Prenatal two-hit stress affects maternal and offspring pregnancy outcomes and uterine gene expression in rats: match or mismatch?†
Bibliographic record
Abstract
Maternal stress and inflammation excesses can lead to adverse pregnancy outcomes and offspring development. We evaluated whether distinct prenatal stressors affect pregnancy, maternal and offspring outcomes, and uterine gene expression differently when combined than either alone. Long-Evans dams were exposed to psychological or/and (two-hit) immune stress (interleukin-1 beta [IL-1β]), on gestational days 12-18 and 17-delivery, respectively. Gestational length, maternal weight gain, glycaemia and corticosterone levels, offspring weight, and gender effects were recorded. Maternal and offspring uteri were collected at weaning and on postnatal day 160 correspondingly. Uterine expression of genes involved in local progesterone metabolism, neuroendocrine and immune systems were analyzed using quantitative real-time polymerase chain reaction. Maternal two-hit stress increased gestational length variation and the occurrence of adverse pregnancy outcomes while reducing gestational weight gain. Pup weight was negatively affected by prenatal stressors in a gender-specific way. In dams, IL-1β upregulated gene expression of neuroendocrine (Crh, Crhr1) and cytokine genes (Il1b, Il1rn, Il6, and Il10). Conversely, transcriptional patterns in offspring uteri were more variable with gene-specific up- or downregulation by each stressor separately, while exposure to both extensively reduced the expression of neuroendocrine (Hsd11b1), cytokine (Il1a, Il1rn, Il6), and IL-1 receptor genes. In conclusion, maternal stress affects physiological and molecular processes in dams and their offspring; two hits have different effects than single stressors. Outcomes appear generation-, gender-, and stressor-specific. Dampening of offspring uterine gene expression after exposure to multiple stressors could fit within the match/mismatch hypothesis of perinatal programming, with offspring preparing for a stressful life.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".