The Regulation of SERCA‐Type Pumps by Phospholamban and Sarcolipin
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Both sarcolipin (SLN) and phospholamban (PLN) lower the apparent affinity of either SERCA1a or SERCA2a for Ca(2+). Since SLN and PLN are coexpressed in the heart, interactions among these three proteins were investigated. When SERCA1a or SERCA2a were coexpressed in HEK-293 cells with both SLN and PLN, superinhibition resulted. The ability of SLN to elevate the content of PLN monomers accounts, at least in part, for the superinhibitory effects of SLN in the presence of PLN. To evaluate the role of SLN in skeletal muscle, SLN cDNA was injected directly into rat soleus muscle and force characteristics were analyzed. Overexpression of SLN resulted in significant reductions in both twitch and tetanic peak force amplitude and maximal rates of contraction and relaxation and increased fatigability with repeated electrical stimulation. Ca(2+) uptake in muscle homogenates was impaired, suggesting that overexpression of SLN may reduce the sarcoplasmic reticulum Ca(2+) store. SLN and PLN appear to bind to the same regulatory site in SERCA. However, in a ternary complex, PLN occupies the regulatory site and SLN binds to the exposed side of PLN and to SERCA.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| 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