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Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach

Metabolomics, as a promising and powerful approach, refers to comprehensive assessment and identification of small molecule endogenous metabolites in a biological system which is capable of further understanding the mechanisms of diseases for early diagnosis, effective treatment and prognosis. Acute...

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Autores principales: Li, Hai-Hong, Pan, Jian-Liang, Hui, Su, Ma, Xiao-Wei, Wang, Zhi-Long, Yao, Hui-Xin, Wang, Jun-Feng, Li, Hong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9079920/
https://www.ncbi.nlm.nih.gov/pubmed/35541357
http://dx.doi.org/10.1039/c8ra01749b
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author Li, Hai-Hong
Pan, Jian-Liang
Hui, Su
Ma, Xiao-Wei
Wang, Zhi-Long
Yao, Hui-Xin
Wang, Jun-Feng
Li, Hong
author_facet Li, Hai-Hong
Pan, Jian-Liang
Hui, Su
Ma, Xiao-Wei
Wang, Zhi-Long
Yao, Hui-Xin
Wang, Jun-Feng
Li, Hong
author_sort Li, Hai-Hong
collection PubMed
description Metabolomics, as a promising and powerful approach, refers to comprehensive assessment and identification of small molecule endogenous metabolites in a biological system which is capable of further understanding the mechanisms of diseases for early diagnosis, effective treatment and prognosis. Acute kidney injury (AKI) induced by contrast is a serious complication in patients undergoing administration of iodinated contrast media. It is becoming a major health concern in clinic, however, the molecular mechanisms of contrast-induced acute kidney injury (CI-AKI) have not been well characterized. In this study, we used serum metabolomics based on liquid chromatography-mass spectrometry (LC-MS) combined with pattern recognition to explore and characterize potential metabolites and metabolic pathway in an experimental model for CI-AKI. Seventeen differentiating metabolites in the serum were identified involving the pivotal metabolic pathways related to tryptophan metabolism, glycerophospholipid metabolism, steroid hormone biosynthesis, pyrimidine metabolism, sphingolipid metabolism, aminoacyl-tRNA biosynthesis. Our study provides novel insight into pathophysiologic mechanisms of AKI by changing biomarkers and pathways.
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spelling pubmed-90799202022-05-09 Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach Li, Hai-Hong Pan, Jian-Liang Hui, Su Ma, Xiao-Wei Wang, Zhi-Long Yao, Hui-Xin Wang, Jun-Feng Li, Hong RSC Adv Chemistry Metabolomics, as a promising and powerful approach, refers to comprehensive assessment and identification of small molecule endogenous metabolites in a biological system which is capable of further understanding the mechanisms of diseases for early diagnosis, effective treatment and prognosis. Acute kidney injury (AKI) induced by contrast is a serious complication in patients undergoing administration of iodinated contrast media. It is becoming a major health concern in clinic, however, the molecular mechanisms of contrast-induced acute kidney injury (CI-AKI) have not been well characterized. In this study, we used serum metabolomics based on liquid chromatography-mass spectrometry (LC-MS) combined with pattern recognition to explore and characterize potential metabolites and metabolic pathway in an experimental model for CI-AKI. Seventeen differentiating metabolites in the serum were identified involving the pivotal metabolic pathways related to tryptophan metabolism, glycerophospholipid metabolism, steroid hormone biosynthesis, pyrimidine metabolism, sphingolipid metabolism, aminoacyl-tRNA biosynthesis. Our study provides novel insight into pathophysiologic mechanisms of AKI by changing biomarkers and pathways. The Royal Society of Chemistry 2018-04-18 /pmc/articles/PMC9079920/ /pubmed/35541357 http://dx.doi.org/10.1039/c8ra01749b Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Chemistry
Li, Hai-Hong
Pan, Jian-Liang
Hui, Su
Ma, Xiao-Wei
Wang, Zhi-Long
Yao, Hui-Xin
Wang, Jun-Feng
Li, Hong
Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach
title Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach
title_full Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach
title_fullStr Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach
title_full_unstemmed Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach
title_short Retracted Article: High-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using LC-MS combined with pattern recognition approach
title_sort retracted article: high-throughput metabolomics identifies serum metabolic signatures in acute kidney injury using lc-ms combined with pattern recognition approach
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9079920/
https://www.ncbi.nlm.nih.gov/pubmed/35541357
http://dx.doi.org/10.1039/c8ra01749b
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