Large language models generate functional protein sequences across diverse families.

Deep-learning language models have shown promise in various biotechnological applications, including protein design and engineering. Here we describe ProGen, a language model that can generate protein sequences with a predictable function across large protein families, akin to generating grammatically and semantically correct natural language sentences on diverse topics. The model was trained on 280 million protein sequences from >19,000 families and is augmented with control tags specifying protein properties.

The Safety and Utility of Ground Transport of Traumatic Cardiopulmonary Arrest Patients by Helicopter Emergency Medical Services Crews.

Objective: Patients suffering from traumatic cardiopulmonary arrest (TCPA) typically demonstrate dismal survival rates. Some helicopter emergency medical services (HEMS) systems transport TCPA patients via ground with a referring agency when cardiopulmonary pulmonary resuscitation is in progress. With expanding research on the inherent risk of ground emergency medical services (GEMS) transport with the use of lights and sirens to both crew and the general public, the benefits may not outweigh the risks of transporting these patients by GEMS.