Gabapentin is neuroprotective through glutamate receptor-independent mechanisms in staurosporine-induced apoptosis of cultured rat cerebellar neurons
Bibliographic record
Abstract
Abstract The anticonvulsants that are currently available modulate the activity of neuronal receptors and ion channels, which are equally involved in apoptotic pathways. We investigated the hypothesis that gabapentin (GP), an anticonvulsant without effect on glutamate receptors acting as GABA analog, has neuroprotective properties. For comparison, we chose topiramate (TPM), which has been reported to be neuroprotective via AMPA receptors blockade. For this purpose, we used rat cerebellar granule neuron (CGN) cultures and we triggered apoptosis independent of glutamate receptors with staurosporine, a broad-spectrum protein kinase inhibitor. GP at therapeutic range concentration significantly increased cell viability in CGN cultures maintained in physiological KCl concentration and reversed apoptosis induced by staurosporine. Blockade of NMDA or AMPA receptors by MK801 or NBQX, respectively, did not alter GP neuroprotection, which was reversed instead by GABA. In contrast, protective effect of TPM on STS-treated CGN cultures was annihilated by NBQX, and not altered by MK801 or GABA. Treatments with neuroprotective concentrations of GP or TPM did not modify the expression of neuronal cell adhesion molecule or synaptophysin or the morphological aspect of neuronal endings. In summary, we report that GP is neuroprotective through glutamate-receptor independent mechanisms and without alteration of neuronal plasticity markers, which makes it a possible candidate for clinical neuroprotection trials.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".