Results 181 to 190 of about 55,247 (210)
This study established a one‐step method inducing pro‐spermatogonia‐like (activating SOX17) and oogonia‐like (activating SOX17/TFAP2C) cells from porcine pgEpiSCs with a NANOS3‐tdTomato reporter. EGF activates the core PGC program and supports survival; BMP4 further induces NANOS3 and DDX4 expression; IWR1 enhances PGCLC efficiency by suppressing ...
Pengcheng He +14 more
wiley +1 more source
Postoperative arteriovenous fistulas exhibit increased RBMS1 in vascular smooth muscle cells (VSMCs). In experimental AVFs, RBMS1 overexpression aggravates, whereas deletion attenuates, neointimal hyperplasia. RBMS1 binds MPZL1 mRNA and promotes exon 5 skipping to generate MPZL1‐Δ5, which interacts with G3BP1 to activate AKT, driving VSMC proliferation,
Zongda Li +14 more
wiley +1 more source
Interpretable Structural Evaluation of Metal-Oxide Nanostructures in Scanning Transmission Electron Microscopy (STEM) Images via Persistent Homology. [PDF]
Eguchi R, Wen Y, Abe H, Hashimoto A.
europepmc +1 more source
Deciphering Intricacies in Directional CO2 Conversion From Electrolysis to CO2 Batteries
This review will delve into the inherent connections and distinctions of CO2‐directed conversion in ECO2RR and CO2 batteries, in terms of product types, catalyst selection, catalytic mechanisms, and electrochemical performances, while proposing a benchmarking framework for the evaluation of CO2 batteries and innovative CO2 battery configurations for ...
Changfan Xu +5 more
wiley +1 more source
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
Harnessing Machine Learning to Understand and Design Disordered Solids
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley +1 more source
ABSTRACT Background Chronic rhinosinusitis (CRS) is frequently associated with polymicrobial biofilms involving Staphylococcus aureus and Pseudomonas aeruginosa. Interactions between these organisms are thought to influence disease severity, but the epithelial effects of exoproteins derived from patient‐matched cocultures remain poorly defined ...
Xiaohan Sun +6 more
wiley +1 more source
A zebrafish xenograft model accurately distinguishes metastatic from non‐metastatic HNSCC and recapitulates cisplatin sensitivity/resistance patterns. Using patient‐derived tumors, it predicts individual therapeutic responses, offering a rapid, clinically applicable platform for guiding personalized treatment. Abstract Background Head and neck squamous
Lu Chen +11 more
wiley +1 more source
Due to the complex pathophysiology of aortic valve disease (AVD) and the resulting lack of effective pharmacotherapy, existing animal models are valuable research tools, but each has its own strengths and limitations. This review systematically surveys the major AVD models, compares their induction methods, pathological features, advantages and ...
Liya Hou +4 more
wiley +1 more source
Background The operational definition and imaging assessment of the no‐reflow phenomenon, a potential contributor to poor clinical outcome despite successful thrombectomy, remains debated. We aimed to develop expert‐based international consensus on the definition, assessment, and reporting standard of cerebral no‐reflow post‐thrombectomy. Methods Three‐
Adnan Mujanovic +21 more
wiley +1 more source

