In vitro reconstitution reveals substrate selectivity of protein S-acyltransferases.

Protein S-acylation, commonly known as protein palmitoylation, is the most prevalent form of protein lipidation with ∼6000 target proteins and in humans, is catalyzed by 23 integral membrane enzymes of the zDHHC family. Recognition of its importance in cellular physiology as well as human diseases has undergone an explosive growth in recent years. Yet, the nature of zDHHC-substrate interactions has remained poorly understood for most zDHHC enzymes.

Two species competition with a "non-smooth" Allee mechanism: applications to soybean aphid population dynamics under climate change.

The soybean aphid () is an invasive insect pest that continues to cause large-scale damage to soybean crops in the North Central United States. Recent empirical evidence points to differential fitness in the pestiferous aphid biotypes under abiotic stresses such as flooding. As climate change predicts increased flooding in the North Central United States, mathematical models that incorporate such factors are required to better inform pest management strategies.

Continuous quality improvement for prehospital STEMI improved triage rates and achievement of gold standard < 90-min EMS-to-balloon time.

Background: ST-elevation myocardial infarction (STEMI) is a type of myocardial infarction caused by a buildup of plaque or clot in the coronary arteries. There are approximately 750,000 STEMI cases each year in the United States. The American Heart Association's Mission Lifeline initiative aimed to optimize prehospital emergency medical services (EMS) and enhance STEMI triage rates through improved standardized protocol.

Data-driven ergonomic risk assessment of complex hand-intensive manufacturing processes.

Hand-intensive manufacturing processes, such as composite layup and textile draping, require significant human dexterity to accommodate task complexity. These strenuous hand motions often lead to musculoskeletal disorders and rehabilitation surgeries. Here we develop a data-driven ergonomic risk assessment system focused on hand and finger activity to better identify and address these risks in manufacturing.