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: 3122
Function: getPubMedXML
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
Background/objectives: Metabolomics provides insights into the biological underpinnings of disease development and treatment. This systematic review investigated the impact of acupuncture on metabolite levels and associated metabolic pathways using a metabolomic approach.
Methods: Five databases (i.e., PubMed, Embase, Scopus, CINAHL, and Cochrane Central) were searched using terms such as "acupuncture" and "metabolites" to retrieve relevant journal articles published through January 2024. Studies utilizing mass spectrometry or nuclear magnetic resonance were included. Risk of bias was evaluated using the Cochrane Risk of Bias tool and the Newcastle-Ottawa scale. Metabolic pathway analysis was conducted using MetaboAnalyst 6.0 to identify common significant pathways affected by acupuncture. Additionally, subgroup pathway enrichment analysis identified metabolites significantly altered in more than two studies.
Results: Among 4019 articles, 22 studies met inclusion criteria, examining changes in metabolomic biomarkers before and after acupuncture for various diseases and symptoms. A total of 226 metabolites showed significant changes, with 14 common metabolites altered in more than two studies (glutamine, androsterone glucuronide, choline, citric acid, decanoylcarnitine, estrone, glutathione, glycine, hypoxanthine, lactic acid, pyruvic acid, serine, proline, and sn-glycero-3-phosphocholine). Common pathways affected by acupuncture were glycine, serine, and threonine metabolism, glutathione metabolism, arginine biosynthesis, and glyoxylate and dicarboxylate metabolism.
Conclusions: This review provides insights of the metabolomic mechanisms underlying acupuncture, highlighting its impact on specific metabolic pathways. Recognizing these changes can enhance acupuncture's effectiveness and support the development of personalized treatments. The findings underscore metabolomics as a valuable tool for understanding and optimizing acupuncture for various diseases and symptoms.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11509109 | PMC |
http://dx.doi.org/10.3390/metabo14100542 | DOI Listing |
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