Postmyocardial Infarct Remodeling and Heart Failure: Potential Contributions from Pro- and Antiaging Factors
Bibliographic record
Abstract
Myocardial infarction and adverse postinfarct remodeling in older persons lead to poor outcome and need greater understanding of the contributions of age-related factors on abnormal cardiac function and management. In this perspective, how normal aging processes could contribute to the events of post-myocardial infarction and remodeling is reviewed. Post-myocardial infarction and remodeling involve cardiomechanical factors and neurohormonal response. Many factors prevent or accelerate aging including immunosenescence, recruitment and regeneration of stem cells, telomere shortening, oxidative damage, antiaging hormones klotho and melatonin, nutrition, and Sirtiun protein family, and these factors could affect post-MI remodeling and heart failure. Interest in stem cell repair of myocardial infarcts to mitigate post-MI remodeling needs more information on aging of stem cells, and potential effects on stem cell use in infarct repair. Integrating genomics and proteomics methods may help find clinically novel therapy in the management of post-MI remodeling and heart failure in aged individuals.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".