Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText.
Kick-your-searchterm to multiple Engines kick-your-query now !>
A dictionary by aggregated review articles of nephrology, medicine and the life sciences
Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

suck abstract from ncbi


suck pdf from google scholar
unlimited free pdf from europmc35557984    free
PDF from PMC    free
html from PMC    free
PDF vom PMID35557984 :   free

suck abstract from ncbi

Nephropedia Template TP Text

Twit Text FOAVip

Twit Text #

English Wikipedia

  • Weighted Gene Co-Expression Network Analysis to Identify Potential Biological Processes and Key Genes in COVID-19-Related Stroke #MMPMID35557984
  • Cen G; Liu L; Wang J; Wang X; Chen S; Song Y; Liang Z
  • Oxid Med Cell Longev 2022[]; 2022 (ä): 4526022 PMID35557984show ga
  • The purpose of this research was to explore the underlying biological processes causing coronavirus disease 2019- (COVID-19-) related stroke. The Gene Expression Omnibus (GEO) database was utilized to obtain four COVID-19 datasets and two stroke datasets. Thereafter, we identified key modules via weighted gene co-expression network analysis, following which COVID-19- and stroke-related crucial modules were crossed to identify the common genes of COVID-19-related stroke. The common genes were intersected with the stroke-related hub genes screened via Cytoscape software to discover the critical genes associated with COVID-19-related stroke. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for common genes associated with COVID-19-related stroke, and the Reactome database was used to annotate and visualize the pathways involved in the key genes. Two COVID-19-related crucial modules and one stroke-related crucial module were identified. Subsequently, the top five genes were screened as hub genes after visualizing the genes of stroke-related critical module using Cytoscape. By intersecting the COVID-19- and stroke-related crucial modules, 28 common genes for COVID-19-related stroke were identified. ITGA2B and ITGB3 have been further identified as crucial genes of COVID-19-related stroke. Functional enrichment analysis indicated that both ITGA2B and ITGB3 were involved in integrin signaling and the response to elevated platelet cytosolic Ca(2+), thus regulating platelet activation, extracellular matrix- (ECM-) receptor interaction, the PI3K-Akt signaling pathway, and hematopoietic cell lineage. Therefore, platelet activation, ECM-receptor interaction, PI3K-Akt signaling pathway, and hematopoietic cell lineage may represent the potential biological processes associated with COVID-19-related stroke, and ITGA2B and ITGB3 may be potential intervention targets for COVID-19-related stroke.
  • |*COVID-19/complications/genetics[MESH]
  • |*Gene Regulatory Networks[MESH]
  • |*Stroke/genetics/virology[MESH]
  • |Computational Biology[MESH]
  • |Gene Expression Profiling[MESH]
  • |Gene Ontology[MESH]
  • |Humans[MESH]
  • |Integrin alpha2/genetics[MESH]
  • |Integrin beta3/genetics[MESH]

  • DeepDyve
  • Pubget Overpricing
  • suck abstract from ncbi

    4526022 ä.2022 2022