Sarcomeric SRX:DRX Equilibrium in Alport and LDLR/P407 Mouse Models of HFpEF
Bibliographic record
Abstract
Abstract Cardiac myosin energetic states that regulate heart contractility define interactions of myosin cross-bridges with actin-containing thin filaments have been functionally linked with the pathology of hypertrophic cardiomyopathy (HCM). In particular, the balance between the disordered relaxed (DRX) and super relaxed (SRX) states that correlate respectively with enhanced force and energy conservation significantly determine myocardial performance and energy utilization. Compelling evidence suggests that a balanced SRX and DRX states proportion is a prerequisite for long-term cardiac health. Whereas roles for altered SRX: DRX proportions in HCM have been studied in depth, the mechanics of sarcomeric dysfunction and SRX: DRX proportions have not been reported in models of acquired heart failure (HF) including HF with preserved ejection fraction (HFpEF). Here, we quantified SRX andDRX myosin populations in two mouse models of HFpEF, including Alport and LDLR/P407 mice that represent cardiorenal/hypertensive and cardiometabolic/hyperlipidemic mouse models of HFpEF, respectively. We report significant changes in the SRX:DRX in both HFpEF mouse models, with an increased DRX state associated with Alport mice and a stabilized SRX state associated with LDLR/P407 mice. These findings correlate respectively with the hypercontractility and metabolic dysregulation with bradycardia phenotypes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".