How cardiomyocyte excitation, calcium release and contraction become altered with age
Bibliographic record
Abstract
Cardiovascular disease is the main cause of death globally, accounting for over 17 million deaths each year. As the incidence of cardiovascular disease rises markedly with age, the overall risk of cardiovascular disease is expected to increase dramatically with the aging of the population such that by 2030 it could account for over 23 million deaths per year. It is therefore vitally important to understand how the heart remodels in response to normal aging for at least two reasons: i) to understand why the aged heart is increasingly susceptible to disease; and ii) since it may be possible to modify treatment of disease in older adults if the underlying substrate upon which the disease first develops is fully understood. It is well known that age modulates cardiac function at the level of the individual cardiomyocyte. Generally, in males, aging reduces cell shortening, which is associated with a decrease in the amplitude of the systolic Ca(2+) transient. This may arise due to a decrease in peak L-type Ca(2+) current. Sarcoplasmic reticulum (SR) Ca(2+) load appears to be maintained during normal aging but evidence suggests that SR function is disrupted, such that the rate of sarco/endoplasmic reticulum Ca(2+)-ATPase (SERCA)-mediated Ca(2+) removal is reduced and the properties of SR Ca(2+) release in terms of Ca(2+) sparks are altered. Interestingly, Ca(2+) handling is modulated by age to a lesser degree in females. Here we review how cellular contraction is altered as a result of the aging process by considering expression levels and functional properties of key proteins involved in controlling intracellular Ca(2+). We consider how changes in both electrical properties and intracellular Ca(2+) handling may interact to modulate cardiomyocyte contraction. We also reflect on why cardiovascular risk may differ between the sexes by highlighting sex-specific variation in the age-associated remodeling process. This article is part of a Special Issue entitled CV Aging.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".