Results 141 to 150 of about 22,931,160 (232)
STWave transforms massive microscopic‐resolution spatial transcriptomics into interpretable fine‐scale tissue maps through patch‐wise inference, wavelet‐based multi‐scale encoding, and dual‐domain reconstruction. It reduces noise while preserving weak spatial signals, enabling efficient analysis of 6 40 000 spots of 2.47 GB GPU memory and revealing ...
Tao Jiang +9 more
wiley +1 more source
A Transformer‐based AI framework, DLINP, screens millions of compounds to identify Co68, a cobalt‐pincer organometallic complex that biases TLR4‐MD2 signaling toward antitumor interferon activation while suppressing inflammatory toxicity through an early TLR4‐SYK‐STAT1 axis.
Xuefei Guo +10 more
wiley +1 more source
Using Benzylated Poplar as Adhesive in Manufacturing Wood-Based Panels
Benzylated poplar was prepared and its properties were characterized by Fourier transform infrared spectroscopy, a soften point test, and differential scanning calorimetry. This study reports on the enhanced thermoplasticity of benzylated poplar with its
Yanzhong, Zhu +3 more
core
NICE: A Two‐Step Non‐Invasive Framework for Embryo cfDNA Read Enrichment and Quality Assessment
The non‐invasive NICE framework, built on an ensemble stacking machine learning model, prioritizes embryos by analyzing cell‐free DNA from spent culture medium. By integrating multimodal signals, including genomic and epigenetic profiles, this automated approach standardizes morphological assessment without human bias, paving the way for more precise ...
Xueya Zhou +6 more
wiley +1 more source
An interpretable, unsupervised artificial intelligence framework identifies a 13‐cellular morphometric biomarker (CMB) signature from routine H&E whole‐slide images. Validated across 2,602 patients, the fixed signature generalizes across colorectal, gastric, and esophageal tissues without retraining, stratifies prognosis and precancerous lesion risk ...
Pin Wang +14 more
wiley +1 more source
Low latency carbon budget estimates for July 2024–June 2025 combine atmospheric CO2 growth rates, fossil emissions, ocean uptake, DGVM land fluxes, and OCO‐2 inversions. The budget shows that late‐2024 land carbon losses dominate the annual anomaly, while early‐2025 recovery differs between bottom‐up models and top‐down inversions, especially in ...
Piyu Ke +32 more
wiley +1 more source
In an invasive beetle–fungus complex, the mutualist Leptographium procerum induces host HSP83 and modulates Toll‐dependent antifungal immunity. HSP83 mediates two‐tiered control by associating with selected fungal recognition receptors and restraining Dorsal‐driven antimicrobial peptide transcription.
Qingtai Yang +8 more
wiley +1 more source
This study establishes a universally applicable framework for vesicle surface analysis by combining engineered amyloid‐β‐displaying nanovesicles with machine‐learning‐optimized impedance spectroscopy. Equivalent‐circuit modeling reveals that membrane capacitance correlates with the surface protein states, enabling label‐free quantification of vesicle ...
Jaeyoon Song +5 more
wiley +1 more source
A Physical Adaptive Material Motor Unit Neural Network: A Hygromorph Composite Material Machine
This study introduces a new class of material‐based intelligent machines. It presents a Physical Adaptive Material Motor Unit Neural Network, an assembly of smart 4D printed actuators and a controlling system that adapt through environmental interaction its shading behavior.
Charles de Kergariou +2 more
wiley +1 more source
Robots and Minimal, Physics‐Informed Features: A Hybrid Framework for Enzyme Catalysis
Robotic experimentation and physics‐informed machine learning combine to predict enzyme substrate scope. With a handful of interpretable features derived from docking and quantum mechanics calculations, our model rivals descriptor‐heavy AI approaches and extrapolates to unseen substrates and enzyme classes.
Natalia Onishchenko +8 more
wiley +1 more source

