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During transfer of organs from a donor to a patient, the organs deteriorate in part due to damage by free radicals. Application of antioxidant solutions could extend organ preservation times. The authors found that vitamin E and butylated hydroxytoluene seemed to be most effective in arresting cell damage of a bovine lung.

This study investigated whether soursop, a ketogenic diet-related compound called BHB, and circadian synchronization could reduce seizure recovery time in fruit flies used as a model for epilepsy.

This study used single-cell RNA sequencing to examine whether B cells can predict response to pembrolizumab and radiation therapy in patients with triple-negative breast cancer.

This study examines the effects of tumeric, and alph-lipoic acid on segment regeneration and cardiovascular pulse rate, using the California blackworm. Results can ultimately demonstrate potential natural compounds for tissue repair and their effect on physiological activity.

This project investigated whether previously identified genetic risk factors in non-Korean populations were associated with high gastric cancer incidence rates in Koreans.

The explored the potential of an epitope-based vaccine for Rocio virus using computational methods and M13 bacteriophage technology. Researchers identified 30 promising B- and T-cell epitopes and designed vaccine candidates using both phage display and E. coli expression systems.

This study explored using iron oxide nanoparticles embedded in liposomes and coated with antibacterial chitosan as a potential alternative to antibiotics for treating bacterial meningitis. The nanoparticles were tested for their ability to cross a model blood–brain barrier and kill E. coli, with and without magnetic guidance.

The authors studied the accuracy of two commonly used explainable AI techniques for detecting pneumonia in chest x-rays.

This study explored sunscreen storage temperature affects the efficacy of sunscreen to block UV light.

This study shows the efficacy of leveraging transfer learning, specifically from residual networks, to detect CVDs and possible signs of CVDs. The findings indicate that leveraging transfer learning from residual networks alongside medical professionals is a highly promising approach for CVD detection and diagnosis, warranting further investigation.