JOURNAL OF CHILEAN CHEMICAL SOCIETY

Vol 64 No 3 (2019): Journal of the Chilean Chemical Society
Original Research Papers

APPLICATION OF RESPONSE SURFACE MODELING FOR OPTIMIZATION AND DETERMINATION OF MALONDIALDIALDEHYDE BY VORTEX-ASSISTED DISPERSIVE LIQUID-LIQUID MICROEXTRACTION AND GC-FID

Majid Mirmoghaddam
Department of Chemistry, Faculty of Sciences, University of Sistan and Baluchestan
Massoud Kaykhaii
Department of Chemistry, Faculty of Sciences, University of Sistan and Baluchestan
Mohammad Hashemi
Department of Biochemistry, School of Medicine, Zahedan University of Medical Sciences
Ahmad Jamali Keikha
Department of Mechanical Engineering, Faculty of Marine Engineering, Chabahar Maritime University
Sayyed Hossein Hashemi
Department of Marine Chemistry, Faculty of Marine Science, Chabahar Maritime University
Hossein Yahyavi
Department of Chemistry, Faculty of Sciences, University of Sistan and Baluchestan
Published October 30, 2019
Keywords
  • Malondialdehyde,
  • Vortex-assisted dispersive liquid-liquid microextraction,
  • Response surface methodology,
  • Human serum analysis,
  • GC-FID
How to Cite
Mirmoghaddam, M., Kaykhaii, M., Hashemi, M., Jamali Keikha, A., Hossein Hashemi, S., & Yahyavi, H. (2019). APPLICATION OF RESPONSE SURFACE MODELING FOR OPTIMIZATION AND DETERMINATION OF MALONDIALDIALDEHYDE BY VORTEX-ASSISTED DISPERSIVE LIQUID-LIQUID MICROEXTRACTION AND GC-FID. Journal of the Chilean Chemical Society, 64(3), 4531-4537. Retrieved from https://jcchems.com/index.php/JCCHEMS/article/view/1315

Abstract

An analytical method based on vortex-assisted dispersive liquid-liquid microextraction and gas chromatography-flame ionization detection is presented for the extraction and determination of malondialdehyde )MDA( in blood plasma of human. Various parameters affecting the extraction efficiency such as type and volume of extraction and dispersive solvents, vortex and centrifuge times, volume, ionic strength and pH of the sample solution were evaluated using, one-variable-at-a-time and response surface methodology. In order to optimize the MDA extraction and determination, seven factors in five- levels were used for design of experiments (DOE). Under optimum extraction condition, this method showed linear range of calibration curve between 10–1150 μg L-1. The detection limit of the proposed method was found to be 0.8 μg L-1 with a relative standard deviation better than 5.5% (n=10) for blood serum samples. Enrichment factor was calculated to be 175 fold and the total analysis time including microextraction was about 13 min. The method was successfully applied for the analysis of MDA in blood plasma of human.

69.jpg

References

1. Z. Singh, I. P. Karthigesu, R. Kaur, Iran J. Public. Health 43, 7, (2014).

2. M. Rosenblat, R. Coleman, M. Aviram, Atherosclerosis 163, 17, (2002).

3. I. Delimaris, E. Faviou, G. Antonakos, E. Stathopoulou, A. Zachari, Clin. Biochem. 40, 1129, (2007).

4. A. M. Domijan, J. Ralić, S. Radić Brkanac, L. Rumora, T. Žanić‐Grubišić, Biomed. Chromatogr. 29, 41, (2015).

5. K. -C. Hsu, P. -F. Hsu, Y. -C. Chen, H. -C. Lin, C. -C. Hung, P. -C. Chen, Y. -L. Huang, J. Chromatogr. B 1019, 112, (2016).

6. E. M. Gioti, Y. C. Fiamegos, D. C. Skalkos, C. D. Stalikas, J. Chromatogr. A 1152, 150, (2007).

7. D. Tsikas, S. Rothmann, J. Y. Schneider, M. -T. Suchy, A. Trettin, D. Modun, N. Stuke, N. Maassen, J. C. Frölich, J. Chromatogr. B 1019, 95, (2015).

8. B. Liu, Y. Qi, M. Li, Y. Gao, X. Chen, Z. -T. Wang, Chin. Sci. Bull. 12, 36, (2010).

9. D. W. Wilson, H. N. Metz, L. M. Graver, P. S. Rao, Clin. Chem. 43, 1982, (1997).

10. S. H. Hashemi, M. Kaykhaii, F. Tabehzar, J. Iran Chem. Soc. 13, 733, (2016).

11. H. Hashemi, M. Khajeh, M. Kaykhaii, Anal. Methods 5, 2778, (2013).

12. M. Khajeh, M. Kaykhaii, M. Mirmoghaddam, H. Hashemi, J. Environ. Anal. Chem. 89, 981, (2009).

13. H. Uslu, D. Datta, D. Santos, H. S. Bamufleh, C. Bayat, Chem. Engineer. J. 299, 342, (2016).

14. M. Kaykhaii, A. Khatibi, J. Iran Chem. Soc. 8, 374, (2011).

15. M. Kaykhaii, H. Yahyavi, M. Hashemi, M. R. Khoshroo, 408, 4907, (2016).

16. J. -L. Chen, Y. -J. Huang, C. -H. Pan, C. -W. Hu, M. -R. Chao, Free Radic. Biol. Med. 51, 1823, (2011).

17. H. -S. Shin, J. Chromatogr. B 877, 3707, (2009).

18. K. Fujioka, T. Shibamoto, J. Agric. Food Chem. 53, 4708, (2005).

19. R. Heydari, S. Zarabi, Anal. Methods 6, 8469, (2014).

20. J. Gañán, D. Pérez-Quintanilla, S. Morante-Zarcero, I. Sierra, J. Hazard. Mater. 260, 609, (2013).

21. A. Mehdinia, A. Ghassempour, H. Rafati, R. Heydari, Anal. Chem. Acta 587, 82, (2007).

22. M. Rezaee, Y. Assadi, M. -R. M. Hosseini, E. Aghaee, F. Ahmadi, S. Berijani, J. Chromatogr. A 1116, 1, (2006).

23. S. H. Hashemi, M. Kaykhaii, R. Dehvari, Current Chromatogr. 4, 1, (2017).

24. M. Nassiri, M. Kaykhaii, S. H. Hashemi, M. Sepahi, Iran. J. Chem. Chem. Eng. 37, 89, (2018).

25. M. Khajeh, M. Kaykhaii, S. H. Hashemi, M. Shakeri, J. Food Compos. Anal. 33, 32, (2014).

26. J. Vichapong, R. Burakham, S. Srijaranai, Talanta 117, 221, (2013).

27. E. Yiantzi, E. Psillakis, K. Tyrovola, N. Kalogerakis, Talanta 80, 2057 (2010).

28. V. Hosseinpour, M. Kazemeini, A. Mohammadrezaee, Appl. Catal. A 394, 166 (2011).

29. K. Yetilmezsoy, S. Demirel, R. J. Vanderbei, J. Hazard. Mater. 171, 551, (2009).

30. M. Mirmoghaddam, M. Kaykhaii, M. Hashemi, Anal. Methods 8, 2456 (2016).

31. J. Lovrić, M. Mesić, M. Macan, M. Koprivanac, M. Kelava, V. Bradamante, Periodicum biologorum 110, 63, (2008).

32. A. H. S. Muñoz, M. P. Puga, K. Wrobel, M. E. G. Sevilla, K. Wrobel, Microchimica Acta 148, 285 (2004).

Copyright @2019 | Designed by: Open Journal Systems Chile Logo Open Journal Systems Chile Support OJS, training, DOI, Indexing, Hosting OJS

Code under GNU license: OJS PKP