Browse Articles

An IoT-enabled CRNN framework for secure wearable sensor-based activity recognition in physical education

Fuzzy-logic-controlled DVR for enhancing the fault resilience of wind energy conversion systems

PCSK9 inhibitors patterns of use in France from nationwide repeated cross-sectional and cohort studies

Author Correction: A Model of Exposure to Extreme Environmental Heat Uncovers the Human Transcriptome to Heat Stress

Integrative mendelian randomization approaches for therapeutic target prioritisation in immune-mediated diseases

Abstract Immune-mediated diseases (IMD) encompass a wide range of autoimmune and inflammatory disorders with aetiology related to immune system dysfunction, signifying a disease area with great potential for drug repurposing. In this study, we employed the genetically informed Mendelian Randomization (MR) method with two distinct exposure types: immune blood cell abundance and protein quantitative trait loci (pQTL) to validate and repurpose 834 drug targets which have been investigated for IMD treatment. Utilizing two-sample MR, we first established causal relationships between major peripheral immune cell types and 14 IMD. Robust associations, particularly with eosinophils, were confirmed across diseases such as asthma, eczema, sinusitis, and rheumatoid arthritis, revealing 59 high-confidence relationships. Intragenic variants associated with causal immune cell types were then extracted to create instruments for 371 existing IMD drug targets (“intermediate trait” MR). In parallel, we leveraged four large blood plasma protein QTL datasets to obtain complementary instruments for 361 targets (“pQTL” MR). In the intermediate trait MR analysis, we identified 811 gene-IMD associations (p-value < 0.05; 137 pairs below Bonferroni-adjusted p-value threshold), 169 of which were supported by strong colocalisation evidence (PP H4 ≥ 0.8). In the pQTL MR analysis, we similarly found 841 protein-IMD associations (p-value < 0.05; 90 pairs below Bonferroni-adjusted p-value threshold), 83 of which were confirmed with colocalization. Comparison with a list of approved drugs indicated low sensitivities across disease outcomes for both exposure types (intermediate trait MR: 0.49 ± 0.23 SD, pQTL MR: 0.28 ± 0.12 SD). Drug targets identified in the pQTL and intermediate trait MR analyses show limited overlap (13% at nominal p-value and 36% at Bonferroni-adjusted p-value threshold), presenting a comprehensive source of drug repurposing opportunities when the two approaches are combined.

Novel universal domain-centric method for protein classification

Explainable multi agent reinforcement learning framework for secure and adaptive communication in UAV swarm based fanets

Association between the geriatric nutritional risk index and all-cause mortality in patients with acute pancreatitis in the intensive care unit: a retrospective cohort study

Sleep quality prediction in basketball athletes using a deep learning framework with an attention mechanism based on multimodal data

Analysis of construction impact and safety evaluation of metro shield tunnel under-crossing existing bridge pile foundation

Human umbilical cord mesenchymal stem cells alleviate hypoxic-ischemia-induced white-matter injury in neonatal rats by regulating polarization of microglia

Scalable and accurate rare-variant association tests for whole genome sequencing time-to-event analysis in large biobanks

Whole genome sequencing (WGS) studies in large biobanks provide an unprecedented opportunity to study the rare-variant (RV) effects on the natural history of human diseases by analyzing censored time-to-event (TTE) phenotypes, such as age at disease diagnosis, disease progression, and lifespan. Unlike existing methods developed for continuous and categorical phenotypes, rare-variant association tests (RVATs) for TTE phenotypes in large biobanks face several major challenges, including heavy censoring, cryptic relatedness, and population structure. We introduce GATE-STAAR (Genetic Analysis of Time-to-Event phenotypes via the variant-Set Test for Association using Annotation infoRmation), a powerful and computationally efficient frailty model framework for RVATs of TTE phenotypes in large biobanks. GATE-STAAR accounts for high censoring rates, cryptic relatedness, and population structure in large biobanks, while incorporating multifaceted variant functional annotations to improve power and result interpretability. We propose a rare-variant saddlepoint approximation method to effectively address heavy censoring in WGS TTE analysis. We demonstrate through extensive simulations that GATE-STAAR is powerful while maintaining proper control of type I error rates. We apply GATE-STAAR to analyze the WGS data of approximately 400,000 UK Biobank participants of white British ancestry across a variety of TTE phenotypes, and validate the findings using participants of European ancestry from the All of Us Research Program. These analyses uncover RV associations with age at diagnosis of a range of diseases.

Influence of synthetic derivatives of cytokinin and auxin on yield and quality of rainy season guava (Psidium guajava L.) cv. Shweta

Electrified release of pure CO ₂ from postcapture liquid: A two-stage system lowers the total energy cost

Electrified carbon capture and release holds promise in carbon management; but it is constrained by high energy demand. Here, we studied two candidate systems for electrochemical CO 2 release from a direct air capture (DAC) postcapture liquid: The first, a hydrogen loop cell, is electricity-efficient, but its evolved CO 2 is mixed with H 2 , introducing a 3 to 4 GJ/tonCO 2 additional energy separation cost. The second system, a solid-state metal oxide redox couple (proton sponge), avoids the gas separation challenge but is stable only in the bicarbonate and not the highly alkaline regime. These considerations led us to examine a two-stage system: An efficient hydrogen loop would first downshift the pH from 13.5 to 9; and a second metal oxide would be used to release CO 2 from bicarbonate. We report an electrified process that provides the release of a pure CO 2 stream from a post-DAC liquid with a measured total energy of ~4.5 GJ/tonCO 2 : 2.4 GJ from the H 2 looping stage and 2.1 GJ from the MnO 2 -based stage—substantially lower than the >=10 GJ/tonCO 2 required by pH-swing methods such as bipolar membrane electrodialysis. We conclude with a generalized analysis of how staged pH downshifting reduces the overall Nernst voltage penalty and facilitates energy-efficient CO 2 release.

Identifying neuromuscular and mental fatigue in elite youth table tennis players using machine learning

Human hippocampal theta–gamma coupling coordinates sequential planning during navigation

Human behavior often relies on executing a specific sequence of actions to achieve a desired outcome. However, the neural mechanisms underlying the dynamic construction and maintenance of such sequences during goal-directed behavior are not yet clear. Empirical and theoretical studies of working memory function suggest that sequential information may be encoded in neural circuits by bursts of gamma activity occurring at consecutive theta phases. Here, we asked whether a similar coding scheme might support sequential planning during goal-directed navigation. Using noninvasive magnetoencephalography and an abstract navigation task, we found that hippocampal theta power during both planning and subsequent navigation decreased with proximity to the current goal, only during accurate navigation. At the same time, theta–gamma phase–amplitude coupling (PAC) increased with goal proximity, consistent with sequences of upcoming locations being represented by gamma bursts occurring at successive theta phases. Importantly, entorhinal high gamma and hippocampal low gamma dominated while traversing novel and previously experienced paths, respectively, consistent with previous rodent studies. These findings suggest that hippocampal theta–gamma PAC flexibly and dynamically coordinates sequences of actions during goal-directed behavior across mammalian species, using different gamma bands for mnemonic and prospective planning.

Multi-omics analysis of NEDD1 in hepatocellular carcinoma: biological function, prognostic value, and clinical significance

Ecological inheritance facilitates the coexistence of environmental helpers and free riders

Many traits influence fitness indirectly by modifying shared environments that are transmitted across generations, a process known as ecological inheritance. Here, we investigate how variation in traits to improve common resources emerges when locally modified environments show ecological inheritance. Using eco-evolutionary modeling, we reveal that ecological inheritance, when combined with limited dispersal, can facilitate the coexistence of two types with opposite ecological legacies: environmental helpers, who improve the local environment for the future at a personal cost, and environmental free riders, who benefit without contributing to the detriment of future generations, particularly when interactions among helpers generate diminishing returns. This polymorphism generates lasting spatial heterogeneity in environmental quality and, consequently, in survival and reproduction—particularly under isolation-by-distance, where it creates stable clusters of high- and low-quality habitats across an otherwise homogeneous landscape. These findings reveal how ecological inheritance and spatial structure interact to stabilize polymorphism, potentially driving long-term behavioral, ecological, and fitness variation across diverse biological systems.

Hybrid fuzzy machine learning models optimized with meta-heuristics for accurate EEG-based neurological assessment

Permeability of silty clay and its prediction model based on NMR T2 double cutoff value