Corticosterone response to gestational stress and postpartum memory function in mice
Bibliographic record
Abstract
Maternal stress is a common adversity during pregnancy. Gestational corticosterone alternations are thought to contribute to the etiology of postpartum behavioral disturbances. However, the impact of stress during pregnancy, in particular noise exposure, on gestational corticosterone fluctuations and spatial cognition in postpartum mice has not been fully understood yet. We hypothesized that noise exposure during pregnancy negatively affects gestational corticosterone levels and postpartum memory function in the dams similar to the physical stressors. Pregnant C57BL/6 mice were randomly assigned to either one of two stress conditions or a control condition. The noise stress (NS) was induced by presenting a loud intermittent 3000 Hz frequency on gestational days (GDs) 12, 14, and 16 for 24 hours, whereas the physical stress (PS) consisted of restraint and exposure to an elevated platform on GDs 12-16. Plasma corticosterone level was collected on GDs 11 and 17, and Morris water task (MWT) was carried out 30 days after parturition. Compared to the control group, the level of corticosterone in the stressed groups was significantly increased on GD17 relative to GD11. Significantly longer swim time and lower swim speed were observed in both stressed groups relative to the control group. Probe time was significantly shorter in the NS group than the other groups. The delta corticosterone level was significantly correlated with the swim time as well as the probe time in the three groups. Given the results, the adverse effects of gestational noise exposure on the hypothalamic pituitary-adrenal (HPA) axis activation and postpartum spatial learning and memory function were as large as/ or a bit stronger than the physical stresses. The findings suggest the significance of conservation against loud noise exposure in daily living, as well as need to further notice to the different aspects of gestational stress in mothers' behavior like 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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".