Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 1034
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3152
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Latent infectious agents, microbial translocation, some metabolites and immune cell subpopulations, as well as senescence modulate the level and quality of activation of our immune system. Here, we tested whether various in vivo immune activation profiles may be distinguished in a general population. We measured 43 markers of immune activation by 8-color flow cytometry and ELISA in 150 adults, and performed a double hierarchical clustering of biomarkers and volunteers. We identified five different immune activation profiles. Profile 1 had a high proportion of naïve T cells. By contrast, Profiles 2 and 3 had an elevated percentage of terminally differentiated and of senescent CD4+ T cells and CD8+ T cells, respectively. The fourth profile was characterized by NK cell activation, and the last profile, Profile 5, by a high proportion of monocytes. In search for etiologic factors that could determine these profiles, we observed a high frequency of naïve Treg cells in Profile 1, contrasting with a tendency to a low percentage of Treg cells in Profiles 2 and 3. Moreover, Profile 5 tended to have a high level of 16s ribosomal DNA, a direct marker of microbial translocation. These data are compatible with a model in which specific causes, as the frequency of Treg or the level of microbial translocation, shape specific profiles of immune activation. It will be of interest to analyze whether some of these profiles drive preferentially some morbidities known to be fueled by immune activation, as insulin resistance, atherothrombosis or liver steatosis.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7704615 | PMC |
http://dx.doi.org/10.1038/s41598-020-77707-6 | DOI Listing |
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