Miracle-dz/UniFAR-FTUs huggingface dataset:
Artificial-neural-network-based nonlinear algebraic models for large-eddy simulation of compressible wall-bounded turbulence

Abstract In this paper, we propose artificial-neural-network-based (ANN-based) nonlinear algebraic models for the large-eddy simulation (LES) of compressible wall-bounded turbulence. An innovative modification is applied to the invariants and the tensor bases of the nonlinear algebraic models through using the local grid widths along each direction to normalise the corresponding gradients of the flow variables. Furthermore, the dimensionless model coefficients are determined by the ANN method. The modified ANN-based nonlinear algebraic model (MANA model) has much higher correlation coefficients and much lower relative errors than the dynamic Smagorinsky model (DSM), Vreman model and wall-adapting local eddy-viscosity model in the a priori test. The significantly more accurate estimations of the mean subgrid-scale (SGS) fluxes of the kinetic energy and temperature variance are also obtained by the MANA models in the a priori test. Furthermore, in the a posteriori test, the MANA model can give much more accurate predictions of the flow statistics and the mean SGS fluxes of the kinetic energy and the temperature variance than other traditional eddy-viscosity models in compressible turbulent channel flows with untrained Reynolds numbers, Mach numbers and grid resolutions. The MANA model has a better performance in predicting the flow statistics in supersonic turbulent boundary layer. The MANA model can well predict both direct and inverse transfer of the kinetic energy and temperature variance, which overcomes the inherent shortcoming that the traditional eddy-viscosity models cannot predict the inverse energy transfer. Moreover, the MANA model is computationally more efficient than the DSM.
Seroprevalence of Toxoplasmosis in Puerperal Women Treated at a Tertiary Referral Hospital

Abstract Objective To evaluate the seroprevalence of toxoplasmosis among puerperal women cared for at a tertiary university hospital and the level of understanding of these puerperal women about toxoplasmosis, vertical transmission, and its prophylaxis. Methods For this cross-sectional study, we evaluated 225 patients using presential interviews, prenatal documentation, and electronic medical records. Data were stored using Research Electronic Data Capture (REDCap) software. Prevalence rates were estimated by the presence of reactive IgG antibodies against Toxoplasma gondii . Data analysis was performed using the chi-square test and calculation of the odds ratio (OR). Seroreactivity to T. gondii and exposure variables (age, educational level, and parity) were analyzed using a confidence interval (95%CI) and a significance level of 5% (p < 0.05). Results The seropositivity rate for T. gondii was 40%. There was no association between seroprevalence and age. Primiparity was a protective factor against seropositivity and low education was a risk factor. Conclusion Knowledge of T. gondii infection and its transmission forms was significantly limited, presenting a risk for acute maternal toxoplasmosis and vertical transmission of this protozoan. Increasing the education level regarding the risk of toxoplasmosis during pregnancy could reduce the rates of infection and vertical transmission of this parasite.
Dual-Task Paradigm Measures of Listening Effort: To Include or Not to Include Secondary Task Responses with Incorrect Primary Task Responses

Abstract Response time–based dual-task paradigms are commonly adopted to measure behavioral listening effort. Most extant studies used an all-response approach that included secondary task responses under both correct and incorrect primary task responses during analysis. However, evidence supporting this strategy is limited. Therefore, the current study investigated the potential differences between including all responses versus only including correct responses. Data from two previous studies were reanalyzed. Experiment 1 included 16 listeners and used a dual-task paradigm to examine the effect of introducing background noise on listening effort. Experiment 2 included 19 participants and used a different dual-task paradigm to examine the effect of reverberation and loudspeaker-to-listener distance on listening effort. ANOVA results obtained using both analysis approaches were compared. The all-response and correct-only approaches revealed similar results. However, larger effect sizes and an additional main effect were found with the all-response approach. The current study supports the use of an all-response approach due to its greater sensitivity to changes in behavioral listening effort. However, a correct-only approach could be utilized to suit specific study purposes.
Impact of Tropospheric Ozone Modulation Due To El Niño on Tides in the MLT

To assess the impacts of the tropospheric ozone modulation due to El Niño on tides, we performed two simulations by using the Ground‐to‐topside Atmosphere Ionosphere model for Aeronomy model: zonally symmetric ozone density and longitudinal ozone variation of an El Niño pattern. Our results show that the ozone modulation strengthens (attenuates) the first symmetric mode of the DW2 (D0 and DW1) tide by ∼+5% (∼−1% and ∼−4%) from ∼20 to ∼100 km altitudes on average. These responses are probably attributed to the tropospheric ozone modulation. These responses are reasonable because both the ozone modulation and these first modes have a peak at the equator. Also, the vertical wavelengths of the first modes are about twice as long as the vertical thickness of the ozone modulation. Our results suggest that the ozone modulation due to El Niño influences the diurnal tides by a few percent because of the ozone modulation spatial structure.
Beyond the reference: gene expression variation and transcriptional response to RNAi in C. elegans

A universal feature of living systems is that natural variation in genotype underpins variation in phenotype. Yet, research in model organisms is often constrained to a single genetic background, the reference strain. Further, genomic studies that do evaluate wild strains typically rely on the reference strain genome for read alignment, leading to the possibility of biased inferences based on incomplete or inaccurate mapping; the extent of reference bias can be difficult to quantify. As an intermediary between genome and organismal traits, gene expression is well positioned to describe natural variability across genotypes generally and in the context of environmental responses, which can represent complex adaptive phenotypes. C. elegans sits at the forefront of investigation into small-RNA gene regulatory mechanisms, or RNA interference (RNAi), and wild strains exhibit natural variation in RNAi competency following environmental triggers. Here, we examine how genetic differences among five wild strains affect the C. elegans transcriptome in general and after inducing RNAi responses to two germline target genes. Approximately 34% of genes were differentially expressed across strains; 411 genes were not expressed at all in at least one strain despite robust expression in others, including 49 genes not expressed in reference strain N2. Despite the presence of hyper-diverse hotspots throughout the C. elegans genome, reference mapping bias was of limited concern: over 92% of variably expressed genes were robust to mapping issues. Overall, the transcriptional response to RNAi was strongly strain-specific and highly specific to the target gene, and the laboratory strain N2 was not representative of the other strains. Moreover, the transcriptional response to RNAi was not correlated with RNAi phenotypic penetrance; the two germline RNAi incompetent strains exhibited substantial differential gene expression following RNAi treatment, indicating an RNAi response despite failure to reduce expression of the target gene. We conclude that gene expression, both generally and in response to RNAi, differs across C. elegans strains such that choice of strain may meaningfully influence scientific conclusions. To provide a public, easily accessible resource for querying gene expression variation in this dataset, we introduce an interactive website at https://wildworm.biosci. gatech.edu/rnai/.
Hierarchical Clustering and Omics Analysis Revealed Massive Molecular Shifts in a Tree under Combined Hypoxia and Salinity

Field and Greenhouse studies that attempted to describe the molecular responses of trees under waterlogging (WL) combined with salinity (ST) are quasi-inexistent. To dissect plant-specific molecular responses and patterns under SWL, we integrated transcriptional and metabolic analyses involving common differentially expressed genes (DEGs) and metabolites (DMs) patterns in Dalbergia odorifera leaflets. SWL-treated seedlings exhibited an impressively high number of DEGs and DMs compared to ST or WL. Although the main common DEGs and DMs showed a neutral pattern, gene ontology enrichment following the classification in different functional categories of SWL-transcripts displayed a predominant synergistic pattern mode. Hierarchical and silhouette analysis regrouped different morpho-physiological clusters following the treatment, SWL was mainly grouped with both single stress. SWL induced a massive shutdown of the photosynthesis apparatus through LHCBs- and PSA-related genes. Starch and plastoglobuli synthesis appeared to be drastically affected by SWL, while ABA content confirmed by ABA synthesis related-genes (ABF, ABA1 and NCED) variations showed a less-needed role. NXN (Nucleoredoxin) genes are the main factors that sustain the antioxidant system under SWL. Here we provide the first molecular responses, characterization and patterns of a tree under SWL that would significantly shed light on our understanding of the molecular mechanisms underlying combined stress.
Gut-associated functions are favored during microbiome assembly across C. elegans life

The microbiome expresses a variety of functions that influence host biology. The range of functions depends on composition of the microbiome, which itself can change during the lifetime of the host as a consequence of neutral assembly processes, host-mediated selection, and/or environmental conditions. To date, the exact dynamics of microbiome assembly, the underlying determinants as well as the resulting effects on host-associated functions are not always well understood. Here, we used the nematode Caenorhabditis elegans and a defined community of fully sequenced, naturally associated bacteria to study microbiome dynamics and functions across the lifetime of individual hosts under controlled experimental conditions. By applying the neutral and null models, we demonstrate that bacterial community composition initially shows strongly declining levels of stochasticity, which, however, increase during late worm life, suggesting the action of random assembly processes in aged hosts following first colonization of C. elegans. The adult microbiome is enriched in strains of the genera Ochrobactrum and Enterobacter in comparison to the direct substrate and a host-free control environment. Using pathway analysis, metabolic, and ecological modelling, we further found that the lifetime assembly dynamics lead to an increase in gut-associated functions in the host-associated microbiome, possibly indicating that the initially colonizing bacteria are beneficial for the worm. Overall, our study introduces a framework for studying microbiome assembly dynamics based on the stochastic models and inference of functions, yielding new insights into the processes determining host-associated microbiome composition and function. Importance The microbiome plays a crucial role in host biology, with its functions depending on microbiome composition that can change during a host’s lifetime. To date, the dynamics of microbiome assembly and the resulting functions are not well understood. This study introduces a new approach to characterize the functional consequences of microbiome assembly by modelling both, the relevance of stochastic processes and metabolic characteristics of microbial community changes. The approach was applied to experimental time series data, obtained for the microbiome of the nematode Caenorhabditis elegans. The results revealed significant differences in host-associated and environmental microbiomes. Stochastic processes only played a minor role, and the host showed an increase in beneficial bacteria and an enrichment of gut-associated functions, possibly indicating that the host actively shapes composition of its microbiome. Overall, this study provides a framework for studying microbiome assembly dynamics and yields new insights into C. elegans microbiome functions.
Understanding Complex Trait Susceptibilities and Ethnical Diversity in a Sample of 4,145 Russians Through Analysis of Clinical and Genetic Data

The population of Russia consists of more than 150 local ethnicities. The ethnic diversity and geographic origins, which extend from eastern Europe to Asia, make the population uniquely positioned to investigate the shared properties of inherited disease risks between European and Asian ethnicities. We present the analysis of genetic and phenotypic data from a cohort of 4,145 individuals collected in three metro areas in western Russia. We show the presence of multiple admixed ancestry clusters spanning from primarily European to Asian and high identity-by-descent sharing with the Finnish population. As a result, there was notable enrichment of Finnish-specific variants in Russia. We illustrate the utility of Russian-descent cohorts for discovery of novel population-specific genetic associations, as well as replication of previously identified associations that were thought to be population-specific in other cohorts. Finally, we provide access to a database of GWAS results for 465 unique phenotypes and allele frequencies.
Genome-wide characterization of T cell responses to Bordetella pertussis reveals broad reactivity and similar polarization irrespective of childhood vaccination profiles

The incidence of whooping cough (pertussis), the respiratory disease caused by Bordetella pertussis (BP) has increased in recent years, and it is suspected that the switch from whole-cell pertussis (wP) to acellular pertussis (aP) vaccines may be a contributing factor to the rise in morbidity. While a growing body of evidence indicates that T cells play a role in the control and prevention of symptomatic disease, nearly all data on human BP-specific T cells is related to the four antigens contained in the aP vaccines, and data detailing T cell responses to additional non-aP antigens, are lacking. Here, we derived a full-genome map of human BP-specific CD4+ T cell responses using a high-throughput ex vivo Activation Induced Marker (AIM) assay, to screen a peptide library spanning over 3000 different BP ORFs. First, our data show that BP specific-CD4+ T cells are associated with a large and previously unrecognized breadth of responses, including hundreds of targets. Notably, fifteen distinct non-aP vaccine antigens were associated with reactivity comparable to that of the aP vaccine antigens. Second, the overall pattern and magnitude of CD4+ T cell reactivity to aP and non-aP vaccine antigens was similar regardless of aP vs wP childhood vaccination history, suggesting that the profile of T cell reactivity in adults is not driven by vaccination, but rather is likely driven by subsequent asymptomatic or sub-clinical infections. Finally, while aP vaccine responses were Th1/Th2 polarized as a function of childhood vaccination, CD4+ T cell responses to non-aP BP antigens vaccine responses were not, suggesting that these antigens could be used to avoid the Th2 bias associated with aP vaccination. Overall, these findings enhance our understanding of human T cell responses against BP and suggest potential targets for designing next-generation pertussis vaccines.
xTrimoGene: An Efficient and Scalable Representation Learner for Single-Cell RNA-Seq Data

The advances in high-throughput sequencing technology have led to significant progress in measuring gene expressions in single-cell level. The amount of publicly available single-cell RNA-seq (scRNA-seq) data is already surpassing 50M records for human with each record measuring 20,000 genes. This highlights the need for unsupervised representation learning to fully ingest these data, yet classical transformer architectures are prohibitive to train on such data in terms of both computation and memory. To address this challenge, we propose a novel asymmetric encoder-decoder transformer for scRNA-seq data, called xTrimoGene, which leverages the sparse characteristic of the data to scale up the pre-training. This scalable design of xTrimoGene reduces FLOPs by one to two orders of magnitude compared to classical transformers while maintaining high accuracy, enabling us to train the largest transformer models over the largest scRNA-seq dataset today. Our experiments also show that the performance of xTrimoGene improves as we increase the model sizes, and it also leads to SOTA performance over various downstream tasks, such as cell classification, perturb-seq effect prediction, and drug combination prediction.
In vitro screening of non-antibiotic alternative growth promoter combinations in broilers

Available research on non-antibiotic alternative growth promoter (NAGPs) mainly focuses on the effect of a single preparation on the substitution effect of antibiotics. However, different NAGP might work together in harmony. Studies related to NAGP combinations are lacking. This study aimed to screen six non-antibiotic alternative growth promoter combinations (NAGPCs) in vitro so as to find a better alternative method to ensure feed efficiency and the broiler health. Pepsin and 42-d broiler ileal fluid were used for the in vitro digestion test, and the optimal addition levels of NAGPs and NAGPCs were selected based on dry matter (DM) and organic matter (OM) digestibility, microbiota of digestive fluid, and antioxidant capacity of digestive fluid. Results showed the optimum addition amount of Mannose oligosaccharide (MOS), fruit oligosaccharide (FOS), mannanase (MAN), Bacillus subtilis (BS), sodium butyrate (SB), guanidinoacetic acid (CA), xylanase (XYL), glucose oxidase (GO), and phytase (PT) were 0.2%, 0.9%, 0.03%, 0.05%, 0.08%, 0.002%, 0.008%, and 0.004%. The six best combinations were 0.2%MOS + 0.03%MAN + 0.15%SB, 0.2%MOS + 0.03%MAN + 0.05%BS, 0.2%MOS + 0.9%FOS + 0.15%SB, 0.2%MOS + 0.9%FOS + 0.05%BS, 0.2%MOS + 0.9%FOS + 0.03%MAN, and 0.2%MOS + 0.05%BS + 0.004%PT. In conclusion, NAGPCs improved the apparent digestibility of ileal DM and OM, intestinal flora and antioxidant capacity. Comparatively, under this condition, using NAGPC has more beneficial effects than using non-antibiotic alternative growth promoter.
Understanding the phytochemical diversity of plants: Quantification, variation and ecological function

Plants produce a great number of phytochemical compounds mediating a variety of different functions. Recently, phytochemical diversity (chemodiversity), a way which to quantify the complex phenotype formed by sets of phytochemicals, has been suggested to be important for function. However, no study has systematically examined the potential (in)direct functional importance of chemodiversity on a general level, partly due to a lack of an agreement on how to quantify this aspect of the plant phenotype. This paper has four aims: 1) We discuss how chemodiversity (deconstructed into components of richness, evenness and disparity) may quantify different aspects of the phenotype that are ecologically relevant. 2) We systematically review the literature on chemodiversity to examine methodological practices, explore ecological patterns of variability in diversity across different levels of biological organization, and investigate the functional role of this diversity in interactions between plants and other organisms. 3) We provide a framework facilitating decisions on which measure of chemodiversity is best used in different contexts. 4) We outline open questions and avenues for future research in this area. A more thorough understanding of phytochemical diversity will increase our knowledge on the functional role phytochemical compounds, and how they shape ecological interactions between plants and their environment.
Propriétés asymptotiques des probabilités de transition des processus de Markov récurrents

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A beneficial adaptive role for CHOP in driving cell fate selection during ER stress

Cellular stresses elicit signaling cascades that are capable of either mitigating the inciting dysfunction or initiating cell death. During endoplasmic reticulum (ER) stress, the transcription factor CHOP is widely recognized to promote cell death. However, it is not clear whether CHOP also has a beneficial role during adaptation. Here, we have combined a new, versatile, genetically modified Chop allele with single cell analysis and with stresses of physiological intensity, to rigorously examine the contribution of CHOP to cell fate. Paradoxically, we found that CHOP promoted death in some cells, but proliferation—and hence recovery—in others. Strikingly, this function of CHOP conferred to cells a stress-specific competitive growth advantage. The dynamics of CHOP expression and UPR activation at the single cell level suggested that CHOP maximizes UPR activation, which in turn favors stress resolution, subsequent UPR deactivation, and proliferation. Taken together, these findings suggest that CHOP’s function can be better described as a “stress test” that drives cells into either of two mutually exclusive fates—adaptation or death—during stresses of physiological intensity.
Proteomics: Potential techniques for discovering the pathogenesis of connective tissue diseases-interstitial lung disease

Interstitial lung disease (ILD) is one of the most serious lung complications of connective tissue disease (CTD). The application of proteomics in the past decade has revealed that various proteins are involved in the pathogenesis of each subtype of CTD-ILD through different pathways, providing novel ideas to study pathological mechanisms and clinical biomarkers. On this basis, a multidimensional diagnosis or prediction model is established. This paper reviews the results of proteomic detection of different subtypes of CTD-ILD and discusses the role of some differentially expressed proteins in the development of pulmonary fibrosis and their potential clinical applications.