Assessment and Optimization of the Interpretability of Machine Learning Models Applied to Transcriptomic Data Explainable artificial intelligence aims to interpret how the machine learning models make decisions, and many model explainers have been developed in the computer vision field. However, the understandings of the applicability of these model explainers to biological data are still lacking. In this study, we comprehensively evaluated multiple explainers by interpreting pretrained models of predicting tissue types from transcriptomic data, and by identifying top contributing genes from each sample with the greatest impacts on model prediction. To improve the reproducibility and interpretability of results generated by model explainers, we proposed a series of optimization strategies for each explainer on two different model architectures of Multilayer Perceptron (MLP) and Convolutional Neural Network (CNN). We observed three groups of explainer and model architecture combinations with high reproducibility. Group II, which contains three model explainers on aggregated MLP models, identified top contributing genes in different tissues that exhibited tissue-specific manifestation and were potential cancer biomarkers. In summary, our work provides novel insights and guidance for exploring biological mechanisms using explainable machine learning models.
Hierarchical autoencoder-based integration improves performance in multi-omics cancer survival models through soft modality selection With decreasing costs of high-throughput sequencing, more and more datasets providing omics profiles of cancer patients become available. Thus, novel survival analysis approaches integrating these differently sized and heterogeneous molecular and clinical groups of variables start being developed. Due to the difficulty of the task of multi-omics data integration, the Cox Proportional-Hazards (PH) model using clinical data has remained one of the best-performing techniques, barely outperformed by models using molecular data modalities. There is therefore a need for methods that can successfully perform multi-omics integration in survival analysis and outperform the clinical Cox PH model. Moreover, while certain deep learning methods have been shown to provide state-of-the-art accuracy of cancer survival prediction, most of them show no benefit or even decay in performance when integrating a larger number of modalities, further motivating a need to investigate how modality-specific representations should be integrated when using neural networks for multi-omics integration. We benchmarked multiple integration techniques for a neural network architecture, revealing that hierarchical autoencoder-based integration of modality-specific representations outperformed other methods such as max-pooling and was comparable with state-of-the-art statistical approaches for multi-omics integration. Further, we showed that the hierarchical autoencoder-based integration of modality-specific representations achieved increased performance through a soft modality selection mechanism, focusing on the most informative modalities for each cancer. We thus framed multiomics integration as a partial group-wise feature selection problem, highlighting that only those models performed well that could adequately weight important modalities in the presence of the high noise imposed by less important modalities.
A platform of patient-derived microtumors identifies individual treatment responses and therapeutic vulnerabilities in ovarian cancer. BackgroundIn light of the frequent development of therapeutic resistance in cancer treatment, there is a strong need for personalized model systems representing patient tumor heterogeneity, while enabling parallel drug testing and identification of appropriate treatment responses in individual patients. Using ovarian cancer as a prime example of a heterogeneous tumor disease with complex microenvironment and high recurrence rates, we developed a 3D preclinical ovarian cancer model comprised of patient-derived microtumors (PDM) and autologous tumor-infiltrating lymphocytes (TILs) for identification of treatment vulnerabilities and validation of anti-cancer drug efficacy using immunohistochemistry, immune cell phenotyping, functional assays and protein profiling analyses.

MethodsPDM and TILs were isolated from fresh primary ovarian cancer tissue specimen using mechanical disruption and limited enzymatic digestion and were subsequently cultured in suspension in defined media in the absence of serum. The heterogeneous cellular composition of isolated PDM as well as autologous TILs was analyzed by FFPE immunohistochemistry and multi-color flow cytometry, respectively. For in-depth protein profiling of PDM we established Reverse Phase Protein Array (RPPA) analyses of >110 total and phospho-proteins. Treatment efficacy in response to chemotherapeutics as well as immunotherapeutic compounds was assessed in PDM and PDM-TIL co-cultures using a functional viability assay in microplate format.

ResultsThe enzymatic digestion of primary ovarian cancer tissue and suspension culture in defined serum-free media allowed fast and efficient recovery of patient-derived microtumors (PDM). Immunohistochemical analyses demonstrated histopathological comparability of ovarian cancer PDM with corresponding patient tumor tissue. Reverse Phase Protein Array (RPPA)-based analyses of >110 total and phospho-proteins enabled the identification of patient-specific sensitivities to standard, platinum-based therapy and thereby the prediction of potential treatment-responders. Finally, combining PDM and autologous TILs for individual efficacy testing of immune checkpoint inhibitor treatment demonstrated the potential for patient-specific enhancement of cytotoxic TIL activity by this therapeutic approach.

Conclusion3D patient-derived ovarian cancer microtumors represent a preclinical, ex vivo tumor model that reflects intertumoral heterogeneity and represent the cellular complexity of individual patient tumors. Combining protein pathway analysis and anti-cancer drug efficacy testing of PDM enables drug mode-of-action analyses and therapeutic sensitivity prediction within a clinically relevant time frame after surgery. Follow-up studies in larger cohorts are currently under way to further evaluate the applicability of this platform to support clinical decision-making and personalizing cancer treatment. The M1 and pre-M1 segments contribute differently to ion selectivity in ASICs and ENaCs The ability to discriminate between different ionic species, termed ion selectivity, is a key feature of ion channels and forms the basis for their physiological function. Members of the degenerin/epithelial sodium channel (DEG/ENaC) superfamily of trimeric ion channels are typically sodium selective, but to a surprisingly variable degree. While acid-sensing ion channels (ASICs) are weakly sodium selective (sodium:potassium around 10:1), ENaCs show a remarkably high preference for sodium over potassium (>500:1). The most obvious explanation for this discrepancy may be expected to originate from differences in the pore-lining second transmembrane segment (M2). However, these show a relatively high degree of sequence conservation between ASICs and ENaCs and previous functional and structural studies could not unequivocally establish that differences in M2 alone can account for the disparate degrees of ion selectivity. By contrast, surprisingly little is known about the contributions of the first transmembrane segment (M1) and the preceding pre-M1 region. In this study, we use conventional and non-canonical amino acid-based mutagenesis in combination with a variety of electrophysiological approaches to show that the pre-M1 and M1 regions of mASIC1a channels are major determinants of ion selectivity. Mutational investigations of the corresponding regions in hENaC show that they contribute less to ion selectivity, despite affecting ion conductance. In conclusion, our work supports the notion that the remarkably different degrees of sodium selectivity in ASICs and ENaCs are achieved through different mechanisms. The results further highlight how M1 and pre-M1 are likely to differentially affect pore structure in these related channels. Identifying and correcting for misspecifications in GWAS summary statistics and polygenic scores Publicly available genome-wide association studies (GWAS) summary statistics exhibit uneven quality, which can impact the validity of follow-up analyses. First, we present an overview of possible misspecifications that come with GWAS summary statistics. Then, in both simulations and real data analyses, we show that additional information such as imputation INFO scores, allele frequencies, and per-variant sample sizes in GWAS summary statistics can be used to detect possible issues and correct for misspecifications in the GWAS summary statistics. One important motivation for us is to improve the predictive performance of polygenic scores built from these summary statistics. Unfortunately, due to the lack of reporting standards for GWAS summary statistics, this additional information is not systematically reported. We also show that using well-matched LD references can improve model fit and translate into more accurate prediction. Finally, we discuss how to make polygenic score methods such as lassosum and LDpred2 more robust to these misspecifications to improve their predictive power. Naming of human diseases on the wrong side of history 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. Effects of a 33-ion sequential beam galactic cosmic ray analog on male mouse behavior and evaluation of CDDO-EA as a radiation countermeasure In long-term spaceflight, astronauts will face unique cognitive loads and social challenges which will be complicated by communication delays with Earth. It is important to understand the central nervous system (CNS) effects of deep spaceflight and the associated unavoidable exposure to galactic cosmic radiation (GCR). Rodent studies show single- or simple-particle combination exposure alters CNS endpoints, including hippocampal-dependent behavior. An even better Earth-based simulation of GCR is now available, consisting of a 33-beam (33-GCR) exposure. However, the effect of whole-body 33-GCR exposure on rodent behavior is unknown, and no 33-GCR CNS countermeasures have been tested. Here astronaut-age-equivalent (6mo-old) C57BL/6J male mice were exposed to 33-GCR (75cGy, a Mars mission dose). Pre-/during/post-Sham or 33-GCR exposure, mice received a diet containing a  vehicle formulation alone or with the antioxidant/anti-inflammatory compound CDDO-EA as a potential countermeasure. Behavioral testing beginning 4mo post-irradiation suggested radiation and diet did not affect measures of exploration/anxiety-like behaviors (open field, elevated plus maze) or recognition of a novel object. However, in 3-Chamber Social Interaction (3-CSI), CDDO-EA/33-GCR mice failed to spend more time exploring a holder containing a novel mouse vs. a novel object (empty holder), suggesting sociability deficits. Also, Vehicle/33-GCR and CDDO-EA/Sham mice failed to discriminate between a novel stranger vs. familiarized stranger mouse, suggesting blunted preference for social novelty. CDDO-EA given pre-/during/post-irradiation did not attenuate the 33-GCR-induced blunting of preference for social novelty. Future elucidation of the mechanisms underlying 33-GCR-induced blunting of preference for social novelty will improve risk analysis for astronauts which may in-turn improve countermeasures. The extracellular matrix controls stem cell specification and crypt morphology in the developing and adult gut The rapid renewal of the epithelial gut lining is fuelled by stem cells that reside at the base of intestinal crypts. In recent years, the signal transduction pathways and morphogens that regulate intestinal stem cell self-renewal and differentiation have been extensively characterised. In contrast, although extracellular matrix (ECM) components form an integral part of the intestinal stem cell niche, their direct influence on the cellular composition is less well understood. Here, we set out to systematically compare the effect of two major ECM classes, fibrillar collagen type I and the basement membrane, on the intestinal epithelium. We found that both collagen I and laminin-containing cultures allow growth of small intestinal epithelial cells with all differentiated and undifferentiated cell types present in both cultures, albeit at different ratios. Specific to the collagen culture was a subset of cells with a fetal-like gene expression program. In contrast, laminin, but not collagen IV, increased Lgr5+ stem cells and Paneth cells, and induced crypt-like morphology changes. The transition from a collagen culture to a laminin culture, resembles the gut development in vivo. Here, the ECM is dramatically remodelled by mesenchymal cells, which is accompanied by a specific and local expression of the laminin receptor ITGA6 in the crypt-forming epithelium. This laminin:ITGA6 signalling is essential for the stem cell induction and crypt formation in vitro. Importantly, deletion of laminin in the adult mouse results in a fetal-like epithelium with a marked reduction of adult intestinal stem cells. Overall, our data support the hypothesis that the formation of intestinal crypts is induced by an increased laminin concentration in the ECM. Computational modeling and quantitative cell physiology reveal central parameters for the brassinosteroid-regulated cell growth of the Arabidopsis root Brassinosteroids (BR) are key hormonal regulators of plant development. However, whereas the individual components of BR perception and signaling are well characterized experimentally, the question of how they can act and whether they are sufficient to carry out the critical function of cellular elongation remains open. Here, we combined computational modeling with quantitative cell physiology to understand the dynamics of the plasma membrane (PM)-localized BR response pathway during the initiation of cell elongation in the epidermis of the Arabidopsis root tip. The model, consisting of ordinary differential equations, comprises the BR induced hyperpolarization of the PM, the acidification of the apoplast and subsequent cell wall swelling. We demonstrated that the competence of the root epidermal cells for the BR response predominantly depends on the amount and activity of H+-ATPases in the PM. The model further predicted that an influx of cations is required to compensate for the shift of positive charges caused by the apoplastic acidification. A potassium channel was subsequently identified and experimentally characterized, fulfilling this function. Thus, we established the landscape of components and parameters capable of triggering and guiding cellular elongation through the fast response to BRs, a central process in plant development. Synthetic periphyton as a model system to understand species dynamics in complex microbial freshwater communities Phototrophic biofilms, also known as periphyton, are microbial freshwater communities that drive crucial ecological processes in streams and lakes. Gaining a deep mechanistic understanding of the biological processes occurring in natural periphyton remains challenging due to the high complexity and variability of such communities. To address this challenge, we rationally developed a workflow to construct a synthetic community by co-culturing 26 phototrophic species (i.e., diatoms, green algae and cyanobacteria) that were inoculated in a successional sequence to create a periphytic biofilm on glass slides. We show that this community is diverse, stable and highly reproducible in terms of microbial composition, function and 3D spatial structure of the biofilm. We also demonstrate the ability to monitor microbial dynamics at the single species level during periphyton development and how their abundances are impacted by stressors such as increased temperature and a herbicide, singly and in combination. Overall, such a synthetic periphyton, grown under controlled conditions, can be used as a model system for theory testing through targeted manipulation. A new method based on the von Mises-Fisher distribution shows that a minority of liver-localized CD8 T cells display hard-to-detect attraction to Plasmodium-infected hepatocytes Malaria is a disease caused by Plasmodium parasites, resulting in over 200 million infections and 400,000 deaths every year. A critical step of malaria infection is when sporozoites, injected by mosquitoes, travel to the liver and form liver stages. Malaria vaccine candidates which induce large numbers of malaria-specific CD8 T cells in mice are able to eliminate all liver stages, preventing fulminant malaria. However, how CD8 T cells find all parasites in 48 hours of the liver stage lifespan is not well understood. Using intravital microscopy of murine livers, we generated unique data on T cell search for malaria liver stages within a few hours after infection. To detect attraction of T cells to an infection site, we used the von Mises-Fisher distribution in 3D, similar to the 2D von Mises distribution previously used in ecology. Our results suggest that the vast majority (70-95%) of malaria-specific and non-specific liver-localized CD8 T cells did not display attraction towards the infection site, suggesting that the search for malaria liver stages occurs randomly. However, a small fraction (15-20%) displayed weak but detectable attraction towards parasites which already had been surrounded by several T cells. We found that speeds and turning angles correlated with attraction, suggesting that understanding mechanisms that determine the speed of T cell movement in the liver may improve the efficacy of future T cell-based vaccines. Stochastic simulations suggest that a small movement bias towards the parasite dramatically reduces the number of CD8 T cells needed to eliminate all malaria liver stages, but to detect such attraction by individual cells requires data from long imaging experiments which are not currently feasible. Importantly, as far as we know this is the first demonstration of how activated/memory CD8 T cells might search for the pathogen in nonlymphoid tissues a few hours after infection. We have also established a framework for how attraction of individual T cells towards a location in 3D can be rigorously evaluated. 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. 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. Polycystins are upregulated in fibrotic kidneys and promote renal fibrosis Autosomal polycystic kidney disease (ADPKD) is caused by mutations in PKD1or PKD2 gene, which encodes polycystin-1 or polycystin-2 respectively. Paradoxically, polycystins are up-regulated in human ADPKD kidneys and overexpression of polycystin-1 even induced renal cyst formation in mice, suggesting that up-regulation of polycystin is pathogenic. In this study, we determined the role of polycystin in renal fibrosis and explored its underlying mechanisms. We found that the expression of polycystin-1 or polycystin-2 was positively correlated with the expression of collagen-I in the kidney of three different fibrotic mouse models. Pharmaceutical inhibition or genetic knockout of polycystin-2 reduced the expression of pro-fibrotic markers in fibrotic kidneys of two animal models. Moreover, conditional knockout of Pkd1 gene attenuated renal fibrosis in two mouse models. Enhancer of Zeste homolog 2 (EZH2) is a methyltransferase which plays important role in renal fibrosis. We found that EZH2 was positively correlated with the expression of polycystins in fibrotic kidneys. Conditional knockout of the Ezh2 attenuated the anti-fibrotic responses induced by Pkd1 deletion in fibrotic kidneys.

In conclusion, polycystins are up-regulated in injured kidneys and polycystins promote renal fibrosis through up-regulation of EZH2 in fibrotic kidneys, suggesting that renal fibrosis in polycystic kidneys is not the direct effect of PKD gene mutations.

SignificanceMutations of polycystins cause autosomal polycystic kidney disease (ADPKD) which is associated with increased renal fibrosis in cystic kidneys. However, the role of polycystin in renal fibrosis remains unclear. Here, we showed that the expression of polycystins is positively correlated with the development of renal fibrosis in injured kidneys. Pharmaceutical inhibition or genetic deletion of polycystin-2 attenuated renal fibrosis in fibrotic kidneys. Moreover, genetic deletion of polycystin-1 inhibited renal fibrosis in two different animal models. Finally, we showed that ablation of the methyltransferase EZH2 mitigated the anti-fibrotic effect of polycystin-1 deletion in fibrotic kidneys. We conclude that polycystin promotes through EZH2 and renal fibrosis in cystic kidney is not the direct effect of PKD gene mutations. 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. Pseudomonas aeruginosa C-terminal processing protease CtpA assembles into a hexameric structure that requires activation by a spiral-shaped lipoprotein binding partner Pseudomonas aeruginosa CtpA is a carboxyl terminal-processing protease that partners with the outer membrane lipoprotein LbcA to degrade at least five cell wall-associated proteins, four of which are cell wall hydrolases. This activity plays an important role in supporting P. aeruginosa virulence in a mouse model of acute pneumonia. However, almost nothing is known about the molecular mechanisms underlying CtpA and LbcA function. Here, we used structural analysis to show that CtpA alone assembles into an inactive hexamer comprising a trimer of dimers, which limits its substrate access and prevents nonspecific degradation. The adaptor protein LbcA is a right-handed open spiral with 11 tetratricopeptide repeats, which might wrap around a substrate to deliver it to CtpA for degradation. By structure-guided mutagenesis and functional assays, we also showed that the interfaces of the CtpA trimer-of-dimers, and an N-terminal helix of LbcA, are important for LbcA-mediated substrate degradation by CtpA both in vitro and in vivo. This work improves our understanding of the molecular mechanism of a CTP within the C-terminal processing peptidase-3 group.

IMPORTANCECarboxyl-terminal processing proteases (CTPs) are found in all three domains of life. In bacteria, some CTPs have been associated with virulence, raising the possibility that they could be theraputic targets. However, relatively little is known about their molecular mechanisms of action. In Pseudomonas aeruginosa, CtpA supports virulence by working in complex with the outer membrane lipoprotein LbcA to degrade cell wall hydrolases. Here, we report structure-function analyses of CtpA and LbcA, which reveals that CtpA assembles into an inactive hexamer comprising a trimer of dimers. LbcA is monomeric, with an N-terminal region important for binding to and activating CtpA, followed by a spiral structure composed of 11 tetratricopetide repeats, which could wrap around a substrate for delivery to CtpA. This work provides the first structure of a CTP-3 group member, revealing a unique mutimeric arrangement and insight into how this important proteolytic system functions. A novel nongenetic murine model of hyperglycemia and hyperlipidemia-associated aggravated atherosclerosis ObjectiveAtherosclerosis, the main pathology underlying cardiovascular diseases is accelerated in diabetic patients. Genetic mouse models require breeding efforts which are time-consuming and costly. Our aim was to establish a new nongenetic model of inducible metabolic risk factors that mimics hyperlipidemia, hyperglycemia, or both and allows the detection of phenotypic differences dependent on the metabolic stressor(s).

Methods and ResultsWild-type mice were injected with gain-of-function PCSK9D377Y (proprotein convertase subtilisin/kexin type 9) mutant adeno-associated viral particles (AAV) and streptozotocin and fed either a high-fat diet (HFD) for 12 or 20 weeks or a high-cholesterol/high-fat diet (Paigen diet, PD) for 8 weeks. To evaluate atherosclerosis, two different vascular sites (aortic sinus and the truncus of the brachiocephalic artery) were examined in the mice. Combined hyperlipidemic and hyperglycemic (HGHCi) mice fed a HFD or PD displayed characteristic features of aggravated atherosclerosis when compared to hyperlipidemia (HCi HFD or PD) mice alone. Atherosclerotic plaques of HGHCi HFD animals were larger, showed a less stable phenotype (measured by the increased necrotic core area, reduced fibrous cap thickness, and less -SMA-positive area) and had more inflammation (increased plasma IL-1{beta} level, aortic pro-inflammatory gene expression, and MOMA-2-positive cells in the BCA) after 20 weeks of HFD. Differences between the HGHCi and HCi HFD models were confirmed using RNA-seq analysis of aortic tissue, revealing that significantly more genes were dysregulated in mice with combined hyperlipidemia and hyperglycemia than in the hyperlipidemia-only group. The HGHCi-associated genes were related to pathways regulating inflammation (increased Cd68, iNos, and Tnfa expression) and extracellular matrix degradation (Adamts4 and Mmp14). When comparing HFD with PD, the PD aggravated atherosclerosis to a greater extent in mice and showed plaque formation after 8 weeks. Hyperlipidemic and hyperglycemic mice fed a PD (HGHCi PD) showed less collagen (Sirius red) and increased inflammation (CD68-positive cells) within aortic plaques than hyperlipidemic mice (HCi PD). HGHCi-PD mice represent a directly inducible hyperglycemic atherosclerosis model compared with HFD-fed mice, in which atherosclerosis is severe by 8 weeks.

ConclusionWe established a nongenetically inducible mouse model allowing comparative analyses of atherosclerosis in HCi and HGHCi conditions and its modification by diet, allowing analyses of multiple metabolic hits in mice. Heat-induced transposition increases drought tolerance in Arabidopsis Eukaryotic genomes contain a vast diversity of transposable elements (TEs). Formerly often described as selfish and parasitic DNA sequences, TEs are now recognized as a source of genetic diversity and powerful drivers of evolution. Yet, because their mobility is tightly controlled by the host, studies experimentally assessing how fast TEs may mediate the emergence of adaptive traits are scare. Here, we show that the heat-induced transposition of a low-copy TE increases phenotypic diversity and leads to the emergence of drought-tolerant individuals in Arabidopsis thaliana. We exposed high-copy TE lines (hcLines) with up to [~]8 fold increased copy numbers of the heat-responsive ONSEN TE (AtCOPIA78) to drought as a straightforward and ecologically highly relevant selection pressure. We provide evidence for increased drought tolerance in five out of the 23 tested hcLines and further pinpoint one of the causative mutations to an exonic insertion of ONSEN in the ribose-5-phosphate-isomerase 2 gene. The resulting loss-of-function mutation caused a decreased rate of photosynthesis and water consumption. This is one of the rare empirical examples substantiating the adaptive potential of mobilized stress-responsive TEs in eukaryotes. Our work sheds light on the relationship between TEs and their hosts and demonstrates the importance of TE-mediated loss-of-function mutations in stress adaptation, particularly in the face of global warming. Clofoctol inhibits SARS-CoV-2 replication and reduces lung pathology in mice Drug repurposing has the advantage of shortening regulatory preclinical development steps. Here, we screened a library of drug compounds, already registered in one or several geographical areas, to identify those exhibiting antiviral activity against SARS-CoV-2 with relevant potency. Of the 1,942 compounds tested, 21 exhibited a substantial antiviral activity in Vero-81 cells. Among them, clofoctol, an antibacterial drug used for the treatment of bacterial respiratory tract infections, was further investigated due to favorable safety profile and pharmacokinetic properties. Notably, the peak concentration of clofoctol that can be achieved in human lungs is more than 20 times higher than its IC50 measured against SARS-CoV-2 in human pulmonary cells. This compound inhibits SARS-CoV-2 at a post-entry step. Lastly, therapeutic treatment of human ACE2 receptor transgenic mice decreased viral load, reduced inflammatory gene expression and lowered pulmonary pathology. Altogether, these data strongly support clofoctol as a therapeutic candidate for the treatment of COVID-19 patients.

SummaryAntivirals targeting SARS-CoV-2 are sorely needed. In this study, we screened a library of drug compounds and identified clofoctol as an antiviral against SARS-CoV-2. We further demonstrated that, in vivo, this compound reduces inflammatory gene expression and lowers pulmonary pathology. EMBED: a low dimensional reconstruction of subject-specific gut microbiome dynamics based on ecological normal modes Dimensionality reduction can offer unique insights into high dimensional microbiome dynamics by leveraging collective abundance fluctuations of multiple bacteria driven by similar ecological perturbations. However, methods providing lower-dimensional representations of microbiome dynamics both at the community and individual taxa level are not currently available. To that end, we present EMBED: Essential MicroBiomE Dynamics, a probabilistic non-linear tensor factorization approach. Similar to normal mode analysis in structural biophysics, EMBED infers ecological normal modes (ECNs), which represent the unique orthogonal modes capturing the collective behavior of microbial communities. A very small number of ECNs can accurately approximate microbiome dynamics across multiple data sets. Inferred ECNs reflect specific ecological behaviors, providing natural templates along which the dynamics of individual bacteria may be partitioned. Moreover, the multi-subject treatment in EMBED systematically identifies subject-specific and universal abundance dynamics that are not detected by traditional approaches. Collectively, these results highlight the utility of EMBED as a versatile dimensionality reduction tool for studies of microbiome dynamics. 3D viscoelastic drag forces contribute to cell shape changes during organogenesis in the zebrafish embryo The left-right organizer in zebrafish embryos, Kupffers Vesicle (KV), is a simple organ that undergoes programmed asymmetric cell shape changes that are necessary to establish the left-right axis of the embryo. We use simulations and experiments to investigate whether 3D mechanical drag forces generated by the posteriorly-directed motion of the KV through the tailbud tissue are sufficient to drive such shape changes. We develop a fully 3D vertex-like (Voronoi) model for the tissue architecture, and demonstrate that the tissue can generate drag forces and drive cell shape changes. Furthermore, we find that tailbud tissue presents a shear-thinning, viscoelastic behavior consistent with those observed in published experiments. We then perform live imaging experiments and particle image velocimetry analysis to quantify the precise tissue velocity gradients around KV as a function of developmental time. We observe robust velocity gradients around the KV, indicating that mechanical drag forces must be exerted on the KV by the tailbud tissue. We demonstrate that experimentally observed velocity fields are consistent with the viscoelastic response seen in simulations. This work also suggests that 3D viscoelastic drag forces could be a generic mechanism for cell shape change in other biological processes.

HighlightsO_LInew physics-based simulation method allows study of dynamic tissue structures in 3D
C_LIO_LImovement of an organ through tissue generates viscoelastic drag forces on the organ
C_LIO_LIthese drag forces can generate precisely the cell shape changes seen in experiment
C_LIO_LIPIV analysis of experimental data matches simulations and probes tissue mechanics
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Graphical abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY Inferring the neural basis of binaural phenomena with a modified autoencoder Broad organizational features of the auditory pathway have been replicated by artificial neural networks trained on diverse and naturalistic stimuli. It is credible that neural network analogues could also reveal specific neural computations underlying targeted auditory phenomena. This remains to be established. Here, we examined a modified autoencoder (a deep neural network akin to symbolic regression) trained to imitate an auditory behavior rooted in the binaural system. The behavior promoted the use of split-second interaural timing cues to improve the detection of a tone presented in noise. In the optimal network, we observed the emergence of specialized computations with prominent similarities to animal models. Artificial neurons developed a sensitivity to temporal delays that increased deeper into the network and were widely distributed in preference (extending to delays beyond the range permitted by head width), and the ensuing dynamics were consistent with a binaural cross-correlation mechanism. Our results attest to the generality of these solutions for performing signal detection at low frequencies. Moreover, this is a primary demonstration that deep learning methods can be used to infer tangible mechanisms underlying auditory perception.

AUTHOR SUMMARYDo artificial intelligence (AI) systems process sounds in a similar way to the brain? If so, they represent a vital resource with which to investigate sensory systems. Here, we report an AI system that automatically developed auditory computations similar to those described in animal neurophysiology. The network learnt to use subtle discrepancies across its "two ears" to better detect a signal amongst a background noise. In the process, tuning to timing cues and established mechanisms of binaural hearing (relating to the use of both ears) developed internally. The results offer insight into computations occurring in deep brain structures that are difficult to measure with non-invasive techniques. Further, the results endorse informed associations made between AI systems and the auditory brain. First detection of herpesvirus and prevalence 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. Plant host shift: The viability and persistence of a polyphagous, non-native insect Assessing the effects of a plant-host shift is important for monitoring insect populations over long time periods and for interventions in a conservation or pest management framework. In a heterogeneous environment, individuals may disperse between sources and sinks in order to persist. Here we propose a single-species two-patch model that aims to capture the generational movement of an insect that exhibits density-dependent dispersal, to see how shifting between hosts could alter its viability and asymptotic dynamics. We then analyse the stability and persistence properties of the model and further validate it using parameter estimates derived from laboratory experiments. In order to evaluate the potential of this model, we applied it to Drosophila suzukii (Diptera: Drosophilidae), which has become a harmful pest in several countries around the world. Although many studies have investigated the preference and attractiveness of potential hosts on this invasive drosophilid, no studies thus far have investigated whether a shift of fruit host could affect such a species ecological viability or spatiotemporal persistence. The model results show that a shift in host choice can significantly affect the growth potential and fecundity of a species such as D. suzukii, which ultimately could aid such invasive populations in their ability to persist within a changing environment. An alternatively spliced TREM2 isoform lacking the ligand binding domain is expressed in human brain BackgroundGenetic variants in TREM2 are strongly associated with Alzheimers Disease (AD) risk but alternative splicing in TREM2 transcripts has not been comprehensively described.

ObjectiveRecognizing that alternative splice variants can result in reduced gene expression and/or altered function, we sought to fully characterize splice variation in TREM2.

MethodsHuman blood and anterior cingulate autopsy tissue from 61 donors were used for end-point and quantitative PCR and Western blotting to identify and quantify novel TREM2 isoforms.

ResultsIn addition to previously described transcripts lacking exon 3 or exon 4, or retaining part of intron 3, we identified novel isoforms lacking exon 2, along with isoforms lacking multiple exons. Isoforms lacking exon 2 were predominant at approximately 10% of TREM2 mRNA in the brain. Expression of TREM2 and frequency of exon 2 skipping did not differ between AD samples and non-AD controls (p = 0.1268 and p = 0.4909, respectively). Further, these novel splice isoforms were also observed across multiple tissues with similar frequency (range 5.3 - 13.0%). We found that the exon 2 skipped isoform D2-TREM2 is translated to protein and localizes similarly to full-length TREM2 protein, that both proteins are primarily retained in the Golgi complex, and that D2-TREM2 is expressed in AD and non-AD brain.

ConclusionSince the TREM2 ligand binding domain is encoded by exon 2, and skipping this exon retains reading frame while conserving localization, we hypothesize that D2-TREM2 acts as an inhibitor of TREM2 and targeting TREM2 splicing may be a novel therapeutic pathway for AD. Interfacial tension driven open droplet microfluidics We developed an open channel droplet microfluidic system that autonomously generates droplets at low Ca (~10-4-10-3) by leveraging competing hydrostatic and capillary pressure. With only our open channel polytetrafluoroethylene (PTFE) device, pipettes, and commercially available carrier fluid, we produce hundreds of microliter droplets; tubing, electronics, or pumps are not required, making droplet technology feasible for research labs without external flow generators. Furthermore, we demonstrated conceptual applications that showcase the process of droplet generation, splitting, transport, incubation, mixing, and sorting in our system. Unlike conventional droplet microfluidics, the open nature of the device enables the use of physical tools such as tweezers and styli to directly access the system; with this, we developed a new method of droplet sorting and transfer that capitalizes on the Cheerios effect, the aggregation of buoyant objects along a liquid interface. Our platform offers enhanced usability, direct access to the droplet contents, easy manufacturability, compact footprint, and high customizability. This design is a first step in exploring the space of power-free open droplet microfluidic systems and provide design rules for similar channel designs.