Exercise-induced increases in the expression and activity of cardiac sarcoplasmic reticulum calcium ATPase 2 is attenuated in AMPKα<sub>2</sub> kinase-dead mice
Bibliographic record
Abstract
Exercise enhances cardiac sarcoplasmic reticulum Ca2+-ATPase 2a (SERCA2a) function through unknown mechanisms. The present study tested the hypothesis that the positive effects of exercise on SERCA2a expression and function in the left ventricle is dependent on adenosine-monophosphate-activated protein kinase (AMPK) α2 function. AMPKα2 kinase-dead (KD) transgenic mice, which overexpress inactivated AMPKα2 subunit, and wild-type C57Bl/6 (WT) mice were randomized into sedentary groups or groups with access to running wheels. After 5 months, exercised KD mice exhibited shortened deceleration time compared with sedentary KD mice. In left ventricular tissue, the ratio of phosphorylated AMPKαThr172:total AMPKα was 65% lower (P < 0.05) in KD mice compared with WT mice. The left ventricle of KD mice had 37% lower levels of SERCA2a compared with WT mice. Although exercise increased SERCA2a protein levels in WT mice by 53%, this response of exercise was abolished in exercised KD mice. Exercise training reduced total phospholamban protein content by 23% in both the WT and KD mice but remained 20% higher overall in KD mice. Collectively, these data suggest that AMPKα influences SERCA2a and phospholamban protein content in the sedentary and exercised heart, and that exercise-induced changes in SERCA2a protein are dependent on AMPKα function.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".