Diagnostic Strategies for Brain Doping in an Animal Model via Quantitative Analysis of Neurochemicals

Authors
CHO, YOESEPHSEONGEUN, JEONLEE, YEJINHana, ParkYinglan XuJEON, Mi jinJUNG, SUN MIKim, Min youngChin, AhlimYoon, Sang SunSON, Jung hyun
Issue Date
2023-07
Publisher
MDPI AG
Citation
Separations, v.10, no.7
Abstract
Brain doping is a novel form of doping that involves stimulating specific brain regions to enhance sports performance. However, to the best of our knowledge, there is currently no established provision or detection method for it. As brain stimulation ultimately induces alterations in neurochemical concentrations, this study aimed to develop a diagnostic strategy for brain doping. We successfully developed and validated a sensitive simultaneous analysis method for 23 neurochemicals present in urine. Simple derivatization was employed to overcome ionization efficiency, enabling the effective detection of all the target compounds within 5 min. Additionally, we developed an animal model system using rats to replicate brain-doping scenarios and establish a diagnostic strategy. Behavior tests confirmed improved sports performance in the brain stimulation group. By examining changes in the distribution patterns of the target substances in urine samples, we observed that neurochemicals could be used as potential biomarkers for brain-doping diagnosis. The developed method allows the effective simultaneous analysis of multiple neurochemicals in biological samples and is expected to have various applications, including doping control. Thus, changes in the distribution pattern of neurochemicals could serve as a basis for brain-doping diagnosis.
Keywords
DIRECT-CURRENT STIMULATION; HUMAN MOTOR CORTEX; LIQUID-CHROMATOGRAPHY; NERVOUS-SYSTEM; PRECOLUMN DERIVATIZATION; VANILLYLMANDELIC ACID; PARKINSONS-DISEASE; HUMAN PLASMA; LC-MS/MS; NEUROTRANSMITTERS; brain doping; neurochemicals; liquid chromatography-mass spectrometry; animal model system; doping diagnosis
ISSN
2297-8739
URI
https://pubs.kist.re.kr/handle/201004/79878
DOI
10.3390/separations10070413
Appears in Collections:
KIST Article > 2023
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