Results 31 to 40 of about 141 (134)
This study demonstrates that iron overload triggers widespread chromatin compaction and transcriptional repression in human granulosa cells, recapitulating features of endometriosis. The epigenetic reprogramming is orchestrated by a TFEB‐SOX4‐SWI/SNF axis, with SOX4 acting as a central, dosage‐sensitive regulator.
Feifei Li +15 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
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
First‐principles calculations reveal that monolayer In2O${\rm In}_2{\rm O}$ hosts type‐II Dirac fermions near the Fermi level, which split into Weyl points under spin‐orbit coupling. The material exhibits negative and giant magnetoresistance, a pronounced spin Hall effect, and phonon‐mediated superconductivity at 1.5 K, establishing it as a unique ...
Qing‐Bo Liu +6 more
wiley +1 more source
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li +8 more
wiley +1 more source
Decoding Spatial Heterogeneity and Multi‐Omics Regulation with Hierarchical Graph Learning
ABSTRACT Recent advances in spatial multi‐omics technologies have enabled the simultaneous profiling of multiple molecular layers within the same tissue slice, providing unprecedented opportunities to investigate tissue spatial organization. However, most existing computational methods identify spatial domains in a purely data‐driven manner, rarely ...
Jiazhou Chen +6 more
wiley +1 more source
STAID is a unified deep learning framework that couples iterative pseudo‐spot refinement with neural network training through a feedback loop and exploits gene co‐expression information to model higher‐order interactions, achieving accurate and robust cell‐type deconvolution in spatial transcriptomics.
Jixin Liu +5 more
wiley +1 more source
We investigate the geometry‐governed optoelectronic anisotropy arising from dielectric confinement in quasi‐1D γ‐GaS nanoribbons with intrinsically isotropic atomic structures. Dielectric mismatch between the nanoribbon and its surroundings leads to a general polarization‐dependent photoresponse during near‐field scattering.
Jiawei Jing +16 more
wiley +1 more source
Topology‐Aware Deep Learning on Higher‐Order Structures for Drug Response Prediction
We present TopDr, a topology‐aware deep learning framework that encodes both drugs and cell lines as multiscale simplicial complexes, capturing interactions at the 0‐, 1‐, and 2‐simplex levels. By jointly integrating local higher‐order neighborhoods and global topological structures, TopDr generates enriched representations for sensitivity prediction ...
Cong Shen +3 more
wiley +1 more source
This review explores the convergence of artificial intelligence technologies in modeling drug–drug and drug–target interactions. By evaluating advanced feature engineering, architectural innovations, and learning paradigms reveals shared evolutionary trends and critical challenges, such as cold‐start settings and shortcut learning.
Xin Sun, Tong Wang
wiley +1 more source
A fully compensated synthetic antiferromagnet (SAF) multilayer exhibits a uniform state at zero field, without skyrmions. We use a SAF bias system to provide RKKY‐mediated exchange bias to the SAF multilayer, promoting zero‐field skyrmion stabilization and polarity control.
Emily Darwin +5 more
wiley +1 more source

