Amorphous aluminum oxide is often used in the form of protective thin films and membranes. However, what happens at the atomic level in the material is poorly understood. Thanks to innovative experiments and machine learning, an interdisciplinary team of Empa researchers was able to model its disordered structure with a high degree of accuracy for the first time.

Key Findings:

AI-powered Aging Clock: The new proteomic clock predicts biological age with high accuracy (R²=0.84, MAE=2.68 years) and captures accelerated aging signatures in severe lung disease cases—patients with severe COVID-19 (and likely fibrosis) exhibited biological ages nearly three years older than healthy controls.

Distinct Molecular Signatures: Analysis with the ipf-P3GPT generative model revealed both shared and unique gene expression patterns between aging lungs and fibrotic disease, highlighting that IPF is not just accelerated aging but entails unique pathological processes.

Pathway-Level Insights: The study identified four key pathways (TGF-ß signaling, oxidative stress, inflammation, ECM remodeling) as central to both IPF and aging, but involved differently at the gene level.

Saliva is more than spit. It helps with chewing and swallowing, protects teeth and gums, and even has antimicrobial and digestive properties. However, certain conditions or medical treatments, such as hemodialysis, chemotherapy and radiation therapy, reduce natural saliva production. Now, researchers publishing in ACS Applied Polymer Materials have created a reusable hydrogel that releases artificial saliva over time, which could help provide sustained relief from dry mouth.