Results 231 to 240 of about 185,504 (288)

Advancing Precision Nutrition Through Multimodal Data and Artificial Intelligence

open access: yesAdvanced Science, EarlyView.
Individual responses to food vary dramatically, challenging traditional dietary advice. This review explores how the unique genetic makeup, gut microbiome, and brain activity shape host metabolic health. We examine how artificial intelligence integrates these multimodal data to predict individualized dietary needs, moving beyond one‐size‐fits‐all ...
Yuanqing Fu   +5 more
wiley   +1 more source

Soft, Flexible, and Stretchable Platforms for Tissue‐Interfaced Bioelectronics

open access: yesAdvanced Science, EarlyView.
Bio‐integrated electronics provide mechanically compliant and stable interfaces with soft biological tissues. Representative applications include neural interfaces, wet‐organadhesive electronics, and skin‐interfaced devices. E represents Young´s modulus and ε represents strain.
Kento Yamagishi   +3 more
wiley   +1 more source

A Laminating Strategy to Manyfold Enhance the Elastic Stretchability of Stretchable Electronics

open access: yesAdvanced Science, EarlyView.
We propose a laminating strategy that laminates a thick‐polymer layer onto the thin‐ribbon metallic structure. Using serpentine structures on soft and hard substrates as representative cases, this approach increases elastic stretchability by 3.5‐fold and 2.3‐fold.
Zanxin Zhou   +6 more
wiley   +1 more source

Patient‐Derived 3D‐Bioprinted Intrahepatic Cholangiocarcinoma Models Recapitulate Tumor Autologous Traits and Predict Personalized Adjuvant Therapy

open access: yesAdvanced Science, EarlyView.
Leveraging 3D bioprinting, this study establishes patient‐derived in vitro models of intrahepatic cholangiocarcinoma. These models faithfully recapitulate the histopathology, molecular profiles, and genomic characteristics of the original patient tumors.
Yuce Lu   +23 more
wiley   +1 more source

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

open access: yesAdvanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan   +8 more
wiley   +1 more source

Home - About - Disclaimer - Privacy