Le magnésium et le calcium réduisent la sévérité des troubles de la mémoire spatiale pour le modèle kaïnique d’épilepsie mésiale temporale chez la souris
Bibliographic record
Abstract
Calcium and magnesium are divalent multipotent ions playing a major role in metabolism, excitability and neuroglial plasticity. Because of these multiple properties, their deficiency induces complex brain processes leading to acute or even lasting disorders in excitability and neural networks. These ions are usually prescribed in clinical contexts of neuronal hyperexcitability such as preeclampsia and chronic stress. Our aim was to evaluate whether magnesium at 20 mg/kg and calcium at 100 mg/kg could improve the memory prognosis in the kainic model of mesial temporal epilepsy in mice. The animals were organized into 6 groups: control group (without kainate), reference group (GR) without administration of ions, groups treated with magnesium or calcium from the third day (respectively G1m, G1c), groups treated with magnesium or calcium from the third week (respectively G2m, G2c). The mice treated by ions performed better than GR mice, but magnesium was more effective. Memory (short term-long term) was differently affected by kainate or improved by magnesium-calcium. In addition, magnesium demonstrated an increasing therapeutic effect over time while calcium had an acute and apparently decreasing action in the G1c group that received calcium early.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".