Results 261 to 270 of about 1,680,534 (386)

Supplementary Figure S4 from β-Catenin Contributes to Lung Tumor Development Induced by EGFR Mutations

open access: gold, 2023
Sohei Nakayama   +14 more
openalex   +1 more source

Supplementary Table 2 from Illegitimate WNT Pathway Activation by β-Catenin Mutation or Autocrine Stimulation in T-Cell Malignancies

open access: gold, 2023
Richard W.J. Groen   +7 more
openalex   +1 more source

Gut Bacterium Lysinibacillus Sphaericus Exacerbates Aspirin‐induced Intestinal Injury by Production of Carboxylesterase EstB

open access: yesAdvanced Science, EarlyView.
Schematic overview illustrating the detrimental role of gut microbiota in aspirin‐induced intestinal injury. L. sphaericus and its secreted carboxylesterase EstB are identified as key drivers that catalyze aspirin hydrolysis into salicylic acid, thereby exacerbating intestinal injury. Inhibition of EstB by the dietary compound flavanomarein effectively
Zeyu Zhao   +13 more
wiley   +1 more source

PRC1 promotes immunosuppressive macrophages in sepsis via β-catenin/STAT3 signaling. [PDF]

open access: yesCell Mol Life Sci
Zuo Y   +9 more
europepmc   +1 more source

Downregulation of β-catenin blocks fibrosis via Wnt2 signaling in human keloid fibroblasts [PDF]

open access: gold, 2017
Cai Yu-mei   +5 more
openalex   +1 more source

Senescent Synovial Intimal Fibroblasts Aggravate Osteoarthritis by Regulating Macrophage Polarization and Chondrocyte Phenotype Through ANGPTL4‐α5β1 Axis

open access: yesAdvanced Science, EarlyView.
Senescent synovial intimal fibroblasts (SIF) are identified as key drivers of osteoarthritis. They promote M1 macrophage polarization and cartilage degeneration via the ANGPTL4–α5β1 axis, regulated by transcription factors EGR1 and ATF3. Pharmacological inhibition of this pathway alleviates disease, revealing SIF senescence as a promising therapeutic ...
Muhai Deng   +7 more
wiley   +1 more source

Inferring Gene Regulatory Networks From Single‐Cell RNA Sequencing Data by Dual‐Role Graph Contrastive Learning

open access: yesAdvanced Science, EarlyView.
RegGAIN is a novel and powerful deep learning framework for inferring gene regulatory networks (GRNs) from single‐cell RNA sequencing data. By integrating self‐supervised contrastive learning with dual‐role gene representations, it consistently outperforms existing methods in both accuracy and robustness.
Qiyuan Guan   +9 more
wiley   +1 more source

Home - About - Disclaimer - Privacy