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.

10.1111/ijlh.13717 http://scihub22266oqcxt.onion/10.1111/ijlh.13717 34623759!8652836!34623759     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=34623759&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 243.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 276.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 276.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 276.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 276.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 276.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 276.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 276.79999999999995 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Lab+Hematol 2021 ; 43 (6): 1325-1333 Nephropedia Template TP {{tp|p=34623759|t=2021. New insights into genetic characteristics between multiple myeloma and COVID-19: An integrative bioinformatics analysis of gene expression omnibus microarray and the cancer genome atlas data |pdf=|usr=}}{{34623759}} gab.com Text New insights into genetic characteristics between multiple myeloma and COVID-19: An integrative bioinformatics analysis of gene expression omnibus microarray and the cancer genome atlas data JO: Int J Lab Hematol http://www.kidney.de/pget.php?&tw=1&pmid=34623759 #FOAvip BACKGROUND: Multiple myeloma (MM) is a hematological malignancy. Coronavirus disease 2019 (COVID-19) infection correlates with MM features. This study aimed to identify MM prognostic biomarkers with potential association with COVID-19. METHODS: Differentially expressed genes (DEGs) in five MM data sets (GSE47552, GSE16558, GSE13591, GSE6477, and GSE39754) with the same expression trends were screened out. Functional enrichment analysis and the protein-protein interaction network were performed for all DEGs. Prognosis-associated DEGs were screened using the stepwise Cox regression analysis in the cancer genome atlas (TCGA) MMRF-CoMMpass cohort and the GSE24080 data set. Prognosis-associated DEGs associated with COVID-19 infection in the GSE164805 data set were also identified. RESULTS: A total of 98 DEGs with the same expression trends in five data sets were identified, and 83 DEGs were included in the protein-protein interaction network. Cox regression analysis identified 16 DEGs were associated with MM prognosis in the TCGA cohort, and only the cytochrome c oxidase subunit 6C (COX6C) gene (HR = 1.717, 95% CI 1.231-2.428, p = .002) and the nucleotide-binding oligomerization domain containing 2 (NOD2) gene (HR = 0.882, 95% CI 0.798-0.975, p = .014) were independent factors related to MM prognosis in the GSE24080 data set. Both of them were downregulated in patients with mild COVID-19 infection compared with controls but were upregulated in patients with severe COVID-19 compared with patients with mild illness. CONCLUSIONS: The NOD2 and COX6C genes might be used as prognostic biomarkers in MM. The two genes might be associated with the development of COVID-19 infection. Twit Text FOAVip New insights into genetic characteristics between multiple myeloma and COVID-19: An integrative bioinformatics analysis of gene expression omnibus microarray and the cancer genome atlas data ????Int J Lab Hematol http://www.kidney.de/pget.php?&tw=1&pmid=34623759 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34623759 #FOAvip English Wikipedia <ref>{{Cite pmid|34623759}}</ref> New insights into genetic characteristics between multiple myeloma and COVID-19: An integrative bioinformatics analysis of gene expression omnibus microarray and the cancer genome atlas data #MMPMID34623759 Wang F; Liu R; Yang J; Chen B Int J Lab Hematol 2021[Dec]; 43 (6): 1325-1333 PMID34623759show ga BACKGROUND: Multiple myeloma (MM) is a hematological malignancy. Coronavirus disease 2019 (COVID-19) infection correlates with MM features. This study aimed to identify MM prognostic biomarkers with potential association with COVID-19. METHODS: Differentially expressed genes (DEGs) in five MM data sets (GSE47552, GSE16558, GSE13591, GSE6477, and GSE39754) with the same expression trends were screened out. Functional enrichment analysis and the protein-protein interaction network were performed for all DEGs. Prognosis-associated DEGs were screened using the stepwise Cox regression analysis in the cancer genome atlas (TCGA) MMRF-CoMMpass cohort and the GSE24080 data set. Prognosis-associated DEGs associated with COVID-19 infection in the GSE164805 data set were also identified. RESULTS: A total of 98 DEGs with the same expression trends in five data sets were identified, and 83 DEGs were included in the protein-protein interaction network. Cox regression analysis identified 16 DEGs were associated with MM prognosis in the TCGA cohort, and only the cytochrome c oxidase subunit 6C (COX6C) gene (HR = 1.717, 95% CI 1.231-2.428, p = .002) and the nucleotide-binding oligomerization domain containing 2 (NOD2) gene (HR = 0.882, 95% CI 0.798-0.975, p = .014) were independent factors related to MM prognosis in the GSE24080 data set. Both of them were downregulated in patients with mild COVID-19 infection compared with controls but were upregulated in patients with severe COVID-19 compared with patients with mild illness. CONCLUSIONS: The NOD2 and COX6C genes might be used as prognostic biomarkers in MM. The two genes might be associated with the development of COVID-19 infection. |*Gene Expression Profiling[MESH] |*SARS-CoV-2[MESH] |COVID-19/*genetics/mortality[MESH] |Computational Biology/*methods[MESH] |Datasets as Topic[MESH] |Electron Transport Complex IV/genetics[MESH] |Gene Expression Regulation, Neoplastic[MESH] |Gene Expression Regulation, Viral[MESH] |Gene Ontology[MESH] |Humans[MESH] |Kaplan-Meier Estimate[MESH] |Microarray Analysis[MESH] |Multiple Myeloma/*genetics[MESH] |Neoplasm Proteins/biosynthesis/genetics[MESH] |Nod2 Signaling Adaptor Protein/genetics[MESH] |Prognosis[MESH] |Proportional Hazards Models[MESH]New insights into genetic characteristics between multiple myeloma and(epmc).pdf DeepDyve Pubget Overpricing