Results 201 to 210 of about 5,528,017 (309)

Thymosin Alpha‐1 Provides Direct Neuroprotection by Engaging the Orexin Receptor HCRTR1 to Suppress Neuronal Necroptosis

open access: yesAdvanced Science, EarlyView.
In this study, we unveil a thymus‐brain endocrine axis wherein Tα1 engages HCRTR1 to inhibit RIPK3‐mediated necroptosis. This study nominates the Tal‐HCRTR1‐RIPK3 axis as a potent and clinically translatable therapeutic target for stroke and neurodegeneration.
Xinmei Kang   +11 more
wiley   +1 more source

GHRHR Deficiency Enhances Retinal Ganglion Cell Survival and Visual Functions in Experimental Glaucoma by Inhibiting Ferroptosis

open access: yesAdvanced Science, EarlyView.
Glaucoma, a major cause of blindness, involves retinal ganglion cell (RGC) degeneration. This study shows growth hormone‐releasing hormone receptor (GHRHR) deficiency preserves RGC survival and restores vision, unlike activation which only aids survival.
Yan Tong   +24 more
wiley   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

open access: yesAdvanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu   +5 more
wiley   +1 more source

Data‐Driven Modeling of Composition–Processing–Microstructure Relations for Recycled Aluminum Cast Alloys

open access: yesAdvanced Science, EarlyView.
Interpretable machine learning reveals how composition and processing govern the formation and microstructural burden of Fe‐rich intermetallic compounds in recycled Al–Si–Fe–Mn alloys. By separating morphology selection from morphology‐conditioned burden partitioning, this framework shows that identical Fe contents can yield different intermetallic ...
Jaemin Wang   +2 more
wiley   +1 more source

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

open access: yesAdvanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou   +3 more
wiley   +1 more source

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