Effect of the Aqueous Extract of Lantana grisebachii Stuck Against Bioaccumulated Arsenic-Induced Oxidative and Lipid Dysfunction in Rat Splenocytes.
Sabina I Ramos ElizagarayPatricia L QuirogaRoberto D PérezCarlos SosaCarlos A PérezGuillermina A BongiovanniElio Andrés SoriaPublished in: Journal of dietary supplements (2018)
Arsenic (As) is a worldwide immunotoxic agent that is in contaminated waters and consumed by mammals. Phytotherapy may counteract its harmful effects. Lantana grisebachii Stuck (LG, Verbenaceae) and its extract are proposed as protective, given vvits in vitro bioactivity. The aim was to determine the protective capacity of the aqueous LG extract on splenocytes exposed in vivo to arsenic. Splenocytes were obtained from an arsenicosis model (Wistar rats consuming orally 0 [control; C] or 5 mg/Kg/d of As) that received 0-100 mg/Kg/d of LG extract for 30 days. As content (total reflection X-ray fluorescence), fatty acid profile (gas chromatography), γ-glutamyl transpeptidase activity (Szasz method), peroxides (xylenol orange-based assay), and nitrites (Griess reaction) were then assayed in viable splenocytes. Data were analyzed with ANOVA and the Tukey's test (p < .05). It was observed that the splenocytes contained 2.2 mg/Kg of this elemental arsenic. With γ-glutamyl transpeptidase inhibition and consequent triggering of hydroperoxides (p < .05), it was observed to increase saturated fatty acids and alter lipid profiles. LG treatment avoided damaging effects with values similar to unexposed C (p < .05), and cellular arsenic concentration (p < .0001). In conclusion, the aqueous extract of L. grisebachii counteracted arsenic toxicity in rat splenocytes by preventing its cellular accumulation and induction of lipid and redox disturbances, which may impair immune function.
Keyphrases
- drinking water
- fatty acid
- oxidative stress
- heavy metals
- diabetic rats
- anti inflammatory
- gas chromatography
- mass spectrometry
- ionic liquid
- risk assessment
- tandem mass spectrometry
- high throughput
- magnetic resonance imaging
- machine learning
- single molecule
- electronic health record
- high glucose
- deep learning
- endothelial cells
- single cell
- artificial intelligence