Effects of propolis, caffeic acid phenethyl ester, and pollen on renal injury in hypertensive rat: An experimental and theoretical approach.
Ramin Ekhteiari SalmasMehmet Fuat GulhanSerdar DurdagiEngin SahnaHuda I AbdullahZeliha SelamogluPublished in: Cell biochemistry and function (2017)
The objective of this study was to evaluate the antioxidant effects of propolis, caffeic acid phenethyl ester (CAPE; active compound in propolis), and pollen on biochemical oxidative stress biomarkers in rat kidney tissue inhibited by Nω -nitro-L-arginine methyl ester (L-NAME). The biomarkers evaluated were paraoxonase (PON1), oxidative stress index (OSI), total antioxidant status (TAS), total oxidant status (TOS), asymmetric dimethylarginine (ADMA), and nuclear factor kappa B (NF-κB). TAS levels and PON1 activity were significantly decreased in kidney tissue samples in the L-NAME-treated group (P < 0.05). The levels of TAS and PONI were higher in the L-NAME plus propolis, CAPE, and pollen groups compared with the L-NAME-treated group. TOS, ADMA, and NF-κB levels were significantly increased in the kidney tissue samples of the L-NAME-treated group (P < 0.05). However, these parameters were significantly lower in the L-NAME plus propolis, CAPE, and pollen groups (P < 0.05) compared with rats administered L-NAME alone (P < 0.05). Furthermore, the binding energy of CAPE within catalytic domain of glutathione reductase (GR) enzyme as well as its inhibitory mechanism was determined using molecular modeling approaches. In conclusion, experimental and theoretical data suggested that oxidative alterations occurring in the kidney tissue of chronic hypertensive rats may be prevented via active compound of propolis, CAPE administration.
Keyphrases
- oxidative stress
- south africa
- nuclear factor
- toll like receptor
- dna damage
- diabetic rats
- signaling pathway
- ischemia reperfusion injury
- induced apoptosis
- blood pressure
- anti inflammatory
- immune response
- nitric oxide
- newly diagnosed
- cell proliferation
- transcription factor
- deep learning
- artificial intelligence
- heat stress
- inflammatory response