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Genome-wide association studies (GWAS) have identified hundreds of genetic signals associated with autoimmune disease. The majority of these signals are located in non-coding regions and likely impact cis-regulatory elements (cRE). Because cRE function is dynamic across cell types and states, profiling the epigenetic status of cRE across physiological processes is necessary to characterize the molecular mechanisms by which autoimmune variants contribute to disease risk. We localized risk variants from 15 autoimmune GWAS to cRE active during TCR-CD28 co-stimulation of naïve human CD4+ T cells. To characterize how dynamic changes in gene expression correlate with cRE activity, we measured transcript levels, chromatin accessibility, and promoter–cRE contacts across three phases of naive CD4+ T cell activation using RNA-seq, ATAC-seq, and HiC. We identified ~1200 protein-coding genes physically connected to accessible disease-associated variants at 423 GWAS signals, at least one-third of which are dynamically regulated by activation. From these maps, we functionally validated a novel stretch of evolutionarily conserved intergenic enhancers whose activity is required for activation-induced IL2 gene expression in human and mouse, and is influenced by autoimmune-associated genetic variation. The set of genes implicated by this approach are enriched for genes controlling CD4+ T cell function and genes involved in human inborn errors of immunity, and we pharmacologically validated eight implicated genes as novel regulators of T cell activation. These studies directly show how autoimmune variants and the genes they regulate influence processes involved in CD4+ T cell proliferation and activation.

Abstract Genes act in concert with each other in specific contexts to perform their functions. Determining how these genes influence complex traits requires a mechanistic understanding of expression regulation across different conditions. It has been shown that this insight is critical for developing new therapies. Transcriptome-wide association studies have helped uncover the role of individual genes in disease-relevant mechanisms. However, modern models of the architecture of complex traits predict that gene-gene interactions play a crucial role in disease origin and progression. Here we introduce PhenoPLIER, a computational approach that maps gene-trait associations and pharmacological perturbation data into a common latent representation for a joint analysis. This representation is based on modules of genes with similar expression patterns across the same conditions. We observe that diseases are significantly associated with gene modules expressed in relevant cell types, and our approach is accurate in predicting known drug-disease pairs and inferring mechanisms of action. Furthermore, using a CRISPR screen to analyze lipid regulation, we find that functionally important players lack associations but are prioritized in trait-associated modules by PhenoPLIER. By incorporating groups of co-expressed genes, PhenoPLIER can contextualize genetic associations and reveal potential targets missed by single-gene strategies.

ABSTRACT Small open reading frames (smORFs) are widely distributed in various living organisms. However, their functions remain largely unexplored. In addition, annotation and detection of smORFs are limited using existing methods and hindered by their specific properties. In this study, we systematically investigated smORFs and smORF-encoded peptides (SEPs) in Streptomyces, which are well-known bacterial producers of diverse bioactive secondary metabolites. We established a peptidogenomic workflow based on multi-integrated comprehensive database search and database-independent de novo sequencing to identify smORFs in Streptomyces xinghaiensis NRRL B-24674T (S187). In addition, we described SEPome related to the secondary metabolism, which include 68 novel SEPs and 79 common smORFs with Streptomyces coelicolor A3 (2). Functional analysis of universal smORFs revealed enrichment in biosynthetic processes, stress response, ribosomes, and nucleic acid binding. Meanwhile, 5 Cryptic smORF-encoded Peptides (CSEPs) distributed in non-annotated regions of the genome, and non-coding RNAs could encode for CSEPs. A total of 66 new RNAs, including 32 non-coding RNAs (ncRNAs) were revealed, and 4 ncRNA-encoded peptides were identified. Furthermore, an investigation of carbon metabolism showed that NagE functions in spore formation and secondary metabolism in Streptomyces. Particularly, NagE was observed to function in the biosynthesis of anti-complement agents in S. xinghaiensis, suggesting a novel role of the phosphoenolpyruvate phosphotransferase system in microbial secondary metabolism. We thus provide an effective strategy for analyzing public data sets of model strains to identify smORFs for non-model species. The ncRNAs and SEPs present rich sources for engineering streptomycetes to produce bioactive compounds. Importance Due to their small size and special chemical features, small open reading frame (smORF)-encoding peptides (SEPs) are often neglected. However, they may play critical roles in regulating gene expression, enzyme activity, and metabolite production. Studies on bacterial microproteins have mainly focused on pathogenic bacteria, which are importance to systematically investigate SEPs in streptomycetes and are rich sources of bioactive secondary metabolites. Our study is the first to perform a global identification of smORFs in streptomycetes. We established a peptidogenomic workflow for non-model microbial strains and identified multiple novel smORFs that are potentially linked to secondary metabolism in streptomycetes. Our multi-integrated approach in this study is meaningful to improve the quality and quantity of the detected smORFs. Ultimately, the workflow we established could be extended to other organisms and would benefit the genome mining of microproteins with critical functions for regulation and engineering useful microorganisms.

Abstract Background SARS-CoV-2 infection results in a broad spectrum of COVID-19 disease, from mild or no symptoms to hospitalization and death. COVID-19 disease severity has been associated with some pre-existing conditions and the magnitude of the adaptive immune response to SARS-CoV-2, and a recent genome-wide association study (GWAS) of the risk of critical illness revealed a significant genetic component. To gain insight into how human genetic variation attenuates or exacerbates disease following SARS-CoV-2 infection, we implicated putatively functional COVID risk variants in the cis-regulatory landscapes of human immune cell types with established roles in disease severity and used high-resolution chromatin conformation capture to map these disease-associated elements to their effector genes. Results This functional genomic approach implicates 16 genes involved in viral replication, the interferon response, and inflammation. Several of these genes (PAXBP1, IFNAR2, OAS1, OAS3, TNFAIP8L1, GART) were differentially expressed in immune cells from patients with severe versus moderate COVID-19 disease, and we demonstrate a previously unappreciated role for GART in T cell-dependent antibody-producing B cell differentiation in a human tonsillar organoid model. Conclusions This study offers immunogenetic insight into the basis of COVID-19 disease severity and implicates new targets for therapeutics that limit SARS-CoV-2 infection and its resultant life-threatening inflammation.

The present work introduces a laser-induced cavitation bubble technique for forming an axisymmetric structure (i.e., microgroove) and the dynamics of a cavitation bubble from initial expansion to the collapse stages that were also simulated. Furthermore, the shock wave signals and dynamic properties of the cavitation bubble were recorded using a hydrophone and a high-speed camera. The experiments on microgrooves formed by laser-induced cavitation bubble stamping were carried out, and the effects of laser energy, the initial position of the bubble, and the number of impacts on the microformability of aluminum sheets are discussed. The depth of the microgroove was investigated using experiments, and it was found that the process can serve as a rapid technique for impressing microfeatures on thin-sheet metals. The experimental results showed that as the initial position of the bubble increased, the deformation depth decreased. As the laser energy and number of impacts increased, the deformation depth increased. The results of the response surface experiments showed that a laser energy of 27 mJ, 3 impacts, and a bubble position of 3 mm were optimal for the process. By using the optimal parameters, flat and smooth microgrooves with a forming depth of 102.54 µm were successfully fabricated. Furthermore, the maximum thickness thinning of the microgroove section occurred at the entrance areas, and this area had the greatest hardness. This also indicated that the greatest amount of plastic deformation of the material and grain refinement occurred in this area. On the other hand, the aluminum foil did not undergo oxidation during the plastic deformation process. These results demonstrated that laser-induced bubble stamping is an advanced micromachining method with promising applications.

Background: General movements assessment (GMA) is a non-invasive tool for early assessment of neonatal spontaneous movements. This study aimed to assess the effectiveness of GMA in predicting the neuromotor development outcomes of high-risk infants with neonatal respiratory distress syndrome (NRDS). Methods: The results of GMA at different phases in 80 children with NRDS expected to be born between September 2020 and July 2021 were collected, and the neuromotor development outcomes were verified by Peabody Developmental Motor Scales-2 (PDMS-2) follow-up from March 2022 to May 2022. The study used the screening method and the Chi-square test to analyze the predictive value of different phases of GMA. Results: The GMA writhing movements phase showed an accuracy of 70.00%, a sensitivity of 82.76%, a specificity of 62.75%, a positive predictive value of 55.81%, a negative predictive value of 86.49%, a Youden index of 0.46, and a positive likelihood ratio of 2.22. The GMA fidgety movements phase showed an accuracy of 95.00%, a sensitivity of 96.55%, a specificity of 94.12%, a positive predictive value of 90.32%, a negative predictive value of 97.96%, a Youden index of 0.91, and a positive likelihood ratio of 16.42. The differences between the specificity, accuracy and negative predictive values of GMA were statistically different (χ22 = 9.600, p2 < 0.005; χ23 = 17.316, p3 < 0.005; χ25 = 10.268, p5 = 0.001), while no statistically significant differences were found in the comparison of sensitivity and positive predictive values (p1 = 1.000; χ24 = 2.690, p4 = 0.101). Conclusions: GMA has a favorable predictive value for neuromotor development outcomes in children with NRDS. Clinical Trial Registration: ChiCTR2200061223.

In countries with a high degree of equity concentration, such as China, the second type of agency problem is serious in which major shareholders of listed companies encroach on the interests of small and medium shareholders through private placement. As a financial transaction system, the short-selling mechanism has the function of external corporate governance. Therefore, this paper examines the impact of relaxing short-selling controls on companies’ private placements. Based on the quasi-natural experiment of China’s gradual relaxation of short-selling controls since 2010, a double-difference model (DID) test is constructed to find that relaxing short-selling controls reduces companies’ private placement tendency and amount, and this effect is mainly reflected in samples with a higher degree of equity checks and balances. Further analysis found that when the size of the company’s financing constraints is different, the impact of relaxing short-selling control on the company’s private placement tendency and amount is different; when the chairman and the general manager have two positions, relaxing short-selling control reduces the company’s private placement options, but it has a negative impact on the company’s private placement. There is no difference in the impact of the company’s private placement amount. It can be excluded that the relaxation of short-selling control suppresses the company’s placement through financing constraints and corporate governance mechanisms. Compared to a good information environment, when the company’s information environment is poor, relaxing short-selling controls reduces the company’s private placement tendency and amount. Significantly, it shows that the relaxation of short-selling control policy and supervision inhibits the company’s private placement through the information environment mechanism, and promotes the sustainable development of enterprises. It not only improves the literature in the field of short-selling mechanism affecting corporate behavior, but it also enriches the research on the transfer of benefits of private placement of companies.

Abstract Autism Spectrum Disorder (ASD) is among the most prevalent neurodevelopmental disorders, yet the current diagnostic procedures rely on behavioral analyses and interviews, without objective screening methods to support the diagnostic process. This study seeks to address this gap by integrating upper limb kinematics and deep learning methods to identify potential biomarkers that could be validated in younger age groups in the future to enhance the identification of ASD. Forty-one school-age children, with and without an ASD diagnosis (mean age ± SE: TD group: 10.3 ± 0.8, 8 males and 7 females; ASD group: 10.3 ± 0.5, 21 males and 5 females), participated in the study. A single Inertial Measurement Unit (IMU) was affixed to the child’s wrist as they engaged in a continuous reaching and placing task. Deep learning techniques were employed to classify children with and without ASD. Our findings suggest differential movement kinematics in school-age children compared to healthy adults. Compared to TD children, children with ASD exhibited poor feedforward/feedback control of arm movements as seen by greater number of movement units, more movement overshooting, and prolonged time to peak velocity/acceleration. Unique movement strategies such as greater velocity and acceleration were also seen in the ASD group. More importantly, using Multilayer Perceptron (MLP) model, we demonstrated an accuracy of ~ 78.1% in classifying children with and without ASD. These findings underscore the potential use of studying upper limb movement kinematics during goal-directed arm movements and deep learning methods as valuable tools for classifying and, consequently, aiding in the diagnosis and early identification of ASD upon further validation of their specificity among younger children.

Although research suggests a relationship among personal characteristics, behaviors, and performance, there has been limited examination of these influences in the context of intelligence tests using eye movement techniques. Thus, this study explored the roles of personal characteristics (i.e., visual/verbal cognitive styles, self-efficacy) and reading behaviors in the reasoning performance of Raven's Advanced Progressive Matrices test based on social cognitive perspectives using eye movement techniques, in order to provide more authentic information about individuals' actual behaviors. A total of 53 undergraduate and graduate students participated. Thirty participants were classified as visual style and the others were classified as verbal style learners. Regarding the role of cognitive styles in reading behaviors and reasoning performance, the results indicated a marginal difference in dispersion reading behavior between participants with visual and verbal cognitive style, and a significant relationship between visual style and dispersion reading behavior. However, no difference was found in performance between these two styles. As for the role of self-efficacy, the results showed that it was positively related to horizontal reading and APM-short performance. Mediation analyses revealed that self-efficacy not only directly impacted reasoning performance, but also had an indirect effect on performance through horizontal and tilted reading. On the other hand, cognitive style had no direct or indirect effect on reasoning performance. Moreover, the results showed that horizontal, vertical and tilted reading significantly predicted reasoning performance. The findings suggest that educators could enhance learners' self-efficacy through goal setting, feedback, and strategy instruction, which would help facilitate their learning behaviors and performance.

BackgroundModifiable lifestyle-related factors heighten the risk and severity of coronavirus disease 2019 (COVID-19) in patients with cancer. Whether exercise lowers susceptibility or severity is not known.MethodsWe identified 944 cancer patients from Memorial Sloan Kettering Cancer Center (mean age: 64; 85% female; 78% White) completing an exercise survey before receiving a confirmed positive or negative SARS-CoV-2 test. Exercise was defined as reporting moderate-intensity ≥5 days per week, ≥30 minutes/session or strenuous-intensity ≥3 days per week, ≥20 minutes/session. Multivariable logistic regression was used to determine the relationship between exercise and COVID-19 susceptibility and severity (i.e., composite of hospital admission or death events) with adjustment for clinical-epidemiologic covariates.ResultsTwenty-four percent (230/944) of the overall cohort were diagnosed with COVID-19 and 35% (333/944) were exercisers. During a median follow-up of 10 months, 26% (156/611) of nonexercising patients were diagnosed with COVID-19 compared with 22% (74/333) of exercising patients. The adjusted OR for risk of COVID-19 was 0.65 [95% confidence interval (CI), 0.44-0.96, P = 0.03] for exercisers compared with nonexercisers. A total of 20% (47/230) of COVID-19 positive patients were hospitalized or died. No difference in the risk of severe COVID-19 as a function of exercise status was observed (P > 0.9).ConclusionsExercise may reduce the risk of COVID-19 infection in patients with a history of cancer, but not its severity.ImpactThis study provides the first data showing that exercise might lower the risk of COVID-19 in cancer patients, but further research is required.

In this study, we propose a fire classification system using image clustering based on a federated learning (FL) structure. This system enables fire detection in various industries, including manufacturing. The accurate classification of fire, smoke, and normal conditions is an important element of fire prevention and response systems in industrial sites. The server in the proposed system extracts data features using a pretrained vision transformer model and clusters the data using the bisecting K-means algorithm to obtain weights. The clients utilize these weights to cluster local data with the K-means algorithm and measure the difference in data distribution using the Kullback–Leibler divergence. Experimental results show that the proposed model achieves nearly 99% accuracy on the server, and the clustering accuracy on the clients remains high. In addition, the normalized mutual information value remains above 0.6 and the silhouette score reaches 0.9 as the rounds progress, indicating improved clustering quality. This study shows that the accuracy of fire classification is enhanced by using FL and clustering techniques and has a high potential for real-time detection. [ABSTRACT FROM AUTHOR]

The canonical Wnt signaling pathway plays crucial roles in cell fate decisions as well as in pathogenesis of various diseases. Previously, we reported Caprin-2 as a new regulator of canonical Wnt signaling through a mechanism of facilitating LRP5/6 phosphorylation. Here, we resolved the crystal structure of the N-terminal homologous region 1 (HR1) domain of human Caprin-2. HR1 domain is so far only observed in Caprin-2 and its homologous protein Caprin-1, and the function of this domain remains largely mysterious. Here, the structure showed that HR1 domain of human Caprin-2 forms a homo-dimer and exhibits an overall structure roughly resembling the appearance of a pair of scissors. Moreover, we found that residues R200 and R201, which located at a basic cluster within the N-terminal "blades" region, are critical for Caprin-2's localization to the plasma membrane. In line with this, mutations targeting these two residues decrease Caprin-2's activity in the canonical Wnt signaling. Overall, we characterized a previously unknown "scissors"-like structure of the fulllength HR1 domain and revealed its function in mediating Caprin-2's localization to the plasma membrane. [ABSTRACT FROM AUTHOR]