A comprehensive peer-reviewed invited review published in Psychedelics examines the therapeutic potential of MDMA across psychiatric conditions, synthesizing evidence from PTSD trials to emerging applications in autism and eating disorders. The authors identify gut-brain axis mechanisms underlying resilience enhancement while addressing critical safety considerations including hyponatremia and neurotoxicity risks. This synthesis provides clinicians and researchers with an integrated framework for understanding MDMA-assisted therapy as regulatory decisions evolve.

The research team led by Dr. Byung Chul Lee at the Bionics Research Center of the Korea Institute of Science and Technology (KIST, President Sang-Rok Oh), in collaboration with Prof. Jae-Woong Jeong at KAIST (President Kwang-Hyung Lee), Prof. Whal Lee at Seoul National University Hospital (Director Young-Tae Kim), and Prof. Pierre T. Khuri-Yakub at Stanford University (President Jonathan Levin), announced the development of a silicon-based disposable eco-friendly ultrasound patch. This achievement marks the first realization of superior performance beyond conventional high-cost lead-based ultrasound transducers without using lead at all.

Diabetes mellitus represents a major global health issue, driving the need for noninvasive alternatives to traditional blood glucose monitoring methods. Recent advancements in wearable technology have introduced skin-interfaced biosensors capable of analyzing sweat and skin biomarkers, providing innovative solutions for diabetes diagnosis and monitoring. This review comprehensively discusses the current developments in noninvasive wearable biosensors, emphasizing simultaneous detection of biochemical biomarkers (such as glucose, cortisol, lactate, branched-chain amino acids, and cytokines) and physiological signals (including heart rate, blood pressure, and sweat rate) for accurate, personalized diabetes management. We explore innovations in multimodal sensor design, materials science, biorecognition elements, and integration techniques, highlighting the importance of advanced data analytics, artificial intelligence-driven predictive algorithms, and closed-loop therapeutic systems. Additionally, the review addresses ongoing challenges in biomarker validation, sensor stability, user compliance, data privacy, and regulatory considerations. A holistic, multimodal approach enabled by these next-generation wearable biosensors holds significant potential for improving patient outcomes and facilitating proactive healthcare interventions in diabetes management.