glyceryl-2-arachidonate and Cognitive-Dysfunction

glyceryl-2-arachidonate has been researched along with Cognitive-Dysfunction* in 1 studies

Other Studies

1 other study(ies) available for glyceryl-2-arachidonate and Cognitive-Dysfunction

ArticleYear
NO2 inhalation promotes Alzheimer's disease-like progression: cyclooxygenase-2-derived prostaglandin E2 modulation and monoacylglycerol lipase inhibition-targeted medication.
    Scientific reports, 2016, Mar-01, Volume: 6

    Air pollution has been reported to be associated with increased risks of cognitive impairment and neurodegenerative diseases. Because NO2 is a typical primary air pollutant and an important contributor to secondary aerosols, NO2-induced neuronal functional abnormalities have attracted greater attention, but the available experimental evidence, modulating mechanisms, and targeting medications remain ambiguous. In this study, we exposed C57BL/6J and APP/PS1 mice to dynamic NO2 inhalation and found for the first time that NO2 inhalation caused deterioration of spatial learning and memory, aggravated amyloid β42 (Aβ42) accumulation, and promoted pathological abnormalities and cognitive defects related to Alzheimer's disease (AD). The microarray and bioinformation data showed that the cyclooxygenase-2 (COX-2)-mediated arachidonic acid (AA) metabolism of prostaglandin E2 (PGE2) played a key role in modulating this aggravation. Furthermore, increasing endocannabinoid 2-arachidonoylglycerol (2-AG) by inhibiting monoacylglycerol lipase (MAGL) prevented PGE2 production, neuroinflammation-associated Aβ42 accumulation, and neurodegeneration, indicating a therapeutic target for relieving cognitive impairment caused by NO2 exposure.

    Topics: Air Pollution; Alzheimer Disease; Amyloid beta-Peptides; Animals; Arachidonic Acid; Arachidonic Acids; Chromatography, Liquid; Cognitive Dysfunction; Cyclooxygenase 2; Dinoprostone; Endocannabinoids; Glycerides; Mice; Mice, Inbred C57BL; Mice, Transgenic; Monoacylglycerol Lipases; Nitrogen Dioxide; Peptide Fragments; Spatial Learning; Tandem Mass Spectrometry

2016