Elevated corticosterone levels in stomach milk, serum, and brain of male and female offspring after maternal corticosterone treatment in the rat
Bibliographic record
Abstract
Early influences such as maternal stress affect the developmental outcome of the offspring. We created an animal model of postpartum depression/stress based on giving high levels of corticosterone (CORT) to the rat dam, which resulted in behavioral and neural changes in the offspring. This study investigated whether highly elevated levels of maternal CORT during pregnancy or the postpartum result in higher levels of CORT in the stomach milk, serum, and brain of offspring. Dams received daily injections of CORT (40 mg/kg) or oil (control) either during pregnancy (gestational days 10-20) or the postpartum (Days 2-21). Pups that were exposed to high gestational maternal CORT had higher CORT levels in serum, but not in stomach milk or brain, on postnatal day (PND) 1. However, on PND7, pups that were exposed to high postpartum maternal CORT had higher CORT levels in stomach milk and brain, but not in serum. Conversely on PND18, pups that were exposed to high postpartum maternal CORT had higher CORT levels in serum, but not in brain (prefrontal cortex, hypothalamus, or hippocampus). Moreover, 24 h after weaning, there were no significant differences in serum CORT levels between the groups. Thus, CORT given to the dam during pregnancy or the postpartum results in elevated levels of CORT in the offspring, but in an age- and tissue-dependent manner. Developmental exposure to high CORT could reprogram the HPA axis and contribute to the behavioral and neural changes seen in adult offspring.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".