Results 251 to 260 of about 1,960,778 (332)

HNF-DDA: subgraph contrastive-driven transformer-style heterogeneous network embedding for drug-disease association prediction. [PDF]

BMC Biol
Shang Y, Wang Z, Chen Y, Yang X, Ren Z, Zeng X, Xu L.   +6 more
europepmc   +1 more source

Peroxidasin enables melanoma immune escape by inhibiting natural killer cell cytotoxicity

Molecular Oncology, EarlyView.
Peroxidasin (PXDN) is secreted by melanoma cells and binds the NK cell receptor NKG2D, thereby suppressing NK cell activation and cytotoxicity. PXDN depletion restores NKG2D signaling and enables effective NK cell–mediated melanoma killing. These findings identify PXDN as a previously unrecognized immune evasion factor and a potential target to improve
Hsu‐Min Sung, David Bickel, Lena C. M. Krause, Daria Ezeriņa, Christian Ickes, Julian Wojtachnia, Christine S. Gibhardt, Magdalena Shumanska, Khadija Wahni, Andrea Paluschkiwitz, Julia Malo Pueyo, Ekaterina Baranova, Wim Vranken, Hedwig Stanisz, Ioana Stejerean‐Todoran, Michael P. Schön, Joris Messens, Ivan Bogeski   +17 more
wiley   +1 more source

Sleep Parameters and Quality of Life in Children with Monosymptomatic Nocturnal Enuresis: Association, Prediction and Moderation Analysis. [PDF]

Int J Environ Res Public Health
Soster L, Rafihi-Ferreira R, Fagundes S, Lebl A, Koch V, Linares I.   +5 more
europepmc   +1 more source

Optimizing Training Population Size and Genotyping Strategy for Genomic Prediction Using Association Study Results and Pedigree Information. A Case of Study in Advanced Wheat Breeding Lines

, 2017
Fabio Cericola, Ahmed Jahoor, Jihad Orabi, Jeppe R. Andersen, Luc L. Janss, Just Jensen   +5 more
openalex   +2 more sources

Crucial parameters for precise copy number variation detection in formalin‐fixed paraffin‐embedded solid cancer samples

Molecular Oncology, EarlyView.
This study shows that copy number variations (CNVs) can be reliably detected in formalin‐fixed paraffin‐embedded (FFPE) solid cancer samples using ultra‐low‐pass whole‐genome sequencing, provided that key (pre)‐analytical parameters are optimized.
Hanne Goris, Vasiliki Siozopoulou, Léon C van Kempen, Anne Sieben, Ella Roelant, Stig Hellemans, Elyne Backx, Laure Sorber, Koen De Winne, Senada Koljenović, Karen Zwaenepoel   +10 more
wiley   +1 more source

AEmiGAP: AutoEncoder-Based miRNA-Gene Association Prediction Using Deep Learning Method. [PDF]

Int J Mol Sci
Yoon S, Yoon H, Cho J, Lee K.
europepmc   +1 more source

Phenotypic and genotypic characterization of single circulating tumor cells in the follow‐up of high‐grade serous ovarian cancer

Molecular Oncology, EarlyView.
Single circulating tumor cells (sCTCs) from high‐grade serous ovarian cancer patients were enriched, imaged, and genomically profiled using WGA and NGS at different time points during treatment. sCTCs revealed enrichment of alterations in Chromosomes 2, 7, and 12 as well as persistent or emerging oncogenic CNAs, supporting sCTC identity.
Carolin Salmon, Rui P. L. Neves, Nikolas H. Stoecklein, Sven‐Thorsten Liffers, Jens Siveke, Jan D. Kuhlmann, Pauline Wimberger, Paul Buderath, Rainer Kimmig, Sabine Kasimir‐Bauer   +9 more
wiley   +1 more source

A large language model framework for literature-based disease-gene association prediction. [PDF]

Brief Bioinform
Li PH, Sun YY, Juan HF, Chen CY, Tsai HK, Huang JH.   +5 more
europepmc   +1 more source

Dammarenediol II enhances etoposide‐induced apoptosis by targeting O‐GlcNAc transferase and Akt/GSK3β/mTOR signaling in liver cancer

Molecular Oncology, EarlyView.
Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee, Byung‐Cheol Han, Gi‐Bang Koo, Jihye Park, Mijin Kwon, Young Bin Park, Jae‐Mun Choi, Seung‐Ho Lee, Sangho Roh   +8 more
wiley   +1 more source

PhyloMix: enhancing microbiome-trait association prediction through phylogeny-mixing augmentation. [PDF]

Bioinformatics
Jiang Y, Liao D, Zhu Q, Lu YY.
europepmc   +1 more source