Molecular Mechanisms Driving Maternal Cardiac Hypertrophy in Murine Pregnancy
Bibliographic record
Abstract
In pregnancy, the maternal heart undergoes hypertrophy to support increasing circulatory demands. There lacks an understanding of molecular mechanisms underlying this process, with hypotheses pointing towards maternal hormonal effects and/or embryonic signaling. This thesis used time-series echocardiography and RNA sequencing to characterize murine maternal cardiac function and transcriptome at multiple murine gestational timepoints, as well as in a pseudo-pregnant mouse model that lacks a true embryo. Echocardiography suggests e8.5 (pre-placentation) marks active cardiac remodeling, showcased by transient systolic impairment compensated by diastolic improvement, and progressive eccentric hypertrophy throughout gestation. Cardiac transcriptomic changes are seen as early as e6.5 (pre-gastrulation) and reach significance at e8.5, including upregulation of carbohydrate catabolism, cell proliferation, and angiogenesis, and downregulation of protein synthesis and immune pathways. In e8.5 pseudo-pregnancies, cardiac hypertrophy and functional improvements are stunted, and molecular pathways are dysregulated. This highlights the significance of the embryo in driving maternal adaptations to pregnancy such as pregnancy-induced cardiac hypertrophy.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".