Central Regulation of the Hypothalamic‐Pituitary‐Adrenal Axis During Fetal Development in the Guinea‐Pig
Bibliographic record
Abstract
We have previously shown that the foetal guinea-pig hypothalamic-pituitary-adrenal (HPA) axis is activated near the time of parturition and that this is associated with changes in limbic glucocorticoid receptors (GR) and mineralocorticoid receptors. In the present study, we hypothesized that the foetal hypothalamic paraventricular nucleus (PVN) and pituitary contribute significantly to foetal HPA drive but that these areas remain sensitive to negative feedback by circulating glucocorticoids in late gestation. However, we observed decreased corticotrophin-releasing hormone mRNA expression in the PVN and decreased pro-opiomelanocortin (POMC) mRNA levels in the anterior pituitary with advanced gestational age. The reduction in POMC mRNA expression was likely the result of negative feedback via circulating glucocorticoids because GR mRNA was unchanged during development in the foetal pituitary. Furthermore, we found that maternally administered glucocorticoids significantly decreased foetal pituitary POMC mRNA expression in a dose-dependent manner at gestational day (gd) 62 with male foetuses being more sensitive to these effects. These findings show that the foetal HPA axis remains highly sensitive to glucocorticoid feedback even as plasma adrenocorticotropic hormone and cortisol levels are elevated at the end of gestation.
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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 | 0.001 |
| 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".