Results 151 to 160 of about 415,263 (295)
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Mapping the “Supply–Demand–Flow” of Ecosystem Services for Ecosystem Management in China
This study develops a “supply–demand–flow” framework clarifies how ecosystem services move between regions by distinguishing potential and actual supply and demand. Using integrated biophysical–socioeconomic modeling, nine services in China were mapped.
Yikun Zhang +3 more
wiley +1 more source
This study outlines the developmental pipeline of a multiplexed nanozyme‐based lateral flow immunoassay for the purpose of ovarian germ cell tumor detection. It demonstrates the application of a design of experiments optimization approach for nanozyme probe conjugate development.
Aida Abdelwahed +10 more
wiley +1 more source
Transcriptomic and Neuroimaging Decoding of Brain‐Immune Crosstalk in Thyroid Eye Disease
This study employed an imaging transcriptomics framework integrating resting‐state fMRI with Allen Human Brain Atlas transcriptomic data, coupled with peripheral blood RNA sequencing, to decode brain‐immune crosstalk in thyroid eye disease. Frontal, parietal, subcortical, and brainstem regions were identified as key neuroimmune‐ vulnerable regions ...
Haiyang Zhang +15 more
wiley +1 more source
Quantitative Kernel estimation from traffic signs using slanted edge spatial frequency response as a sharpness metric. [PDF]
Pandey A +4 more
europepmc +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
A blind image super-resolution network guided by kernel estimation and structural prior knowledge. [PDF]
Zhang J +10 more
europepmc +1 more source
Multi‐omics analyses uncover breed‐specific cis‐regulatory landscapes and higher‐order chromatin architectural differences that underlie early postnatal muscle fiber divergence in pigs. A super‐enhancer upstream of PPP3CB recruits MEF2C to activate PPP3CB transcription, while the PPP3CB–MEF2C positive feedback loop promotes oxidative muscle fiber ...
Shuailong Zheng +8 more
wiley +1 more source
INB3P is a multimodal framework for blood–brain barrier‐penetrating peptide prediction under extreme data scarcity and class imbalance. By combining physicochemical‐guided augmentation, sequence–structure co‐attention, and imbalance‐aware optimization, it improves predictive performance and interpretability.
Jingwei Lv +11 more
wiley +1 more source
Customizing Tactile Sensors via Machine Learning‐Driven Inverse Design
ABSTRACT Replicating the sophisticated sense of touch in artificial systems requires tactile sensors with precisely tailored properties. However, manually navigating the complex microstructure‐property relationship results in inefficient and suboptimal designs.
Baocheng Wang +15 more
wiley +1 more source

