Results 91 to 100 of about 15,587 (201)

A Neuro-Symbolic Bioinformatics Framework for Unlocking Chordate Physiological Dark Data and Validating Allometric Scaling. [PDF]

Biology (Basel)
Duan Z, Zhao G, Li C, Liu B.
europepmc   +1 more source

Mapping Steroidogenic Perturbations Under Endocrine Disruptor Mixtures Across Demographic Subgroups: Structural and Metabolomic Insights

Advanced Science, EarlyView.
Population‐scale EDC–hormone association mapping among 4255 participants across demographic subgroups identifies phthalate metabolites as the most consistent signals associated with lower testosterone‐related markers in males. Integrative mechanistic validation prioritizes MCPP as a key phthalate metabolite linked to CYP17A1‐centered disruption of ...
Yanling Chen, Lei Huang, Yingtong Jiang, Guohong Zhao, Mengyuan Zhu, Xiulian Lu, Lang Lang, Akinpelumi Oluwatobiloba Esther, Longhao Fan, Yuqi Jiang, Chang Sun, Xiaoling Zhang, Kun Zhou, Xiaoming Ji, Minjian Chen   +14 more
wiley   +1 more source

Controls on natural hydrogen generation during serpentinization of mantle rocks. [PDF]

Nat Commun
Christiansen R, Sobh M, Ostertag-Henning C, Gianni G, Saspiturry N, Chevrot S, Langenheim V, García-Pintado J, Gabriel G.   +8 more
europepmc   +1 more source

Chemically Gradient Ordered Nanodomains Enable Large Tensile Ductility in Gigapascal Lightweight Refractory High‐Entropy Alloys

Advanced Science, EarlyView.
A high‐strength lightweight refractory high‐entropy alloy achieves extraordinary ductility owing to the introduction of coherent chemically gradient ordered nanodomains (CGONs). The CGONs not only serve as effective barriers to dislocation motion (strengthening) but also significantly promote dislocation nucleation and multiplication (ductilizing) upon
Wei Zhang, Dingshun Yan, Yong Zhang, Zhiming Li   +3 more
wiley   +1 more source

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

EHMN 2026: A Thermodynamically Refined, SBML-Standardised Human Metabolic Network for Genome-Scale Analysis and QSP Integration. [PDF]

Metabolites
Goryanin I, Slovianov L, Checkley S, Goryanin I.   +3 more
europepmc   +1 more source

8‐Oxoguanine Modified CircMTUS1 Drives PABPC1 Phase Separation to Promote Gastric Cancer Progression and Cisplatin Resistance via Autophagy

Advanced Science, EarlyView.
ABSTRACT Gastric cancer (GC) is a major global health concern, as its prevention and treatment remain significant challenges. The 8‐oxoguanine (o8G) modification of circRNAs, alongside their capacity to orchestrate liquid‐liquid phase separation (LLPS) and autophagy, plays a pivotal role in driving tumor progression and determining therapeutic outcomes.
Lei Peng, Lurong Li, Zhenghui Zhu, Chenyang Li, Huaiming Sang, Guoxin Zhang, Xuan Li, Yini Dang, Yuanyuan Li   +8 more
wiley   +1 more source

Interface and Thermophysical Properties of <i>R</i>32 Refrigerant. [PDF]

ACS Omega
Adekoya-Olowofela A, Manna S, Sankaranarayanan SK.   +2 more
europepmc   +1 more source

Enhanced Ionic Conductivity at the Solid Electrolyte Interphase of Oxygen‐Doped Li6PS5Cl

Advanced Science, EarlyView.
Machine‐learned molecular dynamics and machine‐learning‐based phase identification reveal the kinetically formed SEI at buried Li | Li6PS5Cl interfaces. The SEI is dominated by Li2S‐based anion‐substituted phases, while oxygen doping enhances SEI ionic conductivity.
Sojeong Yang, Sungwoo Kang, Atefeh Yadegarifard, Hyun‐Jae Lee, Nongnuch Artrith, Jung‐Hoon Lee, Byungju Lee   +6 more
wiley   +1 more source

Early-stage environmental impact forecasting of chemicals and processes with machine learning and data analytics tools. [PDF]

Clean Technol Environ Policy
Appiah HD, Conway M, Patel J, McMahon M, Hesketh R, Yenkie KM.   +5 more
europepmc   +1 more source