期刊
ANALYTICAL CHEMISTRY
卷 -, 期 -, 页码 -出版社
AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.2c03368
关键词
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资金
- National Natural Science Foundation of China [82072115]
- National Key R&D Program of China [2022YFC3302002]
- Central Research Institute Public Project [GY2022G-3]
- 2022 Open Foundation of Key Laboratory of Forensic Pathology, Ministry of Public Security, P. R. China [GAFYBL202206]
- Science and Technology Committee of Shanghai Municipality [21DZ2270800, 19DZ2292700]
This study successfully detected biochemical changes in protein conformation in the early phase of myocardial ischemia using Fourier transform infrared (FTIR) spectroscopic imaging combined with multivariate analysis. It also visually classified different disease states. FTIR imaging proves to be a powerful automated quantitative analysis tool for detecting EMI without morphological changes.
Early myocardial ischemia (EMI) is morphologically challenging, and the results from conventional histological staining may be subjective, imprecise, or even silent. The size of myocardial necrosis determines the acute and long-term mortality of EMI. The precise diagnosis of myocardial ischemia is critical for both clinical management and forensic investigation. Fourier transform infrared (FTIR) spectroscopic imaging is a highly sensitive tool for detecting protein conformations and imaging protein profiles. The aim of this study was to evaluate the application of FTIR imaging with multivariate analysis to detect biochemical changes in the protein conformation in the early phase of myocardial ischemia and to visually classify different disease states. The spectra and curve fitting results revealed that the total protein content decreased significantly in the EMI group and that the alpha-helix content of the secondary protein structure continuously decreased as ischemia progressed, while the fl-sheet content increased. Differences in the control and EMI groups and perfused and ischemic myocardium were confirmed using principal component analysis and partial least squares discriminant analysis. Next, two support vector machine classifiers were effectively created. The accuracy, recall, and precision were 99.98, 99.96, and 100.00%, respectively, to differentiate the EMI group from the control group and 99.25, 98.95, and 99.54%, respectively, to differentiate perfused and ischemic myocardium. Ultimately, high EMI diagnostic accuracy was achieved with 100.00% recall and 100.00% precision, and ischemic myocardium diagnostic accuracy was achieved with 99.30% recall and 99.53% precision for the test set. This pilot study demonstrated that FTIR imaging is a powerful automated quantitative analysis tool to detect EMI without morphological changes and will improve diagnostic accuracy and patient prognosis.
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