Researchers from City University of Hong Kong, the Chinese Academy of Sciences, and the Massachusetts Institute of Technology have developed an artificial intelligence-driven workflow called AAPSI (AI-Accelerated PhotoSensitizer Innovation) that integrates expert knowledge, scaffold-based molecule generation, and Bayesian optimization to accelerate the discovery of novel photosensitizers for photodynamic therapy (PDT). Through this workflow, the team generated 6,148 candidate molecules and experimentally validated a hypocrellin-based compound, HB4Ph, which achieves a singlet oxygen quantum yield (ϕ_Δ) of 0.85 and absorption maxima (λ_max) of 645 nm — outperforming all clinical and trial-stage photosensitizers. The work is published in AI for Science .

Researchers at the Yong Loo Lin School of Medicine, National University of Singapore (NUS Medicine) have developed a revolutionary new method to improve compact gene-editing tools known as base editors, which enable smaller, more precise DNA correction tools that may be safer for future gene therapies.Researchers at the Yong Loo Lin School of Medicine, National University of Singapore (NUS Medicine) have developed a revolutionary new method to improve compact gene-editing tools known as base editors, which enable smaller, more precise DNA correction tools that may be safer for future gene therapies.

The introduction of vision-enabled artificial intelligence (AI) to medical scribes – the recording devices used by doctors to document meetings with patients in real-time – could increase the accuracy of patient notes and save valuable time for clinicians.Researchers found that a vision-enabled AI scribe, employing a combination of Google’s Gemini model and Ray-Ban Meta smart glasses, substantially improved the documentation accuracy of pharmacist-patient consultations and reduced omissions and errors in clinical notes.

A paper titled "Tip-enhanced sum frequency generation spectroscopy using temporally asymmetric pulse for detecting weak vibrational signals," published on February 19, 2026 by a research team from the Institute for Molecular Science (Atsunori Sakurai, Shota Takahashi, Tatsuto Mochizuki, and Toshiki Sugimoto) and Tohoku University (Tomonori Hirano and Akihiro Morita), has been selected as a "Featured Article" in The Journal of Chemical Physics, published by the American Institute of Physics (AIP), in recognition of its particularly noteworthy research.

The paper is available at the following URL: https://pubs.aip.org/aip/jcp/article/164/7/074202/3380428/Tip-enhanced-sum-frequency-generation-spectroscopy

Researchers analyzed more than 35,000 images of women’s clothing spanning from 1869 to today. Team measured features like hemlines, necklines and waistlines. Mathematical model shows styles tend to rise in popularity, fall out of favor and return to popularity roughly every 20 years.