Characterization of sarco(endo)plasmic reticulum Ca <sup>2+</sup> ‐ATPase (SERCA) expression and function in Zucker <i> <sup>fa/fa</sup> </i> obese rat skeletal muscle
Bibliographic record
Abstract
The purpose of this study was to characterize SERCA expression and function in extensor digitorum longus (EDL) and soleus (SOL) muscles from Zucker fa/fa obese (321±5 g) and lean (233±10 g) control rats ( n =6/group). The rate of Ca 2+ ‐uptake in EDL and SOL homogenates was measured spectrofluorometrically using Indo‐1. Maximal Ca 2+ ‐ATPase activity (Vmax) was determined using a 96‐well spectrophotometric assay. When comparing Zucker to control rats, there were no differences (p>0.05) in Vmax in either EDL (592±40 vs. 536±31 μmol/g/min) or SOL (120±12 vs. 120±13). However, Ca 2+ ‐uptake rates were higher (p<0.05) in the SOL from Zucker fa/fa rats (4.10±0.30 μmol/g/min) when compared to control animals (2.92±0.61 μmol/g/min). In addition, the rate of Ca 2+ leak from Ca 2+ loaded SR vesicles in the SOL homogenate was lower (p<0.05) in Zucker fa/fa rats compared to controls. These observations were not mirrored in the EDL. Furthermore, the SERCA1a and SERCA2a contents were not different between genotypes in either tissue. These data suggest that the reduced rate of Ca 2+ leak in slow‐twitch skeletal muscle from Zucker fa/fa rats improves Ca 2+ ‐pumping efficiency and may result in a lower energy cost of Ca 2+ cycling. Research supported by NSERC Canada
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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) | 0.000 | 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) | 0.001 | 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".