Stimulation of Prostaglandin EP2 Receptors Prevents NMDA-Induced Excitotoxicity
Bibliographic record
Abstract
Prostaglandin E(2) (PGE(2)) plays an important role in inflammation and neurologic disorders. The neuromodulatory effects of PGE(2) are mediated through regulation of four G-protein-coupled receptors known as EP1, EP2, EP3, and EP4. The goal of the current study was to determine whether EP2 receptor activation protects neurons from acute NMDA-mediated excitotoxicity. To examine the effects of EP2 activation, mice were given an injection of the EP2 receptor-selective agonist butaprost (K (i) = 110 nM for EP2 receptor; K (i) > 10,000 for other prostaglandin receptors) in the cerebral ventricle and then an injection of NMDA in the right striatum. After 48 h, a significant reduction in NMDA-induced lesion volume was observed in groups pretreated with butaprost (1-300 nmol/L), with maximal protection at 100 nmol/L (p < 0.001). To determine if EP2-activated protection was specific to neurons, mouse neuronal cultures were treated with butaprost, and cell viability was analyzed after 24 h of NMDA excitotoxicity. The results showed that butaprost significantly increased neuron survival in a dose-dependent fashion. Furthermore, treatment of primary neurons with butaprost significantly increased cAMP levels (p < 0.001). Together, these data reveal that EP2 receptor stimulation mediates neuroprotection against NMDA excitotoxicity both in vivo and in vitro and that butaprost can limit acute brain damage. Development and testing of specific PGE(2) receptor mimetics could lead to a decrease in side effects associated with anti-inflammatory drugs and could help to fight acute and/or chronic neurologic disorders.
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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) | 0.002 | 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".