Decoding myasthenia gravis: advanced diagnosis with infrared spectroscopy and machine learning
Yükleniyor...
Tarih
2024
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Myasthenia Gravis (MG) is a rare neurological disease. Although there are intensive efforts, the underlying mechanism of MG still has not been fully elucidated, and early diagnosis is still a question mark. Diagnostic paraclinical tests are also time-consuming, burden patients financially, and sometimes all test results can be negative. Therefore, rapid, cost-effective novel methods are essential for the early accurate diagnosis of MG. Here, we aimed to determine MG-induced spectral biomarkers from blood serum using infrared spectroscopy. Furthermore, infrared spectroscopy coupled with multivariate analysis methods e.g., principal component analysis (PCA), support vector machine (SVM), discriminant analysis and Neural Network Classifier were used for rapid MG diagnosis. The detailed spectral characterization studies revealed significant increases in lipid peroxidation; saturated lipid, protein, and DNA concentrations; protein phosphorylation; PO2-asym + sym /protein and PO2-sym/lipid ratios; as well as structural changes in protein with a significant decrease in lipid dynamics. All these spectral parameters can be used as biomarkers for MG diagnosis and also in MG therapy. Furthermore, MG was diagnosed with 100% accuracy, sensitivity and specificity values by infrared spectroscopy coupled with multivariate analysis methods. In conclusion, FTIR spectroscopy coupled with machine learning technology is advancing towards clinical translation as a rapid, low-cost, sensitive novel approach for MG diagnosis.
Açıklama
Anahtar Kelimeler
Myasthenia Gravis (MG), Neurological Diseases, Principal Component Analysis (PCA)
Kaynak
Scientific Reports
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
14
Sayı
1
Künye
Severcan, F., Özyurt, İ., Doğan, A., Severcan, M., Gurbanov, R., Küçükcankurt, F., Elibol, B., Tiftikçioğlu, İ., Gürsoy, E., Yangın, M. N., Zorlu, Y. (2024). Decoding myasthenia gravis: advanced diagnosis with infrared spectroscopy and machine learning. Scientific Reports, 14(1). 10.1038/s41598-024-66501-3
