A multidisciplinary team of researchers from the Istituto Italiano di Tecnologia (IIT-Italian Institute of Technology) and IRCCS Ospedale Policlinico San Martino, coordinated by Fabio Benfenati, head of the Center for Synaptic Neuroscience and Technology at IIT, and Stefano Di Marco, in collaboration with the Politecnico di Milano, has demonstrated the effectiveness of the Ziapin2 molecule as a promising new instrument in countering the effects of retinitis pigmentosa and age-related macular degeneration, conditions that lead to the progressive deterioration of the photoreceptors in the retina, causing progressive blindness.

A research team led by Dr. Tetsuya Muramoto from the Faculty of Science at Toho University has demonstrated the mechanisms by which periodic chemical signal frequencies in cells regulate gene expression via transcription factors and influence the cell fate determination processes. This groundbreaking revelation was made using optogenetic technology, which facilitates the manipulation of biological phenomena using light. Their findings were recently published in the Development journal on January 14, 2025.

Peter Turchin, from the Complexity Science Hub, and an international team of collaborators decided to evaluate the historical knowledge of advanced A.I. models such as ChatGPT-4, Llama, and Gemini. According to the results, the A.I. chatbots struggled with historical knowledge. GPT-4-Turbo emerged as the best-performing model but still only achieved a 46% balanced accuracy—barely above the baseline of random guessing. 

A new study explores the integration of biopolymers with polyacrylic acid hydrogels, highlighting their potential applications in bioresources and bioproducts. This research offers insights into the development of sustainable and functional biomaterials for various fields, including flexible electronics and biosensing.

POSTECH Ushers in a New Era of Clean Hydrogen Production with Microwave Technology.

The research team led by Dr. Youngdo Jeong of the Center for Advanced Biomolecular Recognition the Korea Institute of Science and Technology (KIST), in collaboration with Professor Seok-Ho Kang’s team from the Department of Urology, Korea University College of Medicine, has developed a urine-based diagnostic kit for bladder cancer that can be conveniently used at home. This kit can accurately detect bladder cancer biomarkers without any preprocessing of urine samples.

Professor Shinhyun Choi and Professor Young-Gyu Yoon’s Joint Research Team from the School of Electrical Engineering developed a computing chip that can learn, correct errors, and process AI tasks