Distinct regions in the 3′ untranslated region are responsible for targeting and stabilizing utrophin transcripts in skeletal muscle cells
Bibliographic record
Abstract
In this study, we have sought to determine whether utrophin transcripts are targeted to a distinct subcellular compartment in skeletal muscle cells, and have examined the role of the 3' untranslated region (UTR) in regulating the stability and localization of utrophin transcripts. Our results show that utrophin transcripts associate preferentially with cytoskeleton-bound polysomes via actin microfilaments. Because this association is not evident in myoblasts, our findings also indicate that the localization of utrophin transcripts with cytoskeleton-bound polysomes is under developmental influences. Transfection of LacZ reporter constructs containing the utrophin 3'UTR showed that this region is critical for targeting chimeric mRNAs to cytoskeleton-bound polysomes and controlling transcript stability. Deletion studies resulted in the identification of distinct regions within the 3'UTR responsible for targeting and stabilizing utrophin mRNAs. Together, these results illustrate the contribution of posttranscriptional events in the regulation of utrophin in skeletal muscle. Accordingly, these findings provide novel targets, in addition to transcriptional events, for which pharmacological interventions may be envisaged to ultimately increase the endogenous levels of utrophin in skeletal muscle fibers from Duchenne muscular dystrophy (DMD) patients.
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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) | 0.000 | 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) | 0.001 | 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".