Exploration of the tunability of BRD4 degradation by DCAF16 trans-labelling covalent glues.

Chemically induced proximity modalities such as targeted protein degradation (TPD) hold promise for expanding the number of proteins that can be manipulated pharmacologically. However, current TPD strategies are often limited to proteins with preexisting ligands. Molecular glues (e.

Template-assisted covalent modification underlies activity of covalent molecular glues.

Molecular glues are proximity-inducing small molecules that have emerged as an attractive therapeutic approach. However, developing molecular glues remains challenging, requiring innovative mechanistic strategies to stabilize neoprotein interfaces and expedite discovery. Here we unveil a trans-labeling covalent molecular glue mechanism, termed 'template-assisted covalent modification'.

Exploration of the Tunability of BRD4 Degradation by DCAF16 -labelling Covalent Glues.

Small molecules that can induce protein degradation by inducing proximity between a desired target and an E3 ligase have the potential to greatly expand the number of proteins that can be manipulated pharmacologically. Current strategies for targeted protein degradation are mostly limited in their target scope to proteins with preexisting ligands. Alternate modalities such as molecular glues, as exemplified by the glutarimide class of ligands for the CUL4 ligase, have been mostly discovered serendipitously.

Template-assisted covalent modification of DCAF16 underlies activity of BRD4 molecular glue degraders.

Small molecules that induce protein-protein interactions to exert proximity-driven pharmacology such as targeted protein degradation are a powerful class of therapeutics. Molecular glues are of particular interest given their favorable size and chemical properties and represent the only clinically approved degrader drugs. The discovery and development of molecular glues for novel targets, however, remains challenging.

Using a Deep Learning Algorithm and Integrated Gradients Explanation to Assist Grading for Diabetic Retinopathy.

Purpose: To understand the impact of deep learning diabetic retinopathy (DR) algorithms on physician readers in computer-assisted settings.

Design: Evaluation of diagnostic technology.

Participants: One thousand seven hundred ninety-six retinal fundus images from 1612 diabetic patients.

Real time alert system: a disease management system leveraging health information exchange.

Background: Rates of preventive and disease management services can be improved by providing automated alerts and reminders to primary care providers (PCPs) using of health information technology (HIT) tools.

Methods: Using Adaptive Turnaround Documents (ATAD), an existing Health Information Exchange (HIE) infrastructure and office fax machines, we developed a Real Time Alert (RTA) system. RTA is a computerized decision support system (CDSS) that is able to deliver alerts to PCPs statewide for recommended services around the time of the patient visit.

Targeted screening for pediatric conditions with the CHICA system.

Objective: The Child Health Improvement through Computer Automation (CHICA) system is a decision-support and electronic-medical-record system for pediatric health maintenance and disease management. The purpose of this study was to explore CHICA's ability to screen patients for disorders that have validated screening criteria--specifically tuberculosis (TB) and iron-deficiency anemia.

Design: Children between 0 and 11 years were randomized by the CHICA system.