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Cerebral Lipid Dynamics in Chronic Cerebral Hypoperfusion Model by DESI-MS Imaging.

Authors :
Severiano DLR
Oliveira-Lima OC
Vasconcelos GA
Lemes Marques B
Almeida de Carvalho G
Freitas EMM
Xavier CH
Gomez MV
Pinheiro ACO
Gomez RS
Vaz BG
Pinto MCX
Source :
Neuroscience [Neuroscience] 2020 Feb 01; Vol. 426, pp. 1-12. Date of Electronic Publication: 2019 Nov 27.
Publication Year :
2020

Abstract

Vascular dementia (VD) is a major cognitive disorder originated from a blood flow disruption in the brain. This process leads to chronic cerebral ischemia that deeply affects neuronal tissues and lipid homeostasis. The understanding of cerebral lipid dynamics during chronic ischemia can reveal biomarkers and novel pharmacological targets for the treatment of VD. In this study, we used the Desorption Electrospray Ionization - imaging mass spectrometry (DESI-IMS) technique to map lipids in the rat brain tissues after bilateral common carotid artery occlusion (BCCAO) rat model of chronic cerebral hypoperfusion. The brain imaging enabled the detection of differences in lipids from ischemic and non-ischemic brains. The analysis demonstrated that arachidonic acid (ARA), docosahexaenoic acid (DHA), dihomo-γ-linolenic acid, hydroxyeicosatetraenoic (HETE)-Ala and glycerophosphoethanolamine levels were significantly reduced in the hippocampus and cortex of animals submitted to BCCAO model when compared to control animals. Decanoic acid was increased after 30 days of BCCAO model. Partial least squares discriminant analysis (PLS-DA) could discriminate between BCCAO group and the control group, in which γ-linolenic acid (m/z 277) ion and stearic acid (m/z 283) had the highest discrimination potential. Taken together, these findings indicate that lipid dynamics are altered in chronic ischemia-induced by BCCAO in rats and indicate potential biomarkers and pharmacological targets for VD.<br /> (Copyright © 2019 IBRO. Published by Elsevier Ltd. All rights reserved.)

Details

Language :
English
ISSN :
1873-7544
Volume :
426
Database :
MEDLINE
Journal :
Neuroscience
Publication Type :
Academic Journal
Accession number :
31785353
Full Text :
https://doi.org/10.1016/j.neuroscience.2019.11.014