ArticleRSC advances2024
Surface-enhanced Raman spectroscopy for characterization of filtrates of blood serum samples from patients with tuberculosis obtained by 50 kDa filtration devices.
Article in RSC advances, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 21 citations in OpenAlex.
- Gold- or Silver-Nanoparticle SERS Platforms for Plasma-Based Diagnostics and AI-Driven Analysis.Sensors (Basel, Switzerland) · 2026Review
- Surface-enhanced Raman spectroscopy analysis of glucose in spent embryo culture medium: correlation with embryo developmental potential.Frontiers in cell and developmental biology · 2026Article
- Molecular Insights into α-Synuclein Fibrillation: A Raman Spectroscopy and Machine Learning Approach.ACS chemical neuroscience · 2025Article
- SERS profiling of blood serum filtrate components from patients with type II diabetes using 100 kDa filtration devices.RSC advances · 2025Article
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Authors and funding
15 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The ability of surface-enhanced Raman spectroscopy (SERS) to generate spectroscopic fingerprints has made it an emerging tool for biomedical applications. The objective of this study is to confirm the potential use of Raman spectroscopy for early disease diagnosis based on blood serum. In this study, a total of sixty blood serum samples, consisting of forty from diseased patients and twenty (controls) from healthy individuals, was used. Because disease biomarkers, found in the lower molecular weight fraction, are suppressed by higher molecular weight proteins, 50 kDa Amicon ultrafiltration centrifugation devices were used to produce two fractions from whole blood serum consisting of a filtrate, which is a low molecular weight fraction, and a residue, which is a high molecular weight fraction. These fractions were then analyzed, and their SERS spectral data were compared with those of healthy fractions. The SERS technique was utilized on blood serum, filtrate and residue of patients with tuberculosis to identify characteristic SERS spectral features associated with the development of disease, which can be used to differentiate them from healthy samples using silver nanoparticles as a SERS substrate. For further analysis, the effective chemometric technique of principal component analysis (PCA) was used to qualitatively differentiate all the analyzed samples based on their SERS spectral features. Partial least squares discriminant analysis (PLS-DA) accurately classified the filtrate portions of healthy and tuberculosis samples with 97% accuracy, 97% specificity, 98% sensitivity, and an area under the receiver operating characteristic (AUROC) curve of 0.74.
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Registered trials
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