Is It Good to Have a Stiff Aorta with Aging? Causes and Consequences
Bibliographic record
Abstract
Aortic stiffness increases with advancing age, more than doubling during the human life span, and is a robust predictor of cardiovascular disease (CVD) clinical events independent of traditional risk factors. The aorta increases in diameter and length to accommodate growing body size and cardiac output in youth, but in middle and older age the aorta continues to remodel to a larger diameter, thinning the pool of permanent elastin fibers, increasing intramural wall stress and resulting in the transfer of load bearing onto stiffer collagen fibers. Whereas aortic stiffening in early middle age may be a compensatory mechanism to normalize intramural wall stress and therefore theoretically "good" early in the life span, the negative clinical consequences of accelerated aortic stiffening beyond middle age far outweigh any earlier physiological benefit. Indeed, aortic stiffness and the loss of the "windkessel effect" with advancing age result in elevated pulsatile pressure and flow in downstream microvasculature that is associated with subclinical damage to high-flow, low-resistance organs such as brain, kidney, retina, and heart. The mechanisms of aortic stiffness include alterations in extracellular matrix proteins (collagen deposition, elastin fragmentation), increased arterial tone (oxidative stress and inflammation-related reduced vasodilators and augmented vasoconstrictors; enhanced sympathetic activity), arterial calcification, vascular smooth muscle cell stiffness, and extracellular matrix glycosaminoglycans. Given the rapidly aging population of the United States, aortic stiffening will likely contribute to substantial CVD burden over the next 2-3 decades unless new therapeutic targets and interventions are identified to prevent the potential avalanche of clinical sequelae related to age-related aortic stiffness.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| 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".