Results 121 to 130 of about 481,631 (238)
This study introduces a novel, safe, and effective surgical technique: Cranial bone transport (CBT) to improve traumatic brain injury (TBI) outcomes in rats. CBT significantly accelerated skull defect bone repair in addition to its promoting effects on neurological function recovery. This work provides an alternative therapy for patients suffering from
Shanshan Bai+20 more
wiley +1 more source
A dual‐particle interfacial self‐assembly approach is used to create surface‐accessible Pickering emulsions with Au@Prussian blue nanoparticles acting as the functional component. These emulsions have strong plasmonic properties and are equipped with molecular sieves and internal standards.
Yingrui Zhang+5 more
wiley +1 more source
EGFR‐TKIs Induced DPP4 Drives Metabolic Reprogramming of Persister Cells in Lung Cancer
Drug‐tolerant persister (DTP) cells emerge early during EGFR‐TKI treatment, preceding the development of acquired resistance. Elevated DPP4 in DTP cells drives metabolic reprogramming and antioxidant adaptation, promoting cell survival under drug pressure.
Yuanzhou Zhang+7 more
wiley +1 more source
Astrocytic ET‐1 System Determines Microglia Phenotype Following Spinal Cord Injury
The study reveals that astrocytic ET‐1 system is solely activated by thrombin following SCI via RhoA/NF‐κB and MAPKs/NF‐κB signal pathway. The release of astrocytic ET‐1 drives microglia polarization toward M1 phenotype through YAP signaling via ETA and ETB receptors.
Bingqiang He+11 more
wiley +1 more source
A novel strategy for rapid in situ synthesis of hydrogels using Mo₂C‐derived molybdenum polyoxometalates (Mo‐POM) and ammonium persulfate enables room‐temperature polymerization. The hydrogels exhibit high transparency, conductivity, mechanical robustness, and durability. Integration of LiCl ensures antifreeze and water retention, while Mo‐POM/alginate
W. Yuan, J. Zhao
wiley +1 more source
Rationally Design Thermoelectric Materials Based on Ingenious Machine Learning Methods
A machine learning framework is developed to accurately predict thermoelectric performance of materials. By combining high‐quality data, advanced feature engineering, and machine learning, the model identifies promising candidates like CsCdBr3 and TlBSe3.
Yuqing Sun+4 more
wiley +1 more source
The neural correlates of logical-mathematical symbol systems processing resemble those of spatial cognition more than language processing. [PDF]
Li Y, Xu S, Liu J.
europepmc +1 more source
Iron‐triad‐based materials are attracting attention for green hydrogen production via water electrolysis due to their favorable electronic and flexible chemical properties, enabling the tailoring of electrochemical performance. This review covers the basics of water electrolysis, challenges in catalyst evaluation, and recent advances in tuning iron ...
Jean Marie Vianney Nsanzimana+8 more
wiley +1 more source
Abstract This paper employs machine learning to determine which preferential trade agreement (PTA) provisions are relevant to agricultural trade patterns and the factors that may influence their adoption. Utilizing the three‐way gravity model, we apply plug‐in Lasso regularized regression to pinpoint predictive PTA provisions for agricultural trade ...
Stepan Gordeev+3 more
wiley +1 more source
MetaDAVis: An R shiny application for metagenomic data analysis and visualization. [PDF]
Jagadesan S, Guda C.
europepmc +1 more source