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
- Y. Mohammed Iqbal, M. Mohamed Surputheen, S. Peerbasha, Swarm intelligence-driven HC2NN model for optimized COVID-19 detection using lung imaging , The Scientific Temper: Vol. 16 No. 03 (2025): The Scientific Temper
- R. Sakthiraman, L. Arockiam, RRFSE: RNN biased random forest and SVM ensemble for RPL DDoS in IoT-WSN environment , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- Sivasankar G. A, Study of hybrid fuel injectors for aircraft engines , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- Santosh Kumar Sahu, B. R. Senthil kumar, Y. Aboobucker parvez, Ashish Verma, Assessment of noise levels by using noise prediction modeling , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- P. Rathinabhagya, J. Merline Vinotha, Fuzzy vehicle routing problem for a municipal solid waste management system with greenhouse gas emission at various disposal stages , The Scientific Temper: Vol. 16 No. 04 (2025): The Scientific Temper
- Desalu Tamirat, Tesfaye Getachew , Worku masho, Zelalem Admasu , Morphological and morphometric features of indigenous chicken in North Shewa zone, Oromia regional state, Ethiopia , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- R. Thiagarajan, S. Prakash Kumar, Performance of public transport appraisal using machine learning , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- T. Kanimozhi, V. Gowtham Raaj, C. R. Santhosh, Impulsively intended buying behavior: A new horizon of shopping behavior in the online era , The Scientific Temper: Vol. 16 No. Spl-2 (2025): The Scientific Temper
- S K Bairagi, Ram Chandra, R P Singh, Effect of Different Phosphorus and Potassium Levels on a Seed Crop of French Bean (Phaseolus vulgaris L.) , The Scientific Temper: Vol. 12 No. 1&2 (2021): The Scientific Temper
- Arsha A, Jeena Pearl A, Qualitative Phytochemical Profiling of Amaranthus Dubius Leaves , The Scientific Temper: Vol. 16 No. 09 (2025): The Scientific Temper
<< < 11 12 13 14 15 16 17 18 19 20 > >>
You may also start an advanced similarity search for this article.

