Synergistic Neuroprotective Effects of Cortex of Albizia julibrissin Durazzini and Stems and Branches of Uncariae rhynchophylla (Miq.) Miq. in Models of 6-Hydroxydopamine-Induced Parkinson's Disease.
Аннотация
INTRODUCTION
Parkinson's disease (PD) is characterized by the progressive degeneration of dopaminergic neurons, leading to motor and non-motor symptoms. Current therapeutic options for PD have limited efficacy and cause significant side effects, necessitating the development of novel therapeutic strategies. In this study, we investigated the neuroprotective effects of the cortex of Albizia julibrissin Durazzini (AC) and stems and branches of Uncariae rhynchophylla (Miq.) Miq. (UR), individually and in combination, in cellular and animal models of PD.
METHODS
We evaluated the neuroprotective effects of the water extract of AC and UR individually in 6-hydroxydopamine (6-OHDA)-treated PC12 cells using the MTT assay. Combination index (CI) analysis was employed to determine the optimal AC:UR ratio for synergistic effects. The bioactivity of individual herbs and their optimized combination was assessed in 6-OHDA-lesioned mice through behavioral tests (pole, rotarod, and apomorphine-induced rotation) and immunohistochemical analysis of dopaminergic neurons in the striatum and substantia nigra pars compacta.
RESULTS
Both herbal remedies exhibited neuroprotective effects in 6-OHDA-treated PC12 cells. A 2:1 ratio of AC-to-UR yielded the most potent synergistic neuroprotective effect (CI = 0.38459), significantly improving motor function in 6-OHDA-lesioned mice. Immunohistochemical analysis revealed that the 2:1 AC-to-UR combination significantly protected dopaminergic neurons against 6-OHDA-induced neurodegeneration with efficacy comparable to or exceeding standard levodopa/benserazide treatment.
CONCLUSION
Our findings establish a foundation for developing multi-target therapies based on natural products that may offer comprehensive neuroprotection with potentially fewer side effects than conventional pharmaceuticals.
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