Glucocorticoids and serotonin alter glucocorticoid receptor mRNA levels in fetal guinea-pig hippocampal neurons, in vitro
Bibliographic record
Abstract
The hypothalamic-pituitary-adrenal (HPA) axis is susceptible to programming during fetal life. Such programming occurs, at least partially, at the level of the hippocampus. The hippocampus plays a central role in regulation of the HPA axis and release of endogenous glucocorticoids, via mediation of glucocorticoid negative feedback. Fetal exposure to synthetic glucocorticoids can permanently alter glucocorticoid receptor (GR) and mineralocorticoid receptor (MR) levels within the hippocampus, and serotonin is thought to be involved in this process. In the present study, we hypothesised that dexamethasone, cortisol and serotonin exposure would modify GR mRNA expression within fetal guinea-pig hippocampal cultures. Cultures were derived from 40-day-old guinea-pig fetuses, and were exposed to 0, 1, 10 and 100 nM dexamethasone, cortisol or serotonin for 4 days. Expression of GR and MR mRNA was examined by in situ hybridisation followed by high-resolution silver emulsion autoradiography. Four-day exposure to dexamethasone (P < 0.05; 100 nM) or cortisol (P = 0.08; 100 nM) downregulated the expression of GR mRNA within neurons. There was no change in the expression of MR mRNA levels following cortisol treatment. Exposure to serotonin (100 nM) significantly increased GR mRNA levels in hippocampal neurons. We conclude that synthetic and endogenous glucocorticoids, as well as serotonin, can influence GR expression during hippocampal development and in this way may act to permanently programme HPA function.
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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".