Evidence map›Paper›PMID 36362276›Full record

ArticleInternational journal of molecular sciences2022

An Emerging Strategy for Muscle Evanescent Trauma Discrimination by Spectroscopy and Chemometrics.

Gongji Wang, Hao Wu, Canyu Yang, Zefeng Li, Run Chen, Xinggong Liang, Kai Yu, Huiyu Li, Chen Shen, Ruina Liu and 4 more

Open access · goldAbstract read
In one paragraph

Article in International journal of molecular sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
3.2field-weighted citation impact, top 8% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 12 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 1 institution in 1 country.

Gongji WangDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Hao WuDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Canyu YangDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Zefeng LiDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Run ChenDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Xinggong LiangDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Kai YuDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Huiyu LiDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Chen ShenDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Ruina LiuDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Xin WeiDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Qinru SunDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Kai ZhangDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Zhenyuan WangDepartment of Forensic Pathology, College of Forensic Medicine, Xi'an Jiaotong University, Xi'an 710061, China.
Xi'an Jiaotong University · CN

Funding

Key Research and Development Program of Shaanxi 2020SF-133NHC Key Laboratory of Forensic Science (Xi'an Jiaotong University) Open Projects Fund 2019FYXH005the National Natural Science Foundation of China No. 81730056
6 · The paper itself

Abstract

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.

Indexed as

ChemometricsMuscular DiseasesAnimalsDiscriminant AnalysisHumansLeast-Squares AnalysisMusclesPrincipal Component AnalysisRatsSpectroscopy, Fourier Transform InfraredATR-FTIRchemometricsevanescent traumamicro-IR spectroscopy

Identifiers

PMID36362276
PMCPMC9658611
OpenAlexW4308207272

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.