Genome-Wide Identification and Analysis of the Gene Family in Cotton: Evolution and Expression Profiles During Normal Growth and Stress Response.

Background: The gene family of myelomatosis (MYC), serving as a transcription factor in the jasmonate (JA) signaling pathway, displays a significant level of conservation across diverse animal and plant species. Cotton is the most widely used plant for fiber production. Nevertheless, there is a paucity of literature reporting on the members of MYCs and how they respond to biotic stresses in cotton.

Measures to prevent esophageal stenosis are necessary after endoscopic submucosal dissection for early esophageal cancer lesions with a circumferential ratio of 75%-99%: a retrospective case analysis.

Purpose: Endoscopic submucosal dissection (ESD) is currently one of the most curative treatments for early esophageal cancer. We conducted a retrospective case analysis to identify the characteristics of early esophageal cancer that indicate esophageal stenosis prevention measures. Our aim was to provide a reference for clinical decision-making.

Elucidating the dual roles of apoptosis and necroptosis in diabetic wound healing: implications for therapeutic intervention.

Wound healing is a complex and multistep biological process that involves the cooperation of various cell types. Programmed cell death, including apoptosis and necrotizing apoptosis, plays a crucial role in this process. Apoptosis, a controlled and orderly programmed cell death regulated by genes, helps eliminate unnecessary or abnormal cells and maintain internal environmental stability.

Application of efgartigimod in Chinese patients with myasthenia gravis: a single-center real-world prospective study.

Background: China has a large number of myasthenia gravis (MG) patients, creating an urgent need for rapid and tolerable treatment options. As the first-approved Fc receptor antagonist, efgartigimod has bright prospects for treating MG. However, real-world evidence on its application within the Chinese MG population are limited.

Development and validation of a multi-parametric MRI deep-learning model for preoperative lymphovascular invasion evaluation in rectal cancer.

Background: Lymphovascular invasion (LVI) is an independent prognostic factor for patients with rectal cancer (RC). Recent studies have shown that deep learning (DL)-based magnetic resonance imaging (MRI) has potential in evaluating the treatment response of RC patients, but the role of MRI-based DL in assessing RC LVI remains unclear. This study sought to develop and validate a DL model to evaluate the LVI status of RC patients preoperatively based on MRI, and to test its performance at an external center.