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Showing content from https://pubmed.ncbi.nlm.nih.gov/36222101/ below:

Label-free fibre optic Raman spectroscopy with bounded simplex-structured matrix factorization for the serial study of serum in amyotrophic lateral sclerosis

. 2022 Nov 7;147(22):5113-5120. doi: 10.1039/d2an00936f. Label-free fibre optic Raman spectroscopy with bounded simplex-structured matrix factorization for the serial study of serum in amyotrophic lateral sclerosis

Affiliations

¹ Sheffield Institute for Translational Neuroscience, University of Sheffield, UK. j.alix@sheffield.ac.uk.
² Neuroscience Institute, University of Sheffield, UK.
³ Department of Automatic Control and Systems Engineering, University of Sheffield, UK.
⁴ Nuffield Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
⁵ Blizard Institute, Queen Mary University of London, London, UK.
⁶ Interface Analysis Centre, School of Physics, University of Bristol, UK.

PMID: 36222101
PMCID: PMC9639415
DOI: 10.1039/d2an00936f

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Label-free fibre optic Raman spectroscopy with bounded simplex-structured matrix factorization for the serial study of serum in amyotrophic lateral sclerosis

James J P Alix et al. Analyst. 2022.

. 2022 Nov 7;147(22):5113-5120. doi: 10.1039/d2an00936f. Affiliations

¹ Sheffield Institute for Translational Neuroscience, University of Sheffield, UK. j.alix@sheffield.ac.uk.
² Neuroscience Institute, University of Sheffield, UK.
³ Department of Automatic Control and Systems Engineering, University of Sheffield, UK.
⁴ Nuffield Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
⁵ Blizard Institute, Queen Mary University of London, London, UK.
⁶ Interface Analysis Centre, School of Physics, University of Bristol, UK.

PMID: 36222101
PMCID: PMC9639415
DOI: 10.1039/d2an00936f

Item in Clipboard

Abstract

Amyotrophic lateral sclerosis (ALS) is an incurable neurodegenerative disease in urgent need of disease biomarkers for the assessment of promising therapeutic candidates in clinical trials. Raman spectroscopy is an attractive technique for identifying disease related molecular changes due to its simplicity. Here, we describe a fibre optic fluid cell for undertaking spontaneous Raman spectroscopy studies of human biofluids that is suitable for use away from a standard laboratory setting. Using this system, we examined serum obtained from patients with ALS at their first presentation to our centre (n = 66) and 4 months later (n = 27). We analysed Raman spectra using bounded simplex-structured matrix factorization (BSSMF), a generalisation of non-negative matrix factorisation which uses the distribution of the original data to limit the factorisation modes (spectral patterns). Biomarkers associated with ALS disease such as measures of symptom severity, respiratory function and inflammatory/immune pathways (C3/C-reactive protein) correlated with baseline Raman modes. Between visit spectral changes were highly significant (p = 0.0002) and were related to protein structure. Comparison of Raman data with established ALS biomarkers as a trial outcome measure demonstrated a reduction in required sample size with BSSMF Raman. Our portable, simple to use fibre optic system allied to BSSMF shows promise in the quantification of disease-related changes in ALS over short timescales.

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Conflict of interest statement

J. C. C. D. is the chief executive office of Clifton Photonics Ltd, a company that designs photonic instruments for industrial and research use.

Figures
Fig. 1. The portable fibre optic Raman…

Fig. 1. The portable fibre optic Raman system. (a) The 3D printed fluid cell and…
Fig. 1. The portable fibre optic Raman system. (a) The 3D printed fluid cell and schematic of the system. (b) Mean (± standard deviation) spectra (all samples).
Fig. 2. Spectral patterns arising from the…

Fig. 2. Spectral patterns arising from the BSSMF and their linear combinations. (a) Modes from…
Fig. 2. Spectral patterns arising from the BSSMF and their linear combinations. (a) Modes from the BSSMF factorisation of all data. Visit 1 outputs were then correlated with visit 1 clinical/biomarker data to established associations with disease severity (n=66 samples from 66 patients). (b) Modes were combined with PCA and then the relevant PC1 coefficients used to derive spectral patterns associated with worsening disease (modes 1, 3, 5) and less severe disease (modes 2, 4).
Fig. 3. Change in clinical and biochemical…

Fig. 3. Change in clinical and biochemical measures of disease. (a) Changes in key clinical…
Fig. 3. Change in clinical and biochemical measures of disease. (a) Changes in key clinical and biochemical measures of disease (n = 27; see ESI fig. S2 for data from other measures). (b) Mean (± standard deviation) for Raman spectra obtained from patients attending both visit 1 and visit 2 (n = 27). *p < 0.05, **p < 0.01.
Fig. 4. Longitudinal BSSMF mode and BSSMF-PCA…

Fig. 4. Longitudinal BSSMF mode and BSSMF-PCA changes. (a) Changes in individual BSSMF mode weights.…
Fig. 4. Longitudinal BSSMF mode and BSSMF-PCA changes. (a) Changes in individual BSSMF mode weights. (b) Change in BSSMF-PCA scores from visit 1 and visit 2. ns – not significant, ***p < 0.001. Similar articles

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