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Zhang K, Liu R, Wei X, Wang Z, Huang P. Use of Raman spectroscopy to study rat lung tissues for distinguishing asphyxia from sudden cardiac death. RSC Adv 2024; 14:5665-5674. [PMID: 38357034 PMCID: PMC10865087 DOI: 10.1039/d3ra07684a] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2023] [Accepted: 01/24/2024] [Indexed: 02/16/2024] Open
Abstract
Determining asphyxia as the cause of death is crucial but is based on an exclusive strategy because it lacks sensitive and specific morphological characteristics in forensic practice. In some cases where the deceased has underlying heart disease, differentiation between asphyxia and sudden cardiac death (SCD) as the primary cause of death can be challenging. Herein, Raman spectroscopy was employed to detect pulmonary biochemical differences to discriminate asphyxia from SCD in rat models. Thirty-two rats were used to build asphyxia and SCD models, with lung samples collected immediately or 24 h after death. Twenty Raman spectra were collected for each lung sample, and 640 spectra were obtained for further data preprocessing and analysis. The results showed that different biochemical alterations existed in the lung tissues of the rats that died from asphyxia and SCD and could be used to distinguish between the two causes of death. Moreover, we screened and used 8 of the 11 main differential spectral features that maintained their significant differences at 24 h after death to successfully determine the cause of death, even with decomposition and autolysis. Eventually, seven prevalent machine learning classification algorithms were employed to establish classification models, among which the support vector machine exhibited the best performance, with an area under the curve value of 0.9851 in external validation. This study shows the promise of Raman spectroscopy combined with machine learning algorithms to investigate differential biochemical alterations originating from different deaths to aid determining the cause of death in forensic practice.
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Affiliation(s)
- Kai Zhang
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, China, Academy of Forensic Science Shanghai People's Republic of China
- Department of Forensic Pathology, College of Forensic Medicine, NHC Key Laboratory of Forensic Science, Xi'an Jiaotong University Xi'an People's Republic of China
| | - Ruina Liu
- Center for Translational Medicine, The First Affiliated Hospital of Xi'an Jiaotong University Xi'an People's Republic of China
| | - Xin Wei
- Department of Forensic Pathology, College of Forensic Medicine, NHC Key Laboratory of Forensic Science, Xi'an Jiaotong University Xi'an People's Republic of China
| | - Zhenyuan Wang
- Department of Forensic Pathology, College of Forensic Medicine, NHC Key Laboratory of Forensic Science, Xi'an Jiaotong University Xi'an People's Republic of China
| | - Ping Huang
- Shanghai Key Lab of Forensic Medicine, Key Lab of Forensic Science, Ministry of Justice, China, Academy of Forensic Science Shanghai People's Republic of China
- Institute of Forensic Science, Fudan University Shanghai People's Republic of China
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Zhang K, Liu R, Tuo Y, Ma K, Zhang D, Wang Z, Huang P. Distinguishing Asphyxia from Sudden Cardiac Death as the Cause of Death from the Lung Tissues of Rats and Humans Using Fourier Transform Infrared Spectroscopy. ACS OMEGA 2022; 7:46859-46869. [PMID: 36570197 PMCID: PMC9773813 DOI: 10.1021/acsomega.2c05968] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 11/23/2022] [Indexed: 06/17/2023]
Abstract
The ability to determine asphyxia as a cause of death is important in forensic practice and helps us to judge whether a case is criminal. However, in some cases where the deceased has underlying heart disease, death by asphyxia cannot be determined by traditional autopsy and morphological observation under a microscope because there are no specific morphological features for either asphyxia or sudden cardiac death (SCD). Here, Fourier transform infrared (FTIR) spectroscopy was employed to distinguish asphyxia from SCD. A total of 40 lung tissues (collected at 0 h and 24 h postmortem) from 20 rats (10 died from asphyxia and 10 died from SCD) and 16 human lung tissues from 16 real cases were used for spectral data acquisition. After data preprocessing, 2675 spectra from rat lung tissues and 1526 spectra from human lung tissues were obtained for subsequent analysis. First, we found that there were biochemical differences in the rat lung tissues between the two causes of death by principal component analysis and partial least-squares discriminant analysis (PLS-DA), which were related to alterations in lipids, proteins, and nucleic acids. In addition, a PLS-DA classification model can be built to distinguish asphyxia from SCD. Second, based on the spectral data obtained from lung tissues allowed to decompose for 24 h, we could still distinguish asphyxia from SCD even when decomposition occurred in animal models. Nine important spectral features that contributed to the discrimination in the animal experiment were selected and further analyzed. Third, 7 of the 9 differential spectral features were also found to be significantly different in human lung tissues from 16 real cases. A support vector machine model was finally built by using the seven variables to distinguish asphyxia from SCD in the human samples. Compared with the linear PLS-DA model, its accuracy was significantly improved to 0.798, and the correct rate of determining the cause of death was 100%. This study shows the application potential of FTIR spectroscopy for exploring the subtle biochemical differences resulting from different death processes and determining the cause of death even after decomposition.
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Affiliation(s)
- Kai Zhang
- Department
of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, People’s
Republic of China
| | - Ruina Liu
- Department
of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, People’s
Republic of China
| | - Ya Tuo
- Department
of Biochemistry and Physiology, Shanghai
University of Medicine and Health Sciences, Shanghai 201318, People’s Republic of China
| | - Kaijun Ma
- Shanghai
Key Laboratory of Crime Scene Evidence, Institute of Criminal Science
and Technology, Shanghai Municipal Public
Security Bureau, Shanghai 200042, People’s Republic
of China
| | - Dongchuan Zhang
- Shanghai
Key Laboratory of Crime Scene Evidence, Institute of Criminal Science
and Technology, Shanghai Municipal Public
Security Bureau, Shanghai 200042, People’s Republic
of China
| | - Zhenyuan Wang
- Department
of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, People’s
Republic of China
| | - Ping Huang
- Shanghai
Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Shanghai 200063, People’s Republic of China
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Tian T, Zhang J, Xiong L, Yu H, Deng K, Liao X, Zhang F, Huang P, Zhang J, Chen Y. Evaluating Subtle Pathological Changes in Early Myocardial Ischemia Using Spectral Histopathology. Anal Chem 2022; 94:17112-17120. [PMID: 36442494 DOI: 10.1021/acs.analchem.2c03368] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
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 α-helix content of the secondary protein structure continuously decreased as ischemia progressed, while the β-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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Affiliation(s)
- Tian Tian
- Department of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041, P. R. China.,Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, P. R. China, Shanghai 200063, China
| | - Jianhua Zhang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, P. R. China, Shanghai 200063, China
| | - Ling Xiong
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, P. R. China, Shanghai 200063, China.,Department of Forensic Medicine, Guizhou Medical University, Guiyang, Guizhou 550004, P. R. China
| | - Haixing Yu
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, P. R. China, Shanghai 200063, China.,College of Medicine & Forensics, Xi'an Jiaotong University Health Science Center, Xi'an, Shaanxi 710061, P. R. China
| | - Kaifei Deng
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, P. R. China, Shanghai 200063, China
| | - Xinbiao Liao
- Key Laboratory of Forensic Pathology, Ministry of Public Security, P. R. China, Guangzhou 510050, Guangdong, China
| | - Fu Zhang
- Key Laboratory of Forensic Pathology, Ministry of Public Security, P. R. China, Guangzhou 510050, Guangdong, China
| | - Ping Huang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, P. R. China, Shanghai 200063, China
| | - Ji Zhang
- Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, P. R. China, Shanghai 200063, China
| | - Yijiu Chen
- Department of Forensic Pathology, West China School of Basic Medical Sciences & Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041, P. R. China.,Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, P. R. China, Shanghai 200063, China
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