Salivary Molecular Spectroscopy with Machine Learning Algorithms for a Diagnostic Triage for Amelogenesis Imperfecta
Abstract
:1. Introduction
2. Results
Blood Plasma Infrared Spectroscopy
3. Discussion
4. Materials and Methods
4.1. Study Design
4.2. Saliva Collection
4.3. Chemical Profile of Unstimulated Saliva by ATR-FTIR Spectroscopy
4.4. Chemometric Analysis
4.5. Spectra Data Evaluation Procedures
4.6. Statistical Analysis for Epidemiological Characteristics
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
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Algorithm (Spectral Area) | Pre-Processing | Sensitivity | Specificity | Accuracy |
---|---|---|---|---|
Linear Discriminant Analysis (LDA) 1800–900 cm−1 | rb + amide I * | 82% | 64% | 72% |
Savitzky–Golay | 64% | 57% | 60% | |
Random forest 1800–900 cm−1 | rb + amide I * | 54% | 50% | 52% |
Savitzky–Golay | 64% | 79% | 72% | |
Supporting Vector Machine (SVM) 1800–900 cm−1 | rb + amide I * | 100% | 79% | 88% |
Savitzky–Golay | 73% | 71% | 72% |
Selected Vibrational Mode | Tentative Assignment | Type of Potential Source |
---|---|---|
1017 cm−1 | DNA | DNA |
1015 cm−1 | Antisymmetric stretching mode of PO4 tetrahedra | Hydroxyapatite |
1013 cm−1 | Antisymmetric stretching mode of PO4 tetrahedra | Hydroxyapatite |
1011 cm−1 | Antisymmetric stretching mode of PO4 tetrahedra | Hydroxyapatite |
1010 cm−1 | Stretching C-O deoxyribose | Carbohydrates |
1008 cm−1 | C = C torsion | Proteins |
1006 cm−1 | Sugar moieties from glycoproteins | Glycosylated proteins |
1004 cm−1 | Sugar moieties from glycoproteins | Glycosylated proteins |
1002 cm−1 | Stretching C-O deoxyribose | Carbohydrates |
980 cm−1 | OCH3 (polysaccharides) | Carbohydrates |
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Avelar, F.M.; Lanza, C.R.M.; Bernardino, S.S.; Garcia-Junior, M.A.; Martins, M.M.; Carneiro, M.G.; de Azevedo, V.A.C.; Sabino-Silva, R. Salivary Molecular Spectroscopy with Machine Learning Algorithms for a Diagnostic Triage for Amelogenesis Imperfecta. Int. J. Mol. Sci. 2024, 25, 9464. https://doi.org/10.3390/ijms25179464
Avelar FM, Lanza CRM, Bernardino SS, Garcia-Junior MA, Martins MM, Carneiro MG, de Azevedo VAC, Sabino-Silva R. Salivary Molecular Spectroscopy with Machine Learning Algorithms for a Diagnostic Triage for Amelogenesis Imperfecta. International Journal of Molecular Sciences. 2024; 25(17):9464. https://doi.org/10.3390/ijms25179464
Chicago/Turabian StyleAvelar, Felipe Morando, Célia Regina Moreira Lanza, Sttephany Silva Bernardino, Marcelo Augusto Garcia-Junior, Mario Machado Martins, Murillo Guimarães Carneiro, Vasco Ariston Carvalho de Azevedo, and Robinson Sabino-Silva. 2024. "Salivary Molecular Spectroscopy with Machine Learning Algorithms for a Diagnostic Triage for Amelogenesis Imperfecta" International Journal of Molecular Sciences 25, no. 17: 9464. https://doi.org/10.3390/ijms25179464