Exome sequencing of UK birth cohorts.

Birth cohort studies involve repeated surveys of large numbers of individuals from birth and throughout their lives. They collect information useful for a wide range of life course research domains, and biological samples which can be used to derive data from an increasing collection of omic technologies. This rich source of longitudinal data, when combined with genomic data, offers the scientific community valuable insights ranging from population genetics to applications across the social sciences.

Achilles tendon morphology adaptations in chronic post-stroke hemiparesis: a comparative analysis with neurologically intact controls.

Introduction: In individuals with chronic post-stroke hemiparesis, slow walking speed is a significant concern related to inadequate propulsion of the paretic limb. However, an overlooked factor is this population's altered morphology of the Achilles tendon, which may compromise the propulsive forces by the paretic limb. This study aimed to explore changes in Achilles tendon morphology, including gross thickness and intra-tendinous collagen fiber bundle organization, following stroke-induced brain lesions.

Anxiety and depression in only children versus children with siblings: A cross-sectional study among Chinese medical students.

Objectives: This study aimed to explore the characteristics, overall anxiety and depression status, and influencing factors of only-child and non-only-child students by examining a medical student population in the post-COVID-19 era.

Study Design: This study was a cross-sectional design.

Methods: An online questionnaire survey was administered among medical students.

Machine learning classification and biochemical characteristics in the real-time diagnosis of gastric adenocarcinoma using Raman spectroscopy.

This study aimed to identify biomolecular differences between benign gastric tissues (gastritis/intestinal metaplasia) and gastric adenocarcinoma and to evaluate the diagnostic power of Raman spectroscopy-based machine learning in gastric adenocarcinoma. Raman spectroscopy-based machine learning was applied in real-time during endoscopy in 19 patients (aged 51-85 years) with high-risk for gastric adenocarcinoma. Raman spectra were captured from suspicious lesions and adjacent normal mucosa, which were biopsied for matched histopathologic diagnosis.

Metabolic reprogramming and macrophage expansion define ACPA-negative rheumatoid arthritis: insights from single-cell RNA sequencing.

Background: Anti-citrullinated peptide antibodies (ACPA)-negative (ACPA-) rheumatoid arthritis (RA) presents significant diagnostic and therapeutic challenges due to the absence of specific biomarkers, underscoring the need to elucidate its distinctive cellular and metabolic profiles for more targeted interventions.

Methods: Single-cell RNA sequencing data from peripheral blood mononuclear cells (PBMCs) and synovial tissues of patients with ACPA- and ACPA+ RA, as well as healthy controls, were analyzed. Immune cell populations were classified based on clustering and marker gene expression, with pseudotime trajectory analysis, weighted gene co-expression network analysis (WGCNA), and transcription factor network inference providing further insights.