Metabolism Determination By Soft Computing Methods From Breath Molecules

This article was retracted on October 18, 2023. https://dergipark.org.tr/en/pub/saufenbilder/article/1371123

Abstract

The breath analysis is a non-invasive risk-free and painless method used to diagnose specific diseases. Since the breath analysis method is a new study field than the other methods, there are many unsettled standards and unknown parameters. Numerous complex metabolisms are constantly working in the human body. Therefore, there are numerous unknown molecular relationships. ANN can produce solutions in these unexplained situations. In our pilot study, breath of 19 healthy people has been analyzed. The TD / GC-MS method, which is an analytical method of breath analysis, has been used to detect molecules in the breaths. Using soft computing methods to the results of the 19 breath samples, the relation between fermentation and carbon hydrate metabolism has been associated with breath analysis technique. The results indicated that, there can be a relationship between these metabolisms. There must be done more studies for the exact results.

Keywords

• Breath analysis
• soft computing
• acetone
• hexanal
• butanol

References

1. [1] A. Prabhakar,A. Quach,D. Wang,H. Zhang, M. Terrera, and D. Jackemeyer “Breath acetone as biomarker for lipid oxidation and early ketone detection,” Glob. J. Obesity, Diabetes Metab. Syndr., vol. 1, no. 1, pp. 12–19, 2014.
2. [2] W. Li, Y. Liu, X. Lu, Y. Huang, Y. Liu., and S. Cheng, “A cross-sectional study of breath acetone based on diabetic metabolic disorders,” J. Breath Res., vol. 9, no. 1, p. 16005, 2015.
3. [3] Z. Wang and C. Wang, “Is breath acetone a biomarker of diabetes? A historical review on breath acetone measurements,” J. Breath Res., vol. 7, no. 3, p. 37109, 2013.
4. [4] S. A. Masino and J. M. Rho, “Mechanisms of ketogenic diet action,” Epilepsia, vol. 51, no.. 5, p. 85, 2010.
5. [5] J. W. Wheless, “History of the ketogenic diet,” in Epilepsia, 2008, vol. 49, no. SUPPL. 8, pp. 3–5.
6. [6] C. N. Tassopoulos, D. Barnett, and T. R. Fraser, “Breath-acetone and blood-sugar measurements in diabetes,” Lancet, vol. 293, no. 7609, pp. 1282–1286, 1969.
7. [7] O. E. Owen, V. E. Trapp, C. L. Skutches, M. A. Mozzoli, R. D. Hoeldtke, G. Boden, and G. A.Reichard,., “Acetone metabolism during diabetic ketoacidosis,” Diabetes, vol. 31, no. 3, pp. 242–248, 1982.
8. [8] D. Smith, P. Spanel, and S. Davies, “Trace gases in breath of healthy volunteers when fasting and after a protein-calorie meal: a preliminary study,” J. Appl. Physiol., vol. 87, no. 5, pp. 1584–1588, 1999.

9. [9] M. Righettoni, A. Schmid, A. Amann, and S. E. Pratsinis, “Correlations between blood glucose and breath components from portable gas sensors and PTR-TOF-MS,” J. Breath Res., vol. 7, no. 3, p. 37110, 2013.
10. [10] D. T. Jones and D. R. Woods, “Acetone-butanol fermentation revisited.,” Microbiol. Rev., vol. 50, no. 4, p. 484, 1986.
11. [11] C. C. Pamela, A. H. Richard, and R. F. Denise, “Lippincotts illustrated reviews biochemistry.” Lippincott Williams and Wilkins, Philadelphia, 2005.
12. [12] M. Libardoni, P. Stevens, J. H. Waite, and R. Sacks, “Analysis of human breath samples with a multi-bed sorption trap and comprehensive two-dimensional gas chromatography (GC× GC),” J. Chromatogr. B, vol. 842, no. 1, pp. 13–21, 2006.
13. [13] W. Filipiak, A.Sponring, M. Baur, C. Ager, A.Filipiak, H. Wiesenhofer, M. Nagl, J. Troppmair, and A. Amann, “Characterization of volatile metabolites taken up by or released from Streptococcus pneumoniae and Haemophilus influenzae by using GC-MS,” Microbiology, vol. 158, no. 12, pp. 3044–3053, 2012.
14. [14] I. Kushch K. Schwarz, L. Schwentner, B. Baumann, A. Dzien, and Smith D.., “Compounds enhanced in a mass spectrometric profile of smokers’ exhaled breath versus non-smokers as determined in a pilot study using PTR-MS,” J. Breath Res., vol. 2, no. 2, p. 26002, 2008.
15. [15] J.-E. Huh B.-K. Seo, Y.-H. Baek, S. Lee, J.-D. Lee, D.-Y. Choi, D.-S. Park., “Standardized butanol fraction of WIN-34B suppresses cartilage destruction via inhibited production of matrix metalloproteinase and inflammatory mediator in osteoarthritis human cartilage explants culture and chondrocytes,” BMC Complement. Altern. Med., vol. 12, no. 1, p. 1, 2012.
16. [16] M. Gupta, S. Sasmal, and A. Mukherjee, “Therapeutic effects of acetone extract of saraca asoca seeds on rats with adjuvant-induced arthritis via attenuating inflammatory responses,” ISRN Rheumatol., vol. 2014, 2014.
17. [17] R. Paul, A. Choudhury, and A. Borah, “Cholesterol - A putative endogenous contributor towards Parkinson’s disease,” Neurochemistry International, vol. 90. pp. 125–133, 2015.
18. [18] C. J. Dillard and A. L. Tappel, “Lipid peroxidation products in biological tissues,” Free Radic. Biol. Med., vol. 7, no. 2, pp. 193–196, 1989.
19. [19] H. Orhan, “Analyses of representative biomarkers of exposure and effect by chromatographic, mass spectrometric, and nuclear magnetic resonance techniques: method development and application in life sciences,” J. Sep. Sci., vol. 30, no. 2, pp. 149–174, 2007.
20. [20] H. Esterbauer, R. J. Schaur, and H. Zollner, “Chemistry and biochemistry of 4-hydroxynonenal, malondialdehyde, and related aldehydes,” Free Radic. Biol. Med., vol. 11, no. 1, pp. 81–128, 1991.
21. [21] W. A Pryor, B. Das, and D. F. Church, “The ozonation of unsaturated fatty acids: aldehydes and hydrogen peroxide as products and possible mediators of ozone toxicity.,” Chem. Res. Toxicol., vol. 4, no. 3, pp. 341–348, 1991.
22. [22] M. Kinter, “Analytical technologies for lipid oxidation products analysis,” J. Chromatogr. B Biomed. Sci. Appl., vol. 671, no. 1, pp. 223–236, 1995.
23. [23] S. Demirci, S. Kutluhan, M. Naziroǧlu, and A. C. Uǧuz, V. A. Yürekli, and K. Demirci, “Effects of selenium and topiramate on cytosolic Ca2+ influx and oxidative stress in neuronal PC12 cells,” Neurochem. Res., vol. 38, no. 1, pp. 90–97, 2013.
24. [24] D. E. Stanley, “Tietz Textbook of Clinical Chemistry,” JAMA J. Am. Med. Assoc., vol. 282, no. 3, pp. 283–283, 1999.
25. [25] İ. Akkuş, "Serbest radikaller ve fizyopatolojik etkileri". Mimoza yayınları, 1995.
26. [26] A. Higdon, A. R. Diers, J. Y. Oh, A. Landar, and V. M. Darley-Usmar, “Cell signalling by reactive lipid species: new concepts and molecular mechanisms.,” Biochem. J., vol. 442, no. 3, pp. 453–64, 2012.
27. [27] Ç. Elmas, "Yapay Sinir Ağları" Kuram, Mimari, Eğitim, Uygulama, Seçkin Yayıncılık, Ankara, 2003.
28. [28] H. Ergezer, M. Dikmen and E. Özdemir, "Yapay Sinir Ağları ve Tanıma Sistemleri" - PiVOLKA, vol 2, no. 6, pp. 14-17, 2003.
29. [29] H. Pirim, "Yapay Zeka". Journal of Yaşar University, pp. 81-93, 2006.
30. [30] İ, Gör, "Çok Katmanlı Algılayıcı Yapay Sinir Ağı ile Lineer Diferansiyel Denklem Sisteminin Çözümü". 18. Akademik Bilişim Konferansı, 30 Ocak-5 Şubat 2016, Adnan Menderes Üniversitesi, Aydın, 2016.
31. [31] K. Görgülü,, E. Arpaz, and Ö. Uysal,. Investigation of the effects of blasting design parameters and rock properties on blast-induced ground vibrations. Arab J Geosci., vol. 8, no. 4269, 2015.
32. [32] A.G. Yüksek, H. Bircan, M. Zontul, O. Kaynar, "Sivas İlinde Yapay Sinir Ağları İle Hava Kalitesi Modelinin Oluşturulması Üzerine Bir Uygulama", C.Ü. İktisadi ve İdari Bilimler Dergisi, vol. 8, no. 7, 2007.