R. Shaikh, E. Nippolainen, V. Virtanen, J. Torniainen, L. Rieppo, S. Saarakkala, I. Afara, J. Töyräs
{"title":"拉曼光谱对各种软骨损伤相关的生化变化敏感","authors":"R. Shaikh, E. Nippolainen, V. Virtanen, J. Torniainen, L. Rieppo, S. Saarakkala, I. Afara, J. Töyräs","doi":"10.2139/ssrn.3606831","DOIUrl":null,"url":null,"abstract":"In recent years, Raman spectroscopy has evolved as a promising in vivo tool in various biomedical applications. It has also shown potential for scoring the lesion severity of joint cartilage, which could be useful in determining the best treatment strategy during cartilage arthroscopic repair surgery. However, the effect of different cartilage injury types on Raman spectra is unknown. The study aims to show the potential of Raman spectroscopy to detect different cartilage injury types that mimic physiologically relevant damages. Different types of injuries were induced using established mechanical and enzymatic approaches. The mechanical damage—was induced through surface abrasion (ABR) (n = 12) or impact loading (IMP) (n = 12). Enzymatic damage—was induced using three different treatments: 30 minutes trypsin digestion (T-30)(n = 12), 90 minutes collagenase digestion (C-90)(n = 12), and 24 hours collagenase digestion (C-24)(n = 12). Raman spectra were obtained from all the specimens, and partial least squares discriminant analysis (PLS-DA) was applied to distinguish cartilage injury types from their respective controls. The PLS-DA cross-validation accuracies were higher for C-24 (88%) and IMP (79%) than for C-90 (67%), T-30 (63%), and ABR (58%) groups. This study indicates that Raman spectroscopy, combined with multivariate analysis, can identify different cartilage injury types.","PeriodicalId":8928,"journal":{"name":"Biomaterials eJournal","volume":"17 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2020-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"Raman Spectroscopy is Sensitive to Biochemical Changes Related to Various Cartilage Injuries\",\"authors\":\"R. Shaikh, E. Nippolainen, V. Virtanen, J. Torniainen, L. Rieppo, S. Saarakkala, I. Afara, J. Töyräs\",\"doi\":\"10.2139/ssrn.3606831\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, Raman spectroscopy has evolved as a promising in vivo tool in various biomedical applications. It has also shown potential for scoring the lesion severity of joint cartilage, which could be useful in determining the best treatment strategy during cartilage arthroscopic repair surgery. However, the effect of different cartilage injury types on Raman spectra is unknown. The study aims to show the potential of Raman spectroscopy to detect different cartilage injury types that mimic physiologically relevant damages. Different types of injuries were induced using established mechanical and enzymatic approaches. The mechanical damage—was induced through surface abrasion (ABR) (n = 12) or impact loading (IMP) (n = 12). Enzymatic damage—was induced using three different treatments: 30 minutes trypsin digestion (T-30)(n = 12), 90 minutes collagenase digestion (C-90)(n = 12), and 24 hours collagenase digestion (C-24)(n = 12). Raman spectra were obtained from all the specimens, and partial least squares discriminant analysis (PLS-DA) was applied to distinguish cartilage injury types from their respective controls. The PLS-DA cross-validation accuracies were higher for C-24 (88%) and IMP (79%) than for C-90 (67%), T-30 (63%), and ABR (58%) groups. This study indicates that Raman spectroscopy, combined with multivariate analysis, can identify different cartilage injury types.\",\"PeriodicalId\":8928,\"journal\":{\"name\":\"Biomaterials eJournal\",\"volume\":\"17 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biomaterials eJournal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2139/ssrn.3606831\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biomaterials eJournal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2139/ssrn.3606831","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Raman Spectroscopy is Sensitive to Biochemical Changes Related to Various Cartilage Injuries
In recent years, Raman spectroscopy has evolved as a promising in vivo tool in various biomedical applications. It has also shown potential for scoring the lesion severity of joint cartilage, which could be useful in determining the best treatment strategy during cartilage arthroscopic repair surgery. However, the effect of different cartilage injury types on Raman spectra is unknown. The study aims to show the potential of Raman spectroscopy to detect different cartilage injury types that mimic physiologically relevant damages. Different types of injuries were induced using established mechanical and enzymatic approaches. The mechanical damage—was induced through surface abrasion (ABR) (n = 12) or impact loading (IMP) (n = 12). Enzymatic damage—was induced using three different treatments: 30 minutes trypsin digestion (T-30)(n = 12), 90 minutes collagenase digestion (C-90)(n = 12), and 24 hours collagenase digestion (C-24)(n = 12). Raman spectra were obtained from all the specimens, and partial least squares discriminant analysis (PLS-DA) was applied to distinguish cartilage injury types from their respective controls. The PLS-DA cross-validation accuracies were higher for C-24 (88%) and IMP (79%) than for C-90 (67%), T-30 (63%), and ABR (58%) groups. This study indicates that Raman spectroscopy, combined with multivariate analysis, can identify different cartilage injury types.