Postoperative Apnea-Hypopnea Index Prediction of Velopharyngeal Surgery Based on Machine Learning.

Objective: To investigate machine learning-based regression models to predict the postoperative apnea-hypopnea index (AHI) for evaluating the outcome of velopharyngeal surgery in adult obstructive sleep apnea (OSA) subjects.

Study Design: A single-center, retrospective, cohort study.

Setting: Sleep medical center.

Whole genome sequencing and analysis of a goose-derived in Guangdong Province, China.

Introduction: (MG) infection is a primary cause of chronic respiratory disease in poultry, threatening the economic viability of China's goose-farming industry. This study investigated the pathogenicity and drug resistance of an MG strain isolated from geese and whole-genome sequenced the strain.

Material And Methods: A strain designated MG-GD01/22 was isolated from the air-sac tissues of five geese with chronic respiratory disease on a Guangdong goose farm.

Deep-learning-based image compression for microscopy images: An empirical study.

With the fast development of modern microscopes and bioimaging techniques, an unprecedentedly large amount of imaging data is being generated, stored, analyzed, and shared through networks. The size of the data poses great challenges for current data infrastructure. One common way to reduce the data size is by image compression.

The evaluation of targeted exome sequencing of candidate genes in a Han Chinese population with primary open-angle glaucoma.

Primary open-angle glaucoma (POAG), known as a common ocular disease with genetic heterogeneity, is characterized by progressive optic disc atrophy and visual field defects. This study aimed to assess the contribution of previously reported POAG-associated genes and investigate potential functional variations and genotype-phenotype correlations in a Han Chinese population. DNA from 500 cases and 500 controls was pooled and sequenced using a customized panel of 398 candidate genes.

HERC5/ISG15 Enhances Glioblastoma Stemness and Tumor Progression by mediating SERBP1protein stability.

Glioblastoma (GBM) is the most common malignant brain tumor, and has a low survival rate and a poor prognosis. Intensive studies of pathogenic mechanisms are essential for exploring therapeutic targets for GBM. In this study, the roles played by interferon-stimulated gene 15 (ISG15), HECT, RCC1-containing protein 5 (HERC5), and SERPINE1 mRNA binding protein 1 (SERBP1) in regulating GBM cell stemness were investigated.