The Adverse Effects of Auditory Stress on Mouse Uterus Receptivity and Behaviour
Bibliographic record
Abstract
Stress during gestation has harmful effects on pregnancy outcome and can lead to spontaneous abortion. Few studies, however, have addressed the impact of gestational stress, particularly auditory stress, on behavioural performance and pregnancy outcome in mice. This study aimed to examine the effect of two types of gestational stress on uterus receptivity and behavioural performance. Pregnant C57BL/6 mice were randomly assigned to either auditory or physical stress conditions or a control condition from gestational days 12-16. The auditory stress regimen used loud 3000 Hz tone, while the physical stressor consisted of restraint and exposure to an elevated platform. Three behavioural tests were performed in the dams after weaning. Uterine receptivity was investigated by counting the number of sites of implantation and fetal resorption. Also, the offspring survival rates during the early postnatal period were calculated. Auditory stress caused an increase in anxiety-like behaviour, reduced time spent exploring new object/environment, and reduced balance when compared to the physical stress and control groups. Auditory stress also caused higher rates of resorbed embryos and reduction of litter size. Our results suggest that the adverse effect of noise stress is stronger than physical stress for both uterus receptivity and behavioural performance of the dams.
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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) | 0.002 | 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".