The Acute Anticonvulsant Effects of Deoxycorticosterone in Developing Rats: Role of Metabolites and Mineralocorticoid‐receptor Responses
Bibliographic record
Abstract
PURPOSE: The mechanisms that mediate the acute anticonvulsant effects of deoxycorticosterone (DOC) were investigated in young rats. METHODS: Fifteen-day-old rats were pretreated with a variety of compounds, including (a) agonists of the receptors that bind DOC (mineralocorticoid receptors); (b) the DOC 5alpha- and 5alpha-3alpha-reduced metabolites, plus agonists that bind the receptors of the 5alpha-reduced metabolite of DOC (progesterone receptors); and (c) DOC itself in the presence and absence of metabolism and receptor blockers. Fifteen minutes later, pentylenetetrazol (PTZ) was administered, and maximal pentylenetetrazol (MMT) seizure responses were scored. RESULTS: Agonists of mineralocorticoid receptors increased the latency to forelimb flexion in PTZ seizures and sometimes suppressed the seizures completely. At low, nonconvulsant doses, spironolactone (a mineralocorticoid-receptor antagonist) blocked the anticonvulsant effects of a nonsedating, but not a sedating, dose of DOC. These data suggest the possible direct involvement of mineralocorticoid receptors in the anticonvulsant effects of DOC. At low, nonconvulsant doses, finasteride (which blocks the metabolism of DOC) partially blocked the protective effects of DOC, suggesting the contribution of metabolites to the anticonvulsant actions of DOC. Dihydrodeoxycorticosterone (DHDOC)-the first metabolite of DOC, an agonist at progesterone receptors, and an allosteric modulator of the gamma-aminobutyric acid (GABA)(A) receptor-and tetrahydrodeoxycorticosterone, a secondary metabolite of DOC and an allosteric modulator of the GABA(A) receptor, both blocked MMT seizures. CONCLUSIONS: These findings suggest that both DOC and its metabolites may contribute to the anticonvulsant effects seen in young rats, perhaps acting via interactions with several different receptors.
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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 | 0.001 |
| 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".