Social Isolation Stress Modulates Pregnancy Outcomes and the Inflammatory Profile of Rat Uterus
Bibliographic record
Abstract
Prenatal stressors have been linked to adverse pregnancy outcomes; including preterm birth (PTB). Recent work demonstrates that social isolation in mothers represents a silent stressor contributing to PTB risk. Here; we investigate the association of inflammatory and stress markers with PTB risk in Long–Evans rats exposed to social isolation stress (SIS) during preconception and pregnancy across four generations (F0-F3). Gestational length; blood glucose; corticosterone levels; and maternal and offspring weights were assessed in two SIS paradigms: transgenerational (TG) and multigenerational (MG) exposure. Maternal uterine tissues were collected 21 days after the dams gave birth. Exposure to SIS reduced pregnancy lengths in the parental generation and neonatal birth weights in the F1 and F2 generations. Interleukin (IL)-1β (Il1b) mRNA levels increased in F0 animals but decreased in the offspring of both stress lineages. Protein levels of IL-1β decreased in the TG lineage. Corticotrophin-releasing hormone receptor 1 (Crhr1) expression decreased in SIS-exposed F0 animals and increased in the TG-F2 and MG-F1 offspring. Expression of enzyme 11-β hydroxysteroid dehydrogenase-2 (11bHSD2) was enhanced in F1 animals. These findings suggest SIS has adverse consequences on the F0 mothers; but their F1–F3 progeny may adapt to this chronic stress; thus supporting the fetal programming hypothesis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".