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. 2022 Aug 20:20:4542-4548.
doi: 10.1016/j.csbj.2022.08.038. eCollection 2022.

Attenuated total reflection FTIR dataset for identification of type 2 diabetes using saliva

Miguel Sanchez-Brito  1   2 , Gustavo J Vazquez-Zapien  3 , Francisco J Luna-Rosas  1 , Ricardo Mendoza-Gonzalez  1 , Julio C Martinez-Romo  1 , Monica M Mata-Miranda  3
Affiliations

Attenuated total reflection FTIR dataset for identification of type 2 diabetes using saliva

Miguel Sanchez-Brito et al. Comput Struct Biotechnol J. .

Abstract

Diabetes is one of the top 5 non-communicable diseases that occur worldwide according to the World Health Organization. Despite not being a fatal disease, a late diagnosis as well as poor control can cause a fatal outcome, because of that, several studies have been carried out with the aim of proposing additional techniques to the gold standard to assist in the diagnosis and control of this disease in a non-invasive way. Considering the above, and in order to provide a solid starting point for future researches, we share a primary research dataset with 1040 saliva samples obtained by Fourier Transform Infrared Spectroscopy considering the Attenuated Total Reflectance method. Database include: gender, age, individuals (patients) with/without diabetes, the glucose value, and the result to the A1C test for the diabetic population. We believe that sharing dataset as is could increase experimentation, research, and analysis of spectra through different strategies broaden its range of applicability by chemists, doctors, physicists, computer scientists, among others, to identify the effects that the virus causes in the body and to propose possible clinical treatments as well as to develop devices that allow us to assist in the characterization of possible carriers.

Keywords: A1C Test; Attenuated total reflection FTIR; Dataset; Diabetes; Glucose; Saliva.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Gender and age distribution of the groups studied.
Fig. 2
Fig. 2
Distribution of glucose and hemoglobin values recorded for diabetic patients.
Fig. 3
Fig. 3
Mean spectra of populations with and without type 2 diabetes (red and blue, respectively). The dotted lines involve adding and subtracting one standard deviation from the mean. In the third figure, 20 spectra of the control group (blue) are contrasted against 20 spectra of the diabetes group (red). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 4
Fig. 4
Behavior of the means of the glucose and hemoglobin groups.
See this image and copyright information in PMC

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