Artificial intelligence system for outcome evaluations of human in vitro fertilization-derived embryos.

Background: In vitro fertilization (IVF) has emerged as a transformative solution for infertility. However, achieving favorable live-birth outcomes remains challenging. Current clinical IVF practices in IVF involve the collection of heterogeneous embryo data through diverse methods, including static images and temporal videos.

Deep-learning-enabled protein-protein interaction analysis for prediction of SARS-CoV-2 infectivity and variant evolution.

Host-pathogen interactions and pathogen evolution are underpinned by protein-protein interactions between viral and host proteins. An understanding of how viral variants affect protein-protein binding is important for predicting viral-host interactions, such as the emergence of new pathogenic SARS-CoV-2 variants. Here we propose an artificial intelligence-based framework called UniBind, in which proteins are represented as a graph at the residue and atom levels.

Homologous or heterogenous vaccination boosters enhance neutralizing activities against SARS-CoV-2 Omicron BA.1 variant.

The SARS-CoV-2 Omicron BA.1 variant of concern contains more than 30 mutations in the spike protein, with half of these mutations localized in the receptor-binding domain (RBD). Emerging evidence suggests that these large number of mutations impact the neutralizing efficacy of vaccines and monoclonal antibodies.

Pathological observation of brain arteries and spontaneous aneurysms in hypertensive rats.

Objective: To investigate the role of hypertension in the pathogenesis of cerebral aneurysms in rats.

Methods: Twenty spontaneous hypertensive rats (SHR) and 10 Wistar-Kyoto rats (WKY) were included in this observational study. Animals were fed with normal diet and drinking water.