Identification of important genes related to anoikis in acute myocardial infarction.

Acute myocardial infarction (AMI) increasingly precipitates severe heart failure, with diagnoses now extending to progressively younger demographics. The focus of this study was to pinpoint critical genes linked to both AMI and anoikis, thereby unveiling potential novel biomarkers for AMI detection and intervention. Differential analysis was performed to identify significant differences in expression, and gene functionality was explored.

The Underlying Mechanism Involved in Gefitinib Resistance and Corresponding Experiment Validation in Lung Cancer.

Background: Gefitinib resistance remains a major problem in the treatment of lung cancer. However, the underlying mechanisms involved in gefitinib resistance are largely unclear.

Methods: Open-accessed data of lung cancer patients were downloaded from The Cancer Genome Atlas Program and Gene Expression Omnibus databases.

Development and validation of a machine learning model for survival risk stratification after esophageal cancer surgery.

Background: Prediction of prognosis for patients with esophageal cancer(EC) is beneficial for their postoperative clinical decision-making. This study's goal was to create a dependable machine learning (ML) model for predicting the prognosis of patients with EC after surgery.

Methods: The files of patients with esophageal squamous cell carcinoma (ESCC) of the thoracic segment from China who received radical surgery for EC were analyzed.

McKeown esophagectomy: robot-assisted versus conventional minimally invasive technique-systematic review and meta-analysis.

Background And Purpose: This meta-analysis assesses the surgical outcomes between robot-assisted minimally-invasive McKeown esophagectomy and conventional one.

Method: This meta-analysis searched the Web of Science, PUBMED, and EMBASE from the database's inception to January 2022. Altogether, 1073 records were identified in the literature search.