Epigenetics in autosomal dominant polycystic kidney disease.

Autosomal dominant polycystic kidney disease (ADPKD) is the fourth leading cause of end-stage renal disease, contributing substantially to patient morbidity, mortality, and healthcare system strain. Emerging research highlights a pivotal role of epigenetics in ADPKD's pathophysiology, where mechanisms like DNA methylation, histone modifications, and non-coding RNA regulation significantly impact disease onset and progression. These epigenetic factors influence gene expression and regulate key processes involved in cyst formation and expansion, fibrosis, and inflammatory infiltration, thus accelerating ADPKD progression.

Age Differences in the Associations Between Interpersonal Relationships and Short-Form Video Addiction Symptoms: A Network Analysis.

Purpose: A considerable body of evidence indicated that interpersonal relationships were significantly associated with short-form video addiction (SFVA) among adolescents, but how they are related on a symptom level at different ages remains unclear. This study aimed to explore the central symptoms of SFVA and distinct associations between three primary interpersonal relationships (ie, teacher-student relationships, parent-child relationships, peer relationships) and SFVA symptoms in early and middle adolescence.

Participants And Methods: After completing scales of SFVA, teacher-student relationship, parent-child relationship and peer relationship in 2022, a sample of 1579 fourth-grade students (age range: 10-12; = 10.

Diabetes mellitus in patients with myasthenia gravis: a systematic review and meta-analysis.

Objectives: With the prolongation of life expectancy in patients with myasthenia gravis, the number of comorbidities is increasing. Diabetes mellitus is one of the main comorbidities faced by patients with myasthenia gravis. However, there is not enough epidemiological information on diabetes mellitus.

Data-Driven Machine Learning Strategy for Designing Metal-Ion-Doped γ-BiMoO Photocatalysts to Enhance Degradation Performance.

Doped semiconductors are often used to improve photocatalytic efficiency and address the challenges of easy recombination of electron-hole pairs and poor photoluminescence. However, the reproducibility and complexity of experimental studies result in time-consuming and less cost-effective studies, and it is difficult to gain insights into the intrinsic properties of doped photocatalysts to control their performance. Introducing a machine learning approach, we constructed a photocatalytic model of transition-metal- and rare earth metal-ion-doped γ-BiMoO.

Identification and validation of differentially expressed disulfidptosis-related genes in hypertrophic cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is one of the most common cardiovascular diseases with no effective treatment due to its complex pathogenesis. A novel cell death, disulfidptosis, has been extensively studied in the cancer field but rarely in cardiovascular diseases. This study revealed the potential relationship between disulfidptosis and hypertrophic cardiomyopathy and put forward a predictive model containing disulfidptosis-associated genes (DRGs) of GYS1, MYH10, PDMIL1, SLC3A2, CAPZB, showing excellent performance by SVM machine learning model.