Rapid Changes in Cardiac Myofilament Function following the Acute Activation of Estrogen Receptor-Alpha
Bibliographic record
Abstract
Estrogens have well-recognized and complex cardiovascular effects, including altering myocardial contractility through changes in myofilament function. The presence of multiple estrogen receptor (ER) isoforms in the heart may explain some discrepant findings about the cardiac effects of estrogens. Most studies examining the impact of estrogens on the heart have focused on chronic changes in estrogen levels, and have not investigated rapid, non-genomic pathways. The first objective of this study was to determine how acute activation of ERα impacts cardiac myofilaments. Nongenomic myocardial estrogen signaling is associated with the activation of a variety of signaling pathways. p38 MAPK has been implicated in acute ER signaling in the heart, and is known to affect myofilament function. Thus, the second objective of this study was to determine if acute ERα activation mediates its myofilament effects through p38 MAPK recruitment. Hearts from female C57Bl/6 mice were perfused with the ERα agonist PPT and myofilaments isolated. Activation of ERα depressed actomyosin MgATPase activity and decreased myofilament calcium sensitivity. Inhibition of p38 MAPK attenuated the myofilament effects of ERα activation. ERα stimulation did not affect global myofilament protein phosphorylation, but troponin I phosphorylation at the putative PKA phosphorylation sites was decreased. Changes in myofilament activation did not translate into alterations in whole heart function. The present study provides evidence supporting rapid, non-genomic changes in cardiac myofilament function following acute ERα stimulation mediated by the p38 MAPK pathway.
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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) | 0.002 | 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".