Diagnosis of Periodontal Disease from Saliva Samples Using Fourier Transform Infrared Microscopy Coupled with Partial Least Squares Discriminant Analysis

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  • FUJII Satoshi
    Department of Bioscience and Bioinformatics, Kyushu Institute of Technology Research Center for Bio-microsensing Technology, Kyushu Institute of Technology
  • SATO Shinobu
    Research Center for Bio-microsensing Technology, Kyushu Institute of Technology Department of Applied Chemistry, Kyushu Institute of Technology
  • FUKUDA Keisuke
    Research Center for Bio-microsensing Technology, Kyushu Institute of Technology
  • OKINAGA Toshinori
    Division of Periodontology, Department of Oral Function, Kyushu Dental University, Department of Oral Function
  • ARIYOSHI Wataru
    Division of Periodontology, Department of Oral Function, Kyushu Dental University, Department of Oral Function
  • USUI Michihiko
    Division of Infections and Molecular Biology, Department of Health Promotion, Kyushu Dental University
  • NAKASHIMA Keisuke
    Division of Infections and Molecular Biology, Department of Health Promotion, Kyushu Dental University
  • NISHIHARA Tatsuji
    Division of Periodontology, Department of Oral Function, Kyushu Dental University, Department of Oral Function
  • TAKENAKA Shigeori
    Research Center for Bio-microsensing Technology, Kyushu Institute of Technology Department of Applied Chemistry, Kyushu Institute of Technology

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Abstract

Diagnosis of periodontal disease by Fourier transform infrared (FT-IR) microscopic technique was achieved for saliva samples. Twenty-two saliva samples, collected from 10 patients with periodontal disease and 12 normal volunteers, were pre-processed and analyzed by FT-IR microscopy. We found that the periodontal samples showed a larger raw IR spectrum than the control samples. In addition, the shape of the second derivative spectrum was clearly different between the periodontal and control samples. Furthermore, the amount of saliva content and the mixture ratio were different between the two samples. Partial least squares discriminant analysis was used for the discrimination of periodontal samples based on the second derivative spectrum. The leave-one-out cross-validation discrimination accuracy was 94.3%. Thus, these results show that periodontal disease may be diagnosed by analyzing saliva samples with FT-IR microscopy.

Journal

  • Analytical Sciences

    Analytical Sciences 32 (2), 225-231, 2016

    The Japan Society for Analytical Chemistry

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