A National Science Foundation grant will support Anne Brown’s goal to enhance the technical and practical data science skills of students studying molecular bioscience.

Deep in Guatemala’s Maya rainforest, a team led by Washington State University researchers captured more than just photos of jaguars, tapirs and ocelots. They also captured a rare success story: a way for humans and wildlife to share a forest without destroying it. In a new study published in Conservation Biology, scientists from WSU and the Wildlife Conservation Society found that a community-managed forest in Guatemala’s Maya Biosphere Reserve supports a rich variety of wildlife. The area, where residents legally log timber and hunt for subsistence, harbors medium-to-large mammals and birds in numbers comparable to those in a strictly protected national park and a wildlife preserve.

A deep blue organic light-emitting diode (OLED) developed by researchers at Science Tokyo operates on just a single 1.5 V, overcoming the high-voltage and color-purity problems that have long limited blue OLEDs. The breakthrough was achieved by introducing a new molecular dopant that prevents charge trapping, a problem that previously hampered the performance of low-voltage OLEDs. The resulting device produces sharp blue emission that meets BT.2020 standards, paving the way toward brighter, more energy-efficient displays.

A multicenter study led by Prof. Shuixing Zhang and Prof. Bin Zhang from the First Affiliated Hospital of Jinan University enrolled 246 patients with locally advanced NPC treated with immunotherapy. By applying artificial intelligence algorithms, the team extracted and selected optimal radiomic features from medical imaging to construct a predictive model.

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.