The fatty acid omega hydroxylase genes (CYP4 family) in the progression of metabolic dysfunction-associated steatotic liver disease (MASLD): An RNA sequence database analysis and review. [PDF]
Leahy C+9 more
europepmc +1 more source
20 Hz mechanical vibration induced A431 cancer cells' apoptosis without such effect on other healthy cell lines of L929 and C2C12. Lowered glucose consumption is observed specifically in A431. The expressions of ROS, HMGB1, and HSP1 levels initially increase and subsequently decrease in the cancer cell line, as opposed to L929 and C2C12, which ...
Wresti L. Anggayasti+5 more
wiley +1 more source
A cuproptosis-related gene expression signature predicting clinical prognosis and immune responses in intrahepatic cholangiocarcinoma detected by single-cell RNA sequence analysis. [PDF]
Ren H+9 more
europepmc +1 more source
In the blood–testis barrier, occludin is crucial for tight junctions. This study demonstrates that occludin‐targeting short peptides disrupt junction integrity, inducing immune cell infiltration, tumor necrosis factor‐α/interleukin‐6 secretion and mitochondrial dysfunction, ultimately triggering apoptosis.
Heng Wang, Xiaofang Tan, Deyu Chen
wiley +1 more source
Integration of scRNA and bulk RNA-sequence to construct the 5-gene molecular prognostic model based on the heterogeneity of thyroid carcinoma endothelial cell. [PDF]
Ni Z+9 more
europepmc +1 more source
Current trends in single‐cell RNA sequencing applications in diabetes mellitus
Single‐cell RNA sequencing is a powerful approach to decipher the cellular and molecular landscape at a single‐cell resolution. The rapid development of this technology has led to a wide range of applications, including the detection of cellular and molecular mechanisms and the identification and introduction of novel potential diagnostic and ...
Seyed Sajjad Zadian+6 more
wiley +1 more source
Single-cell and bulk RNA-sequence identified fibroblasts signature and CD8 + T-cell - fibroblast subtype predicting prognosis and immune therapeutic response of bladder cancer, based on machine learning: bioinformatics multi-omics study. [PDF]
Li J+8 more
europepmc +1 more source