Dataset Information

Raman spectroscopy reveals age- and sex-related differences in cortical bone from people with osteoarthritis.

ABSTRACT: Bone strength in human cortical bone is determined by the composition and structure of both the mineral and collagen matrices and influenced by factors such as age, gender, health, lifestyle and genetic factors. Age-related changes in the bone matrix are known to result in loss of mechanical strength and increased fragility. In this study we show how Raman spectroscopy, with its exquisite sensitivity to the molecular structure of bone, reveals new insights into age- and sex-related differences. Raman analysis of 18 samples of cortical hip bone obtained from people aged between 47-82 years with osteoarthritis (OA) found subtle changes in the lipid and collagen secondary structure, and the carbonate (CO32-) and phosphate (PO43-) mineral ratios in the bone matrix. Significant differences were observed between older and younger bones, and between older female and older male bones; no significant differences were observed between younger male and female bones. Older female bones presented the lowest mineral to matrix ratios (MMR) and highest CO32-/PO43- ratios, and relative to lipid/collagen -CH2 deformation modes at 1450 cm-1 they had lowest overall mineral content, higher collagen cross linking and lipid content but lower levels of ?-helix collagen structures than older male and younger male and female bones. These observations provided further insight on bone composition changes observed in the bone volume fraction (BV/TV) for the older female bones from microCT measurements on the same samples, while tissue mineral density (TMD) measurements had shown no significant differences between the samples.

SUBMITTER: Nieuwoudt MK

PROVIDER: S-EPMC7656243 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

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Raman spectroscopy reveals age- and sex-related differences in cortical bone from people with osteoarthritis.

Nieuwoudt Michel K MK Shahlori Rayomand R Naot Dorit D Patel Rhea R Holtkamp Hannah H Aguergaray Claude C Watson Maureen M Musson David D Brown Cameron C Dalbeth Nicola N Cornish Jillian J Simpson M Cather MC

Scientific reports 20201110 1

Bone strength in human cortical bone is determined by the composition and structure of both the mineral and collagen matrices and influenced by factors such as age, gender, health, lifestyle and genetic factors. Age-related changes in the bone matrix are known to result in loss of mechanical strength and increased fragility. In this study we show how Raman spectroscopy, with its exquisite sensitivity to the molecular structure of bone, reveals new insights into age- and sex-related differences. ...[more]

PMID: 33173169

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Project description:The accurate analytical characterization of metastatic phenotype at primary tumor diagnosis and its evolution with time are critical for controlling metastatic progression of cancer. Here, we report a label-free optical strategy using Raman spectroscopy and machine learning to identify distinct metastatic phenotypes observed in tumors formed by isogenic murine breast cancer cell lines of progressively increasing metastatic propensities. Methods: We employed the 4T1 isogenic panel of murine breast cancer cells to grow tumors of varying metastatic potential and acquired label-free spectra using a fiber probe-based portable Raman spectroscopy system. We used MCR-ALS and random forests classifiers to identify putative spectral markers and predict metastatic phenotype of tumors based on their optical spectra. We also used tumors derived from 4T1 cells silenced for the expression of TWIST, FOXC2 and CXCR3 genes to assess their metastatic phenotype based on their Raman spectra. Results: The MCR-ALS spectral decomposition showed consistent differences in the contribution of components that resembled collagen and lipids between the non-metastatic 67NR tumors and the metastatic tumors formed by FARN, 4T07, and 4T1 cells. Our Raman spectra-based random forest analysis provided evidence that machine learning models built on spectral data can allow the accurate identification of metastatic phenotype of independent test tumors. By silencing genes critical for metastasis in highly metastatic cell lines, we showed that the random forest classifiers provided predictions consistent with the observed phenotypic switch of the resultant tumors towards lower metastatic potential. Furthermore, the spectral assessment of lipid and collagen content of these tumors was consistent with the observed phenotypic switch. Conclusion: Overall, our findings indicate that Raman spectroscopy may offer a novel strategy to evaluate metastatic risk during primary tumor biopsies in clinical patients.

Dataset Information

Raman spectroscopy reveals age- and sex-related differences in cortical bone from people with osteoarthritis.

Publications

Raman spectroscopy reveals age- and sex-related differences in cortical bone from people with osteoarthritis.

Similar Datasets

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