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	DETECTION OF DIABETES MELLITUS TYPE II BY INFRARED SPECTROSCOPY AND MULTIVARIATE ANALYSIS</div>

Nosenko Tatiana N. , Sitnikova Vera E, Olekhnovich Roman O, Uspenskaya Maya Valerievna

doi:10.17586/2226-1494-2019-19-2-202-208

2019 , VOLUME 19, NUMBER 2 ( MARCH–APRIL )

ISSN 2226-1494 (print), ISSN 2500-0373 (online)

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Nikiforov
Vladimir O.
D.Sc., Prof.

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doi: 10.17586/2226-1494-2019-19-2-202-208

DETECTION OF DIABETES MELLITUS TYPE II BY INFRARED SPECTROSCOPY AND MULTIVARIATE ANALYSIS

T. N. Nosenko, V. E. Sitnikova, R. O. Olekhnovich, M. V. Uspenskaya

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Article in Russian

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Nosenko T.N., Sitnikova V.E., Olekhnovich R.O.,Uspenskaya M.V. Detection of diabetes mellitus type II by infrared spectroscopy and multivariate analysis. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2019, vol. 19, no. 2, pp. 202–208 (in Russian). doi: 10.17586/2226-1494-2019-19-2-202-208

Abstract

The paper presents detection method for one of the most common diseases. Diabetes mellitus is a group of metabolic disorders in which blood sugar level rises over a long period. Type II diabetes begins with insulin resistance, a condition when cells do not respond properly to insulin. Type II diabetes accounts for about 90 % of all diagnosed diabetes cases. Therefore, the development of new methods for diagnosing is relevant. We applied the method of IR-spectroscopy combined with multivariate analysis for blood serum analysis. The research is based on serum samples from 44 patients with diabetes and an observational group of 30 healthy donors. Cluster analysis, projection on latent structures, principal component analysis is used to differentiate groups of healthy donors and patients with diabetes. Each of the three presented methods gives the best results when the first derivative of the spectra is considered in the whole range of the spectrum. Cluster analysis, according to the procedure performed, gives the sensitivity of 100% and the specificity of 95.8 % for the considered sample. Principal Component Analysis provides a visual separation of the sample into groups of healthy donors and patients with diabetes mellitus. When analyzing this sample, using the procedure, the sensitivity was 100 % and the specificity of the analysis was 96.6 %.

Keywords: diabetes mellitus, IR spectroscopy, multivariate analysis, serum, cluster analysis, PCA, PLS

References

McNeillJ.H.,Rodrigues B. The diabetic heart: metabolic causes for the development of cardiomyopathy. Cardiovascular Research, 1996, vol. 26, no. 10, pp. 913–922.doi: 10.1093/cvr/26.10.913
Pyorla K., Laasko M., Uusitupa M. Diabetes and atherosclerosis: an epidemiological view. Diabetes / Metabolism Reviews, 1987, vol. 3, no. 2, pp. 463–524.doi: 10.1002/dmr.5610030206
DhallaN.S., Pierce G.N., Innes I.R., Beamish R.E. Pathogenesis of cardiac dysfunction in diabetes mellitus. Canadian Journal of Cardiology,1985, vol. 1, p. 26.
Barer R., Cole A.R., Thompson H.W. Infra-red spectroscopy with the reflecting microscope in physics, chemistry and biology. Nature, 1949, vol. 163, no. 4136, pp. 198–201.doi: 10.1038/163198a0
Petrich W.,Staib A., Otto M.,Somorjai R.L. Correlation between the state of health of blood donors and the corresponding mid-infrared spectra of the serum. Vibrational Spectroscopy, 2002, vol. 28, pp. 117–129.doi: 10.1016/s0924-2031(01)00151-5
Khudyakov E.S., Kochelaev E.A., Volchek A.O., Kirsanov D.O., Jahatspanian I.E. Application of chemometrics for analysis of bioaerosols by flow-optical method. Scientific and Technical Journal of Information Technologies, Mechanics and Optics, 2016, vol. 16, no. 1, pp. 30–38. doi: 10.17586/2226-1494-2016-16-1-30-38
Juqiang L.,Zufang H., Jing W.Raman spectroscopy of human hemoglobin for diabetes detection. Journal of Innovative Optical Health Sciences, 2014, vol. 7, no. 1, p. 1350051. doi: 10.1142/s179354581350051x
Kan-ZhiL.,RatnaB., Henry H.M.Infrared spectroscopic study of diabetic platelets. Vibrational Spectroscopy, 2002, vol. 28, no. 1, pp. 131–136.doi: 10.1016/s0924-2031(01)00163-1
Nord C., Eriksson M., Dicker A., Eriksson A., Grong E.,Ilegems E.,Marvik R., Kulseng B., Berggren P., Gorzsas A., Ahlgren U.Biochemical profiling of diabetes disease progression by multivariate vibrational microspectroscopy of the pancreas. Scientific Reports, 2017, vol. 7,no. 1, art. 6646. doi: 10.1038/s41598-017-07015-z
Feride S.,Kaptan N., Turan B.Fourier transform infrared spectroscopic studies of diabetic rat heart crude membranes. Spectroscopy, 2003, vol. 17, no. 2-3, pp. 569–577.
Mediani A.,Abas F., Maulidiani M.,Abu Bakar Sajak A., Alfi Kh., Chin P.T.,Intan SafinarI.,Khozirah Sh.,AminI., Lajis N.H. Metabolomic analysis and biochemical changes in the urine and serum of strep to zotocin-induced normal- and obese-diabetic rats. Journal of Physiology and Biochemistry,2018,vol. 74,no. 3,pp. 403–416. doi: 10.1007/s13105-018-0631-3
Srividya P., Renuga Devi T.S., Gunasekaran S.FTIR spectral study on diabetic blood samples-monotherapy and combination therapy. OJP, 2012, vol. 4, pp. 17–26.
Esbensen K.H. Multivariate Data Analysis in Practice. 5th ed. CAMO Software AS: Oslo, Norway, 2001, 594 p.
Mitchell A.L.,GajjarK.B.,TheophilouG., Martin F.L., Martin H. Vibrational spectroscopy of biofluids for disease screening or diagnosis: translation from the laboratory to a clinical setting. Journal of Biophotonics, 2014, vol. 7, no. 3–4, pp. 153–165. doi: 10.1002/jbio.201400018

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