Synergistic effects of acetylcholinesterase (AChE) inhibition and NMDA receptor modulation on acetylcholine levels
Bibliographic record
Abstract
AChE inhibitors increase brain acetylcholine (ACh) levels by preventing the breakdown of ACh. Systemic administration of NMDA or NMDA receptor antagonists does not alter AChE activity. However, brain ACh levels are decreased or increased by NMDA or NMDA antagonists, respectively, by altering the glutamatergic regulation of ACh release, a mechanism distinct from AChE inhibition. In the present study, the effects of an NMDA receptor antagonist (memantine) and an AChE inhibitor (donepezil) on hippocampal ACh levels were determined in anesthetized rats using a microdialysis technique. Donepezil (0.25, 0.5 & 1.0 mg/kg, i.p.) dose-dependently increased the basal ACh level (+ 50%–100%). Memantine (2.5, 5 & 10 mg/kg, i.p.) also dose-dependently increased the basal ACh levels (+110%–250%) in the rat hippocampus. The concomitant administration of donepezil (0.5 mg/kg, i.p.) and memantine (5 mg/kg, i.p.) increased the basal ACh levels by 580%. In support of earlier findings with other NMDA receptor antagonists and AChE inhibitors, systemic administration of memantine and donepezil increased the basal ACh levels in the rat hippocampus. Concomitant administration of these drugs produced a greater increase in ACh levels than predicted from simple additivity indicating a synergistic effect of the two mechanisms involved, increased release by memantine and decreased breakdown by donepezil.
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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 | 0.001 |
| 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".