The regulation of sarco(endo)plasmic reticulum calcium-ATPases (SERCA)
Bibliographic record
Abstract
The sarco(endo)plasmic reticulum calcium ATPase (SERCA) is responsible for transporting calcium (Ca(2+)) from the cytosol into the lumen of the sarcoplasmic reticulum (SR) following muscular contraction. The Ca(2+) sequestering activity of SERCA facilitates muscular relaxation in both cardiac and skeletal muscle. There are more than 10 distinct isoforms of SERCA expressed in different tissues. SERCA2a is the primary isoform expressed in cardiac tissue, whereas SERCA1a is the predominant isoform expressed in fast-twitch skeletal muscle. The Ca(2+) sequestering activity of SERCA is regulated at the level of protein content and is further modified by the endogenous proteins phospholamban (PLN) and sarcolipin (SLN). Additionally, several novel mechanisms, including post-translational modifications and microRNAs (miRNAs) are emerging as integral regulators of Ca(2+) transport activity. These regulatory mechanisms are clinically relevant, as dysregulated SERCA function has been implicated in the pathology of several disease states, including heart failure. Currently, several clinical trials are underway that utilize novel therapeutic approaches to restore SERCA2a activity in humans. The purpose of this review is to examine the regulatory mechanisms of the SERCA pump, with a particular emphasis on the influence of exercise in preventing the pathological conditions associated with impaired SERCA function.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".