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
The Posner-Schlossman syndrome (PSS) is a disease with clinically recurrent unilateral anterior uveitis with markedly elevated intraocular pressure (IOP) and subsequent progression to optic neuropathy. Retrospective studies have reported increased annual incidence of PSS, especially in China. While currently, the clinical management of PSS is still challenging. Metabolomics is considered to be a sensitive approach for the development of novel targeted therapeutics because of its direct elucidation of pathophysiological mechanisms. Therefore, we adopted gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) technology-based non-targeted metabolomics approach to measure comprehensive metabolic profiles of aqueous humor (AH) samples obtained from patients with PSS, with an aim to demonstrate the underlying pathophysiology, identify potential biomarkers specific to PSS, and develop effective treatment strategies. A comparative analysis was used to indicate the distinct metabolites of PSS. Pathway analysis was conducted using MetaboAnalyst 4.0 to explore the metabolic reprogramming pathways involved in PSS. Logistic regression and receiver-operating characteristic (ROC) analyses were employed to evaluate the diagnostic capability of selected metabolites. Comparative analysis revealed a clear separation between PSS and control groups. Fourteen novel differentiating metabolites from AH samples obtained from patients with PSS were highlighted. Pathway analysis identified 11 carbohydrate, amino acid metabolism and energy metabolism pathways as the major disturbed pathways associated with PSS. The abnormal lysine degradation metabolism, valine-leucine-isoleucine biosynthesis, and citrate circle were considered to weigh the most in the development of PSS. The ROC analysis implied that the combination of glycine and homogentisic acid could serve as potential biomarkers for the discrimination of control and PSS groups. In conclusion, these results revealed for the first time the identity of important metabolites and pathways contributing to the development/progression of PSS, enabled the better understanding of the mechanism of PSS, and might lead to the development of metabolic biomarkers and novel therapeutic strategies to restrict the development/progression of PSS.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6855217 | PMC |
http://dx.doi.org/10.3389/fphar.2019.01322 | DOI Listing |
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