Effects of metformin on apoptosis and α-synuclein in a rat model of pentylenetetrazole-induced epilepsy
Bibliographic record
Abstract
The present study was designed to examine the possible neuroprotective and antiepileptic effects of metformin (Metf) in a rat model of pentylenetetrazole (PTZ)-induced epilepsy and its possible underlying mechanisms. Forty male albino rats were assigned to 4 groups of equal size: (1) normal control (NC) group, (2) Metf group: daily treatment with Metf (200 mg/kg, i.p.) for 2 weeks, (3) PTZ group: treatment with PTZ (50 mg/kg, i.p.) every other day for 2 weeks, and (4) Metf + PTZ group: daily treatment with PTZ and metformin (200 mg/kg, i.p.) for 2 weeks. Administration of PTZ caused a significant increase in seizure score and duration, induced a state of oxidative stress (high malondialdehyde, low reduced glutathione and catalase activity), and led to the upregulation of β-catenin, caspase-3, and its cleavage products, Hsp70 and α-synuclein, in hippocampal regions as well as a significant reduction in seizure latency. While Metf treatment significantly ameliorated PTZ-induced seizures, attenuated oxidative stress, and upregulated α-synuclein and β-catenin expression, it also inhibited caspase-3 activation and the release of the cleavage product and caused more upregulation in Hsp70 expression in hippocampal regions (p < 0.05). In conclusion, the antiepileptic and neuroprotective effects of Metf in PTZ-induced epilepsy might be due to the inhibition of apoptosis, attenuation of oxidative stress and α-synuclein expression, and upregulation of Hsp70.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".