Estrogen potentiates the behavioral and nucleus accumbens dopamine response to continuous haloperidol treatment in female rats
Bibliographic record
Abstract
Estrogen has been shown to enhance the effects of antipsychotics in humans. To investigate the mechanisms of how this may occur, the current study examined estradiol's effects on dopaminergic transmission and behavior in amphetamine-sensitized and non-sensitized female rats. Sixty-four ovariectomized female Sprague-Dawley rats were used for this study. Half of the rats were sensitized to four once-daily injections of 1 mg/kg amphetamine and the other half served as controls. Rats received chronic administration of either low-dose haloperidol (0.25 mg/kg/day) or saline vehicle via osmotic minipumps implanted subcutaneously. The groups were further subdivided with respect to estradiol treatment: low chronic estrogen (subcutaneous estradiol implant, 0.36 mg/pellet: 90-day release, plus an additional oil vehicle injection every second day) and high pulsatile estrogen (subcutaneous estradiol implant plus an additional 10 μg/kg estradiol injection every second day). Motor activity was assessed at day 2 and day 12 during haloperidol treatment, while nucleus accumbens dopamine availability was assessed via microdialysis 10 days into antipsychotic treatment. Haloperidol treatment along with high, but not low, estradiol replacement was effective in reducing amphetamine-induced locomotor activity in sensitized rats. High estradiol treatment also augmented the effects of chronic haloperidol in reducing dopaminergic release in sensitized rats. These data suggest that estradiol levels affect both the behavioral and the dopamine responses to chronic antipsychotic treatment.
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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) | 0.000 | 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".