Results 151 to 160 of about 88,883 (264)

Selenium Nanoparticles Selectively Target KRAS G13D to Inhibit Colorectal Cancer

Advanced Science, EarlyView.
The mechanisms of SeNPs therapy in cancer treatment, encompass three parallel actions: (1) seleno‐amino acids, key metabolites, upregulate GPX2 expression, thereby inhibiting tumor metastasis via the GPX2‐HIF1α‐VEGF signaling pathway; (2) selenite (SeO32−), an inorganic metabolite, forms hydrogen bonds with amino acid residues 13–17 of the KRAS G13D ...
Xiaoting Liu, Chong Wu, Shiyao Song, Li Ma, Shaoqing Huang, Yuting He, Qinghai Li, Yanzhou Chang, Dan Jiang, Yong Mei, Junchao Cai, Zhenshuang Du, Tianfeng Chen, Weiling He   +13 more
wiley   +1 more source

Fractional charge density functional theory elucidates electro-inductive and electric field effects at electrochemical interfaces. [PDF]

Proc Natl Acad Sci U S A
Kim JH, Yang W.
europepmc   +1 more source

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced 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, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Soft Mechanical Inductive Sensors: Principles, Design, and Applications. [PDF]

Micromachines (Basel)
Awais M, Indukumar G, Cafiso D, Beccai L.   +3 more
europepmc   +1 more source

Magnetoelectric Nanoparticle‐Based Wireless Brain–Computer Interface: Underlying Physics and Projected Technology Pathway

Advanced Science, EarlyView.
Magnetoelectric nanoparticles (MENPs) enable fully wireless, minutely invasive neuromodulation, and potentially neural recording, by converting magnetic into electric and, conversely, electric into magnetic fields, respectively, at high spatiotemporal resolution.
Elric Zhang, Max Shotbolt, Mostafa Abdel‐Mottaleb, Shawnus Chen, Victoria Andre, Jieyuan Tian, Jonathan Shulgach, Max Murphy, Brian Noga, Ping Liang, Darcy Griffin, Douglas Weber, Marta Pardo, Salvador Pane, Sakhrat Khizroev   +14 more
wiley   +1 more source

Rethinking the Nature and Extent of Inductive Effects in Organic Compounds. [PDF]

J Chem Educ
Elliott MC, Johnson EC, Gregory KP, Hughes CE.   +3 more
europepmc   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Inductive Microsensor for Magnetic Field Detection: Application in Wireless Power Transfer Systems. [PDF]

Sensors (Basel)
Cortes-Aguilar TA, Vidaña-Morales RY, Gómez-Gutiérrez D, Vidaña-Morales DR.   +3 more
europepmc   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source