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Eve, Alicia Arredondo; Tunc, Elif; Liu, Yu-Jeh; Agrawal, Saumya; Yilmaz, Huriye Erbak; Emren, Sadik Volkan; Akcay, Filiz Akyildiz; Mainzer, Luidmila; Zurauskien, Justina; Erdogan, Zeynep Madak
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<identifier identifierType="URL">https://aperta.ulakbim.gov.tr/record/239448</identifier>
<creators>
<creator>
<creatorName>Eve, Alicia Arredondo</creatorName>
<givenName>Alicia Arredondo</givenName>
<familyName>Eve</familyName>
<affiliation>Univ Illinois, Dept Food Sci & Human Nutr, Div Nutr Sci, Urbana, IL 61801 USA</affiliation>
</creator>
<creator>
<creatorName>Tunc, Elif</creatorName>
<givenName>Elif</givenName>
<familyName>Tunc</familyName>
</creator>
<creator>
<creatorName>Liu, Yu-Jeh</creatorName>
<givenName>Yu-Jeh</givenName>
<familyName>Liu</familyName>
<affiliation>Univ Illinois, Dept Food Sci & Human Nutr, Div Nutr Sci, Urbana, IL 61801 USA</affiliation>
</creator>
<creator>
<creatorName>Agrawal, Saumya</creatorName>
<givenName>Saumya</givenName>
<familyName>Agrawal</familyName>
<affiliation>Univ Illinois, Dept Comp Sci, Urbana, IL 61801 USA</affiliation>
</creator>
<creator>
<creatorName>Yilmaz, Huriye Erbak</creatorName>
<givenName>Huriye Erbak</givenName>
<familyName>Yilmaz</familyName>
</creator>
<creator>
<creatorName>Emren, Sadik Volkan</creatorName>
<givenName>Sadik Volkan</givenName>
<familyName>Emren</familyName>
<affiliation>Katip Celebi Univ, Res & Training Hosp, TR-35620 Izmir, Turkey</affiliation>
</creator>
<creator>
<creatorName>Akcay, Filiz Akyildiz</creatorName>
<givenName>Filiz Akyildiz</givenName>
<familyName>Akcay</familyName>
<affiliation>Katip Celebi Univ, Res & Training Hosp, TR-35620 Izmir, Turkey</affiliation>
</creator>
<creator>
<creatorName>Mainzer, Luidmila</creatorName>
<givenName>Luidmila</givenName>
<familyName>Mainzer</familyName>
</creator>
<creator>
<creatorName>Zurauskien, Justina</creatorName>
<givenName>Justina</givenName>
<familyName>Zurauskien</familyName>
</creator>
<creator>
<creatorName>Erdogan, Zeynep Madak</creatorName>
<givenName>Zeynep Madak</givenName>
<familyName>Erdogan</familyName>
</creator>
</creators>
<titles>
<title>Identification Of Circulating Diagnostic Biomarkers For Coronary Microvascular Disease In Postmenopausal Women Using Machine-Learning Techniques</title>
</titles>
<publisher>Aperta</publisher>
<publicationYear>2021</publicationYear>
<dates>
<date dateType="Issued">2021-01-01</date>
</dates>
<resourceType resourceTypeGeneral="Text">Journal article</resourceType>
<alternateIdentifiers>
<alternateIdentifier alternateIdentifierType="url">https://aperta.ulakbim.gov.tr/record/239448</alternateIdentifier>
</alternateIdentifiers>
<relatedIdentifiers>
<relatedIdentifier relatedIdentifierType="DOI" relationType="IsIdenticalTo">10.3390/metabo11060339</relatedIdentifier>
</relatedIdentifiers>
<rightsList>
<rights rightsURI="http://www.opendefinition.org/licenses/cc-by">Creative Commons Attribution</rights>
<rights rightsURI="info:eu-repo/semantics/openAccess">Open Access</rights>
</rightsList>
<descriptions>
<description descriptionType="Abstract">Coronary microvascular disease (CMD) is a common form of heart disease in postmenopausal women. It is not due to plaque formation but dysfunction of microvessels that feed the heart muscle. The majority of the patients do not receive a proper diagnosis, are discharged prematurely and must go back to the hospital with persistent symptoms. Because of the lack of diagnostic biomarkers, in the current study, we focused on identifying novel circulating biomarkers of CMV (cytomegalovirus) that could potentially be used for developing a diagnostic test. We hypothesized that plasma metabolite composition is different for postmenopausal women with no heart disease, CAD (coronary artery disease), or CMD. A total of 70 postmenopausal women, 26 healthy individuals, 23 individuals with CMD and 21 individuals with CAD were recruited. Their full health screening and tests were completed. Basic cardiac examination, including detailed clinical history, additional disease and prescribed drugs, were noted. Electrocardiograph, transthoracic echocardiography and laboratory analysis were also obtained. Additionally, we performed full metabolite profiling of plasma samples from these individuals using gas chromatography-mass spectrometry (GC-MS) analysis, identified and classified circulating biomarkers using machine learning approaches. Stearic acid and ornithine levels were significantly higher in postmenopausal women with CMD. In contrast, valine levels were higher for women with CAD. Our research identified potential circulating plasma biomarkers of this debilitating heart disease in postmenopausal women, which will have a clinical impact on diagnostic test design in the future.</description>
</descriptions>
</resource>
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