Plasticity of the heart in response to changes in physical activity
Bibliographic record
Abstract
The human heart is very adaptable, with chamber size, wall thickness and ventricular stiffness all modified by periods of inactivity or exercise training. Herein, we summarize the cardiac adaptations induced by changes in physical activity, ranging from bed rest and spaceflight to endurance exercise training, while also highlighting how the ageing process (a long-term model of inactivity) affects cardiac plasticity. Severe inactivity during bed rest or spaceflight leads to cardiac atrophy and ventriculo-vascular stiffening. Conversely, endurance training induces eccentric hypertrophy and enhances ventricular compliance, and can be used as an effective countermeasure to prevent adverse cardiac changes during prolonged periods of bed rest or spaceflight. With sedentary ageing, the heart undergoes concentric remodelling and irreversibly stiffens at advanced age. Specifically, older adults who initiate endurance training later in life are unable to improve ventricular compliance and diastolic function, suggesting reduced cardiac plasticity with advanced age; however, lifelong exercise training prevents age-associated cardiac remodelling and maintains cardiac compliance of older adults at a level similar to those of younger healthy individuals. Nevertheless, there are still many knowledge gaps related to cardiac remodelling and changes in cardiac function induced by bed rest, exercise training and spaceflight, as well as how these different stimuli may interact with advancing age. Future studies should focus on understanding what factors (sex, age, heritability, etc.) may influence the heart's responsiveness to training or deconditioning, as well as understanding the long-term cardiac consequences of spaceflight beyond low-Earth orbit with the added stimulus of galactic cosmic radiation.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".