Characterization of regression of exercise‐induced cardiac hypertrophy
Bibliographic record
Abstract
The heart is capable of changing size in response to changes in chronic stress or demand. Exercise and hypertension are classic examples of stimuli that promote physiologic and pathologic hypertrophy respectively. Although initially beneficial for maintaining function with increased stress, pathologic hypertrophy can progress to heart failure if the inducing stress is not mitigated. Additionally, in contrast to physiologic hypertrophy, reverse remodeling of pathologic hypertrophy is often incomplete in respect to returning to normal size and function. In order to understand the molecular mechanisms involved in the reversal of hypertrophy we subjected mice to a three‐week swim protocol followed by 0, 3, and 6 days of rest. Swim‐training induced a 25.4±2.0% (n=19, p<0.05) increase in heart weight/body weight compared to sedentary controls (n=13). Hypertrophy regressed by 31.8% and 90.0% after 3 and 6 days of rest respectively. Interestingly, western blot analysis showed an increase in cardiac LC3B II in rested mice, suggesting the involvement of autophagy in reverse remodeling. Unexpectedly the phosphorylation of Akt (308, 473), GSK3β, and S6 were not increased in rested hearts, but actually decreased in hypertrophied hearts. These data suggest that the observed increase in LC3B II is not mediated by the Akt‐mTOR pathway. Support: NCRR 5P20RR016477 (WV INBRE), NIA K01AG026337 (MRM), AHA (MRM)
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".