Oestrogen and Testosterone Modulate the Firing Activity of Dorsal Raphe Nucleus Serotonergic Neurones in Both Male and Female Rats
Bibliographic record
Abstract
Women are twice as likely to suffer from mood disorders than men. Moreover, a growing body of evidence suggests a reciprocal modulation between sex steroids and the serotonin (5-HT) system. A previous study from our laboratory has shown that the progesterone metabolites 5beta-pregnane-3,20-dione (5beta-DHP) and 5alpha-pregnan-3alpha-ol,20-one (3alpha,5alpha-THP), as well as dehydroepiandrosterone (DHEA), increase the firing activity of dorsal raphe nucleus (DRN) 5-HT neurones in female rats. The present study was undertaken to assess the effects of these steroids in male rats, as well as the effects of testosterone and 17beta-oestradiol (17beta-E) in both sexes, and finally to evaluate gender differences in the modulation of the 5-HT neuronal firing activity by these different neuroactive steroids. Male rats were treated i.c.v., for 7 days, with a dose of 50 microg/kg/day of one of the following steroids: progesterone, 5beta-DHP, 3alpha,5alpha-THP, DHEA, testosterone, 17beta-hydroxy-5alpha-androstan-3-one (5alpha-DHT) and 17beta-E. Some rats also received a 3-day administration of testosterone (50 microg/kg/day, i.c.v). Females were treated in the same fashion with testosterone and 17beta-E. Extracellular unitary recordings of 5-HT neurones, obtained in vivo in the DRN of these rats, revealed that testosterone and 17beta-E increased the firing activity of 5-HT neurones in both males and females. In males, the effect of testosterone could already be seen after 3 days of treatment. Neither castration nor any treatment with other steroids significantly modified the firing rate of male 5-HT neurones. Taken together with previous findings, the results of the present study indicate both similarities and differences between sexes in the modulation of 5-HT neurones by some steroids. This could prove important in understanding gender differences in mood 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".