Researchers at Baylor College of Medicine have developed an artificial intelligence (AI) model that reveals how protein modifications link genetic mutations to disease. The method, called DeepMVP, significantly outperforms previously published models and has implications for the development of novel therapeutics.

Deep inside the body, a slow-growing cluster of mutated blood cells can form. This cluster, found in 1 in 5 older adults, can raise the risk of leukemia and heart disease, often without warning. To better understand this hidden risk, Mayo Clinic researchers have developed an artificial intelligence (AI) tool to help investigators uncover how it contributes to disease risk and progression.

Researchers made significant improvements to the Rangeland Analysis Platform (RAP) by using higher resolution images captured by the Sentinel-2 mission, which provides a 10-meter cover dataset. The Sentinel-2 mission utilizes three satellites to produce more detailed images with finer resolution and faster updates than the previous 30-meter datasets. These enhanced images offer a more precise understanding of rangeland vegetation structure and composition, covering the period from 2018 to 2024. This new satellite dataset allows RAP to provide new cover information, specifically invasive species, pinyon-juniper, sagebrush, as well as the distribution of bare ground. These new RAP layers allow ranchers and land managers to detect and manage invasive species spread and consequent wildfire risks, woody species encroachment, wildlife habitat condition, and wind erosion risks with high precision across the western United States.