Impact of polymorphisms on gene expression and splicing in response to exercise and diet-induced weight loss in human skeletal muscle tissues.

Weight loss through exercise and diet reduces the risk of type 2 diabetes, but the genetic regulation of gene expression and splicing in response to weight loss remains unclear in humans. We collected clinical data and skeletal muscle biopsies from 54 overweight/obese Asian individuals before and after a 16-week lifestyle intervention, which resulted in an average of ∼10% weight loss, accompanied by an ∼30% increase in insulin-stimulated glucose uptake. Improvements were observed in 118 of 252 clinical traits and six blood lipids.

Correction: Effect of individualized end-inspiratory pause guided by driving pressure on respiratory mechanics during prone spinal surgery: a randomized controlled trial.

[This corrects the article DOI: 10.3389/fmed.2025.

Integrated Microbiome, Transcriptome, and Physiology Analyses Reveal the Response Of Kuruma Shrimp (Penaeus japonicus) to Oxygen Nanobubble Exposure.

Penaeus japonicus is a high-value crustacean species, but its response to oxygen nanobubble (NB-O) remains poorly understood. This study evaluated the effects of NB-O exposure on juvenile P. japonicus cultured in two recirculating aquaculture systems (RAS).

Effect of individualized end-inspiratory pause guided by driving pressure on respiratory mechanics during prone spinal surgery: a randomized controlled trial.

Purpose: The prone position is commonly used in spinal surgery, but it can lead to decreased lung compliance and increased airway pressure. This study aimed to evaluate the effect of individualized end-inspiratory pause guided by driving pressure on respiratory mechanics in patients undergoing prone spinal surgery.

Methods: A randomized controlled trial was conducted from August to October 2023.

Asian diversity in human immune cells.

The relationships of human diversity with biomedical phenotypes are pervasive yet remain understudied, particularly in a single-cell genomics context. Here, we present the Asian Immune Diversity Atlas (AIDA), a multi-national single-cell RNA sequencing (scRNA-seq) healthy reference atlas of human immune cells. AIDA comprises 1,265,624 circulating immune cells from 619 donors, spanning 7 population groups across 5 Asian countries, and 6 controls.

Effects of Rhodopseudomonas palustris and composite probiotics on growth performance, intestinal health, and non-specific immunity of sea urchin (Strongylocentrotus intermedius).

In recent decades, antibiotics have been widely used in sea urchin aquaculture to prevent diseases and improve water quality. However, their use leads to the emergence of resistant strains and environmental problems. Probiotics can serve as a green and pollution-free alternative.

Single-cell RNA sequencing of peripheral blood links cell-type-specific regulation of splicing to autoimmune and inflammatory diseases.

Alternative splicing contributes to complex traits, but whether this differs in trait-relevant cell types across diverse genetic ancestries is unclear. Here we describe cell-type-specific, sex-biased and ancestry-biased alternative splicing in ~1 M peripheral blood mononuclear cells from 474 healthy donors from the Asian Immune Diversity Atlas. We identify widespread sex-biased and ancestry-biased differential splicing, most of which is cell-type-specific.

Bloch-Wave Phase Matching of High Harmonic Generation in Solids.

There has been a longstanding doubt that the conversion efficiency of high harmonics in solids is much lower than expected at such a high level of electron density. To address this issue, we revisit the dynamical process of high harmonic generation (HHG) in solids in terms of wavelet interference. We find that the constructive interference among the wavelets has intrinsic consistency with the phase matching of coupled waves in nonlinear optics, which we call Bloch-wave phase matching.

KinPred-RNA-kinase activity inference and cancer type classification using machine learning on RNA-seq data.

Kinases as important enzymes can transfer phosphate groups from high-energy and phosphate-donating molecules to specific substrates and play essential roles in various cellular processes. Existing algorithms for kinase activity from phosphorylated proteomics data are often costly, requiring valuable samples. Moreover, methods to extract kinase activities from bulk RNA sequencing data remain undeveloped.

A Robust Drug-Target Interaction Prediction Framework with Capsule Network and Transfer Learning.

Drug-target interactions (DTIs) are considered a crucial component of drug design and drug discovery. To date, many computational methods were developed for drug-target interactions, but they are insufficiently informative for accurately predicting DTIs due to the lack of experimentally verified negative datasets, inaccurate molecular feature representation, and ineffective DTI classifiers. Therefore, we address the limitations of randomly selecting negative DTI data from unknown drug-target pairs by establishing two experimentally validated datasets and propose a capsule network-based framework called CapBM-DTI to capture hierarchical relationships of drugs and targets, which adopts pre-trained bidirectional encoder representations from transformers (BERT) for contextual sequence feature extraction from target proteins through transfer learning and the message-passing neural network (MPNN) for the 2-D graph feature extraction of compounds to accurately and robustly identify drug-target interactions.

DeepAFP: An effective computational framework for identifying antifungal peptides based on deep learning.

Fungal infections have become a significant global health issue, affecting millions worldwide. Antifungal peptides (AFPs) have emerged as a promising alternative to conventional antifungal drugs due to their low toxicity and low propensity for inducing resistance. In this study, we developed a deep learning-based framework called DeepAFP to efficiently identify AFPs.

Accelerating the Discovery of Anticancer Peptides through Deep Forest Architecture with Deep Graphical Representation.

Cancer is one of the leading diseases threatening human life and health worldwide. Peptide-based therapies have attracted much attention in recent years. Therefore, the precise prediction of anticancer peptides (ACPs) is crucial for discovering and designing novel cancer treatments.

Road to entire insulation for resonances from a forced mechanical system.

The effective solution to avoid machinery damage caused by resonance has been perplexing the field of engineering as a core research direction since the resonance phenomenon was discovered by Euler in 1750. Numerous attempts have been performed to reduce the influence of resonance since the earlier of last century, by introducing a nonlinear structure or a closed-loop control system. However, the existed methodologies cannot eliminate resonance completely even extra problems were introduced inevitably, which means the technical choke-point of resonance-free remains unsolved.

Revealing the Immune Heterogeneity between Systemic Lupus Erythematosus and Rheumatoid Arthritis Based on Multi-Omics Data Analysis.

The pathogenesis of systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are greatly influenced by different immune cells. Nowadays both T-cell receptor (TCR) and B-cell receptor (BCR) sequencing technology have emerged with the maturity of NGS technology. However, both SLE and RA peripheral blood TCR or BCR repertoire sequencing remains lacking because repertoire sequencing is an expensive assay and consumes valuable tissue samples.

The mitigating role of climate smart villages to the impacts of COVID-19 pandemic in the Myanmar rural communities.

Climate smart village approach is identified as an important strategy laid out in the Myanmar Climate Smart Agriculture Strategy (MCSAS, 2016) Four climate smart villages were established in 2017 to facilitate participatory action research to develop the CSV approach as well as to generate evidence of outcomes. The CSV approach is based on the principle of community-directed research process where community-members collaborate with an external researcher to investigate community challenges and their solutions. Like other countries in 2020, the height of the COVID-19 pandemic, Myanmar implemented wide-scale national and local restrictions on mobility that impacted trade and business resulting to an economic slowdown.

Extensive conformational and physical plasticity protects HER2-HER3 tumorigenic signaling.

Surface-targeting biotherapeutic agents have been successful in treating HER2-amplified cancers through immunostimulation or chemodelivery but have failed to produce effective inhibitors of constitutive HER2-HER3 signaling. We report an extensive structure-function analysis of this tumor driver, revealing complete uncoupling of intracellular signaling and tumorigenic function from regulation or constraints from their extracellular domains (ECDs). The canonical HER3 ECD conformational changes and exposure of the dimerization interface are nonessential, and the entire ECDs of HER2 and HER3 are redundant for tumorigenic signaling.

Protein Tyrosine Phosphatase 1B (PTP1B): Insights into its New Implications in Tumorigenesis.

In vivo, tyrosine phosphorylation is a reversible and dynamic process governed by the opposing activities of protein tyrosine kinases and phosphatases. Defective or inappropriate operation of these proteins leads to aberrant tyrosine phosphorylation, which contributes to the development of many human diseases, including cancers. PTP1B, a non-transmembrane phosphatase, is generally considered a negative regulator of the metabolic signaling pathways and a promising drug target for type II diabetes and obesity.

Structured H∞ Control for Spacecraft with Flexible Appendages.

Spacecraft with large flexible appendages are characterized by multiple system modes. They suffer from inherent low-frequency disturbances in the operating environment that consequently result in considerable interference in the operational performance of the system. It is required that the control design ensures the system's high pointing precision, and it is also necessary to suppress low-frequency resonant interference as well as take into account multiple performance criteria such as attitude stability and bandwidth constraints.

Deep Learning-Enabled Label-Free On-Chip Detection and Selective Extraction of Cell Aggregate-Laden Hydrogel Microcapsules.

Microfluidic encapsulation of cells/tissues in hydrogel microcapsules has attracted tremendous attention in the burgeoning field of cell-based medicine. However, when encapsulating rare cells and tissues (e.g.