediction of higher-order structures of -helical transmembrane proteins. The novel approach involves identification of the amino acid residues at the interface of complexes with a 3D structure. The identified residues compose then interaction motifs that are conveniently expressed as mathematical regular expressions. These are used for motif search in databases, and for the prediction of intramembrane protein-protein complexes. Our template interface-based approach predicted 21, 544 binary complexes between 1, 504 eukaryotic plasma membrane proteins across 39 species. We compared our predictions to experimental datasets of protein-protein interactions as a first validation method. The PPIMem online database with the annotated predicted interactions is implemented as a web server and can be accessed directly at https://transint.shinyapps.io/transint/. A potent human monoclonal antibody with pan-neutralizing activities directly dislocates S trimer of SARS-CoV-2 through binding both up and down forms of RBD The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused a global pandemic of novel corona virus disease (COVID-19). The neutralizing monoclonal antibodies (mAbs) targeting the receptor binding domain (RBD) of SARS-CoV-2 are among the most promising strategies to prevent and treat COVID-19. However, SARS-CoV-2 variants of concern (VOCs) profoundly reduced the efficacies of most of mAbs and vaccines approved for clinical use. Herein, we demonstrated mAb 35B5 efficiently neutralizes both wild-type (WT) SARS-CoV-2 and VOCs, including B.1.617.2 (delta) variant, in vitro and in vivo. Cryo-electron microscopy (cryo-EM) revealed that 35B5 neutralizes SARS-CoV-2 by targeting a unique epitope that avoids the prevailing mutation sites on RBD identified in circulating VOCs, providing the molecular basis for its pan-neutralizing efficacy. The 35B5-binding epitope could also be exploited for the rational design of a universal SARS-CoV-2 vaccine. 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. Accuracy and Power Analysis of Social Networks Built From Count Data O_LIPower analysis is used to estimate the probability of correctly rejecting a null hypothesis for a given statistical model and dataset. Conventional power analyses assume complete information, but the stochastic nature of behavioural sampling can mean that true and estimated networks are poorly correlated. Power analyses do not currently take the effect of sampling into account. This could lead to inaccurate estimates of statistical power, potentially yielding misleading results.
C_LIO_LIHere we develop a method for computing network correlation: the correlation between an estimated social network and its true network, using a Gamma-Poisson model of social event rates for networks constructed from count data. We use simulations to assess how the level of network correlation affects the power of nodal regression analyses. We also develop a generic method of power analysis applicable to any statistical test, based on the concept of diminishing returns.
C_LIO_LIWe demonstrate that our network correlation estimator is both accurate and moderately robust to its assumptions being broken. We show that social differentiation, mean social event rate, and the harmonic mean of sampling times positively impacts the strength of network correlation. We also show that the required level of network correlation to achieve a given power level depends on many factors, but that 0.80 network correlation usually corresponds to around 0.80 power for nodal regression in ideal circumstances.
C_LIO_LIWe provide guidelines for using our network correlation estimator to verify the accuracy of networks built from count data, and to conduct power analysis. This can be used prior to data collection, in post hoc analyses, or even for subsetting networks in dynamic network analysis. The network correlation estimator and custom power analysis methods have been made available as an R package.
C_LI 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. A small molecule antagonizes jasmonic acid perception and auxin responses in vascular and nonvascular plants The phytohormone JA-Ile regulates many stress responses and developmental processes in plants. A co-receptor complex formed by the F-box protein COI1 (Coronatine Insensitive 1) and a JAZ (Jasmonate ZIM-domain) repressor perceives the hormone. JA-Ile antagonists are invaluable tools for exploring the role of JA-Ile in specific tissues and developmental stages, and for identifying regulatory processes of the signalling pathway. Using two complementary chemical screens, we identified three compounds that exhibit a robust inhibitory effect on both the hormone-mediated COI-JAZ interaction and degradation of JAZ1 and JAZ9 in vivo. One molecule, J4, also restrains specific JA-induced physiological responses in different angiosperm plants, including JA-mediated gene expression, growth inhibition, chlorophyll degradation and anthocyanin accumulation. Interaction experiments with purified proteins indicate that J4 directly interferes with the formation of the Arabidopsis (Arabidopsis thaliana) COI1-JAZ complex otherwise induced by JA. The antagonistic effect of J4 on COI1- JAZ also occurs in the liverwort Marchantia polymorpha, suggesting the mode of action is conserved in land plants. Besides JA signalling, J4 works as an antagonist of the closely-related auxin signalling pathway, preventing TIR1/Aux-IAA interaction and auxin responses in planta, including hormone-mediated degradation of an auxin repressor, gene expression and gravitropic response. However, J4 does not affect other hormonal pathways. Altogether, our results show that this dual antagonist competes with JA-Ile and auxin, preventing the formation of phylogenetically related receptor complexes. J4 may be a useful tool to dissect both the JA-Ile and auxin pathways in particular tissues and developmental stages since it reversibly inhibits these pathways.

One sentence summaryA chemical screen identified a molecule that antagonizes jasmonate perception by directly interfering with receptor complex formation in phylogenetically distant vascular and non-vascular plants. Fixed or random? On the reliability of mixed-effects models for a small number of levels in grouping variables O_LIBiological data are often intrinsically hierarchical. Due to their ability to account for such dependencies, mixed-effects models have become a common analysis technique in ecology and evolution. While many questions around their theoretical foundations and practical applications are solved, one fundamental question is still highly debated: When facing a low number of levels should we model a grouping (blocking, clustering) variable as a random or fixed effect? In such situation, the variance of the random effect is imprecise, but whether this affects the statistical properties of the population effect is unclear.
C_LIO_LIHere, we analyzed the consequences of including a grouping variable as fixed or random effect in the correctly specified and other possible miss-specified models (too simple or too complex models) for data with small number of levels (2 - 8). For all these options, we calculated type I error rates and power. Moreover, we show how these statistical properties change with the study design.
C_LIO_LIWe found that the model choice does not influence the statistical properties of the population effect when the effect is the same at all levels However, if an ecological effect differs among levels, using a random slope and intercept model, and switching to a fixed-effect model only in case of a singular fit, avoids overconfidence in the results. Additionally, power and type I error are strongly influenced by the number of and difference between levels.
C_LIO_LIWe conclude that inferring the correct random effect structure is of high importance to get correct statistical properties. When in doubt, we recommend starting with the simpler model and using model diagnostics to identify missing components. When having identified the correct structure, we encourage to start with a mixed-effects model independent of the number of levels and switch to a fixed-effect model only in case of a singular fit. With these recommendations, we allow for more informative choices about study design and data analysis and thus make ecological inference with mixed-effects models more robust for small number of levels.
C_LI Modeling miRNA-driven post-transcriptional regulatory signals by using exon-intron split analysis (EISA) in pigs The contribution of microRNAs (miRNAs) to mRNA regulation has often been explored by post hoc selection of downregulated genes and determining whether they harbor binding sites for miRNAs of interest. This approach, however, does not discriminate whether these mRNAs are also downregulated at the transcriptional level. Here, we have characterized the transcriptional and post-transcriptional changes of mRNA expression in two porcine tissues: gluteus medius muscle of fasted and fed Duroc gilts and adipose tissue of lean and obese Duroc-Gottingen minipigs. Exon-intron split analysis (EISA) of RNA-seq data allowed us to identify downregulated mRNAs with high post-transcriptional signals in fed or obese states, and we assessed whether they harbor binding sites for upregulated miRNAs in any of these two physiological states. We found 26 downregulated mRNAs with high post-transcriptional signals in the muscle of fed gilts and 21 of these were predicted targets of upregulated miRNAs also in the fed state. For adipose tissue, 44 downregulated mRNAs in obese minipigs displayed high post-transcriptional signals, and 25 of these were predicted targets of miRNAs upregulated in the obese state. These results suggest that the contribution of miRNAs to mRNA repression is more prominent in the skeletal muscle system. Finally, we identified several genes that may play relevant roles in the energy homeostasis of the pig skeletal muscle (DKK2 and PDK4) and adipose (SESN3 and ESRRG) tissues. By differentiating transcriptional from post-transcriptional changes in mRNA expression, EISA provides a valuable view about the regulation of gene expression, complementary to canonical differential expression analyses. Crowdsourced identification of multi-target kinase inhibitors for RET- and TAU- based disease: the Multi-Targeting Drug DREAM Challenge A continuing challenge in modern medicine is the identification of safer and more efficacious drugs. Precision therapeutics, which have one molecular target, have been long promised to be safer and more effective than traditional therapies. This approach has proven to be challenging for multiple reasons including lack of efficacy, rapidly acquired drug resistance, and narrow patient eligibility criteria. An alternative approach is the development of drugs that address the overall disease network by targeting multiple biological targets ( polypharmacology). Rational development of these molecules will require improved methods for predicting single chemical structures that target multiple drug targets. To address this need, we developed the Multi-Targeting Drug DREAM Challenge, in which we challenged participants to predict single chemical entities that target pro-targets but avoid anti-targets for two unrelated diseases: RET-based tumors and a common form of inherited Tauopathy. Here, we report the results of this DREAM Challenge and the development of two neural network-based machine learning approaches that were applied to the challenge of rational polypharmacology. Together, these platforms provide a potentially useful first step towards developing lead therapeutic compounds that address disease complexity through rational polypharmacology.

Author SummaryMany modern drugs are developed with the goal of modulating a single cellular pathway or target. However, many drugs are, in fact,  dirty; they target multiple cellular pathways or targets. This phenomenon is known as multi-targeting or polypharmacology. While some strive to develop  cleaner therapeutics that eliminate secondary targets, recent work has shown that multi-targeting therapeutics have key advantages for a variety of diseases. However, while multi-targeting drugs that affect a precisely-defined profile of targets may be more effective, it is difficult to computationally predict which molecules have desirable target profiles. Here, we report the results of a competitive crowdsourcing project (the Multi-Targeting Drug DREAM Challenge), where we challenged participants to predict chemicals that have desired target profiles for cancer and neurodegenerative disease. Cellular-level phenotyping of tumor-immune microenvironment (TiME) in patients in vivo reveals distinct inflammation and endothelial anergy signatures Immunotherapies have shown unprecedented clinical benefits in several malignancies1-3. However, clinical responses remain variable and unpredictable, indicating the need to develop predictive platforms that can improve patient stratification4. Phenotyping of tumors into hot, altered, or cold5 based on assessment of only T-cell infiltration in static tumor biopsies provides suboptimal prediction of immunotherapy response6,7. In vivo dynamic mechanisms within the tumor microenvironment such as tumor angiogenesis and leukocyte trafficking5,8,9 also play a central role in modulating anti-tumor immunity and therefore immunotherapy response. Here, we report novel tumor immune microenvironment (TiME) phenotyping in vivo in patients with non-invasive spatially-resolved cellular-level imaging based on endogenous contrast. Investigating skin cancers as a model, with reflectance confocal microscopy (RCM) imaging10, we determined four major phenotypes with variable prevalence of vasculature (Vasc) and inflammation (Inf) features: VaschiInfhi, VaschiInflo, VascloInfhi and Vascmed/hiInflo. The VaschiInfhi phenotype correlates with high immune activation, exhaustion, and vascular signatures while VaschiInflo with endothelial anergy and immune exclusion. Automated quantification of TiME features demonstrates moderate-high accuracy and correlation with corresponding gene expression. Prospectively analyzed response to topical immunotherapy show highest response in VascloInfhi, and reveals the added value of vascular features in predicting treatment response. Our novel in vivo cellular-level imaging and phenotyping approach can potentially advance our fundamental understanding of TiME, develop robust predictors for immunotherapy outcomes and identify novel targetable pathways in future. A Eukaryotic Circuit for Secretion-coupled Cellular Autonomy Cancers represent complex autonomous robust systems, displaying interconnectivity with feedback control. Autonomous growth is fueled by a cancer cells ability to  secrete-and-sense growth factors: a poorly understood phenomenon. Using an integrated systems and experimental approach, here we dissect the impact of a feedback-coupled GTPase circuit within the secretory pathway that imparts secretion-coupled autonomy. The circuit is assembled when the Ras-superfamily monomeric GTPase Arf1, and the heterotrimeric GTPase Giabg and their corresponding GAPs and GEFs are coupled by GIV/Girdin, a protein that is known to fuel aggressive traits in diverse cancers. One forward and two key negative feedback loops within the circuit create closed-loop control (CLC), allow the two GTPases to coregulate each other, and convert the expected switch-like behavior of Arf1-dependent secretion into an unexpected dose response alignment behavior of sensing and secretion. Such behavior translates into cell survival that is self-sustained by stimuli-proportionate secretion. Findings highlight how enhanced coupling of two biological switches in cancer cells is critical for multiscale feedback control to achieve secretion-coupled autonomy.

GRAPHIC ABSTRACT

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org.highwire.dtl.DTLVardef@183ff5corg.highwire.dtl.DTLVardef@f21de7org.highwire.dtl.DTLVardef@1893683org.highwire.dtl.DTLVardef@159d966_HPS_FORMAT_FIGEXP  M_FIG C_FIG In BriefThis work delivers an experimentally validated dynamical systems model of the cooperativity between two distinct classes of biological switches in eukaryotic cells and reveals the basis of secretion-coupled cellular autonomy in cancer.

HIGHLIGHTSO_LIModeling and experimental approaches were used to dissect a coupled GTPase circuit
C_LIO_LICoupling enables closed loop feedback and mutual control of GTPases
C_LIO_LICoupling generates dose response alignment behavior of sensing and secretion.
C_LIO_LICoupling is critical for multiscale feedback control to achieve secretion-coupled autonomy.
C_LI 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. An Evolutionary Process Without Variation and Selection Natural selection successfully explains how organisms accumulate adaptive change despite that traits acquired over a lifetime are eliminated at the end of each generation. However, in some domains that exhibit cumulative, adaptive change--e.g., cultural evolution, and earliest life--acquired traits are retained; these domains do not face the problem that Darwins theory was designed to solve. Lack of transmission of acquired traits occurs when germ cells are protected from environmental change, due to a self-assembly code used in two distinct ways: (i) actively interpreted during development to generate a soma, and (ii) passively copied without interpretation during reproduction to generate germ cells. Early life and cultural evolution appear not to involve a self-assembly code used in these two ways. We suggest that cumulative, adaptive change in these domains is due to a lower-fidelity evolutionary process, and model it using Reflexively Autocatalytic and Foodset-generated networks. We refer to this more primitive evolutionary process as Self-Other Reorganisation (SOR) because it involves internal self-organising and self-maintaining processes within entities, as well as interaction between entities. SOR encompasses learning but in general operates across groups. We discuss the relationship between SOR and Lamarckism, and illustrate a special case of SOR without variation. The Consequences of Differential Origin Licensing Dynamics in Distinct Chromatin Environments MCM complexes are loaded onto chromosomes to license DNA replication origins in G1 phase of the cell cycle, but it is not yet known how mammalian MCM complexes are adequately distributed to both euchromatin and heterochromatin. To address this question, we combined time-lapse live-cell imaging with fixed cell immunofluorescence imaging of single human cells to quantify the relative rates of MCM loading in heterochromatin and euchromatin at different times within G1. We report here that MCM loading in euchromatin is faster than in heterochromatin in very early G1, but surprisingly, heterochromatin loading accelerates relative to euchromatin loading in middle and late G1. These different loading dynamics require ORCA-dependent differences in ORC distribution during G1. A consequence of heterochromatin origin licensing dynamics is that cells experiencing a truncated G1 phase from premature cyclin E expression enter S phase with under-licensed heterochromatin, and DNA damage accumulates preferentially in heterochromatin in the subsequent S/G2 phase. Thus G1 length is critical for sufficient MCM loading, particularly in heterochromatin, to ensure complete genome duplication and to maintain genome stability. wnt16 exerts pleiotropic effects on bone and lean mass in zebrafish Osteoporosis, a disease of bone fragility, and sarcopenia, a condition of reduced muscle mass and strength, commonly occur in the same individual--a condition termed osteosarcopenia. Genetic variants at the CPED1-WNT16 locus have pleiotropic effects on human bone mineral density (BMD) and lean tissue mass. However, our current understanding of Wnt16 and its influence on bone fails to explain effects on lean mass at this locus. In this study, we sought to better understand the biological mechanism underlying pleiotropy at the CPED1-WNT16 locus on BMD and lean mass. Using single cell analysis, microCT imaging, and genetic approaches in zebrafish, we show that wnt16 exerts dual influence on muscle and bone, and provide evidence that this occurs through a function in somite development, a period in which precursors for both of these tissues are specified. We show that mutations in wnt16 alter vertebral size and lean mass during axial skeletogenesis. We show that wnt16+ cells transcriptionally resemble cells within the amniote dermomyotome, and provide evidence they function as myogenic precursors during embryonic development. We also provide evidence that WNT16 is a gene of major effect on lean mass at the CPED-WNT16 locus. Our studies support the potential for wnt16 to exert pleiotropic effects on bone and lean mass through a function in myogenic precursors. Discovery of pan-ErbB inhibitors protecting from SARS-CoV-2 replication, inflammation, and lung injury by a drug repurposing screen Effective therapies are needed to combat emerging viruses. Seventeen candidates that rescue cells from SARS-CoV-2-induced lethality and target diverse functions emerged in a screen of 4,413 compounds. Among the hits was lapatinib, an approved inhibitor of the ErbB family of receptor tyrosine kinases. Lapatinib and other pan-ErbB inhibitors suppress replication of SARS-CoV-2 and unrelated viruses with a high barrier to resistance. ErbB4, but not lapatinibs cancer targets ErbB1 and ErbB2, is required for SARS-CoV-2 entry and encephalitis alphavirus infection and is a molecular target mediating lapatinibs antiviral effect. In human lung organoids, lapatinib protects from SARS-CoV-2-induced activation of pathways implicated in non-infectious acute lung injury and fibrosis downstream of ErbBs (p38-MAPK, MEK/ERK, and AKT/mTOR), pro-inflammatory cytokine production, and epithelial barrier injury. These findings reveal regulation of viral infection, inflammation, and lung injury via ErbBs and propose approved candidates to counteract these effects with implications for pandemic coronaviruses and unrelated viruses. Microbial colonization of tannin-rich tropical plants: interplay between degradability, methane production and tannin disappearance in the rumen AO_SCPLOWBSTRACTC_SCPLOWCondensed tannins in plants are found free and attached to protein and fibre but it is not known whether these fractions influence rumen degradation and microbial colonization. This study explored the rumen degradation of tropical tannins-rich plants and the relationship between condensed tannins fractions disappearance and microbial communities colonising plant particles. Leaves from Calliandra calothyrsus, Gliricidia sepium, and Leucaena leucocephala, pods from Acacia nilotica and the leaves of two agricultural by-products: Manihot esculenta and Musa spp. were incubated in situ in the rumen of dairy cows. An in vitro approach was also used to assess the effects of these plants on rumen fermentation parameters. All plants contained more than 100 g/kg of condensed tannins with a large proportion (32 to 61%) bound to proteins. Calliandra calothyrsus had the highest concentration of condensed tannins at 361 g/kg, whereas Acacia nilotica was particularly rich in hydrolysable tannins (350 g/kg). Hydrolysable and free condensed tannins from all plants completely disappeared after 24 h incubation in the rumen. Disappearance of protein-bound condensed tannins was variable with values ranging from 93% for Gliricidia sepium to 21% for Acacia nilotica. In contrast, fibre-bound condensed tannins disappearance averaged ~82% and did not vary between plants. Disappearance of bound fractions of condensed tannins was not associated with degradability of plant fractions. The presence of tannins interfered with the microbial colonisation of plants. Each plant had distinct bacterial and archaeal communities after 3 and 12 h of incubation in the rumen and distinct protozoal communities at 3 h. Adherent communities in tannin-rich plants had a lower relative abundance of fibrolytic microbes, notably Fibrobacter spp. Whereas, archaea diversity was reduced in high tannin-containing Calliandra calothyrsus and Acacia nilotica at 12 h of incubation. Concurrently, in vitro methane production was lower for Calliandra calothyrsus, Acacia nilotica and Leucaena leucocephala although for the latter total volatile fatty acids production was not affected and was similar to control. Here we show that the total amount of hydrolysable and condensed tannins contained in a plant govern the interaction with rumen microbes affecting degradability and fermentation. The effect of protein- and fibre-bound condensed tannins on degradability is less important. Probing the rules of cell coordination in live tissues by interpretable machine learning based on graph neural networks Robustness in developing and homeostatic tissues is supported by various types of spatiotemporal cell-to-cell interactions. Although live imaging and cell tracking are powerful in providing direct evidence of cell coordination rules, extracting and comparing these rules across many tissues with potentially different length and timescales of coordination requires a versatile framework of analysis. Here we demonstrate that graph neural network (GNN) models are suited for this purpose, by showing how they can be applied to predict cell fate in tissues and utilized to infer the cell interactions governing the multicellular dynamics. Analyzing the live mammalian epidermis data, where spatiotemporal graphs constructed from cell tracks and cell contacts are given as inputs, GNN discovers distinct neighbor cell fate coordination rules that depend on the region of the body. This approach demonstrates how the GNN framework is powerful in inferring general cell interaction rules from live data without prior knowledge of the signaling involved. Tracheal tube fusion in Drosophila involves release of extracellular vesicles from multivesicular bodies Extracellular vesicles (EVs) comprise diverse types of cell-released membranous structures that are thought to play important roles in intercellular communication. Despite extensive work on the formation and functions of EVs in cultured cells, studies of EVs in vivo have remained scarce. We report here that EVs are present in the developing lumen of tracheal tubes in Drosophila embryos. We defined two distinct EV subpopulations, one of which contains the Munc13-4 homologue Staccato (Stac) and is spatially and temporally associated with tracheal tube fusion events. The formation of Stac-positive luminal EVs depends on the tip-cell-specific GTPase Arl3, which is also required for the formation of Stac-positive multivesicular bodies, suggesting that Stac-EVs derive from fusion of Stac-MVBs with the luminal membrane in tip cells during anastomosis formation. The GTPases Rab27 and Rab35 cooperate downstream of Arl3 to promote Stac-MVB formation and tube fusion. We propose that Stac-MVBs act as membrane reservoirs that facilitate tracheal lumen fusion in a process regulated by Arl3, Rab27, Rab35, and Stac/Munc13-4. Robust and Remote Measurement of Heart Rate Based on A Surveillance Camera Arrhythmia is a marked symptom of many cardiovascular diseases (CVDs). The accurate and timely detection of heart rate can greatly reduce the harm of arrhythmia to people. However, it is still a challenge to robustly and remotely measure heart rate in daily life due to the changing environmental conditions during measurement, such as the varying light intensity, the movement of people, and the uncertain distance between the sensor to people. In this study, we propose a method to accurately measure human heart rate within a distance of 4.5 meters under different light intensities by simply using a surveillance camera. After a 20-second color video of a persons hand is captured by the camera, a method based on the Fast Fourier Transform (FFT) algorithm is designed to extract the blood volume pulse wave to calculate the heart rate. According to the comparison between the real heart rate and results measured by electrocardiography (ECG), the proposed method achieves an accuracy of 95.8% when the measurement is performed within a distance of 4.5 meters and 90% when within 5.0 meters. Our experiments show that when the illuminance varies between 100-1000 lux (lighting level indoor), we still get the correct results. Our experiments also demonstrate that the proposed method accurately obtain heart rate even when the light intensity is below 32 lux (300-500 lux in a workplace environment). The methods strong adaptability to changing environmental conditions makes it applicable to many scenarios, such as homes of the elderly, classrooms, and other public spaces. Main protease mutants of SARS-CoV-2 variants remain susceptible to nirmatrelvir (PF-07321332) The COVID-19 pandemic continues to be a public health threat. Multiple mutations in the spike protein of emerging variants of SARS-CoV-2 appear to impact on the effectiveness of available vaccines. Specific antiviral agents are keenly anticipated but their efficacy may also be compromised in emerging variants. One of the most attractive coronaviral drug targets is the main protease (Mpro). A promising Mpro inhibitor of clinical relevance is the peptidomimetic nirmatrelvir (PF-07321332). We expressed Mpro of six SARS-CoV-2 lineages (C.37 Lambda, B.1.1.318, B.1.2, B.1.351 Beta, B.1.1.529 Omicron, P.2 Zeta), each of which carries a strongly prevalent missense mutation (G15S, T21I, L89F, K90R, P132H, L205V). Enzyme kinetics showed that these Mpro variants are similarly catalytically competent as the wildtype. We show that nirmatrelvir has similar potency against the variants as against the wildtype. Our in vitro data suggest that the efficacy of the specific Mpro inhibitor nirmatrelvir is not compromised in current COVID-19 variants.

Graphical abstract

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org.highwire.dtl.DTLVardef@182cc6org.highwire.dtl.DTLVardef@1239d10org.highwire.dtl.DTLVardef@11ca6d9org.highwire.dtl.DTLVardef@df53b_HPS_FORMAT_FIGEXP  M_FIG C_FIG TRACT revisited: an algebraic solution for determining overall rotational correlation times from cross-correlated relaxation rates Accurate rotational correlation times ({tau}c) are critical for quantitative analysis of fast timescale NMR dynamics. As molecular weights increase, the classic derivation of{tau} c using transverse and longitudinal relaxation rates becomes increasingly unsuitable due to the non-trivial contribution of remote dipole-dipole interactions to longitudinal relaxation. Derivations using cross-correlated relaxation experiments, such as TRACT, overcome these limitations but are erroneously calculated in 65% of the citing literature. Herein, we developed an algebraic solutions to the Goldman relationship that facilitate rapid, point-by-point calculations for straightforward identification of appropriate spectral regions where global tumbling is likely to be dominant. The rigid-body approximation of the Goldman relationship has been previously shown to underestimate TRACT-based rotational correlation time estimates. This motivated us to develop a second algebraic solution that employs a simplified model-free spectral density function including an order parameter term that could, in principle, be set to an average backbone S2 {approx} 0.9 to further improve the accuracy of{tau} c estimation. These solutions enabled us to explore the boundaries of the Goldman relationship as a function of the H-N internuclear distance (r), difference of the two principal components of the axially-symmetric 15N CSA tensor ({Delta}{delta}N), and angle of the CSA tensor relative to the N-H bond vector ({theta}). We hope our algebraic solutions and analytical strategies will increase the accuracy and application of the TRACT experiment. Differences in gait stability and acceleration characteristics between healthy young and older females Our aim was to evaluate differences in gait acceleration intensity, variability and stability of feet and trunk between older females and young females using inertial sensors. Twenty older females (OF; mean age 68.4, SD 4.1 years) and eighteen young females (YF; mean age 22.3, SD 1.7 years) were asked to walk straight for 100 meters at their preferred speed, while wearing inertial sensors on heels and lower back. We calculated spatiotemporal measures, foot and trunk acceleration characteristics and their variability, as well as trunk stability using the local divergence exponent (LDE). Two-way analysis of variance (including the factors foot and age), Students t-test, and Mann-Whitney U test were used to compare statistical differences of measures between groups. Cohens d effects were calculated for each variable. Foot maximum vertical acceleration and amplitude, trunk-foot vertical acceleration attenuation, as well as their variability were significantly smaller in OF than in YF. In contrast, trunk mediolateral acceleration amplitude, maximum vertical acceleration, and amplitude, as well as their variability were significantly larger in OF than in YF. Moreover, OF showed lower stability (i.e., higher LDE values) in mediolateral acceleration, mediolateral and vertical angular velocity of the trunk. Even though we measured healthy older females, these participants showed lower vertical foot accelerations with higher vertical trunk acceleration, lower trunk-foot vertical acceleration attenuation, less gait stability, and more variability of the trunk, and hence, were more likely to fall. These findings suggest that instrumented gait measurements may help for early detection of changes or impairments in gait performance, even before this can be observed by clinical eye or gait speed.