Year: 2024
Type: article
Study design: Observational Study
Abstract: Osteoporosis (OP) is a chronic disease characterized by diminished bone mass and structural deterioration, ultimately leading to compromised bone strength and an increased risk of fractures. Diagnosis primarily relies on medical imaging findings and clinical symptoms. This study aims to explore an adjunctive diagnostic technique for OP based on surface-enhanced Raman scattering (SERS). Serum SERS spectra from the normal, low bone density, and osteoporosis groups were analyzed to discern OP-related expression profiles. This study utilized partial least squares (PLS) and support vector machine (SVM) algorithms to establish an OP diagnostic model. The combination of Raman peak assignments and spectral difference analysis reflected biochemical changes associated with OP, including amino acids, carbohydrates, and collagen. Using the PLS-SVM approach, sensitivity, specificity, and accuracy for screening OP were determined to be 77.78%, 100%, and 88.24%, respectively. This study demonstrates the substantial potential of SERS as an adjunctive diagnostic technology for OP.
Authors: Weihang Yang, Shuang Xia, Xu Jia, Yuwei Zhu, Liang Li, Cheng Jiang, Hongjian Ji, Fengchao Shi
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,090
Awards: G3034894740, G7243879434
OpenAlex ID: W4402983833