Tokyo, Japan – Researchers from Tokyo Metropolitan University have applied ideas from polymer physics to illuminate the mechanism behind a key pathology in Alzheimer's disease, the formation of fibrils of tau proteins. They showed that fibril formation is preceded by the birth of large protein clusters, mirroring the crystallization of polymers. Crucially, dissolving these clusters helped to prevent fibrils forming in solution. Their work signals a paradigm shift for the development of treatments for neurodegenerative diseases.

Over the past 50 years, geographers have embraced each new technological shift in geographic information systems (GIS) — the technology that turns location data into maps and insights about how places and people interact — first the computer boom, then the rise of the internet and data-sharing capabilities with web-based GIS, and later the emergence of smartphone data and cloud-based GIS systems. Now, another paradigm shift is transforming the field: the advent of artificial intelligence (AI) as an independent “agent” capable of performing GIS functions with minimal human oversight.  

There’s a lion’s share of potential energy in the vibrations produced by footsteps on dance floors, exercise machines in the gym, or the engines of cars, planes or construction equipment. Some tech companies have already begun to harvest electricity from waste vibrations to power lights and recharge batteries using a class of piezoelectric ceramic materials, which emit electrical charges when stepped on or manipulated.

Sometimes, less really is more. By removing oxygen during synthesis, a team led by materials scientists at Penn State created seven new high-entropy oxides, or HEOs: a class of ceramics composed of five or more metals with potential for applications in energy storage, electronics and protective coatings.

A research paper by scientists at Shanghai Jiao Tong University School of Medicine presented BioCompNet—an end-to-end deep learning workflow that integrates dual-parametric magnetic resonance imaging (MRI) sequences (water/fat) with a hierarchical U-Net architecture to enable fully automated quantification of 15 biomechanically critical BC components..

The research paper, published on Aug. 20, 2025 in the journal Cyborg and Bionic Systems.