Background: Drug-drug interactions (DDIs) are a significant source of morbidity and adverse drug events (ADEs), particularly in situations of polypharmacy and complex medication regimens. While rules- Show more
Background: Drug-drug interactions (DDIs) are a significant source of morbidity and adverse drug events (ADEs), particularly in situations of polypharmacy and complex medication regimens. While rules-based software integrated in electronic health records (EHRs) has demonstrated proficiency in identifying DDIs present in medication regimens, large language model (LLM) based identification requires thorough benchmarking and performance evaluation using high-quality datasets for safe use. The purpose of this study was to develop a series of Show less
Efforts to identify anti-cancer therapeutics and understand tumor-immune interactions are built with in vitro models that do not match the microenvironmental characteristics of human tissues. Using in Show more
Efforts to identify anti-cancer therapeutics and understand tumor-immune interactions are built with in vitro models that do not match the microenvironmental characteristics of human tissues. Using in vitro models which mimic the physical properties of healthy or cancerous tissues and a physiologically relevant culture medium, we demonstrate that the chemical and physical properties of the microenvironment regulate the composition and topology of the glycocalyx. Remarkably, we find that cancer and age-related Show less