GLUCOCORTICOIDS, HYPOTHALAMO-PITUITARY-ADRENAL (HPA) DEVELOPMENT, AND LIFE AFTER BIRTH
Bibliographic record
Abstract
Approximately 10% of women in North America are treated with synthetic glucocorticoid (sGC) between 24 and 32 weeks of pregnancy (term approximately 40 weeks), to promote lung maturation in fetuses at risk of preterm delivery. Such therapy is highly effective in reducing the frequency of respiratory complications, and as a result, repeated course treatment has become widespread. Nothing is known about the impact of repeated sGC treatment on neuroendocrine development in the human, or if specific time windows of increased sensitivity exist. Glucocorticoids are essential for many aspects of normal brain development. However, there is growing evidence from a number of species, that exposure of the fetal brain to excess glucocorticoid can have life-long effects on behaviour and neuroendocrine function. We have shown that exposure of fetuses to sGC in late gestation permanently alters HPA function in pre-pubertal, post-pubertal, and aging offspring, in a sex-dependent manner. These effects are linked to changes in central glucocorticoid feedback. Prenatal glucocorticoid exposure also leads to modification of HPA-associated behaviours and organ morphology, as well as altered regulation of other neuroendocrine systems. Permanent changes in HPA function will have a long-term impact on health, since elevated cumulative exposure to endogenous glucocorticoid has been linked to the premature onset of pathologies associated with aging.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".