Phospholamban deficiency does not alter skeletal muscle SERCA pumping efficiency or predispose mice to diet-induced obesity
Bibliographic record
Abstract
The sarco(endo)plasmic reticulum Ca2+-ATPase (SERCA) pump is a major contributor to skeletal muscle Ca2+homeostasis and metabolic rate. SERCA activity can become adaptively uncoupled by its regulator sarcolipin (SLN) to increase the energy demand of Ca2+pumping, preventing excessive obesity and glucose intolerance in mice. Several other SERCA regulators bear structural and functional resemblance to SLN, including phospholamban (PLN). Here, we sought to examine whether endogenous levels of skeletal muscle PLN control SERCA Ca2+pumping efficiency and whole body metabolism. Using PLN-null mice ( Pln−/−), we found that soleus (SOL) muscle’s SERCA pumping efficiency (measured as an apparent coupling ratio: Ca2+uptake/ATP hydrolysis) was unaffected by PLN. Expression of Ca2+-handling proteins within the SOL, including SLN, were comparable between Pln−/−and wild-type (WT) littermates, as were fiber-type characteristics. Not surprisingly then, Pln−/−mice developed a similar degree of diet-induced obesity and glucose intolerance as WT controls when given a “Western” high-fat diet. Lack of an excessively obesogenic phenotype of Pln−/−could not be explained by compensation from skeletal muscle SLN or brown adipose tissue uncoupling protein-1 content. In agreement with several other reports, our study lends support to the notion that PLN serves a functionally distinct role from that of SLN in skeletal muscle physiology.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".