Show simple item record

dc.contributor.authorBibi Fatemeh Bibi
dc.contributor.authorBibi Fatemeh Bibi
dc.contributor.authorRasoul Aliannejad
dc.contributor.authorAfsaneh Arefi Oskouie
dc.contributor.authorFariba Fathi
dc.contributor.authorHossein Ali Sahakhah
dc.contributor.authorMostafa Rezaei-Tavirani
dc.date.accessioned2017-09-18T11:16:45Z
dc.date.available2017-09-18T11:16:45Z
dc.date.issued2016-03-01
dc.identifier.urihttp://dsp.sbmu.ac.ir/xmlui/handle/123456789/70431
dc.description.abstract© 2016, Semnan University of Medical Sciences. All rights reserved. Introduction: Metabolomics is a powerful technique for determination of biomarkers. Here, we aimed to determine discriminatory metabolomic profiles in different stages of sulfur mustard-exposed patients (SMEPs). Materials and methods: Nuclear magnetic resonance spectroscopy was used to analyze serum samples from 17 SMEPs (normal group patients) and 17 SMEPs (severe group patients). Multivariate statistical analysis using random forest (RF) was performed on a ‘training set’ (70% of the total sample) in order to produce a discriminatory model classifying two groups of patients, and the model tested in the remaining subjects. Results: A classification model was derived using data from the training set with an area under the receiver operating curve (AUC) of 0.87. In the test set (the remaining 30% of subjects), the AUC was 0.8, thus RF model had good predictive power. We observed significant changes in lipid, amino acids and energy metabolism between two groups of patients. Conclusion: Nuclear magnetic resonance spectroscopy of serum successfully differentiates two groups of patients exposed to sulfur mustard. This technique has the potential to provide novel diagnostics and identify novel pathophysiological mechanisms, biomarkers and therapeutic targets.
dc.sourceKoomesh
dc.subjectMetabolomics
dc.subjectMustard gas
dc.subjectSerum
dc.titleNuclear magnetic resonance -based metabolomics analysis of patients exposed to sulfur mustard in different stages using random forest method
dc.journal.volume17
dc.journal.issue3
dc.journal.pages701-706
dc.contributor.authorid57006703300
dc.contributor.authorid57006703300
dc.contributor.authorid16244367100
dc.contributor.authorid54684894100
dc.contributor.authorid55314182400
dc.contributor.authorid57188721937
dc.contributor.authorid55891568600
dc.contributor.citation57006703300|60018934|Bibi Fatemeh Bibi
dc.contributor.citation57006703300|60018934|Bibi Fatemeh Bibi
dc.contributor.citation16244367100|60027708|Rasoul Aliannejad
dc.contributor.citation54684894100|60018934|Afsaneh Arefi Oskouie
dc.contributor.citation55314182400|60027666|Fariba Fathi
dc.contributor.citation57188721937|60024530|Hossein Ali Sahakhah
dc.contributor.citation55891568600|60018934|Mostafa Rezaei-Tavirani
dc.contributor.affiliationid60018934
dc.contributor.affiliationid60018934
dc.contributor.affiliationid60027708
dc.contributor.affiliationid60018934
dc.contributor.affiliationid60027666
dc.contributor.affiliationid60024530
dc.contributor.affiliationid60018934


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record