Perimenopause Decreases SERCA2a Activity in the Hearts of a Mouse Model of Ovarian Failure
Bibliographic record
Abstract
Risk of cardiovascular disease mortality rises in women after menopause. While increased cardiovascular risk is largely attributed to postmenopausal declines in estrogens, the molecular changes in the heart that contribute to risk are poorly understood. Disruptions in intracellular calcium handling develop in ovariectomized mice and have been implicated in cardiac dysfunction. Using a mouse model of menopause in which ovarian failure occurs over 120 days, we sought to determine if perimenopause impacted calcium removal mechanisms in the heart and identify the molecular mechanisms. Mice were injected with 4-vinylcyclohexene diepoxide (VCD) to induce ovarian failure over 120 days, mimicking perimenopause. Hearts were removed at 60 and 120 days after VCD injections, representing the middle and end of perimenopause. SERCA2a function was significantly diminished at the end of perimenopause. Neither SERCA2a nor phospholamban expression changed at either time point, but phospholamban phosphorylation at S16 and T17 was dynamically altered. Intrinsic SERCA inhibitors sarcolipin and myoregulin increased >4-fold at day 60, as did the native activator DWORF. At the end of perimenopause, sarcolipin and myoregulin returned to baseline levels while DWORF was significantly reduced below controls. Sodium-calcium exchanger expression was significantly increased at the end of perimenopause. These results show that the foundation for increased cardiovascular disease mortality develops in the heart during perimenopause and that regulators of calcium handling exhibit significant fluctuations over time. Understanding the temporal development of cardiovascular risk associated with menopause and the underlying mechanisms is critical to developing interventions that mitigate the rise in cardiovascular mortality that arises after menopause.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".