Multiple regions within junctin drive its interaction with calsequestrin-1 and its localization to triads in skeletal muscle
Bibliographic record
Abstract
Junctin is a transmembrane protein of striated muscles, located at the junctional sarcoplasmic reticulum (SR). It is characterized by a luminal C-terminal tail, through which it functionally interacts with calsequestrin and the ryanodine receptor (RyR). Interaction with calsequestrin was ascribed to the presence of stretches of charged amino acids (aa). However, the regions able to bind calsequestrin have not been defined in detail. We report here that, in non-muscle cells, junctin and calsequestrin assemble in long linear regions within the endoplasmic reticulum, mirroring the formation of calsequestrin polymers. In differentiating myotubes, the two proteins colocalize at triads, where they assemble with other proteins of the junctional SR. By performing GST pull-down assays with distinct regions of the junctin tail, we identified two KEKE motifs that can bind calsequestrin. In addition, stretches of charged aa downstream these motifs were found to also bind calsequestrin and the RyR. Deletion of even one of these regions impaired the ability of junctin to localize at the junctional SR, suggesting that interaction with other proteins at this site represents a key element in junctin targeting.
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.
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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".