Sarcolipin Inhibits Polymerization of Phospholamban to Induce Superinhibition of Sarco(endo)plasmic Reticulum Ca2+-ATPases (SERCAs)
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Bibliographic record
Abstract
Sarcolipin (SLN), a regulator of the sarco(endo)plasmic reticulum Ca(2+)-ATPase of fast-twitch skeletal muscle (SERCA1a), is also expressed in cardiac and slow-twitch skeletal muscles where phospholamban (PLN) and SERCA2a are expressed. Co-expression in HEK-293 cells of SLN tagged N-terminally with a FLAG epitope (NF-SLN), PLN, and SERCAs followed by measurement of the Ca(2+) dependence of Ca(2+) transport activity in isolated microsomal fractions showed that NF-SLN can reduce the apparent Ca(2+) affinity of both SERCA1a (DeltaK(Ca) = -0.22 +/- 0.01 pCa units) and SERCA2a (DeltaK(Ca) = -0.37 +/- 0.04 pCa units). When SERCA1a or SERCA2a were co-expressed with both NF-SLN and PLN, inhibition was synergistic, reducing DeltaK(Ca) by about -1.0 pCa units. Co-immunoprecipitation showed that NF-SLN increased the binding of PLN to SERCA, whereas PLN did not increase the binding of NF-SLN to SERCA. Elevated Ca(2+) dissociates both PLN and NF-SLN from their complexes with both SERCA1a and SERCA2a, but NF-SLN induced resistance to Ca(2+) dissociation of the PLN.SERCA complex. Co-immunoprecipitation of PLN and NF-SLN without SERCA showed that NF-SLN binds directly to PLN and that NF-SLN inhibits the formation of PLN pentamers. Thus the ability of NF-SLN to elevate the content of PLN monomers can account, at least in part, for the superinhibitory effects of NF-SLN in the presence of PLN.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it