Caries detection analysis in human saliva alpha amylase

Abstract

Human saliva has been studied as a potential diagnostic tool to detect various types of diseases including dental caries. Caries is a multifactorial disease that occurs due to imbalance of host, environmental and microorganism factor. Salivary alpha-amylase direct relationship with caries activity makes it an important biomarker from host-related factor. This work is focused on the caries host predictor detection to identify the patient caries risk group using saliva. Early detection of this biomarker can help the clinicians to detect early risk of caries occurrence before irreversible damage occurs. The salivary alpha-amylase is detected at 282 nm wavelength for all samples. The result shows a significant increase of absorption spectrum level of alpha-amylase in samples of caries group compared to healthy patient without caries. The absorption spectrum data is further investigated using chemo-metric analysis. The spectrum measurement dataset is analyzed using Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) method. The score plot is able to show a clustering patent to distinguish a healthy and caries group samples at 95.79% confident level. This study has shown that ultraviolet absorption spectroscopy coupled with Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) method can be used to identify the salivary biomarker for caries risk determination.