Early-Life Glucocorticoid Exposure: The Hypothalamic-Pituitary-Adrenal Axis, Placental Function, and Long-term Disease Risk
Bibliographic record
Abstract
An adverse early-life environment is associated with long-term disease consequences. Adversity early in life is hypothesized to elicit developmental adaptations that serve to improve fetal and postnatal survival and prepare the organism for a particular range of postnatal environments. These processes, although adaptive in their nature, may later prove to be maladaptive or disadvantageous if the prenatal and postnatal environments are widely discrepant. The exposure of the fetus to elevated levels of either endogenous or synthetic glucocorticoids is one model of early-life adversity that contributes substantially to the propensity of developing disease. Moreover, early-life glucocorticoid exposure has direct clinical relevance because synthetic glucocorticoids are routinely used in the management of women at risk of early preterm birth. In this regard, reports of adverse events in human newborns have raised concerns about the safety of glucocorticoid treatment; synthetic glucocorticoids have detrimental effects on fetal growth and development, childhood cognition, and long-term behavioral outcomes. Experimental evidence supports a link between prenatal exposure to synthetic glucocorticoids and alterations in fetal development and changes in placental function, and many of these alterations appear to be permanent. Because the placenta is the conduit between the maternal and fetal environments, it is likely that placental function plays a key role in mediating effects of fetal glucocorticoid exposure on hypothalamic-pituitary-adrenal axis development and long-term disease risk. Here we review recent insights into how the placenta responds to changes in the intrauterine glucocorticoid environment and discuss possible mechanisms by which the placenta mediates fetal hypothalamic-pituitary-adrenal development, metabolism, cardiovascular function, and reproduction.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".