An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics
Trauma is one of the most common conditions in the biomedical field. It is important to identify it quickly and accurately. However, when evanescent trauma occurs, it presents a great challenge to professionals. There are few reports on the establishment of a rapid and accurate trauma identification...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | International Journal of Molecular Sciences |
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| Online Access: | https://www.mdpi.com/1422-0067/23/21/13489 |
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| author | Gongji Wang Hao Wu Canyu Yang Zefeng Li Run Chen Xinggong Liang Kai Yu Huiyu Li Chen Shen Ruina Liu Xin Wei Qinru Sun Kai Zhang Zhenyuan Wang |
| author_facet | Gongji Wang Hao Wu Canyu Yang Zefeng Li Run Chen Xinggong Liang Kai Yu Huiyu Li Chen Shen Ruina Liu Xin Wei Qinru Sun Kai Zhang Zhenyuan Wang |
| author_sort | Gongji Wang |
| collection | DOAJ |
| description | Trauma is one of the most common conditions in the biomedical field. It is important to identify it quickly and accurately. However, when evanescent trauma occurs, it presents a great challenge to professionals. There are few reports on the establishment of a rapid and accurate trauma identification and prediction model. In this study, Fourier transform infrared spectroscopy (FTIR) and microscopic spectroscopy (micro-IR) combined with chemometrics were used to establish prediction models for the rapid identification of muscle trauma in humans and rats. The results of the average spectrum, principal component analysis (PCA) and loading maps showed that the differences between the rat muscle trauma group and the rat control group were mainly related to biological macromolecules, such as proteins, nucleic acids and carbohydrates. The differences between the human muscle trauma group and the human control group were mainly related to proteins, polysaccharides, phospholipids and phosphates. Then, a partial least squares discriminant analysis (PLS-DA) was used to evaluate the classification ability of the training and test datasets. The classification accuracies were 99.10% and 93.69%, respectively. Moreover, a trauma classification and recognition model of human muscle tissue was constructed, and a good classification effect was obtained. The classification accuracies were 99.52% and 91.95%. In conclusion, spectroscopy and stoichiometry have the advantages of being rapid, accurate and objective and of having high resolution and a strong recognition ability, and they are emerging strategies for the identification of evanescent trauma. In addition, the combination of spectroscopy and stoichiometry has great potential in the application of medicine and criminal law under practical conditions. |
| first_indexed | 2024-03-09T18:59:43Z |
| format | Article |
| id | doaj.art-86fa44605b9d4234afbc416ebcb58f17 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-09T18:59:43Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-86fa44605b9d4234afbc416ebcb58f172023-11-24T05:08:49ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672022-11-0123211348910.3390/ijms232113489An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and ChemometricsGongji Wang0Hao Wu1Canyu Yang2Zefeng Li3Run Chen4Xinggong Liang5Kai Yu6Huiyu Li7Chen Shen8Ruina Liu9Xin Wei10Qinru Sun11Kai Zhang12Zhenyuan Wang13Department of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaDepartment of Forensic Pathology, College of Forensic Medicine, Xi’an Jiaotong University, Xi’an 710061, ChinaTrauma is one of the most common conditions in the biomedical field. It is important to identify it quickly and accurately. However, when evanescent trauma occurs, it presents a great challenge to professionals. There are few reports on the establishment of a rapid and accurate trauma identification and prediction model. In this study, Fourier transform infrared spectroscopy (FTIR) and microscopic spectroscopy (micro-IR) combined with chemometrics were used to establish prediction models for the rapid identification of muscle trauma in humans and rats. The results of the average spectrum, principal component analysis (PCA) and loading maps showed that the differences between the rat muscle trauma group and the rat control group were mainly related to biological macromolecules, such as proteins, nucleic acids and carbohydrates. The differences between the human muscle trauma group and the human control group were mainly related to proteins, polysaccharides, phospholipids and phosphates. Then, a partial least squares discriminant analysis (PLS-DA) was used to evaluate the classification ability of the training and test datasets. The classification accuracies were 99.10% and 93.69%, respectively. Moreover, a trauma classification and recognition model of human muscle tissue was constructed, and a good classification effect was obtained. The classification accuracies were 99.52% and 91.95%. In conclusion, spectroscopy and stoichiometry have the advantages of being rapid, accurate and objective and of having high resolution and a strong recognition ability, and they are emerging strategies for the identification of evanescent trauma. In addition, the combination of spectroscopy and stoichiometry has great potential in the application of medicine and criminal law under practical conditions.https://www.mdpi.com/1422-0067/23/21/13489evanescent traumaATR-FTIRmicro-IR spectroscopychemometrics |
| spellingShingle | Gongji Wang Hao Wu Canyu Yang Zefeng Li Run Chen Xinggong Liang Kai Yu Huiyu Li Chen Shen Ruina Liu Xin Wei Qinru Sun Kai Zhang Zhenyuan Wang An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics International Journal of Molecular Sciences evanescent trauma ATR-FTIR micro-IR spectroscopy chemometrics |
| title | An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics |
| title_full | An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics |
| title_fullStr | An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics |
| title_full_unstemmed | An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics |
| title_short | An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics |
| title_sort | emerging strategy for muscle evanescent trauma discrimination by spectroscopy and chemometrics |
| topic | evanescent trauma ATR-FTIR micro-IR spectroscopy chemometrics |
| url | https://www.mdpi.com/1422-0067/23/21/13489 |
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