Diagnosis of neuropsychiatric systemic lupus erythematosus by label-free serum microsphere-coupled SERS fingerprints with machine learning.
Biosens Bioelectron
; 260: 116414, 2024 Sep 15.
Article
em En
| MEDLINE
| ID: mdl-38815463
ABSTRACT
Surface-enhanced Raman spectroscopy (SERS) is a powerful optical technique for non-invasive and label-free bioanalysis of liquid biopsy, facilitating to diagnosis of potential diseases. Neuropsychiatric systemic lupus erythematosus (NPSLE) is one of the subgroups of systemic lupus erythematosus (SLE) with serious manifestations for a high mortality rate. Unfortunately, lack of well-established gold standards results in the clinical diagnosis of NPSLE being a challenge so far. Here we develop a novel Raman fingerprinting machine learning (ML-) assisted diagnostic method. The microsphere-coupled SERS (McSERS) substrates are employed to acquire Raman spectra for analysis via convolutional neural network (CNN). The McSERS substrates demonstrate better performance to distinguish the Raman spectra from serums between SLE and NPSLE, attributed to the boosted signal-to-noise ratio of Raman intensities due to the multiple optical regulation in microspheres and AuNPs. Eight statistically-significant (p-value <0.05) Raman shifts are identified, for the first time, as the characteristic spectral markers. The classification model established by CNN algorithm demonstrates 95.0% in accuracy, 95.9% in sensitivity, and 93.5% in specificity for NPSLE diagnosis. The present work paves a new way achieving clinical label-free serum diagnosis of rheumatic diseases by enhanced Raman fingerprints with machine learning.
Palavras-chave
Texto completo:
1
Base de dados:
MEDLINE
Assunto principal:
Análise Espectral Raman
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Vasculite Associada ao Lúpus do Sistema Nervoso Central
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Aprendizado de Máquina
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Microesferas
Limite:
Humans
Idioma:
En
Revista:
Biosens Bioelectron
Assunto da revista:
BIOTECNOLOGIA
Ano de publicação:
2024
Tipo de documento:
Article
País de afiliação:
China