Scientists have long known that dopamine helps the brain learn from rewards, but a new computational model shows how for people with schizophrenia this learning system can break down and simultaneously produce two very different symptoms — delusions and a loss of motivation.

Professor Kazuhiro Ogata and Senior Lecturer Canh Minh Do at the Japan Advanced Institute of Science and Technology are addressing the critical need for reliable quantum computing by developing formal verification methods. By creating frameworks such as the Concurrent Dynamic Quantum Logic (CDQL) to model and verify quantum protocols, their work aims to make quantum systems dependable and ready for real-world applications.

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.