Abstract P3119: Identifying The Windows Of Cardiac Risk And Opportunity In Menopause
Bibliographic record
Abstract
Post-acute myocardial infarction (AMI) mortality has significant sex differences with a bias towards higher rates in women. While treatment inequities and access to care profoundly impact outcomes, biological factors also contribute to survival discrepancies. One complicating factor that drives worse outcomes in women is menopause. Understanding the biological basis for AMI mortality risk and the exacerbating role of menopause has been hampered by the lack of an animal model that recapitulates the dynamic changes associated with the perimenopausal transition. We used a mouse model of menopause in which ovarian failure is gradually induced following treatment with 4-vinylcyclohexene diepoxide (VCD, 160 mg/kg, 15d), allowing for examination of cardiac alterations established during perimenopause. Echocardiography revealed no contractile changes during perimenopause, but cardiac myofilament activation was significantly affected. Calcium re-uptake by SERCA was impaired by the end of perimenopause. Changes in calcium handling were associated with alterations in calcium handling protein expression and phosphorylation. Activation of RISK and SAFE signaling molecules that protect against ischemia-reperfusion (IR) injury was altered throughout perimenopause, and the RISK-SAFE response to IR differed at points during perimenopause. The myocardial response to cardioprotective estrogen receptor activation also varied throughout perimenopause. Together these data reveal significant, nonlinear alterations in myocardial physiology and endogenous protective signing pathways during perimenopause. Disruptions in endogenous protection and calcium handling are established prior to menopause, providing possible mechanisms for worse post-menopausal AMI outcomes. The altered response to estrogen receptor activation preceding menopause may explain the inconsistent effectiveness of post-menopausal estrogen replacement therapy.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".