Results 241 to 250 of about 183,994 (309)
KRT15 identified by scRNA-Seq and machine learning as stemness regulator and prognostic biomarker in ESCC. [PDF]
Xiong K +6 more
europepmc +1 more source
Radiotherapy triggers LTβR N‐glycosylation, enhancing its overall protein stability and nuclear retention. This accumulation drives TRIM28‐mediated PCBP2 SUMOylation, suppressing pyroptosis and conferring gastric cancer radioresistance. Therapeutically, a targeted nanoplatform (cRGD‐Lipo@EMD) effectively disrupts this regulatory axis, offering a highly
Weijie Zang +8 more
wiley +1 more source
HIDF: Integrating Tree-Structured scRNA-seq Heterogeneity for Hierarchical Deconvolution of Spatial Transcriptomics. [PDF]
Zou Z +5 more
europepmc +1 more source
We present a chromosome‐level genome assembly of Siraitia grosvenorii and, through comparative genomics, uncover a conserved UGT73 tandem array driving triterpenoid saponin diversification in Cucurbitaceae. Crystalized SgUGT73AM30 further reveals the regioselectivity mechanism underlying its catalytic activity.
Guangyi Wang +13 more
wiley +1 more source
scDock: streamlining drug discovery targeting cell-cell communication via scRNA-seq analysis and molecular docking. [PDF]
Huang CH, Oyang YJ, Huang HC, Juan HF.
europepmc +1 more source
Fibrotic liver stiffness activates hepatic stellate cells through Piezo1‐dependent calcium influx and ER stress, promoting EV‐associated GMFG release. Delivered GMFG engages TNS4 in pancreatic cancer cells, triggering FAK/AKT signaling, adhesion, and fatty acid synthesis.
Biwen Zhu +11 more
wiley +1 more source
Unraveling new characteristics of γδ T cells using scRNA-seq in TCR KO chicken. [PDF]
von Heyl T +5 more
europepmc +1 more source
CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang +11 more
wiley +1 more source
Decoupling biological signals from unwanted variation in multi‑condition single‑cell RNA sequencing data remains challenging. CAPER disentangles condition‑associated biological effects from sample heterogeneity through matrix factorization, producing interpretable latent factors and a batch‑corrected expression matrix.
Ye Li +6 more
wiley +1 more source
Lung scRNA-seq reveals chronic inflammation and emphysemous phenotype in mice with osteogenesis imperfecta. [PDF]
Zieba J +8 more
europepmc +1 more source

