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Temporal expression of wound healing–related genes inform wound age estimation in rats after a skeletal muscle contusion: a multivariate statistical model analysis

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Abstract

Although many time-dependent parameters involved in wound healing have been exhaustively investigated, establishing an objective and reliable means for estimating wound age remains a challenge. In this study, 78 Sprague–Dawley rats were divided randomly into a control group and contusion groups at 4, 8, 12, 16, 20, 24, 28, 32, 36, 40, 44, and 48 h post-injury (n = 6 per group). The expression of 35 wound healing–related genes was explored in contused skeletal muscle by real-time polymerase chain reaction. Differences between the groups were assessed by partial least squares discriminant analysis (PLS-DA). The results show that the samples were classified into three groups by wound age (4–12, 16–24, and 28–48 h). A Fisher discriminant analysis model of 14 selected genes was constructed, and 94.9% cross-validated grouped cases were correctly classified. A PLS regression analysis using 14 genes showed reasonable internal predictive validity, with a root mean squared error of cross-validation of approximately 8 h. To examine whether the prediction models were capable of analyzing new (ungrouped) cases, an external validation was carried out using the expression data from an additional 30 rats. Approximately 76.7% of ungrouped cases were correctly classified, which was a lower proportion than that for cross-validation. Similarly, the prediction results of the PLS model showed lower relatively external predictive validity (root mean squared error of prediction = 11 h) than internal predictive validity. Although the prediction results were less accurate than expected, the gene expression modeling and multivariate analyses showed great potential for estimating injury time. These multivariate methods may be valuable when devising future wound time estimation strategies.

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References

  1. Wang L-L, Zhao R, Liu C-S, Liu M, Li S-S, Li J-Y, Jiang S-K, Zhang M, Tian Z-L, Wang M, Zhang M-Z, Guan D-W (2016) A fundamental study on the dynamics of multiple biomarkers in mouse excisional wounds for wound age estimation. J Forensic Legal Med 39:138–146. https://doi.org/10.1016/j.jflm.2016.01.027

    Article  Google Scholar 

  2. Ishida Y, Kuninaka Y, Nosaka M, Kimura A, Kawaguchi T, Hama M, Sakamoto S, Shinozaki K, Eisenmenger W, Kondo T (2015) Immunohistochemical analysis on MMP-2 and MMP-9 for wound age determination. Int J Legal Med 129(5):1043–1048. https://doi.org/10.1007/s00414-015-1167-5

    Article  PubMed  Google Scholar 

  3. Yagi Y, Murase T, Kagawa S, Tsuruya S, Nakahara A, Yamamoto T, Umehara T, Ikematsu K (2016) Immunohistochemical detection of CD14 and combined assessment with CD32B and CD68 for wound age estimation. Forensic Sci Int 262:113–120. https://doi.org/10.1016/j.forsciint.2016.02.031

    Article  CAS  PubMed  Google Scholar 

  4. Sun JH, Zhu XY, Dong TN, Zhang XH, Liu QQ, Li SQ, Du QX (2017) An “up, no change, or down” system: time-dependent expression of mRNAs in contused skeletal muscle of rats used for wound age estimation. Forensic Sci Int 272:104–110. https://doi.org/10.1016/j.forsciint.2017.01.012

    Article  CAS  PubMed  Google Scholar 

  5. Palagummi S, Harbison S, Fleming R (2014) A time-course analysis of mRNA expression during injury healing in human dermal injuries. Int J Legal Med 128(3):403–414. https://doi.org/10.1007/s00414-013-0941-5

    Article  PubMed  Google Scholar 

  6. Liu R, Sun Q, Hu T, Li L, Nie L, Wang J, Zhou W, Zang H (2018) Multi-parameters monitoring during traditional Chinese medicine concentration process with near infrared spectroscopy and chemometrics. Spectrochim Acta A Mol Biomol Spectrosc 192:75–81. https://doi.org/10.1016/j.saa.2017.10.068

    Article  CAS  PubMed  Google Scholar 

  7. Rathore AS, Bhambure R, Ghare V (2010) Process analytical technology (PAT) for biopharmaceutical products. Anal Bioanal Chem 398(1):137–154. https://doi.org/10.1007/s00216-010-3781-x

    Article  CAS  PubMed  Google Scholar 

  8. Zhu X-y, Du Q-x, Li S-q, Sun J-h (2016) Comparison of the homogeneity of mRNAs encoding SFRP5, FZD4, and Fosl1 in post-injury intervals: subcellular localization of markers may influence wound age estimation. J Forensic Legal Med 43:90–96. https://doi.org/10.1016/j.jflm.2016.07.013

    Article  Google Scholar 

  9. Sun JH, Nan LH, Gao CR, Wang YY (2012) Validation of reference genes for estimating wound age in contused rat skeletal muscle by quantitative real-time PCR. Int J Legal Med 126(1):113–120. https://doi.org/10.1007/s00414-011-0604-3

    Article  PubMed  Google Scholar 

  10. Hassan Gaballah M, Fukuta M, Maeno Y, Seko-Nakamura Y, Monma-Ohtaki J, Shibata Y, Kato H, Aoki Y, Takamiya M (2016) Simultaneous time course analysis of multiple markers based on DNA microarray in incised wound in skeletal muscle for wound aging. Forensic Sci Int 266:357–368. https://doi.org/10.1016/j.forsciint.2016.06.027

    Article  CAS  PubMed  Google Scholar 

  11. Kimura A, Ishida Y, Nosaka M, Shiraki M, Hama M, Kawaguchi T, Kuninaka Y, Shimada E, Yamamoto H, Takayasu T, Kondo T (2015) Autophagy in skin wounds: a novel marker for vital reactions. Int J Legal Med 129(3):537–541. https://doi.org/10.1007/s00414-015-1168-4

    Article  PubMed  Google Scholar 

  12. van de Goot FR, Korkmaz HI, Fronczek J, Witte BI, Visser R, Ulrich MM, Begieneman MP, Rozendaal L, Krijnen PA, Niessen HW (2014) A new method to determine wound age in early vital skin injuries: a probability scoring system using expression levels of fibronectin, CD62p and factor VIII in wound hemorrhage. Forensic Sci Int 244:128–135. https://doi.org/10.1016/j.forsciint.2014.08.015

    Article  CAS  PubMed  Google Scholar 

  13. Wang Y, Yamamoto Y, Kuninaka Y, Kondo T, Furukawa F (2015) Forensic potential of MMPs and CC chemokines for wound age determination. J Forensic Sci 60(6):1511–1515. https://doi.org/10.1111/1556-4029.12831

    Article  CAS  PubMed  Google Scholar 

  14. Kubo H, Hayashi T, Ago K, Ago M, Kanekura T, Ogata M (2014) Temporal expression of wound-healing-related genes in skin burn injury. Legal Med 16(1):8–13. https://doi.org/10.1016/j.legalmed.2013.10.002

    Article  CAS  PubMed  Google Scholar 

  15. Ibrahim SF, Issak M, Bayoumy AA, Abd El-Fatah DS (2016) Cutaneous (tPA) and skeletal (TnI) mRNA as markers of aging in contused wound. J Forensic Sci 61(4):1007–1010. https://doi.org/10.1111/1556-4029.13072

    Article  CAS  PubMed  Google Scholar 

  16. Zheng JL, Yu TS, Li XN, Fan YY, Ma WX, Du Y, Zhao R, Guan DW (2012) Cannabinoid receptor type 2 is time-dependently expressed during skin wound healing in mice. Int J Legal Med 126(5):807–814. https://doi.org/10.1007/s00414-012-0741-3

    Article  PubMed  Google Scholar 

  17. Fan YY, Zhang ST, Yu LS, Ye GH, Lin KZ, Wu SZ, Dong MW, Han JG, Feng XP, Li XB (2014) The time-dependent expression of alpha7nAChR during skeletal muscle wound healing in rats. Int J Legal Med 128(5):779–786. https://doi.org/10.1007/s00414-014-1001-5

    Article  PubMed  Google Scholar 

  18. Tian ZL, Jiang SK, Zhang M, Wang M, Li JY, Zhao R, Wang LL, Li SS, Liu M, Zhang MZ, Guan DW (2016) Detection of satellite cells during skeletal muscle wound healing in rats: time-dependent expressions of Pax7 and MyoD in relation to wound age. Int J Legal Med 130(1):163–172. https://doi.org/10.1007/s00414-015-1251-x

    Article  PubMed  Google Scholar 

  19. Fronczek J, Lulf R, Korkmaz HI, Witte BI, van de Goot FR, Begieneman MP, Schalkwijk CG, Krijnen PA, Rozendaal L, Niessen HW, Reijnders UJ (2015) Analysis of inflammatory cells and mediators in skin wound biopsies to determine wound age in living subjects in forensic medicine. Forensic Sci Int 247:7–13. https://doi.org/10.1016/j.forsciint.2014.11.014

    Article  CAS  PubMed  Google Scholar 

  20. Takamiya M, Fujita S, Saigusa K, Aoki Y (2007) Simultaneous detections of 27 cytokines during cerebral wound healing by multiplexed bead-based immunoassay for wound age estimation. J Neurotrauma 24(12):1833–1844. https://doi.org/10.1089/neu.2007.0336

    Article  PubMed  Google Scholar 

  21. Li N, Du Q, Bai R, Sun J (2018) Vitality and wound-age estimation in forensic pathology: review and future prospects. FSR 1–10. https://doi.org/10.1080/20961790.2018.1445441

  22. Casse JM, Martrille L, Vignaud JM, Gauchotte G (2016) Skin wounds vitality markers in forensic pathology: an updated review. Med Sci Law 56(2):128–137. https://doi.org/10.1177/0025802415590175

    Article  PubMed  Google Scholar 

  23. Kondo T, Ishida Y (2010) Molecular pathology of wound healing. Forensic Sci Int 203(1–3):93–98. https://doi.org/10.1016/j.forsciint.2010.07.004

    Article  CAS  PubMed  Google Scholar 

  24. Kondo T (2007) Timing of skin wounds. Legal Med 9(2):109–114. https://doi.org/10.1016/j.legalmed.2006.11.009

    Article  PubMed  Google Scholar 

  25. Sun J-h, Wang Y-y, Zhang L, Gao C-r, Zhang L-z, Guo Z (2009) Time-dependent expression of skeletal muscle troponin I mRNA in the contused skeletal muscle of rats: a possible marker for wound age estimation. Int J Legal Med 124(1):27–33. https://doi.org/10.1007/s00414-009-0323-1

    Article  PubMed  Google Scholar 

  26. Fisher BD, Baracos VE, Shnitka TK, Mendryk SW, Reid DC (1990) Ultrastructural events following acute muscle trauma. Med Sci Sports Exerc 22(2):185–193

    CAS  PubMed  Google Scholar 

  27. Papadimitriou JM, Robertson TA, Mitchell CA, Grounds MD (1990) The process of new plasmalemma formation in focally injured skeletal muscle fibers. J Struct Biol 103(2):124–134

    Article  CAS  PubMed  Google Scholar 

  28. Chen Y, Wang H, Zhang J, Garty G, Simaan N, Yao YL, Brenner DJ (2012) Automated recognition of robotic manipulation failures in high-throughput biodosimetry tool. Expert Syst Appl 39(10):9602–9611

    Article  PubMed  PubMed Central  Google Scholar 

  29. Toziou PM, Barmpalexis P, Boukouvala P, Verghese S, Nikolakakis I (2018) Quantification of live lactobacillus acidophilus in mixed populations of live and killed by application of attenuated reflection Fourier transform infrared spectroscopy combined with chemometrics. J Pharm Biomed Anal 154:16–22. https://doi.org/10.1016/j.jpba.2018.03.009

    Article  CAS  PubMed  Google Scholar 

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Funding

This project is financially supported by grants from the National Natural Science Foundation of China (grant numbers 81601646, 81571852).

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Authors and Affiliations

  1. School of Forensic Medicine, Shanxi Medical University, 56 South Xinjian Road, Taiyuan, 030001, Shanxi, People’s Republic of China

    Qiu-xiang Du, Na Li, Li-hong Dang, Ta-na Dong, Han-lin Lu, Fu-xia Shi, Qian-qian Jin, Cao Jie & Jun-hong Sun

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  1. Qiu-xiang Du
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  2. Na Li
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  4. Ta-na Dong
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Correspondence to Cao Jie or Jun-hong Sun.

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This article does not contain any studies with human participants performed by any of the authors. The principles of the Guide for the Care and Use of Laboratory Animals protocol, published by the Ministry of the People’s Republic of China, were followed.

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Du, Qx., Li, N., Dang, Lh. et al. Temporal expression of wound healing–related genes inform wound age estimation in rats after a skeletal muscle contusion: a multivariate statistical model analysis. Int J Legal Med 134, 273–282 (2020). https://doi.org/10.1007/s00414-018-01990-2

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