Structures of the Omicron spike trimer with ACE2 and an anti-Omicron antibody: mechanisms for the high infectivity, immune evasion and antibody drug discovery The Omicron variant of SARS-CoV-2 has rapidly become the dominant infective strain and the focus efforts against the ongoing COVID-19 pandemic. Here we report an extensive set of structures of the Omicron spike trimer by its own or in complex with ACE2 and an anti-Omicron antibody. These structures reveal that most Omicron mutations are located on the surface of the spike protein, which confer stronger ACE2 binding by nearly 10 folds but become inactive epitopes resistant to many therapeutic antibodies. Importantly, both RBD and the closed conformation of the Omicron spike trimer are thermodynamically unstable, with the melting temperature of the Omicron RBD decreased by as much as 7{degrees}C, making the spiker trimer prone to random open conformations. An unusual RBD-RBD interaction in the ACE2-spike complex unique to Omicron is observed to support the open conformation and ACE2 binding, serving the basis for the higher infectivity of Omicron. A broad-spectrum therapeutic antibody JMB2002, which has completed Phase 1 clinical trial, is found to interact with the same two RBDs to inhibit ACE2 binding, in a mode that is distinguished from all previous antibodies, thus providing the structural basis for the potent inhibition of Omicron by this antibody. Together with biochemical data, our structures provide crucial insights into higher infectivity, antibody evasion and inhibition of Omicron.
Uncovering Differences in Hydration Free Energies and Structures for Model Compound Mimics of Charged Sidechains of Amino Acids Free energies of hydration are of fundamental interest for modeling and understanding conformational and phase equilibria of macromolecular solutes in aqueous phases. Of particular relevance to systems such as intrinsically disordered proteins are the free energies of hydration and hydration structures of model compounds that mimic charged sidechains of Arg, Lys, Asp, and Glu. Here, we deploy a Thermodynamic Cycle based Proton Dissociation (TCPD) approach in conjunction with data from direct measurements to obtain estimates for the free energies of hydration for model compounds that mimic the sidechains of Arg+, Lys+, Asp-, and Glu-. Irrespective of the choice made for the hydration free energy of the proton, the TCPD approach reveals clear trends regarding the free energies of hydration for Arg+, Lys+, Asp-, and Glu-. These trends include asymmetries between the hydration free energies of acidic (Asp- and Glu-) and basic (Arg+ and Lys+) residues. Further, the TCPD analysis, which relies on a combination of experimental data, shows that the free energy of hydration of Arg+ is less favorable than that of Lys+. We sought a physical explanation for the TCPD derived trends free energies of hydration. To this end, we performed temperature dependent calculations of free energies of hydration and analyzed hydration structures from simulations that use the polarizable AMOEBA (Atomic Multipole Optimized Energetics for Biomolecular Applications) forcefield and water model. At 298 K, the AMOEBA model generates estimates of free energies of hydration that are consistent with TCPD values with a free energy of hydration for the proton of {approx} -259 kcal / mol. Analysis of temperature dependent simulations leads to a structural explanation for the observed differences in free energies of hydration of ionizable residues and reveals that the heat capacity of hydration is positive for Arg+ and Lys+ and negative for Asp- and Glu-.
Stress alters the activity of Leydig cells dependently on the diurnal time BackgroundThe increasing amount of data points to the circadian timing system as an essential part of processes regulating androgen homeostasis. However, the relationship between stress response, timekeeping-, and steroidogenesis-related systems is unexplored.

ObjectiveThe purpose of the study was to analyze the stress-response of the testosterone-producing Leydig cells depending on the stressful events time.

Materials and methodsThe study was designed to follow the effects of 3-hour immobilization (IMO) applied at different periods during the day. The IMO performed once (1xIMO) or repeated in 10 consecutive days (10xIMO). Principal-component-analysis (PCA) followed the expression study of the clock and steroidogenic-related genes in Leydig cells.

ResultsBoth types of IMO in all investigated periods increased corticosterone and decreased testosterone blood level. Transcriptional analysis revealed different sensitivity to IMO events depending on the circadian time. The majority of steroidogenesis-related genes (Lhcgr, Cyp11a1, Cyp17a1, Hsd3b1/2) were down-regulated in the inactive but unchanged or even up-regulated in the active phase of the day. Both types of IMO potentiated the expression of clock elements Bmal1/BMAL1, Per1/PER1 regardless of the days stage and reduced Reverba in the inactive phase. The PCA confirmed a major shift, for both IMO-types, in the transcription of steroidogenesis and clock genes across the inactive/active phase. Further, the diurnal pattern of the glucocorticoid receptor (Nr3c1/GR) expression in Leydig cells was increased in the inactive phase due to 10xIMO. The observed time-dependent IMO-response of the Leydig cells correlated with different GR engagements.

DiscussionStress- and the circadian-system coordinatively shape Leydig cells physiology, assuming diverse GR engagement as a possible factor in mediating the diurnal effect of stress.

ConclusionThe Leydig cells stress-response depends on the time of the stressful situation, emphasizing the importance of circadian activity in supporting androgen homeostasis and male fertility. Haplotype-resolved powdery mildew resistance loci reveal the impact of heterozygous structural variation on NLR genes in Muscadinia rotundifolia Muscadinia rotundifolia cv. Trayshed is a valuable source of resistance to grape powdery mildew. It carries two powdery mildew resistance-associated genetic loci, Run1.2 on chromosome 12 and Run2.2 on chromosome 18. In this study, we identified, phased, and reconstructed the two haplotypes of each resistance-associated locus. Haplotype phasing allowed the identification of several structural variation events between haplotypes of both loci. Combined with manual refinement of the gene models, we found that the heterozygous structural variants affected the gene content, with some resulting in duplicated or hemizygous nucleotide-binding leucine-rich repeat (NLR) genes. Structural variations also impacted the domain composition of some NLRs. These findings emphasize the need of generating haplotype-resolved sequences instead of using consensus sequences for identifying haplotype-specific candidate genes. Comparison of the NLRs in the Run1.2 and Run2.2 loci indicated that the two loci are composed of a different number and classes of NLR genes. We provide a list of candidate NLR genes from the Run1.2b and Run2.2 loci, whose expression suggests a role in powdery mildew resistance in Trayshed. These first complete and haplotype-resolved resistance-associated loci, and their candidate NLR genes, represent new resources to develop powdery mildew-resistant grape cultivars. Force profile of the two-handed hardstyle kettlebell swing performed by an RKC-certified Instructor BackgroundThe effects of hardstyle kettlebell training are increasingly cited in strength and conditioning research, yet reference data from a proficient swing is scarce. The aim of this exploratory study was to investigate the force profile of a two-handed hardstyle swing performed by a Russian Kettlebell Challenge (RKC) instructor.

MethodsThe subject is a 44-year-old male, body mass 75.6 kg, height 173.5 cm, with six years of regular hardstyle training experience. Two-handed hardstyle swings were performed with a series of incremental mass kettlebells (8-68 kg). Ground reaction force (GRFs) was obtained from a floor-mounted force platform. Force-time curves (FTCs), peak force, forward force, rate of force development (RFD) and swing cadence were investigated.

ResultsData revealed the FTC of a proficient swing is highly consistent and dominated by a single force peak (mean SD = 47 N), with a profile that remained largely unchanged to 24 kg. Pearson correlation analysis revealed a very strong positive correlation in peak force with kettlebell mass (r = 0.95), which increased disproportionately from the lightest to heaviest kettlebells; net peak force increased from 8.36 {+/-} 0.75 N.kg-1 (0.85 x BW) to 12.82 {+/-} 0.39 N.kg-1 (1.3x BW). There was a strong negative correlation between RFD and kettlebell mass (r = 0.82) that decreased from 39.2 N.s-1.kg-1 to 21.5 N.s-1.kg-1. There was a very strong positive correlation in forward ground reaction force with kettlebell mass (r = 0.99), expressed as a ratio of vertical ground reaction, that increased from 0.092 (9.2%) to 0.205 (20.5%). Swing cadence exceeded 40 swings per minute (SPM) with all kettlebells.

ConclusionOur findings challenge some of the popular beliefs of the hardstyle kettlebell swing. Consistent with hardstyle practice, and previous kinematic analysis of expert and novice, force-time curves show a characteristic single large force peak, differentiating passive from active shoulder flexion. Ground reaction force did not increase proportionate to kettlebell mass, with a magnitude of forward force smaller than described in practice. These results could be useful for coaches and trainers wanting to improve athletic performance, and healthcare providers using the kettlebell swing for therapeutic purposes. Findings from this study were used to inform the BELL Trial, a pragmatic controlled trial of kettlebell training with older adults. www.anzctr.org.au ACTRN12619001177145. Multi-omic analysis of the Arabidopsis clock activator mutant rve 4 6 8 reveals connections to carbohydrate metabolism and proteasome regulation Plants are able to sense changes in their light environments, such as the onset of day and night, as well as anticipate these changes in order to adapt and survive. Central to this ability is the plant circadian clock, a molecular circuit that precisely orchestrates plant cell processes over the course of a day. REVEILLE proteins (RVEs) are recently discovered members of the plant circadian circuitry that activate the evening complex and PRR genes to maintain regular circadian oscillation. The RVE 8 protein and its two homologs, RVE 4 and 6, have been shown to limit the length of the circadian period, with rve 4 6 8 triple-knockout plants possessing an elongated period along with increased leaf surface area, biomass, cell size and delayed flowering relative to wild-type Col-0 plants. Here, using a multi-omics approach consisting of phenomics, transcriptomics, proteomics, and metabolomics we draw novel connections between RVE8-like proteins and a number of core plant cell processes. In particular, we reveal that loss of RVE8-like proteins results in altered carbohydrate, organic acid and lipid metabolism, including a starch excess phenotype at dawn. We further demonstrate that rve 4 6 8 plants have lower levels of 20S proteasome subunits and possess significantly reduced proteasome activity, potentially explaining the increase in cell-size observed in RVE8-like mutants. Overall, this robust, multi-omic dataset, provides substantial new insights into the far reaching impact RVE8-like proteins have on the diel plant cell environment. Intermittent KHz-frequency electrical stimulation selectively engages small unmyelinated vagal afferents Afferent and efferent vagal fibers mediate bidirectional communication between the brain and visceral organs. Small, unmyelinated C-afferents constitute the majority of vagal fibers, play critical roles in numerous interoceptive circuits and autonomic reflexes in health and disease and may contribute to the efficacy and safety of vagus nerve stimulation (VNS). Selective engagement of C-afferents with electrical stimuli has not been feasible, due to the default fiber recruitment order: larger fibers first, smaller fibers last. Here, we determine and optimize an electrical stimulus that selectively engages vagal C-afferents. Intermittent KHz-frequency electrical stimulation (KES) activates motor and, preferentially, sensory vagal neurons in the brainstem. During KES, asynchronous activity of C-afferents increases, while that of larger fibers remains largely unchanged. In parallel, KES effectively blocks excitability of larger fibers while moderately suppressing excitability of C-afferents. By compiling selectivity indices in individual animals, we find that optimal KES parameters for C-afferents are >5KHz frequency and 7-10 times engagement threshold (xT) intensity in rats, 15-25xT in mice. These effects can be explained in computational models by how sodium channel responses to KES are shaped by axonal size and myelin. Our results indicate that selective engagement of vagal C-afferents is attainable by intermittent KES. Correlation between speed and turning naturally arises for sparsely sampled cell movements Mechanisms regulating cell movement are not fully understood. One feature of cell movement that determines how far cells displace from an initial position is persistence, the ability to perform movements in a direction similar to the previous movement direction. Persistence is thus determined by turning angles between two sequential displacements and be characterized by an average turning angle or persistence time. Recent studies found that a cells average speed and turning are negatively correlated, suggesting a fundamental cell-intrinsic program whereby cells with a lower turning ability (i.e., larger persistence time) are intrinsically faster (or faster cells turn less). By simulating correlated or persistent random walks (PRWs) using two different frameworks (one based on von Mises-Fisher (vMF) distribution and another based on Ornstein-Uhlenbeck (OU) process) we show that the negative correlation between speed and turning naturally arises when cell trajectories are sub-sampled, i.e., when the frequency of sampling is lower than frequency at which cells make movements. This effect is strongest when the sampling frequency is on the order of magnitude with the typical cell persistence time and when cells vary in persistence time. Both conditions are observed for datasets of T cell movements in vivo that we have analyzed. In simulations the correlation arises due to randomness of cell movements resulting in highly variable persistence times for individual cells that with sub-sampling leads to large variability of average cell speeds. Interestingly, previously suggested methodology of calculating displacement of cell cohorts with different speeds resulted in similar results whether or not there is a cell-intrinsic correlation between cell speed and persistence. For both vMF- and OU-based simulations of PRWs we could find parameter values (distribution of persistence times, speeds, and sampling frequency) that matched experimentally measured correlations between speed and turning for two datasets of T cell movement in vivo suggesting that such simple correlations are not fully informative on the intrinsic link between speed and persistence. Our results thus suggest that sub-sampling may contribute to (and perhaps fully explains) the observed correlation between speed and turning at least for some cell trajectory data and emphasize the role of sampling frequency in inference of critical cellular parameters of cell motility such as speeds.

Secondary AbstractMeasurement of cell movements often results in a negative correlation between average speed and average turning angle suggesting an existence of a universal, cell-intrinsic movement program. We show that such a negative correlation may arise if cells in the population differ in their ability for persistent movement when the movement data are sub-sampled. We show that sub-sampling of cell trajectories generated using two different frameworks of persistent random walk can match the experimentally observed correlation between speed and turning for T cell movements in vivo. Spontaneous Chiral Symmetry Breaking in a Random Driven Chemical System Living systems have evolved to efficiently consume available energy sources using an elaborate circuitry of chemical reactions which, puzzlingly, bear a strict restriction to asymmetric chiral configurations. While autocatalysis is known to promote such chiral symmetry breaking, whether a similar phenomenon may also be induced in a more general class of configurable chemical systems--via energy exploitation--is a sensible yet underappreciated possibility. This work examines this question within a model of randomly generated complex chemical networks. We show that chiral symmetry breaking may occur spontaneously and generically by harnessing energy sources from external environmental drives. Key to this transition are intrinsic fluctuations of achiral-to-chiral reactions and tight matching of system configurations to the environmental drives, which together amplify and sustain diverged enantiomer distributions. These asymmetric states emerge through steep energetic transitions from the corresponding symmetric states and sharply cluster as highly-dissipating states. The results thus demonstrate a generic mechanism in which energetic drives may give rise to homochirality in an otherwise totally symmetrical environment, and from an early-life perspective, might emerge as a competitive, energy-harvesting advantage. The joint evolution of animal movement and competition strategies Competition typically takes place in a spatial context, but eco-evolutionary models rarely address the joint evolution of movement and competition strategies. Here we investigate a spatially explicit producer-scrounger model where consumers can either forage on a heterogeneous resource landscape or steal resource items from conspecifics (kleptoparasitism). We consider three scenarios: (1) a population of foragers in the absence of kleptoparasites; (2) a population of consumers that are either specialized on foraging or on kleptoparasitism; and (3) a population of individuals that can fine-tune their behavior by switching between foraging and kleptoparasitism depending on local conditions. By means of individual-based simulations, we study the joint evolution of movement and competition strategies, and we investigate the implications on the resource landscape and the distribution of consumers over this landscape. In all scenarios and for all parameters considered, movement and competition strategies evolved rapidly and consistently across replicate simulations. The evolved movement and resource exploitation patterns differ considerably across the three scenarios. For example, foragers are attracted by conspecifics in scenario (1), while they are repelled by conspecifics in scenario (2). Generally the movement strategies of kleptoparasites differ markedly from those of foragers, but even within each class of consumers polymorphisms emerge, corresponding to pronounced differences in movement patterns. In all scenarios, the distribution of consumers over resources differs substantially from  ideal free predictions. We show that this is related to the intrinsic difficulty of moving effectively on a depleted landscape with few reliable cues for movement. Our study emphasises the advantages of a mechanistic approach when studying competition in a spatial context, and suggests how evolutionary modelling can be integrated with current work in animal movement ecology. Cell-specific Bioorthogonal Tagging of Glycoproteins Altered glycosylation is an undisputed corollary of cancer development. Understanding these alterations is paramount but hampered by limitations underlying cellular model systems. For instance, the intricate interactions between tumour and host cannot be adequately recapitulated in monoculture of tumour-derived cell lines. More complex co-culture models usually rely on sorting procedures for proteome analyses and rarely capture the details of protein glycosylation. Here, we report a strategy termed Bio-Orthogonal Cell line-specific Tagging of Glycoproteins (BOCTAG). Cells are equipped by transfection with an artificial biosynthetic pathway that transforms bioorthogonally tagged sugars into the corresponding nucleotide-sugars. Only transfected cells incorporate bioorthogonal tags into glycoproteins in the presence of non-transfected cells. We employ BOCTAG as an imaging technique and to annotate cell-specific glycosylation sites in mass spectrometry-glycoproteomics. We demonstrate application in co-culture and mouse models, allowing for profiling of the glycoproteome as an important modulator of cellular function. 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. A novel Boolean network inference strategy to model early hematopoiesis aging Hematopoietic stem cell (HSC) aging is a multifactorial event that leads to changes in HSC properties and function. These changes are intrinsically coordinated and affect the early hematopoiesis, involving hematopoietic stem and progenitor cells (HSPCs). The objective of this work is to better understand the mechanisms and factors controlling these changes. We have therefore developed an original strategy to construct a Boolean network of genes explaining the priming and homeostasis of HSCs (graphical abstract). Based on our previous scRNA-seq data, we performed an exhaustive analysis of the transcriptional network and identified active transcription modules or regulons along the differentiation trajectory of selected HSPC states. This global view of transcriptional regulation led us to focus on 15 components, 13 selected TFs (Tal1, Fli1, Gata2, Gata1, Zfpm1, Egr1, Junb, Ikzf1, Myc, Cebpa, Bclaf1, Klf1, Spi1) and 2 complexes regulating the ability of HSC to cycle (CDK4/6 - Cyclin D and CIP/KIP). We then defined the connections controlling the differentiation dynamics of HSC states and constructed an influence graph between the TFs involved in the dynamics by mixing observations from our scRNA-seq data and knowledge from the literature. Then, using answer set programming (ASP) and in silico perturbation analysis, we obtained a Boolean model which is the solution of a Boolean satisfiability problem. Finally, perturbation of the model based on age-related changes revealed important regulations, such as the overactivation of Egr1 and Junb or the loss of Cebpa activation by Gata2, which were found to be relevant for the myeloid bias of aged HSC. Our work shows the efficiency of the combination of manual and systematic methods to elaborate a Boolean model. The developed strategy led to the proposal of new regulatory mechanisms underlying the differentiation bias of aged HSCs, explaining the decreased transcriptional priming of HSCs to all mature cell types except megakaryocytes. The snoGloBe interaction predictor reveals a broad spectrum of C/D snoRNA RNA targets Box C/D small nucleolar RNAs (snoRNAs) are a conserved class of RNA known for their role in guiding ribosomal RNA 2-O-ribose methylation. Recently, C/D snoRNAs were also implicated in regulating the expression of non-ribosomal genes through different modes of binding. Large scale RNA-RNA interaction datasets detect many snoRNAs binding messenger RNA, but are limited by specific experimental conditions. To enable a more comprehensive study of C/D snoRNA interactions, we created snoGloBe, a human C/D snoRNA interaction predictor based on a gradient boosting classifier. SnoGloBe considers the target type, position and sequence of the interactions, enabling it to outperform existing predictors. Interestingly, for specific snoRNAs, snoGloBe identifies strong enrichment of interactions near gene expression regulatory elements including splice sites. Abundance and splicing of predicted targets were altered upon the knockdown of their associated snoRNA. Strikingly, the predicted snoRNA interactions often overlap with the binding sites of functionally related RNA binding proteins, reinforcing their role in gene expression regulation. SnoGloBe is also an excellent tool for discovering viral RNA targets, as shown by its capacity to identify snoRNAs targeting the heavily methylated SARS-CoV-2 RNA. Overall, snoGloBe is capable of identifying experimentally validated binding sites and predicting novel sites with shared regulatory function. Prevention and therapy of SARS-CoV-2 and the B.1.351 variant in mice Improving the standard of clinical care for individuals infected with SARS-CoV-2 variants is a global health priority. Small molecule antivirals like remdesivir (RDV) and biologics such as human monoclonal antibodies (mAb) have demonstrated therapeutic efficacy against SARS-CoV-2, the causative agent of COVID-19. However, it is not known if combination RDV/mAb will improve outcomes over single agent therapies or whether antibody therapies will remain efficacious against variants. In kinetic studies in a mouse-adapted model of ancestral SARS-CoV-2 pathogenesis, we show that a combination of two mAbs in clinical trials, C144 and C135, have potent antiviral effects against even when initiated 48 hours after infection. The same antibody combination was also effective in prevention and therapy against the B.1.351 variant of concern (VOC). Combining RDV and antibodies provided a modest improvement in outcomes compared to single agents. These data support the continued use of RDV to treat SARS-CoV-2 infections and support the continued clinical development of the C144 and C135 antibody combination to treat patients infected with SARS-CoV-2 variants. High-quality Arabidopsis thaliana Genome Assembly with Nanopore and HiFi Long Reads Arabidopsis thaliana is an important and long-established model species for plant molecular biology, genetics, epigenetics, and genomics. However, the latest version of reference genome still contains significant number of missing segments. Here, we report a high-quality and almost complete Col-0 genome assembly with two gaps (Col-XJTU) using combination of Oxford Nanopore Technology ultra-long reads, PacBio high-fidelity long reads, and Hi-C data. The total genome assembly size is 133,725,193 bp, introducing 14.6 Mb of novel sequences compared to the TAIR10.1 reference genome. All five chromosomes of Col-XJTU assembly are highly accurate with consensus quality (QV) scores > 60 (ranging from 62 to 68), which are higher than those of TAIR10.1 reference (QV scores ranging from 45 to 52). We have completely resolved chromosome (Chr) 3 and Chr5 in a telomere-to-telomere manner. Chr4 has been completely resolved except the nucleolar organizing regions, which comprise long repetitive DNA fragments. The Chr1 centromere (CEN1), reportedly around 9 Mb in length, is particularly challenging to assemble due to the presence of tens of thousands of CEN180 satellite repeats. Using the cutting-edge sequencing data and novel computational approaches, we assembled about 4 Mb of sequence for CEN1 and a 3.5-Mb-long CEN2. We investigated the structure and epigenetics of centromeres. We detected four clusters of CEN180 monomers, and found that the centromere-specific histone H3-like protein (CENH3) exhibits a strong preference for CEN180 cluster 3. Moreover, we observed hypomethylation patterns in CENH3-enriched regions. We believe that this high-quality genome assembly, Col-XJTU, would serve as a valuable reference to better understand the global pattern of centromeric polymorphisms, as well as genetic and epigenetic features in plants. Continental generalization of an AI system for clinical seizure recognition BackgroundElectroencephalogram (EEG) monitoring and objective seizure identification is an essential clinical investigation for some patients with epilepsy. Accurate annotation is done through a time-consuming process by EEG specialists. Computer-assisted systems for seizure detection currently lack extensive clinical utility due to retrospective, patient-specific, and/or irreproducible studies that result in low sensitivity or high false positives in clinical tests. We aim to significantly reduce the time and resources on data annotation by demonstrating a continental generalization of seizure detection that balances sensitivity and specificity.

MethodsThis is a prospective inference test of artificial intelligence on nearly 14,590 hours of adult EEG data from patients with epilepsy between 2011 and 2019 in a hospital in Sydney, Australia. The inference set includes patients with different types and frequencies of seizures across a wide range of ages and EEG recording hours. The artificial intelligence (AI) is a convolutional long short-term memory network that is trained on a USA-based dataset. The Australian set is about 16 times larger than the US training dataset with very long interictal periods (between seizures), which is way more realistic than the training set and makes our false positives highly reliable. We validated our inference model in an AI-assisted mode with a human expert arbiter and a result review panel of expert neurologists and EEG specialists on 66 sessions to demonstrate achievement of the same performance with over an order-of-magnitude reduction in time.

FindingsOur inference on 1,006 EEG recording sessions on the Australian dataset achieved 76.68% with nearly 56 [0, 115] false alarms per 24 hours on average, against legacy ground-truth annotations by human experts, conducted independently over nine years. Our pilot test of 66 sessions with a human arbiter, and reviewed ground truth by a panel of experts, confirmed an identical human performance of 92.19% with an AI-assisted system, while the time requirements reduce significantly from 90 to 7.62 minutes on average.

InterpretationAccurate and objective seizure counting is an important factor in epilepsy. An AI-assisted system can help improve efficiency and accuracy alongside human experts, particularly in low and middle-income countries with limited expert human resources.

FundingsSOAR Fellowship from The University of Sydney, a Microsoft AI for Accessibility grant, and a Research Training Program (RTP) support provided by the Australian Government.

Research in contextO_ST_ABSEvidence before this studyC_ST_ABSDuring the development of our artificial intelligence (AI) system, we did a systematic review of the scientific literature with search via PubMed for research articles published on seizure detection with the following inclusion criteria: (1) Tests or inference evaluation is conducted on large-scale clinical EEG data; (2) Generalization is attempted or potentials for generalization is considered, e.g., in commercialized tools; (3) Seizure detection delay and real-time (aka. online) operation were not considered critical in this context as long as the test was conducted on raw EEG data. Note that ICU seizure detection or portable seizure alert systems are relying on detection delay and real-time needs. Our keywords include "prospective seizure detection", "automated seizure detection", "non-patient specific seizure detection", "seizure detection on continuous EEG", and "deep learning-based seizure detection" and "machine learning-based seizure detection". We found that the only two categories of works meet our criteria: two research papers published in 2020 and works published by commercial tools developers. We cited a recent review of 89 deep learning-based seizure detection, all of which are retrospective. One work from Stanford reported seizure detection on all ages (pediatric to adult ages) using post-acquisition EEG recordings and provided an avenue for independent evaluation by providing a test on a publicly available Temple University Hospital (TUH) EEG dataset. The other work pivoted on algorithmic-assisted real-time seizure risk monitoring in continuous EEG in neonatal intensive care unit (NICU) with 128 neonates (32 with seizures) showing about 20% improvement in seizure identification over 130 neonates (38 with seizures) with no algorithmic assistance.

Commercial tools we studied are Encevis (EpiScan), Besa, and Persyst. There is a recent comparative study on these tools on 81 patients. Encevis is reported as the best performing tool, and hence we provided a comparative study with Encevis ver. 1.9.2. Encevis is also the only tool that provided an avenue for comparative study on publicly available EEG data. The Stanford work, published in 2020, confirms many false positives with Persyst 13. We excluded our tests on Persyst 14 as it highly under-performed relative to Encevis. Only Stanfords work provides code availability. We compared our results with Stanfords work outcome and provided pilot test results with the Encevis (EpiScan) tool on the Australian dataset, which shows a considerably lower sensitivity.

Added value of this studyTo the best of our knowledge, the current study is the first continental generalization that demonstrates the potential to achieve an expert human-level seizure recognition rate in a clinical setting and in just a fraction of time. The two datasets used in this study are recorded with different infrastructure, which adds to the independence of inference from hardware types and improves clinical utility. This is particularly important as 80% of patients with epilepsy live in low and middle-income countries with limited resources, particularly EEG specialists and neurologists.

Implications of all the available evidenceOur results support the potential benefits of deep learning AI in clinical settings for seizure recognition and its contribution to significant sensitivity over available solutions. Our AI-assisted system achieves more than a ten-fold increase in time efficiency and reports identical performance to human experts for EEG interpretation with access to great neurophysiology support and auxiliary data. Our findings, particularly our tests on an available commercial tool, recommend that the evaluation, test, or inference in AI systems be performed on different datasets, with diverse infrastructures, and on large-scale and realistic sets with long interictal periods. Rho Kinase regulates neutrophil NET formation that is involved in UVB-induced skin inflammation ObjectiveUltraviolet B (UVB) is an important trigger of skin inflammation and lupus with leukocyte recruitment to inflamed skin. We recently reported the involvement of neutrophil NETosis in UVB-induced skin inflammation, and that NETotic nuclear envelope rupture is driven by PKC-mediated nuclear lamin B disassembly. To address the role of Actin cytoskeleton in NETosis, we investigated the effects of Rho kinase (ROCK) and its downstream actomyosin cytoskeletal networks on PKC nuclear translocation and NET formation, as well as their involvement in UVB-induced skin inflammation.

MethodsWe studied the dynamic changes of ROCK and actomyosin cytoskeletal networks during NETosis induction and their involvement in PKC nuclear translocation. Using mice with hematopoietic-specific ROCK1 deficiency, we investigated the effects of ROCK1 deficiency on NETosis, and its involvement in UVB-induced skin inflammation.

ResultsOur time course studies demonstrated the dynamic changes of actin polymerization and ROCK activation, support the role of actin cytoskeleton in nuclear translocation of cytosolic PKC in early stage of NETosis induction. Inhibition of actin polymerization or key molecules of the ROCK/MLCK/myosin pathway decreased PKC nuclear translocation and NET formation. Genetic deficiency of ROCK1, inhibited NETosis ex vivo and in vivo, decreased extracellular display of NET-associated IL-17A, TNF, IFN{gamma}, and IFN in inflamed skin, which were correlated with the ameliorated skin inflammation in UVB-irradiated mice with hematopoietic-specific ROCK1 deficiency.

ConclusionsROCK regulated NETosis through modulation of PKC nuclear translocation via actomyosin cytoskeletal networks in neutrophils. ROCK1 deficiency ameliorated UVB- induced skin inflammation by attenuation of NETosis and NET-associated cytokines. Synergy of chemotherapy and macrophage depletion leads to B cell-mediated T cell memory activation and durable triple negative breast cancer regression Immunosuppressive elements within the tumor microenvironment such as Tumor Associated Macrophages (TAMs) can present a barrier to successful anti-tumor responses by cytolytic T cells. We employed preclinical syngeneic p53 null mouse models of triple negative breast cancer (TNBC) to develop a treatment regimen that harnessed the immunostimulatory effects of low-dose cyclophosphamide coupled with the pharmacologic inhibition of TAMs using either a small molecule CSF1R inhibitor or an anti-CSF1R antibody. This therapeutic combination was used to successfully treat several highly aggressive TNBC murine mammary tumors and lung metastasis. Using this regimen and single cell RNA sequencing we characterized tumor infiltrating lymphocytes (TILs) including helper T cells and antigen-presenting B cells that were highly enriched in good responders to combination therapy. Using high dimensional imaging techniques, we identified the close spatial localization of B220+ CD86+ activated B cells and CD4+ T cells in tertiary lymphoid structures that were present up to 6 weeks post-treatment in one model that also exhibited long-term tumor regression post-treatment. We also characterized the transcriptional and metabolic heterogeneity of TAMS in these two closely related claudin-low/mesenchymal subtype tumor models with differential treatment responses. A murine TAM signature derived from the T12 model is highly expressed and conserved in human claudin-low breast cancers, and high expression of the T12 signature correlated with reduced overall survival. This T12 tumor TAM signature may help identify human claudin-low breast cancer patients that will benefit from the combination of cyclophosphamide and anti-CSF1R therapy. These studies illustrate the complexity of the tumor immune microenvironment and highlight different immune responses that result from rationale combinations of immunotherapy.

SignificanceA treatment regimen that harnessed the immunostimulatory effects of cyclophosphamide coupled with the inhibition of CSF1R was used to successfully treat several highly aggressive claudin-low TNBC murine mammary tumors and lung metastasis. Patterned apoptosis has an instructive role for local growth and tissue shape in a fast-growing epithelium What regulates organ size and shape remains one of the fundamental mysteries of modern biology. So far, research in this area has primarily focused on deciphering the regulation in time and space of growth and cell division, while the contribution of cell death has been much more neglected. This includes studies of the Drosophila wing imaginal disc, the prospective fly wing which undergoes massive growth during larval stage, and represents one of the best characterised systems for the study of growth and patterning. So far, it has been assumed that cell death was relatively neglectable in this tissue and as a result the pattern of growth was usually attributed to the distribution of cell division. Here, using systematic mapping and registration combined with quantitative assessment of clone size and disappearance, we show for the first time that cell death is not neglectable, and outline a persistent pattern of cell death and clone elimination in the disc. Local variation of cell death is associated with local variation of clone size, pointing to an impact of cell death on local growth which is not fully compensated by proliferation. Using morphometric analyses of adult wing shape and genetic perturbations, we provide evidence that patterned death affects locally and globally adult wing shape and size. This study describes a roadmap for accurate assessment of the contribution of cell death to tissue shape, and outlines for the first time an important instructive role of cell death in modulating quantitatively local growth and the morphogenesis of a fast-growing tissue. A terrain treadmill to study animal locomotion through large obstacles A major challenge to understanding locomotion in complex 3-D terrain with large obstacles is to create tools for controlled, systematic lab experiments. Existing terrain arenas only allow observations at small spatiotemporal scales ([~]10 body length, [~]10 stride cycles). Here, we create a terrain treadmill to enable high-resolution observations of animal locomotion through large obstacles over large spatiotemporal scales. An animal moves through modular obstacles on an inner sphere, while a rigidly-attached, concentric, transparent outer sphere rotated with the opposite velocity via closed-loop feedback to keep the animal on top. During sustained locomotion, a discoid cockroach moved through pillar obstacles for 25 minutes ({approx} 2500 strides) over 67 m ({approx} 1500 body lengths), and was contained within a radius of 4 cm (0.9 body length) for 83% of the duration, even at speeds of up to 10 body length/s. The treadmill enabled observation of diverse locomotor behaviors and quantification of animal-obstacle interaction.

Summary StatementA device keeps a small animal on top of a sphere while it traverses obstacles, creating a "terrain treadmill" to study locomotion over a long time and distance at high-resolution. Maf/ham1-like pyrophosphatases of non-canonical nucleotides are host-specific partners of viral RNA-dependent RNA polymerases Cassava brown streak disease (CBSD), dubbed the "Ebola of plants", is a serious threat to food security in Africa caused by two viruses of the family Potyviridae: cassava brown streak virus (CBSV) and Ugandan (U)CBSV. Intriguingly, U/CBSV, along with another member of this family and one secoviridae, are the only known RNA viruses encoding a protein of the Maf/ham1-like family, a group of widespread pyrophosphatase of non-canonical nucleotides (ITPase) expressed by all living organisms. Despite the socio-economic impact of CDSD, the relevance and role of this atypical viral factor has not been yet established. Here, using an infectious cDNA clone and reverse genetics, we demonstrate that UCBSV requires the ITPase activity for infectivity in cassava, but not in the model plant Nicotiana benthamiana. HPLC MS/MS experiments showed that, quite likely, this host-specific constraint is due to an unexpected high concentration of non-canonical nucleotides in cassava. Finally, protein analyses and experimental evolution of mutant viruses indicated that keeping a fraction of the yielded UCBSV ITPase covalently bound to the viral RNA-dependent RNA polymerase (RdRP) optimizes viral fitness, and this seems to be a feature shared by the other members of the Potyviridae family expressing Maf/ham1-like proteins. All in all, our work (i) reveals that the over-accumulation of non-canonical nucleotides in the host might have a key role in antiviral defense, and (ii) provides the first example of an RdRP-ITPase partnership, reinforcing the idea that RNA viruses are incredibly versatile at adaptation to different host setups. Critical re-evaluation of the slope factor of the operational model of agonism Background and PurposeAlthough being a relative term, agonist efficacy is a cornerstone in the proper assessment of agonist selectivity and signalling bias. The operational model of agonism (OMA) has become successful in the determination of agonist efficacies and ranking them. In 1985, Black et al. introduced the slope factor to the OMA to make it more flexible and allow for fitting steep as well as flat concentration-response curves.

Experimental ApproachFunctional analysis of OMA demonstrates that the slope factor implemented by Black et al. affects relationships among parameters of the OMA, leading to wrong estimates of operational efficacy and affinity of an agonist. In contrast, functional analysis of OMA with Hill coefficient as a slope factor has not this flaw.

Key ResultsFitting of the OMA with Black et al. slope factor to concentration-response curves of several models (homotropic allosteric modulation, substrate inhibition and non-competitive auto-inhibition) gives wrong estimates of operational efficacy and affinity. In contrast, fitting of the OMA modified by the Hill coefficient to concentration-response curves of these several models gives correct estimates of operational efficacy and affinity.

Conclusion and ImplicationsThe OMA modified by the Hill coefficient can be used for correct ranking of agonism and subsequent analysis, like quantification of signalling bias. High school science fair: Experiences of two groups of undergraduate bioscience students Science fairs offer potential opportunities for students to learn first-hand about the practices of science. Over the past six years we have been carrying out voluntary and anonymous surveys with regional and national groups of high school and post high school students to learn about their high school science fair experiences regarding help received, obstacles encountered, and opinions about the value and impact of science fair. Understanding what students think about science fairs will help educators make science fairs more effective learning opportunities. In this paper, we focus on the findings with two national groups of post high school students - undergraduate research fellows (SURF students) who did research at UT Southwestern Medical Center during 2014-2019 and undergraduates biology students attending the 2019 Howard Hughes Medical Institute Science Education Alliance (SEA) summer symposium. About 25% of the students who completed surveys indicated that they had participated in high school science fair, but more than half attended high schools where science fairs were unavailable. Effectively, 6 out of every 10 students participated in science fair if available. Students who could have participated in high school science fair but chose not to do so identified not enough time and coming up with their project idea as major reasons why not. About half the SURF students favored requiring non-competitive science fair regardless whether they themselves had participated in science fair. On the other hand, less than 1 in 5 thought that competitive science fair should be required. Introduction to the scientific process and general learning were mentioned most frequently as the reasons to require non-competitive science fair; these reasons were mentioned rarely in connection with competitive science fair. Unlike the national cohort of high school students we surveyed previously, who mostly did science fair in 9th and 10th grades, SURF students participated in science fair throughout high school and were twice as likely as high school students to have carried out science fair more than once. In conclusion, our findings suggest that participation of the undergraduate bioscience majors in high school science fairs occurs far more frequently than recognized previously. The findings emphasize further the importance of incentivizing rather than requiring science fair participation, especially in 9th and 10th grades, and the potential value of developing non-competitive science fairs. The ecological consequences and evolution of retron-mediated suicide as a way to protect Escherichia coli from being killed by phage In 1984, retrons were described as DNA sequences that code for a reverse transcriptase and a unique single-stranded DNA/RNA hybrid called multicopy single-stranded DNA (msDNA). It would not be until 2020 that a function was shown, when compelling evidence was presented that retrons can protect bacteria from infections by lytic phage via an abortive infection mechanism. When infected with the virulent mutant of the phage lambda, {lambda}VIR, and to a lesser extent other phages, a retron designated Ec48 is activated, the Escherichia coli bearing this element dies and the infecting phage is lost. With the aid of a mathematical model, we explored the a priori conditions under which retrons will protect bacterial populations from invasion by phage and when retron-bearing bacteria will evolve in populations without this element. Using E. coli with and without Ec48, and {lambda}VIR we estimated the parameters of this model and tested the hypotheses generated from our analysis of its properties. Our models and experiments suggest cells expressing retron-mediated abortive infection have no advantage over cells lacking this system as a defense against phage, and we question whether the protection against phage infection is the unique selective force responsible for their evolution in bacteria. First detection of herpesvirus and frequency of mycoplasma infection in free-ranging Hermann s tortoises (Testudo hermanni), and in potential pet vectors AO_SCPLOWBSTRACTC_SCPLOWTwo types of pathogens cause highly contagious upper respiratory tract diseases (URTD) in Chelonians: testudinid herpesviruses (TeHV) and a mycoplasma (Mycoplasma agassizii). In captivity, these infections are frequent and can provoke outbreaks. Pet trade generates international flow of tortoises, often without sanitary checking; individuals intentionally or accidentally released in the wild may spread pathogens. A better understanding of the transmission of infectious agents from captivity to wild tortoises is needed. Many exotic individuals have been introduced in populations of the endangered western Hermanns tortoise (Testudo hermanni hermanni), notably spur-thighed tortoises (Testudo graeca). We assessed the presence of TeHV and mycoplasma in native western Hermanns tortoises and in potential pet vectors in south-eastern France. Using a large sample (N=572 tortoises), this study revealed, by PCR, the worrying presence of herpesvirus in 7 free-ranging individuals (3 sub-populations). Additionally, Mycoplasma agassizii was detected, by PCR, in 15 of the 18 populations sampled with a frequency ranging from 3.4% (1 of 29 tortoises) to 25% (3 of 12 tortoises). Exotic spur-thighed tortoises showed high frequency of mycoplasma infection in captivity (18.2%) and in individuals (50%) found in native Hermanns tortoise sub-populations, suggesting that this species could be a significant vector. The paucity of information of TeHV on European tortoise URTD in natural settings, especially in combination with mycoplasma, prompts for further studies. Indeed, sick tortoises remain concealed and may not be easily detected in the field. Our results indicate a good health for most infected tortoise but it should be screened in the field as well as in captivity.