Preview

Journal Biomed

Advanced search

Analytical Evaluation of Treating Depression in Animal Models by Quantitative Pharmaco-EEG

https://doi.org/10.33647/2074-5982-16-3-43-47

Abstract

The treatment of depressive disorders remains a relevant problem in medical practice. Depression is frequently treated by selective serotonin reuptake inhibitors (SSRIs), among which fluoxetine is one of the most popular drugs. In order to improve the pharmacotherapy of depression, combinations of SSRIs with other pharmaceutical groups, e.g. epiphyseal hormone melatonin, are practiced. The key aim in improving the quality of depression treatment remains the search and development of more powerful and fast-acting antidepressants. In this context, research attention has recently been focused on valdoxan, an agonist of melatonin MT1 and MT2 and serotonin 5-HT2c receptors. Quantitative pharmaco-EEG is the most efficient method for evaluating the efficacy of the pharmacotherapy of mental pathologies. In this study, EEG rhythms of rats with experimental depression were analyzed following the administration of the aforementioned drugs. It was found that valdoxan, compared to fluoxetine and its combination with melaxen, contributes to the fastest normalization of the brain’s bioelectric activity in animals. In particular, this drug contributes to a significant increase in the activity of the EEG theta rhythm, which dominates in animals in the norm.

About the Authors

O. M. Kudelina
Rostov State Medical University of the Ministry of Health Care of Russia
Russian Federation

Oksana M. Kudelina, Cand. Sci. (Med.)

344022, Rostov-on-Don, Nakhichevansky lane, 29



A. V. Safronenko
Rostov State Medical University of the Ministry of Health Care of Russia
Russian Federation

Andrey V. Safronenko, Dr. Sci. (Med.), Assoc. Prof.

344022, Rostov-on-Don, Nakhichevansky lane, 29



Yu. S. Maklyakov
Rostov State Medical University of the Ministry of Health Care of Russia
Russian Federation

Yuri S. Maklyakov, Dr. Sci. (Med.), Prof.

344022, Rostov-on-Don, Nakhichevansky lane, 29



E. V. Gantsgorn
Rostov State Medical University of the Ministry of Health Care of Russia
Russian Federation

Elena V. Gantsgorn, Cand. Sci. (Med.)

344022, Rostov-on-Don, Nakhichevansky lane, 29



N. M. Morozov
Rostov State Medical University of the Ministry of Health Care of Russia
Russian Federation

Nikolay M. Morozov, Cand. Sci. (Med.), Assoc. Prof.

344022, Rostov-on-Don, Nakhichevansky lane, 29



M. A. Jabr
Rostov State Medical University of the Ministry of Health Care of Russia
Russian Federation

Mohamad A. Jabr

344022, Rostov-on-Don, Nakhichevansky lane, 29



References

1. Arushanyan E.B. Melatonin kak lechebnoe sredstvo: sostoyanie voprosa segodnya i gryadushie perspektivi [Melatonin as a treatment: state of the issue today and future prospects]. Eksperimental’naia i klinicheskaia farmakologiia [Experimental and clinical pharmacology]. 2014;77(6):39–44. (In Russian).

2. Bochkarev V.K. Kolichestvennaya farmakoelektroencephalographiya v issledovaniyah psichotropnyh sredstv [Quantitative pharmacoelectroencephalography in research of psychotropic drugs]. Moscow: Pharmateka Publ., 2007. P. 28–32. (In Russian).

3. Bykov Yu.V., Bekker R.A. Agomelatin; rasshirennye pocazaniya v psichiatrii, nevrologii i narcologii (obzor literatury) [Agomelatine: extended indications for its use in psychiatry, neurology and substance abuse medicine]. Psichiatriya i psichopharmacoterapiya [Psychiatry and Psychopharmacotherapy]. 2018;20(3–4):4–18. (In Russian).

4. http://www.who.int/mediacentre/factsheets/fs369/ru/

5. Wenthur C.J., Bennett M.R., Lindsley C.W. Classics in chemical neuroscience: fluoxetine (prozac). ACS Chem. Neurosci. 2014;5(1):14–23.


Review

For citations:


Kudelina O.M., Safronenko A.V., Maklyakov Yu.S., Gantsgorn E.V., Morozov N.M., Jabr M.A. Analytical Evaluation of Treating Depression in Animal Models by Quantitative Pharmaco-EEG. Journal Biomed. 2020;16(3):43-47. (In Russ.) https://doi.org/10.33647/2074-5982-16-3-43-47

Views: 524


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2074-5982 (Print)
ISSN 2713-0428 (Online)