The impact of maternal synthetic glucocorticoid administration in late pregnancy on fetal and early neonatal hypothalamic–pituitary–adrenal axes regulatory genes is dependent upon dose and gestational age at exposure
Bibliographic record
Abstract
In this study, we determined the gene and/or protein expression of hypothalamic-pituitary-adrenal (HPA) axis regulatory molecules following synthetic glucocorticoid exposures. Pregnant sheep received intramuscular saline or betamethasone (BET) injections at 104 (BET-1), 104 and 111(BET-2) or 104, 111 and 118 (BET-3) days of gestation (dG). Samples were collected at numerous time-points between 75 dG and 12 weeks postnatal age. In the BET-3 treatment group, fetal plasma cortisol levels were lower at 145 dG than controls and gestational length was lengthened significantly. The cortisol:adrenocorticotropic hormone (ACTH) ratio in fetal plasma of control and BET-3 fetuses rose significantly between132 and 145 dG, and remained elevated in lambs at 6 and 12 weeks of age; this rise was truncated at day 145 in fetuses of BET-3 treated mothers. After BET treatment, fetal and postnatal pituitary proopiomelanocortin mRNA levels were reduced from 109 dG to 12 weeks postnatal age; pituitary prohormone convertase 1 and 2 mRNA levels were reduced at 145 dG and postnatally; hypothalamic arginine vasopressin mRNA levels were lowered at all time-points, but corticotrophin-releasing hormone mRNA levels were reduced only in postnatal lambs. Maternal BET increased late fetal and/or postnatal adrenal mRNA levels of ACTH receptor and 3β hydroxysteroid dehydrogenase but decreased steroidogenic acute regulatory protein and P450 17-α hydroxylase. The altered mRNA levels of key HPA axis regulatory proteins after maternal BET injections suggests processes that may subserve long-term changes in HPA activity in later life after prenatal exposure to synthetic glucocorticoids.
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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".