ArticleJournal of thoracic disease2023
A bioinformatics analysis of the susceptibility genes in Stanford type A aortic dissection.
Article in Journal of thoracic disease, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- Genome wide DNA methylation and transcriptome integration analysis reveals potential markers in type A aortic dissection pathogenesis.Scientific reports · 2025Article
- Development and validation of a 6-gene signature derived from RNA modification-associated genes for the diagnosis of Acute Stanford Type A Aortic Dissection.Journal of geriatric cardiology : JGC · 2024Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The expression levels of long noncoding RNAs (lncRNAs) and mRNAs in human acute Stanford type A aortic dissecting aneurysm and normal active vascular tissues were compared using the array lncRNA/mRNA expression profile chip technology. Methods: The tissue samples of 5 patients who presented with Stanford type A aortic dissections and the normal ascending aorta tissues from 5 donor heart transplantation patients receiving surgical treatment in Ganzhou People's Hospital were collected. Hematoxylin and eosin (HE) staining were performed to investigate the structural features of the ascending aortic vascular tissue. Nanodropnd-100 was used to detect the surface level of RNA in 10 samples included in the experiment, to ensure that the quality of the standard was consistent with the core plate detection. NanoDrop ND-1000 was used to detect the RNA expression levels in 10 specimens included in the experiment to ensure that the quality of specimens satisfied the requirements of the microarray detection experiment. The Arraystar Human LncRNA/mRNAV3.0 expression profile chip (8×60K, Arraystar) was used to detect the expression levels of lncRNAs and mRNAs in the tissue samples. Results: A total of 29,198 lncRNAs and 22,959 mRNA target genes could be detected in the above tissue samples after the initial data were standardized and low-expression information was filtered. The data in the middle of the range of 50% value consistency was higher. The scatterplot results preliminarily suggested that there were large numbers of lncRNAs with increased and decreased expression in Stanford type A aortic dissection tissues compared with normal aortic tissues. The differentially expressed lncRNAs were enriched in BPs including apoptosis, nitric oxide synthesis, estradiol response, angiogenesis, inflammatory response, oxidative stress, and acute response; cell components (CCs) including cytoplasm, nucleus, cytoplasmic matrix, extracellular space, protein complex, and platelet α granule lumen; and MFs including protease binding, zinc ion binding, steroid compound binding, steroid hormone receptor activity, heme binding, protein kinase, cytokine, superoxide dismutase, and nitric oxide synthase activities. Conclusions: Gene ontology analysis demonstrated that many genes in Stanford type A aortic dissection were involved in cell biological functions, cell components, and molecular functions through upregulating and downregulating the levels of expression.
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