Employ machine learning to identify NAD+ metabolism-related diagnostic markers for ischemic stroke and develop a diagnostic model DOI Creative Commons
Yameng Sun,

Shenghao Ding,

Fei Shen

и другие.

Experimental Gerontology, Год журнала: 2024, Номер 196, С. 112584 - 112584

Опубликована: Сен. 19, 2024

Язык: Английский

Genetic polymorphisms of bone marrow stromal cell antigen-1 (BST-1/CD157): implications for immune/inflammatory dysfunction in neuropsychiatric disorders DOI Creative Commons
Shigeru Yokoyama

Frontiers in Immunology, Год журнала: 2023, Номер 14

Опубликована: Май 29, 2023

Bone marrow stromal cell antigen-1 (BST-1/CD157) is an immune/inflammatory regulator that functions as both nicotinamide adenine dinucleotide-metabolizing ectoenzyme and cell-surface signaling receptor. BST-1/CD157 expressed not only in peripheral tissues, but the central nervous system (CNS). Although its pathophysiological significance CNS still unclear, clinical genetic studies over a decade have begun revealing relationships between neuropsychiatric diseases including Parkinson’s disease, autism spectrum disorders, sleep depressive disorders restless leg syndrome. This review summarizes accumulating evidence for involvement of these disorders.

Язык: Английский

Процитировано

5

Targeting inhibition of prognosis-related nicotinamide metabolism genes, including poly (ADP-ribose) polymerase 9 (PARP-9) attenuates glioma progression DOI
Wei Zeng,

Haixiao Jiang,

Guan Sun

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Июль 19, 2024

Abstract Background Nicotinamide (NAM) metabolism plays a significant role in glioma development. This study aimed to investigate the correlation between NAM metabolic genes and prognosis, immune microenvironment, tumor progression glioma. Methods We analyzed expression prognostic significance of NAM-metabolism-related patients with develop new metabolism-related signature (NMRS) nomograms using data from The Cancer Genome Atlas (TCGA) Gene Expression Omnibus (GEO) databases compared differences gene set enrichment analysis (GSEA), protein-protein interaction networks, competing endogenous RNA (ceRNA) regulatory network, mutation load, landscape different groups. Additionally, we employed Western blotting, cell proliferation apoptosis analysis, Semi-quantitative Reverse Transcription-Polymerase Chain Reaction(SqRT-PCR), xenograft model nude mice PARP9 progression. Results Our identified eight genes, including NT5C1A, NNMT, CDKN1A, PTGS2, PNP, PARP10, PARP14, PARP9, that exhibited prognosis could act as an independent indicator. Risk stratification was conducted based on NMRS, low-risk group more favorable clinical results. GSEA revealed immune-associated pathways, while high-risk showed cancer-related pathways. ESTIMATE single-sample algorithms indicated displayed higher antitumor immunocyte infiltration. TIDE responded favorably immunotherapy. Furthermore, validation experiments is proto-oncogene associated PARP9-JAK2-STAT3 signaling pathway. Conclusion developed NMRS for predicting treatment efficacy gene, potential therapeutic target

Язык: Английский

Процитировано

0

Employ machine learning to identify NAD+ metabolism-related diagnostic markers for ischemic stroke and develop a diagnostic model DOI Creative Commons
Yameng Sun,

Shenghao Ding,

Fei Shen

и другие.

Experimental Gerontology, Год журнала: 2024, Номер 196, С. 112584 - 112584

Опубликована: Сен. 19, 2024

Язык: Английский

Процитировано

0