Deciphering gp120 sequence variation and structural dynamics in HIV neutralization phenotype by molecular dynamics simulations and graph machine learning.

Human immunodeficiency virus (HIV) exploits the sequence variation and structural dynamics of the envelope glycoprotein gp120 to evade the immune attack of neutralization antibodies, contributing to various HIV neutralization phenotypes. Although the HIV neutralization phenotype has been experimentally characterized, the roles of rapid sequence variability and significant structural dynamics of gp120 are not well understood. Here, 45 prefusion gp120 from different HIV strains belong to three tiers of sensitive, moderate, and resistant neutralization phenotype are structurally modeled by homology modeling and then investigated by molecular dynamics (MD) simulations and graph machine learning (ML).

An automatic method for removing empty camera trap images using ensemble learning.

Camera traps often produce massive images, and empty images that do not contain animals are usually overwhelming. Deep learning is a machine-learning algorithm and widely used to identify empty camera trap images automatically. Existing methods with high accuracy are based on millions of training samples (images) and require a lot of time and personnel costs to label the training samples manually.

Risk Factors for Postoperative Retention After Hemorrhoidectomy: A Cohort Study.

The objective of this study was to identify the risk factors for urinary retention after hemorrhoidectomy. With the approval of West China Hospital of Sichuan University Ethics Board, data were abstracted from 961 charts of patients who underwent hemorrhoidectomy from January 1, 2009, to June 30, 2011. The outcome was urinary retention in the first 24 hours after surgery.