Phytochemical analysis of Cistus salviifolius leaves and their anti-diabetic potential: In vitro and in vivo evaluation in alloxan-induced diabetic mice
Diabetes and its associated complications arise from prolonged increased blood sugar levels cause significant oxidative stress and the production of advanced glycation end products, which are the root causes of diabetes and its accompanying problems. However, in the search for novel therapies, particularly those for diabetes, medicinal plants still hold promise. Our study used alloxan-induced diabetic mice to investigate the anti-diabetic and antioxidant effects of Cistus salviifolius leaves extract. We assessed both methanolic (80 %) in vitro, paying particular attention to their phytochemical makeup and antioxidant capacity. Furthermore, in order to quantify their antiglycation activities, we studied their ability to inhibit AGEs and Amadori products. In vitro enzymatic assays of α-glucosidase and α-amylase inhibition were used to measure the antidiabetic effects, and validation was carried out using in vivo diabetic mice induced with alloxan. Additionally, we examined how methanolic extract administration affected the body weight and blood glucose levels of diabetic mice. The methanolic extract had notable antiglycation, enzyme inhibition, and antioxidant properties. It was particularly rich in phenolic components. Oral treatment of Cistus salviifolius leaves extract at doses of 250 mg/kg as a high dose and also a low dose of 150 mg/kg each day (3 weeks) produced hypoglycemic effects compared to the reference drug, glibenclamide (10 mg/kg). Furthermore, in comparison to the diabetic control group, the extract dramatically increased the antioxidant and glycolysis enzyme effect in the diabetic mice's spleen, liver and kidney. These results highlight the potential of C. salviifolius leaves extract as a substitute for therapy for managing diabetes by reducing hyperglycemia and oxidative damage.
Publication Details
- Journal
- Food Chemistry Advances
- Published
- 2025-10-12
- DOI
- https://doi.org/10.1016/j.focha.2025.101134
- Primary Topic
- Power Systems Fault Detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00