Neuroprotective effect of alcoholic extract of Selaginella bryopteris leaves in experimental models of epilepsy
Downloads
Published
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.4.14Keywords:
Antiepileptic, Selaginella bryopteris leaves Extract, Seizure Model, Neuroprotection, LC-MSDimensions Badge
Issue
Section
License
Copyright (c) 2024 The Scientific Temper

This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Epilepsy, a neurological disorder, is characterized by recurrent, uncontrolled seizures due to an imbalance between inhibitory and excitatory neuronal interactions in the central nervous system (CNS). This study explores the neuroprotective effects of an alcoholic extract from Selaginella bryopteris leaves in experimental epilepsy models. Swiss albino mice (25–30 g) were used, and epilepsy was induced via pentylenetetrazol (PTZ, 60 mg/kg) and maximal electric shock (MES). The extract was administered orally at varying doses and compared with conventional antiepileptic drugs, phenytoin and diazepam. LC-MS analysis identified amentoflavone as a key bioactive compound with antiepileptic properties. The extract demonstrated significant dose-dependent protection in both PTZ and MES models, delaying convulsions in the PTZ model at 500 mg/kg, comparable to diazepam, and providing convulsion protection in the MES model similar to phenytoin. Additionally, the extract increased gamma-aminobutyric acid (GABA) and glutathione (GSH) levels while reducing lipid peroxidation (LPO) levels, indicating its neuroprotective properties. These findings suggest that S. bryopteris leaves possess significant antiepileptic properties and may serve as a promising treatment for epilepsy.Abstract
How to Cite
Downloads
Similar Articles
- Saarumathi R, Ritha W, Impregnable inventory stewardship for a closed loop supply chain besides energy usage, defective production and green investment manoeuvring pentagonal fuzzy number , The Scientific Temper: Vol. 16 No. 01 (2025): The Scientific Temper
- Naveena Somasundaram, Vigneshkumar M, Sanjay R. Pawar, M. Amutha, Balu S, Priya V, AI-driven material design for tissue engineering a comprehensive approach integrating generative adversarial networks and high-throughput experimentation , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- Nisha Patil, Archana Bhise, Rajesh K. Tiwari, Fusion deep learning with pre-post harvest quality management of grapes within the realm of supply chain management , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- J. Fathima Fouzia, M. Mohamed Surputheen, M. Rajakumar, Hybrid pigeon optimization-based feature selection and modified multi-class semantic segmentation for skin cancer detection (HPO-MMSS) , The Scientific Temper: Vol. 16 No. 05 (2025): The Scientific Temper
- Moyliev Gayrat, Yunuskhodjaev Akhmadkhodja, Saidov Saidamir, Babakhanov Otabek, Mirsultanov Jakhongir, To study references and analysis of an experimental model for skin burns in rats , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
- R. Sakthiraman, L. Arockiam, RFSVMDD: Ensemble of multi-dimension random forest and custom-made support vector machine for detecting RPL DDoS attacks in an IoT-based WSN environment , The Scientific Temper: Vol. 16 No. 03 (2025): The Scientific Temper
- Ravi Kumar P, C. Gowri Shankar, Optimizing power converters for enhanced electric vehicle propulsion: A novel research methodology , The Scientific Temper: Vol. 15 No. 04 (2024): The Scientific Temper
- Anil Kumar, Aditya Kumar, Synthesis, spectral characterization and antimicrobial effect of Cu(II) complexes of schiff Base Ligand, N-(3,4- dimethoxybenzylidene)-3-aminopyridine (DMBAP) Derived from 3,4-dimethoxybenzaldehyde and 3-aminopyridine , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- Ahmed Mustefa, Validating the dairy marketing performance of Mizan-Aman town, Bench-Sheko zone, Ethiopia , The Scientific Temper: Vol. 14 No. 01 (2023): The Scientific Temper
- K. Fathima, A. R. Mohamed Shanavas, TALEX: Transformer-Attention-Led EXplainable Feature Selection for Sentiment Classification , The Scientific Temper: Vol. 16 No. 11 (2025): The Scientific Temper
<< < 7 8 9 10 11 12 13 14 15 16 > >>
You may also start an advanced similarity search for this article.

