Characterising ontogeny of numerosity discrimination in zebrafish reveals the use of multiple, numerical and non- numerical mechanisms. A sense of non-symbolic numerical magnitudes is widespread in the animal kingdom and has been documented in adult zebrafish. Here we investigated the ontogeny of this ability using a group size preference task in juvenile zebrafish. Fish showed group size preference from 21 days post fertilization (dpf) and reliably chose the larger group when presented with discriminations of between 1 vs. 3, 2 vs. 5 and 2 vs. 3 conspecifics but not 2 vs. 4 conspecifics. When the ratio between the number of conspecifics in each group was maintained at 1:2, fish could discriminate between 1 vs. 2 individuals and 3 vs. 6, but again, not when given a choice between 2 vs. 4 individuals. These findings are in agreement with studies in other species suggesting the systems involved in quantity representation do not operate separately from other cognitive mechanisms. Rather they suggest quantity processing in fish may be the result of an interplay between attentional, cognitive and memory-related mechanisms as in humans and other animals. Our results emphasise the potential of the use of zebrafish to explore the genetic and neural processes underlying the ontogeny and function of number cognition.
Effect of Adolescent Stress on Adult Morphine-Induced Behavioral Sensitization is Dependent Upon Genetic Background 1Deaths related to opioid use have skyrocketed in the United States, leading to a public health epidemic. Research has shown that both biological (genes) and environmental (stress) precursors are linked to opioid use. In particular, stress during adolescence - a critical period of frontal lobe development - influences the likelihood of abusing drugs. However, little is known about the biological mechanisms through which adolescent stress leads to long-term risk of opioid use, or whether genetic background moderates this response. Male and female C57BL/6J and BALB/cJ mice were exposed to chronic variable social stress (CVSS) or control conditions throughout adolescence and then tested for morphine locomotor sensitization or morphine consumption in adulthood. To examine possible mechanisms that underlie stress-induced changes in morphine behaviors, we assessed physiological changes in response to acute stress exposure and prefrontal cortex miRNA gene expression. Adolescent stress did not influence morphine sensitization or consumption in BALB/cJ animals, and there was limited evidence of stress effects in female C57BL/6J mice. In contrast, male C57BL/6J mice exposed to adolescent CVSS had blunted morphine sensitization compared to control animals; no differences were observed in the acute locomotor response to morphine administration or morphine consumption. Physiologically, C57BL/6J mice exposed to CVSS had an attenuated corticosterone recovery following an acute stressor and downregulation of twelve miRNA in the prefrontal cortex compared to control mice. The specificity of the effects for C57BL/6J versus BALB/cJ mice provides evidence of a gene by environmental interaction influencing opioid behaviors. Long-term differences in stress reactivity or miRNA expression suggests two possible biological mechanisms to evaluate in future research.
Pipeline to detect the positional relationship between transposable elements and adjacent genes in host genome AO_SCPLOWBSTRACTC_SCPLOWUnderstanding the relationship between transposable elements (TEs) and their closest positional genes in the host genome is a key point to explore their potential role in genome evolution. Transposable elements can regulate and affect gene expression not only because of their mobility within the genome but also because of their transcriptional activity. A comprehensive knowledge of structural organization between transposable elements and neighboring genes is important to study TE functional role in gene regulation. We implemented a pipeline to display the relationship between the distribution of TEs and adjacent genes in host genomes. Our tool is freely available here: https://github.com/marieBvr/TEs_genes_relationship_pipeline. Ecological correlates of gene family size in a pine-feeding sawfly genome and across Hymenoptera A central goal in evolutionary biology is to determine the predictability of adaptive genetic changes. Despite many documented cases of convergent evolution at individual loci, little is known about the repeatability of gene family expansions and contractions. To address this void, we examined gene family evolution in the redheaded pine sawfly Neodiprion lecontei, a non-eusocial hymenopteran and exemplar of a pine-specialized lineage evolved from angiosperm-feeding ancestors. After assembling and annotating a draft genome, we manually annotated multiple gene families with chemosensory, detoxification, or immunity functions and characterized their genomic distributions and evolutionary history. Our results suggest that expansions of bitter gustatory receptor (GR), clan 3 cytochrome P450 (CYP3), and antimicrobial peptide (AMP) subfamilies may have contributed to pine adaptation. By contrast, there was no evidence of recent gene family contraction via pseudogenization. Next, we compared the number of genes in these same families across insect taxa that vary in diet, dietary specialization, and social behavior. In Hymenoptera, herbivory was associated with small GR and olfactory receptor (OR) families, eusociality was associated with large OR and small AMP families, and--unlike investigations in more closely related taxa--ecological specialization was not related to gene family size. Overall, our results suggest that gene families that mediate ecological interactions may expand and contract predictably in response to particular selection pressures, however, the ecological drivers and temporal pace of gene gain and loss likely varies considerably across gene families. Fatal neuroinvasion and SARS-CoV-2 tropism in K18-hACE2 mice is partially independent on hACE2 expression Animal models recapitulating distinctive features of severe COVID-19 are critical to enhance our understanding of SARS-CoV-2 pathogenesis. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. The precise mechanisms of lethality in this mouse model remain unclear. Here, we evaluated the spatiotemporal dynamics of SARS-CoV-2 infection for up to 14 days post-infection. Despite infection and moderate pneumonia, rapid clinical decline or death of mice was invariably associated with viral neuroinvasion and direct neuronal injury (including brain and spinal neurons). Neuroinvasion was observed as early as 4 dpi, with virus initially restricted to the olfactory bulb supporting axonal transport via the olfactory neuroepithelium as the earliest portal of entry. No evidence of viremia was detected suggesting neuroinvasion occurs independently of entry across the blood brain barrier. SARS-CoV-2 tropism was not restricted to ACE2-expressing cells (e.g., AT1 pneumocytes), and some ACE2-positive lineages were not associated with the presence of viral antigen (e.g., bronchiolar epithelium and brain capillaries). Detectable ACE2 expression was not observed in neurons, supporting overexpression of ACE2 in the nasal passages and neuroepithelium as more likely determinants of neuroinvasion in the K18-hACE2 model. Although our work incites caution in the utility of the K18-hACE2 model to study global aspects of SARS-CoV-2 pathogenesis, it underscores this model as a unique platform for exploring the mechanisms of SARS-CoV-2 neuropathogenesis that may have clinical relevance acknowledging the growing body of evidence that suggests COVID-19 may result in long-standing neurologic consequences.

IMPORTANCECOVID-19 is predominantly a respiratory disease caused by SARS-CoV-2 that has infected more than 191 million people with over 4 million fatalities (2021-07-20). The development of animal models recapitulating distinctive features of severe COVID-19 is critical to enhancing our understanding of SARS-CoV-2 pathogenesis and in the evaluation of vaccine and therapeutic efficacy. Transgenic mice expressing human angiotensin-converting enzyme 2 (hACE2) under the cytokeratin 18 promoter (K18-hACE2) represent a lethal model of SARS-CoV-2 infection. Here, we show lethality of this model is invariably associated with viral neuroinvasion linked with viral replication and assembly. Importantly, pneumonia albeit invariably present was generally moderate with the absence of culturable infectious virus at peak neuroinvasion. The dynamics of viral neuroinvasion and pneumonia were only partially dependent on hACE2. Overall, this study provides an in-depth sequential characterization of the K18-hACE2 model following SARS-CoV-2 infection, highlighting its significance to further study the mechanisms of SARS-CoV-2 neuropathogenesis. 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. Genome editing excisase origins illuminated by somatic genome of Blepharisma Massive DNA excision occurs regularly in ciliates, ubiquitous microbial eukaryotes with somatic and germline nuclei in the same cell. Tens of thousands of internally eliminated sequences (IESs) scattered throughout a copy of the ciliate germline genome are deleted during development of the streamlined somatic genome. Blepharisma represents one of the two earliest diverging ciliate classes, and, unusually, has dual pathways of somatic nuclear development, making it ideal for investigating the functioning and evolution of these processes. Here, we report the somatic genome assembly of Blepharisma stoltei strain ATCC 30299 (41 Mb), arranged as numerous alternative telomere-capped minichromosomes. This genome encodes eight PiggyBac transposase homologs liberated from transposons. All are subject to purifying selection, but just one, the putative IES excisase, has a complete catalytic triad. We propose PiggyBac homologs were ancestral excisases that enabled evolution of extensive, natural genome editing. Activation of the type 3 secretion system of enteropathogenic E. coli leads to remodeling of its membrane composition and function The cell envelope of gram-negative bacteria is a complex structure, essential for bacterial survival and for resistance to many antibiotics. Channels that cross the bacterial envelope and the host cell membrane form secretion systems that are activated upon attachment to host, enabling bacteria to inject effector molecules into the host cell, required for bacterial-host interaction. The type III secretion system (T3SS) is critical for the virulence of several pathogenic bacteria, including enteropathogenic E. coli (EPEC). The EPEC T3SS activation is associated with repression of carbon storage regulator (CsrA), resulting in gene expression remodeling, which is known to affect EPEC central carbon metabolism and contributes to the adaptation to a cell-adherent lifestyle in a poorly understood manner. We reasoned that the changes in bacterial envelope upon attachment to host and the activation of a secretion system may involve a modification of the lipid composition of bacterial envelope. Accordingly, we performed a lipidomics analysis on mutant strains that simulate T3SS activation. We saw a shift in glycerophospholipid metabolism towards the formation of lysophospholipids, attributed to corresponding upregulation of the phospholipase pldA and the acyltransferase ygiH upon T3SS activation in EPEC. We also detected a shift from menaquinones and ubiquinones to undecaprenyl lipids, concomitant to abnormal synthesis of O-antigen. The remodeling of lipid metabolism is mediated by CsrA and associated with increased bacteria cell size and Zeta potential, and a corresponding alteration in EPEC permeability to vancomycin, increasing the sensitivity of T3SS-activated strains and of adherent wild type EPEC to the antibiotic.

ImportanceThe characterization of EPEC membrane lipid metabolism upon attachment to host is an important step towards a better understanding the shift of EPEC, a notable human pathogen, from a planktonic to adherent life style. It may also apply to other pathogenic bacteria that use this secretion system. We predict that upon attachment to host cells the lipid remodeling upon T3SS activation contributes to bacterial fitness and promotes host colonization, and show that it is associated with increased cell permeability and higher sensitivity to vancomycin.

To the best of our knowledge, this is the first demonstration of a bacterial lipid remodeling due to activation of a secretion system. 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. Genetic variation associated with plastic and homeostatic growth responses to drought in Arabidopsis O_LINatural genetic variation influences plant responses to environmental stressors. However, the extent to which such variation underlies plastic versus homeostatic response phenotypes has been little studied.
C_LIO_LIWe quantified the extent of drought-induced changes in leaf area in a set of Iberian Arabidopsis accessions and then performed association studies correlating variation in this phenotype with genomic and transcriptomic variation.
C_LIO_LIDrought-induced plastic reductions in relative leaf area typified accessions originating from productive environments. In contrast, homeostasis in relative leaf area typified accessions originating from unproductive environments. Genome-Wide Association Studies (GWAS), Transcriptome Wide Association Studies (TWAS), and expression GWAS (eGWAS) highlighted the importance of auxin-related processes and, in particular, the potential role of the SMALL AUXIN UP RNA 26 (SAUR26) gene in conferring leaf area plasticity. Homeostatic responses in relative leaf area were associated with a diverse gene set and positively associated with a higher intrinsic water use efficiency (WUEi) as confirmed in a TWAS metanalysis of previously published {delta}13C measurements.
C_LIO_LIWe have identified not only candidate "plasticity genes" but also candidate "homeostasis genes" controlling leaf area. Our results demonstrate the value of a combined GWAS, TWAS, and eGWAS approach to identify mechanisms underlying phenotypic responses to stress.
C_LI

One-sentence summaryInformation on phenotype, genotype, and transcript abundance is integrated to identify both plasticity and homeostasis genes and processes associated with local adaptation to drought stress in Arabidopsis accessions of the Iberian Peninsula. Regulation of the PKD2 channel function by TACAN Autosomal dominant polycystic kidney disease (ADPKD) is caused by mutations in membrane receptor PKD1 or cation channel PKD2. TACAN (also named TMEM120A), recently reported as an ion channel in neuron cells for mechano and pain sensing, is also distributed in diverse non-neuronal tissues such as kidney, heart and intestine, suggesting its involvement in other functions. In this study, we found that TACAN is in complex with PKD2 in native renal cell lines. Using the two-electrode voltage clamp in Xenopus oocytes we found that TACAN inhibited the channel activity of PKD2 gain-of-function mutant F604P. The first and last transmembrane domains of TACAN were found to interact with the PKD2 C-and N-terminal portions, respectively. We showed that the TACAN N-terminus acted as a blocking peptide and that TACAN inhibits the PKD2 function through the PKD2/TACAN binding. By patch clamping in mammalian cells, we found that TACAN inhibits both the single channel conductance and open probability of PKD2 and mutant F604P. PKD2 co-expressed with TACAN, but not PKD2 alone, exhibited pressure sensitivity. Furthermore, we also found that TACAN aggravates PKD2-dependent tail curvature and pronephric cysts in larval zebrafish, in support of the in vitro inhibitory effects of TACAN. In summary, this study revealed that TACAN acts as a PKD2 inhibitor and mediates mechano sensitivity of the PKD2/TACAN channel complex. A Bayesian model selection approach to mediation analysis Mediation analysis is a powerful tool for discovery of causal relationships. We describe a Bayesian model selection approach to mediation analysis that is implemented in our bmediatR software. Using simulations, we show that bmediatR performs as well or better than established methods including the Sobel test, while allowing greater flexibility in both model specification and in the types of inference that are possible. We applied bmediatR to genetic data from mice and human cell lines to demonstrate its ability to derive biologically meaningful findings. The Bayesian model selection framework is extensible to support a wide variety of mediation models. Dynamic tracing using ultra-bright labelling and multi-photon microscopy identifies endothelial uptake of poloxamer-188 coated poly(lactic-co-glycolic acid)nano-carriers in vivo Poly(lactic-co-glycolic acid) (PLGA)-based drug formulations are approved for the use in humans, however, the potential of PLGA to design nanoparticles (NPs) and target the central nervous system remains to be exploited.

The aim of the current study was design PLGA NPs, loading them with bulky fluorophores thereby increasing single particle fluorescence to a level visible by in vivo microscopy, and investigate their brain biodistribution. We developed, highly fluorescent 70 nm PLGA NPs significantly brighter then quantum dots enabling their visualization by intravital real-time 2-photon microscopy. We found that PLGA NPs coated with pluronic F-68 (PF-68) had a substantially longer plasma half-life than uncoated NPs and were taken up by cerebro-vascular endothelial cells. High resolution confocal microscopy revealed that coated PLGA NPs were present in late endothelial endosomes of cerebral vessels within 1 hour after systemic injection and were more readily taken up by endothelial cells in peripheral organs.

The current data suggest that PF-68 coated PLGA NPs are taken up by mouse cerebral and peripheral endothelial cells in vivo. The combination of ultra-bright NPs and in vivo imaging may thus represent a promising approach to reduce the gap between development and clinical application of nanoparticle-based drug carriers. In vivo profiling of site-specific human cancer cell states in zebrafish Tissue microenvironments affect the functional states of cancer cells, but determining these influences in vivo has remained a significant challenge. We present a quantitative high-resolution imaging assay of cancer cell morphology in zebrafish xenografts to probe functional adaptation to variable cell extrinsic cues and molecular interventions. We focus on Ewing Sarcoma, a pediatric cancer driven by a single oncogenic fusion protein EWSR1-FLI1, and with little to no additional somatic mutations, making it a prototypical form of cancer whose adaptation to microenvironments is likely driven by acute, non-genomic mechanisms. Using computer vision analysis of 3D cell shapes, we find systematic shifts in the distribution of cell morphotypes between distinct sites in the fish embryo. We also find site-specific morphological responses to differential expression of EWSR1-FLI1. Combining these data we propose a model where Ewing Sarcoma cancer cell plasticity is sensitive both to expression fluctuation of EWSR1-FLI1 and signals from the surrounding tissue microenvironment, with either or both factors possibly contributing to the oncogenic potential of these cells. Naming Human Diseases: Ethical Principles of Curating Exclusive Substitute for Inopportune Nosology BackgroundIn the medical sphere, understanding naming conventions strengthen the integrity of naming human diseases remains nominal rather than substantial yet. Since the current nosology-based standard for human diseases could not offer a one-size-fits-all corrective mechanism, many idiomatic but flawed names frequently appear in scientific literature and news outlets at the cost of sociocultural impacts.

ObjectiveWe attempt to examine the ethical oversights of current naming practices and propose heuristic rationales and approaches to determine a pithy name instead of an inopportune nosology.

MethodsFirst, we examined the compiled global online news volumes and emotional tones on some inopportune nosology like German measles, Middle Eastern Respiratory Syndrome, Spanish flu, Hong Kong flu, and Huntingtons disease in the wake of COVID-19. Second, we prototypically scrutinize the lexical dynamics and pathological differentials of German measles and common synonyms by leveraging the capacity of the Google Books Ngram Corpus. Third, we demonstrated the empirical approaches to curate an exclusive substitute for an anachronistic nosology German measles based on deep learning models and post-hoc explanations.

ResultsThe infodemiological study shows that the public informed the offensive names with extremely negative tones in textual and visual narratives. The findings of the historiographical study indicate that many synonyms of German measles did not survive, while German measles became an anachronistic usage, and rubella has taken the dominant place since 1994. The PubMedBERT model could identify rubella as a potential substitution for German measles with the highest semantic similarity. The results of the semantic drift experiments further indicate that rubella tends to survive during the ebb and flow of semantic drift.

ConclusionsOur findings indicate that the nosological evolution of anachronistic names could result in sociocultural impacts without a corrective mechanism. To mitigate such impacts, we introduce some ethical principles for formulating an improved naming scheme. Based on deep learning models and post-hoc explanations, our illustrated experiments could provide hallmark references to the remedial mechanism of naming practices and pertinent credit allocations. Remarked Suppression of Aβ42 Protomer-protomer Dissociation Reaction via Pentamer Dimerization Elucidated by Molecular Dynamics Simulation Multimeric protein complexes are molecular apparatuses to regulate biological systems and often determine their fate. Among proteins forming such molecular assemblies, amyloid proteins have drawn attention over a half-century since amyloid fibril formation of these proteins is supposed to be a common pathogenic cause for neurodegenerative diseases. This process is triggered by the accumulation of fibril-like aggregates, while the microscopic mechanisms are mostly elusive due to technical limitation of experimental methodologies in individually observing each of diverse aggregate species in the aqueous solution. We then addressed this problem by employing atomistic molecular dynamics simulations for the paradigmatic amyloid protein, amyloid-{beta} (1-42) (A{beta}42). Seven different dimeric forms of oligomeric A{beta}42 fibril-like aggregate in aqueous solution, ranging from tetramer to decamer, were considered. We found additive effects of the size of these fibril-like aggregates on their thermodynamic stability and have clarified kinetic suppression of protomer-protomer dissociation reactions at and beyond the point of pentamer dimer formation. This observation was obtained from the specific combination of the A{beta}42 protomer structure and the physicochemical condition that we here examined, while it is worthwhile to recall that several amyloid fibrils take dimeric forms of their protomers. We could thus conclude that the stable formation of fibril-like protomer dimer should be involved in a turning point where rapid growth of amyloid fibrils is triggered. 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. Selective Src-Family B Kinase Inhibition Promotes Pulmonary Artery Endothelial Cell Dysfunction. Protein tyrosine kinases (PTKs) are essential for eukaryotic signaling. By targeting select PTKs, the group of drugs known as Tyrosine kinase inhibitors (TKIs) have proven to be effective for treating multiple diseases ranging from cancer to pulmonary fibrosis. However, some TKIs also paradoxically lead to the development of adverse conditions such as pulmonary arterial hypertension (PAH) by promoting endothelial cell dysfunction (ECD). We hypothesize that (1) subsets of PTKs may disproportionately modulate signaling pathways critical for endothelial homeostasis, such as BMPR2 signaling, and (2) inhibiting those pro-endothelial PTKs can promote the development of ECD. Herein we use an agnostic high-throughput siRNA screen to investigate how PTKs affect the canonical BMPR2 signaling pathway. Our major finding is that within the Src-family of non-receptor PTKs, the Src-B family promotes canonical BMPR2 signaling while the Src-A family suppresses it. We focus on two representative members of each family, Lck (for Src-B) and Fyn (for Src-A) that are the strongest activators or inhibitors of BMPR2 signaling in the screen. We confirm that Lck is expressed in the endothelium of pulmonary arteries and show that Lck knockout (termed si-Lck) in pulmonary artery endothelial cells (PAECs) suppresses canonical BMPR2 signaling while Fyn knockout (termed si-Fyn) promotes canonical BMPR2 signaling. Furthermore, Lck and Fyn are responsible for opposing functional behaviors in PAECs: si-Lck promotes apoptosis and interferes with tube formation while si-Fyn suppresses apoptosis and promotes tube formation. After analyzing the whole-transcriptome signature of si-Lck and si-Fyn PAECs we find that in addition to BMPR2 signaling suppression, si-Lck (and not si-Fyn) increases a broad number of ECD markers and increases canonical NF-{kappa}{beta} signaling. In summary, for the first time we show that Src-A and B Family of PTKs exert differential control over key endothelial cell signaling pathways resulting in direct phenotypic consequences. This knowledge may help to guide the design of more precise TKIs which avoid adverse drug reactions brought about through endothelial cell dysfunction. A chemical screen based on an interruption of zebrafish gastrulation identifies the HTR2C inhibitor Pizotifen as a suppressor of EMT-mediated metastasis Metastasis is responsible for approximately 90% of cancer-associated mortality but few models exist that allow for rapid and effective screening of anti-metastasis drugs. Current mouse models of metastasis are too expensive and time consuming to use for rapid and high-throughput screening. Therefore, we created a unique screening concept utilizing conserved mechanisms between zebrafish gastrulation and cancer metastasis for identification of potential anti-metastatic drugs. We hypothesized that small chemicals that interrupt zebrafish gastrulation might also suppress metastatic progression of cancer cells and developed a phenotype-based chemical screen to test the hypothesis. The screen used epiboly, the first morphogenetic movement in gastrulation, as a marker and enabled 100 chemicals to be tested in five hours. The screen tested 1280 FDA-approved drugs and identified Pizotifen, an antagonist for serotonin receptor 2C (HTR2C) as an epiboly-interrupting drug. Pharmacologic and genetic inhibition of HTR2C suppressed metastatic progression in a mouse model. Blocking HTR2C with Pizotifen restored epithelial properties to metastatic cells through inhibition of Wnt-signaling. In contrast, HTR2C induced epithelial to mesenchymal transition (EMT) through activation of Wnt-signaling and promoted metastatic dissemination of human cancer cells in a zebrafish xenotransplantation model. Taken together, our concept offers a novel platform for discovery of anti-metastasis drugs. Is the radial growth of irrigated urban trees more strongly correlated to light and temperature than water? BackgroundReal-time monitoring of tree growth can provide novel information about trees in urban/suburban areas and the myriad ecosystem services they provide. By monitoring irrigated specimen trees we test the hypothesis that in trees with sufficient water, growth is governed by environmental factors regulating energy gain rather than by factors related to water use.

MethodsInternet enabled, high-resolution dendrometers were installed on three trees in Southampton, NY. The instruments, along with a weather station, streamed data to a project web page that was updated once an hour. (https://ecosensornetwork.com). Growing periods were determined using a Hidden Markov Model based on Zweifel et al.s (2016) zero-growth model. Linear models and conditional inference trees correlated environmental variables to growth magnitude and rate of growth.

ResultsGrowth was governed by the interacting environmental variables of air temperature, soil moisture, VPD and took place primarily at night. Radial growth of spruce began April 14 after the accumulation of 69.7 {degrees}C growing degrees days and ended September 7th. Cedar growth began later (April 26th), after the accumulation of 160.6 {degrees}C and ended later (November 3rd). During the observation period, these three modest suburban trees sequestered 108.3 kg of CO2.

ConclusionsThough irrigated, residential tree growth in our experiment was affected by environmental factors relating to both water use and energy gain through photosynthesis. Linking tree growth to fluctuations in environmental conditions facilitates the development of a predictive understanding useful for ecosystem management and growth forecasting across future altering climates. Anisotropic expansion of hepatocyte lumina enforced by apical bulkheads Lumen morphogenesis is key to the function of organs and results from the integration of molecular pathways and mechanical forces1-3. The mechanisms governing anisotropic lumen expansion remain elusive4-6. In contrast to epithelial cells which have simple apico-basal polarity and form tubes, hepatocytes are multi-polar and form narrow lumina that grow anisotropically between adjacent cells, collectively generating a complex 3D network of bile canaliculi (BC)7,8. Here, we studied lumen elongation and BC morphogenesis in differentiating primary mouse hepatoblasts in vitro. Remarkably, we discovered a pattern of specific extensions of the apical membrane traversing the lumen between adjacent hepatocytes and sealed by tight junctions, reminiscent of the bulkheads of boats. These structures were also present in the developing liver. A targeted screen revealed that silencing of Rab35 caused loss of the bulkheads, conversion of hepatocyte into simple epithelial polarity and formation of spherical lumina in vitro. Strikingly, we could re-engineer hepatocyte polarity and tissue morphogenesis in vivo in the embryonic liver, converting BC into simple epithelial tubes. Our results suggest that the apical bulkheads of hepatocytes are cell-intrinsic anisotropic mechanical elements that ensure stability of the elongating lumen between two cells, thus determining the structure of BC during liver tissue morphogenesis. Bispecific antibody neutralizes circulating SARS-CoV-2 variants, prevents escape and protects mice from disease Neutralizing antibodies targeting the receptor binding domain (RBD) of the SARS-CoV-2 Spike (S) are among the most promising approaches against coronavirus disease 2019 (COVID-19)1,2. We developed a bispecific, IgG1-like molecule (CoV-X2) based on two antibodies derived from COVID-19 convalescent donors, C121 and C1353. CoV-X2 simultaneously binds two independent sites on the RBD and, unlike its parental antibodies, prevents detectable S binding to Angiotensin-Converting Enzyme 2 (ACE2), the virus cellular receptor. Furthermore, CoV-X2 neutralizes SARS-CoV-2 and its variants of concern, as well as the escape mutants generated by the parental monoclonals. In a novel animal model of SARS-CoV-2 infection with lung inflammation, CoV-X2 protects mice from disease and suppresses viral escape. Thus, simultaneous targeting of non-overlapping RBD epitopes by IgG-like bispecific antibodies is feasible and effective, combining into a single molecule the advantages of antibody cocktails. Evaluating the Anti-aging Effects of Chinese Herbal Medicine Rhodiola rosea L. in Cultured Keratinocytes Among the many health benefits Chinese herbal medicine (CHM) presents, anti-aging is of special interest (Shen, Jiang, Yang, Wang, & Zhu, 2017; Zhao & Luo, 2017). Reported to possess anti-aging effects, the CHM Rhodiola rosea L., known colloquially as the "golden root", has been widely incorporated in various drinks, daily supplements, and even cosmetics. This study investigates the effects of commercial R. rosea extracts and natural R. rosea roots on preventing UV-induced photoaging of the skin and correlates such effects with the composition of active ingredients in the extracts. To simulate the photoaging process, drug treated HaCaT cells were exposed to UVA and UVB radiation. The pharmacological anti-aging effects of R. rosea extracts were evaluated qualitatively and quantitatively through confocal immunofluorescence images with {gamma}-H2A.X marker and telomerase activity assay (Telo TAGGG Telomerase PCR-ELISA). Preparatory thin layer chromatography and high-performance liquid chromatography were performed to isolate and quantify active ingredients. Cultured HaCaT cells showed morphological change after exposure to both UVA (>15.0 J) and UVB (>2000 mJ). The photoaging of keratinocytes was rescued by pretreating cells with R. rosea extracts as well as salidroside and rosavin active ingredients (P < 0.05). R. rosea-treated cells were characterized by increased telomerase activity and fewer {gamma}-H2A.X foci compared to that of the control. Extracts with better preventative effects contained higher salidroside and rosavin content. The findings in this study reaffirm R. roseas efficacy as an anti-aging remedy and provide a basis for CHMs integration into the mainstream of global healthcare. Integration of the Salmonella Typhimurium methylome and transcriptome reveals DNA methylation and transcriptional regulation are largely decoupled under virulence-related conditions Despite being in a golden age of bacterial epigenomics, little work has systematically examined the plasticity and functional impacts of the bacterial DNA methylome. Here, we leveraged SMRT sequencing to examine the m6A DNA methylome of two Salmonella enterica ser. Typhimurium strains: 14028s and a {Delta}metJ mutant with derepressed methionine metabolism, grown in Luria Broth or a media that simulates the intracellular environment. We find that the methylome is remarkably static--over 95% of adenosine bases retain their methylation status across conditions. Integration of methylation with transcriptomic data revealed limited correlation between changes in methylation and gene expression. Further, examining the transcriptome in {Delta}yhdJ bacteria, lacking the m6A methylase with the most dynamic methylation pattern in our dataset, revealed little evidence of YhdJ-mediated gene regulation. Curiously, despite G(m6A)TC motifs being particularly resistant to change across conditions, incorporating dam mutants into our analyses revealed two examples where changes in methylation and transcription may be linked across conditions. This includes the novel finding that the {Delta}metJ motility defect may be partially driven by hypermethylation of the chemotaxis gene tsr. Together, these data redefine the S. Typhimurium epigenome as a highly stable system that has rare, but important, roles in transcriptional regulation. Incorporating these lessons into future studies will be critical as we progress through the epigenomic era.

ImportanceWhile recent breakthroughs have enabled intense study of bacterial DNA modifications, limitations in current work have potentiated a surprisingly untested narrative that DNA methylation is a common mechanism of the bacterial response to environmental conditions. Essentially, whether epigenetic regulation of bacterial transcription is a common, generalizable phenomenon is a critical unanswered question that we address here. We find that most DNA methylation is static in Salmonella enterica serovar Typhimurium, even when the bacteria are grown under dramatically different conditions that cause broad changes in the transcriptome. Further, even when the methylation of individual bases change, these changes generally do not correlate with changes in gene expression. Finally, we demonstrate methods by which data can be stratified in order to identify coupled changes in methylation and gene expression. A nontoxic tetrodotoxin analog, 5,6,11-trideoxytetrodotoxin, as an olfactory chemoattractant for the grass puffer Toxic puffers contain the potent neurotoxin, tetrodotoxin (TTX). Although TTX is considered to serve as a defense substance, previous behavioral studies have demonstrated that TTX acts as an attractive pheromone for some toxic puffers. To elucidate the physiological mechanism of putative pheromonal action of TTX, we examined whether grass puffers Takifugu alboplumbeus can detect TTX. Electroolfactogram (EOG) results suggest that the olfactory epithelium (OE) of grass puffers responded to a type of TTX analog (5,6,11-trideoxyTTX), although it did not respond to TTX. We also examined the attractive action of 5,6,11-trideoxyTTX on grass puffers by recording their swimming behavior under dark conditions. Grass puffers preferred to stay on the side of the aquarium where 5,6,11-trideoxyTTX was administered, and their swimming speed decreased. Additionally, odorant-induced labeling of olfactory sensory neurons by immunohistochemistry against neural activity marker (phosphorylated extracellular signal regulated kinase; pERK) revealed that labeled olfactory sensory neurons were localized in the region surrounding "islets" where there was considered as nonsensory epithelium. 5,6,11-trideoxyTTX has been known to accumulate in grass puffers, but its toxicity is much lower (almost nontoxic) than TTX. Our results suggest that toxic puffers may positively use this unknown function TTX analog as an olfactory chemoattractant. A network approach to genetic circuit designs As genetic circuits become more sophisticated, the size and complexity of data about their designs increases. This data captured goes beyond monolithic genetic sequences and towards circuit modularity and functional details, which are beneficial for analyzing circuit performance and establishing design automation techniques. However, the accessibility, visualisation and usability of design data (and metadata) have received relatively little attention to date. Here, we present a method to turn circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into sub-networks of relevant information based on requirements such as abstraction, hierarchy and protein interactions. Additionally, several visual changes can be applied, such as colouring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. Therefore, we advocate using networks to structure, access and improve synthetic biology information.