AIDA, a Class I Metabotropic Glutamate‐receptor Antagonist Limits Kainate‐induced Hippocampal Dysfunction
Bibliographic record
Abstract
PURPOSE: In the developing animal, intraperitoneal injections of kainic acid (KA) lead to a prolonged initial seizure followed by chronic recurrent seizures and long-term hippocampal dysfunction. We investigated whether the class I metabotropic glutamate receptor (mGluR) antagonist 1-aminoindan-1,5-dicarboxylic acid (AIDA) is neuroprotective in the KA model of epilepsy. METHODS: Immature rats aged postnatal day 20 (P20) and P30 were injected with fixed volumes of KA, KA + AIDA, AIDA, or saline. We monitored recurrent seizures. Thirty days later, we tested hippocampal function with the Morris water-maze test or prepared hippocampal slices to record extracellularly evoked and spontaneous potentials from the CA1 area. In a third group, we performed neuronal counts. RESULTS: In both age groups, acute seizures were similar in KA and KA + AIDA groups. Rare spontaneous recurrent seizures occurred only in KA-injected rats. The KA P20 group performed significantly worse than controls in the water-maze test. The KA + AIDA group showed impaired performance on day 1, but learning improved substantially, reaching control values in the remaining 3 days. The P30 KA rats performed worse than controls on all trial days, whereas the KA + AIDA rats improved by day 3, but did not reach control values. Electrophysiologic recordings showed small but consistent differences between KA and control animals, suggestive of an adaptive modification in the gamma-aminobutyric acid (GABA)ergic system, reversed by AIDA. On histology, we observed a loss of CA1 interneurons in both ages. Cell loss was reversed by the use of AIDA. CONCLUSIONS: Blockade of the class I mGluR during KA-induced seizures in the developing brain limits seizure-induced hippocampal dysfunction.
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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) | 0.000 | 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".