Gene Dysregulation in the Adult Rat Paraventricular Nucleus and Amygdala by Prenatal Exposure to Dexamethasone
Bibliographic record
Abstract
Fetal programming is the concept that maternal stressors during critical periods of fetal development can alter offspring phenotypes postnatally. Excess glucocorticoids can interact with the fetus to effect genetic and epigenetic changes implicated in adverse developmental outcomes. The present study investigates how chronic exposure to the synthetic glucocorticoid dexamethasone during late gestation alters the expression of genes related to behavior in brain areas relevant to the regulation and function of the hypothalamic–pituitary–adrenal axis. Pregnant Wistar Kyoto rats received subcutaneous injections of dexamethasone (100 μg/kg) daily from gestational day 15–21 or vehicle only as sham controls. The amygdala and paraventricular nucleus (PVN) were micro-punched to extract mRNA for reverse transcription and quantitative polymerase chain reaction for the analysis of the expression of specific genes. In the PVN, the expression of the glucocorticoid receptor NR3C1 was downregulated in female rats in response to programming. The expression of CACNA1C encoding the Cav1.2 pore subunit of L-type voltage-gated calcium channels was downregulated in male and female rats prenatally exposed to dexamethasone. Collectively, the results suggest that prenatal exposure to elevated levels of glucocorticoids plays a role in the dysregulation of the hypothalamic–pituitary–adrenal axis and potentially learning and memory by altering the expression of specific genes within the amygdala and 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 | 0.001 |
| 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".