Increased locomotor activity does not mitigate the effects of advanced maternal age in a mouse model
Bibliographic record
Abstract
INTRODUCTION: Advanced maternal age (AMA) increases the risk of pregnancy complications, in part due to impaired placentation. While exercise during pregnancy can improve outcomes, its potential to mitigate the effects of AMA has not been investigated. We evaluated the impact of exercise in a mouse model of AMA. METHODS: Females were paired with males at 9 or 34 weeks of age, with one group of aged females having access to running wheels four weeks prior to and during pregnancy. Pregnant females (N = 19 per group) were collected at gestational day (GD) 11.5. Placentas were collected for RNA sequencing (N = 17-20 per group). RESULTS: Aged females with access to running wheels had lighter fat depots (1.0 ± 0.1 g) than those without (2.2 ± 0.1 g; p < 0.0001), but did not differ from young females (0.8 ± 0.1 g; p = 0.5). Both groups of aged females had fewer viable conceptuses (without wheels: 4.0 ± 0.5, with wheels: 4.3 ± 0.5) than young mice (8.3 ± 0.5; p < 0.0001 for both comparisons). Fetal crown-rump length was also lower in aged females (without wheels: 5.7 ± 0.2 mm, with wheels: 5.5 ± 0.2 mm, young: 6.6 ± 0.2 mm; p < 0.0001 for both comparisons). Placental expression of only one gene was affected by access to running wheels, but 423 and 967 genes were differentially expressed between young and aged females without and with access to wheels, respectively. Placental transcriptomes suggested delayed placental development in aged females. CONCLUSIONS: Our model reproduced previously-reported effects of age on fetal development and placental transcriptomics, but these were not mitigated by increased voluntary locomotor activity, despite a reduction in adiposity. Remarkably, increased voluntary locomotor activity had almost no effects on placental gene expression in aged mice.
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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".