Maternal Undernutrition in Early Gestation Alters Molecular Regulation of the Hypothalamic‐Pituitary‐Adrenal Axis in the Ovine Fetus
Bibliographic record
Abstract
We have demonstrated previously that plasma adrenocorticotropin hormone and cortisol responses to exogenous and endogenous stimuli are reduced in fetuses of mildly undernourished ewes. In the present study, we examined the molecular regulation of fetal hypothalamic-pituitary-adrenal (HPA) axis function at 127-130 days gestation (dGA) following 15% reduction in maternal nutrition between 0 and 70 dGA. Using in situ hybridization, we found that corticotropin releasing hormone (CRH) mRNA expression in the hypothalamic paraventricular nucleus (PVN) was lower in fetuses from nutrient restricted ewes than in controls. Restricted fetuses also had greater levels of mRNA encoding preproenkephalin (PENK) and magnocellular arginine vasopressin (AVP) in the PVN. Expression of oxytocin mRNA and parvocellular AVP mRNA in the PVN and pro-opiomelanocortin mRNA in the pituitary were unchanged. Glucocorticoid receptor mRNA expression was unaltered at the PVN, but was reduced (> 40%) in the anterior pituitary of restricted fetuses. Northern blot analysis demonstrated that levels of adrenal P450scc mRNA and P450(C17) mRNA were not different between the groups. We conclude that the reduction in HPA function reported previously is mediated, at least in part, by a decrease in expression of CRH mRNA and increase in PENK mRNA in the PVN.
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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".