Prenatal Bystander Stress Alters Brain, Behavior, and the Epigenome of Developing Rat Offspring
Bibliographic record
Abstract
The prenatal environment, including prenatal stress, has been extensively studied in laboratory animals and humans. However, studies of the prenatal environment usually directly stress pregnant females, but stress may come 'indirectly', through stress to a cage-mate. The current study used indirect prenatal bystander stress and investigated the effects on the gross morphology, pre-weaning behavior, and epigenome of rat offspring. Pregnant Long-Evans rats were housed with another female rat that underwent elevated platform stress from gestational days 12 to 16. We found that ultrasonic vocalizations of female cage-mates were disrupted following the stress procedure. After birth, offspring were tested on two behavioral tasks and sacrificed at postnatal day 21 (p21). Frontal cortex and hippocampal tissue was used to measure global DNA methylation and gene expression changes. At p21, bystander-stressed female offspring exhibited increased body weight. Offspring behavior on the negative geotaxis task was altered by prenatal bystander stress, and locomotor behavior was reduced in female offspring. Global DNA methylation increased in the frontal cortex and hippocampus of bystander-stressed offspring. Microarray analysis revealed significant gene expression level changes in 558 different genes, of which only 10 exhibited overlap between males and females or brain areas. These alterations in gene expression were associated with overrepresentation of 36 biological processes and 34 canonical pathways. Prenatal stress thus does not have to be experienced by the mother herself to influence offspring brain development. Furthermore, this type of 'indirect' prenatal stress alters offspring DNA methylation patterns, gene expression profiles, and behavior.
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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 | 0.000 |
| 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".