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Early Detection on Pancreatic Cancer: 1H NMR Metabolomics Study of its Connection with Diabetes Mellitus.
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SYSNO ASEP 0520609 Document Type C - Proceedings Paper (int. conf.) R&D Document Type The record was not marked in the RIV Title Early Detection on Pancreatic Cancer: 1H NMR Metabolomics Study of its Connection with Diabetes Mellitus. Author(s) Michálková, Lenka (UCHP-M) RID, ORCID, SAI
Horník, Štěpán (UCHP-M) ORCID, RID, SAI
Habartová, L. (CZ)
Sýkora, Jan (UCHP-M) RID, ORCID, SAI
Setnička, V. (CZ)Article number 34 Source Title Conference Program. - Porto : SMASH NMR Conference, 2019 - ISBN N Pages s. 115-116 Number of pages 2 s. Publication form Online - E Action Small Molecular NMR Conference 2019 (SMASH 2019) Event date 22.09.2019 - 25.09.2019 VEvent location Porto Country PT - Portugal Event type EUR Language eng - English Country PT - Portugal Keywords diabetes mellitus ; nmr spectroscopy ; statistical analysis Subject RIV FS - Medical Facilities ; Equipment OECD category Medical engineering Institutional support UCHP-M - RVO:67985858 Annotation In this work, we tested the strategy for the detection of T3cDM and early PC based on NMR metabolomics. ’H NMR spectroscopy was used to detect changes in the concentration of low molecular metabolites in the blood plasma of four groups: PC patients, long-term T2DM (lasting more than 5 years), new-onset diabetic patients (lasting less than 3 years, potential T3cDM) and healthy controls. The ChenomX software was used to identify 65 metabolites across all samples. Based on the concentrations of the identified metabolites, methods of pattern recognition (primarily PCA and OPLS-DA) and statistical tests (t-test and Wilcoxon rank sum test) were used to differentiate between the studied groups. The obtained results suggested a panel of biomarkers for the detection of PC. Within the group of new-onset diabetics, our proposed OPLS- DA model, (verified by Monte Carlo cross-validation), was able to predict possible T3cDM patients at risk of developing PC. Regarding such results, the suggested model might serve as a screening method for the early detection of PC. Workplace Institute of Chemical Process Fundamentals Contact Eva Jirsová, jirsova@icpf.cas.cz, Tel.: 220 390 227 Year of Publishing 2020
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