Phospholamban is a Potential Regulator of Skeletal Muscle and Whole‐Body Metabolism
Bibliographic record
Abstract
Phospholamban (PLN) is a known inhibitor of the sarco(endo)plasmic reticulum Ca 2+ ‐ATPase (SERCA) pump and modulator of muscular contractility. We have previously shown that the PLN homologue, sarcolipin, is an uncoupler of SERCA function, increasing the energy demand of skeletal muscle to pump Ca 2+ . Here, we sought to determine whether PLN has a similar effect on SERCA energetics and metabolism. To examine this, SERCA function and whole‐body metabolic rate were measured in PLN knock‐out mice and wild‐type (WT) littermates (n = 5–6/group). Ca 2+ ‐dependent ATPase activity was measured in left ventricle (LV) and soleus (SOL) homogenates in both the absence (i.e. presence of the Ca 2+ ionophore A23187) and presence (i.e. no ionophore) of a Ca 2+ gradient. The ionophore ratio, an indication of membrane leak, was calculated by dividing maximal activity in the presence of ionophore by that without. Indirect calorimetry was also used to measure whole‐body metabolic rate. In the presence of ionophore, maximal SERCA activity was 25% and 33% greater with PLN ablation in LV ( P < 0.05) and SOL ( P < 0.01), respectively, while no differences were found in the absence of ionophore in either LV ( P = 0.82) or SOL ( P = 0.11). The LV ionophore ratio was 22% lower in WT mice ( P < 0.05), suggesting that the presence of PLN is associated with membrane leak. While not statistically significant ( P = 0.21), the SOL ionophore ratio was 11% lower in WT mice. Lastly, whole‐body energy expenditure tended ( P = 0.07) to be lower with PLN ablation. Together, these findings suggest that PLN may alter SERCA pumping energetics and whole‐body metabolic rate. Support or Funding Information Canadian Institutes for Health Research
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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".