Can Muscle Sarcoplasmic Reticulum Ca2+-ATPase Defects Be Implicated In Exercise Intolerance In Chronic Heart Failure?
Bibliographic record
Abstract
PURPOSE The purpose of this study was to determine the effects of experimental chronic heart failure (CHF) on maximal sarcoplasmic reticulum Ca2+-ATPase activity (Vmax) and Hill co-efficient (nH) in soleus (SOL), red gastrocnemius (RG) and white gastrocnemius (WG) and left ventricle (LV). METHODS Experimental CHF following ligation of the left main coronary artery in adult rats was confirmed by elevations (p < 0.05) in left-ventricle to body wt ratios (0.168±0.04 vs 0.186±0.07 g/g.100) in CHF compared to controls (CON). RESULTS Comparisons between CHF (n = 8) and CON (n = 8) indicated reduced (p < 0.05) Vmax (μmol.g protein−1·min−1) in SOL (197±22 vs 152±20), RG (399±8.2 vs 314±25) and WG (584±47 vs 449±59) in CHF. The nH was not different between CHF and CON for any of the muscles examined. The lower Vmax was accompanied by increases (p < 0.05) in SERCA 2 (% standard) in RG (38.7±10 vs 56.1±7.6) and WG (19.4±3.0 vs 27.0±2.2) only. No changes were observed in SERCA 1, as measured by Western blotting techniques. Reductions in Vmax were observed for LV (207±22 vs 162±14) in the absence of change in SERCA 2. CONCLUSION These results suggest that altered protein levels cannot explain the reduced Vmax observed in CHF. The results also suggest that defects in Ca2+-cycling may be involved in weakness and fatigue in CHF. Supported by Heart and Stroke Foundation (Ontario)
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| 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".