Results 211 to 220 of about 168,331 (269)
The E3 ubiquitin ligase TRIM56 promotes aggregation and activation of Src protein through Lys63-linked polyubiquitination in hepatocellular carcinoma. [PDF]
Zhu L, Cui X, Xu H, Yang M, Han L.
europepmc +1 more source
ABSTRACT Forest ecosystems play a critical role in the global carbon cycle. As a significant terrestrial carbon sink, plantations exhibit carbon stock patterns that are shaped by tree species composition, stand structure, and environmental conditions. Here, we investigated typical plantation types in the Mufu Mountain, Hubei Province.
Mingyang Ding +5 more
wiley +1 more source
Sweat sodium composition and sweat loss estimation through wearable sensors and predictive equations in dry and humid hot conditions. [PDF]
Bandiera D +9 more
europepmc +1 more source
Beyond PD‐1/PD‐L1: New Immune Checkpoints and Therapeutic Combinations in Cancer Immunotherapy
ABSTRACT Recently, immune checkpoint inhibitors (ICIs), particularly PD‐1/PD‐L1 and CTLA‐4 inhibitors, have revolutionized cancer treatment, significantly improving survival rates for various malignancies. However, ICI therapies targeting single checkpoints on T cells still face numerous challenges, such as low response rates and post‐treatment ...
Yangyang Li, Zizhen Kang, Yanyun Du
wiley +1 more source
Molecular Imaging in Gastric Cancer: [¹⁸F]FDG and Fibroblast Activation Protein-Targeted PET/CT. [PDF]
Sakulpisuti C, Suh M.
europepmc +1 more source
Intra‐tumour heterogeneity is present in gastrointestinal tumours at the single‐cell level. Cell cycling, EMT, MYC and TNF‐α are the four main consensus meta‐programs in gastrointestinal tumours. Then, a prognostic model based on intratumoral heterogeneity was constructed using an artificial intelligence‐derived prognostic index.
Zhizhan Ni +12 more
wiley +1 more source
An update on regulation of the polymodal TRPV4 channel by protein phosphorylation. [PDF]
Parthasarathy A, Zhang DX.
europepmc +1 more source
Machine Learning for Predictive Modeling in Nanomedicine‐Based Cancer Drug Delivery
The integration of AI/ML into nanomedicine offers a transformative approach to therapeutic design and optimization. Unlike conventional empirical methods, AI/ML models (such as classification, regression, and neural networks) enable the analysis of complex clinical and formulation datasets to predict optimal nanoparticle characteristics and therapeutic
Rohan Chand Sahu +3 more
wiley +1 more source

