As cities grow denser and hotter, creating space for greenery becomes increasingly difficult. To address this challenge, researchers from Chiba University developed a data-driven framework that integrates artificial intelligence and spatial analysis to map vertical greenery across Tokyo’s 23 wards. By analyzing over 80,000 street-view images, the team identified uneven distribution patterns and proposed a vertical greening demand index to guide future urban greening initiatives and climate-resilient urban planning.

A new review highlights major advances in bio-hydrovoltaic technology, marking a shift from traditional non-living materials to living biological systems that generate electricity through metabolic processes. This revolutionary energy approach offers self-regulation, environmental adaptability, and biodegradability, with strong potential in wearables, environmental monitoring, and distributed energy networks. Future directions include a “hydrovoltaic internet,” “hydrovoltaic intelligence,” and “hydrovoltaic ecology,” while key challenges remain in material stability, scalable manufacturing, and biosafety.

Biomarkers for predicting suicide risk in hospitalised patients with mental disorders have been understudied. Currently, suicide risk assessment tools based on objective indicators are limited in China. To examine the value of various biomarkers in suicide risk prediction and develop a risk assessment model with clinical utility using machine learning.