Environmental perturbation of the circadian clock during pregnancy leads to transgenerational mood disorder-like behaviors in mice
Bibliographic record
Abstract
It remains unknown whether chronic circadian disturbance (CCD) during pregnancy can lead to mood disorders in the offspring. Here we show that pregnant mice in the F0 generation that were exposed to CCD stress displayed depression-like behaviors, and produced offspring in the F1 and F2 generations that also exhibited mood-associated behavioral phenotypes despite the lack of direct stressful experiences during their postnatal or adult period. Prenatal CCD stress was correlated with the elevation of plasma corticosterone levels in F1 mice. Furthermore, the diurnal expression profiles of core circadian clock genes were disrupted in the suprachiasmatic nucleus of F1 mice. Proteomics analysis revealed that prenatal CCD stress resulted in distinct changes in protein expression in the hypothalamus of female F1 mice, in particular proteins that were associated with cellular activities, metabolism, development and diseases. Sex-specific differences in melanocortin 4 receptor expression were apparent in the CCD F1 generation. We conclude that maternal exposure to chronic circadian disturbance during pregnancy can lead to sex-specific mood disorders that persist for at least two filial generations. The underlying mechanisms may depend on transgenerational changes in plasma corticosterone levels, circadian pacemaking, and hypothalamic protein expression.
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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 | 0.001 | 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".