Calcium ATPase (PMCA) and GLUT-4 Upregulation in the Transverse Tubule Membrane of Skeletal Muscle from a Rat Model of Chronic Heart Failure
Bibliographic record
Abstract
Intolerance to exercise is a symptom associated with chronic heart failure (CHF) resulting in SM waste and weakness in humans. The effect of CHF on skeletal muscle (SM) arose from experimental evidence in rat models to explain the underlying mechanism. We investigated SM mechanical and metabolic properties in sham rats and with coronary ligation-induced CHF. After twelve weeks of CHF, rats were catheterized to measure right auricular pressure, SM mechanical properties, SERCA-ATPase activity and plasma membrane Ca2+-ATPase (PMCA) hydrolytic activity in isolated sarcoplasmic reticulum (SR) and transverse tubule (TT membrane), respectively, in the sham and CHF. The right auricular pressure and plasma nitrite concentration in CHF increased two-fold with respect to the sham. Pleural effusion and ascites were detected in CHF, confirming CHF. SERCA activity was conserved in CHF. In TT membranes from CHF, the glucose transporter GLUT4 increased seven-fold, and the PMCA hydrolytic activity increased five-fold, but in isolated muscle, the mechanical properties were unaffected. The absence of a deleterious effect of coronary ligation-induced CHF in the rat model on SM could be explained by the increased activity of PMCA and increased presence of GLUT-4 on the TT membrane, which may be involved in the mechanical outcome of the EDL.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".