Retracted: MyoD-dependent regulation of NF-κB activity couples cell-cycle withdrawal to myogenic differentiation
Post-publication record
Source: Retraction Watch, joined by DOI. OpenAlex records retraction as is_retracted, a boolean over a state space with at least four values, so it cannot express an expression of concern, a correction or a reinstatement; it reports them as false, which reads as “fine”.
Bibliographic record
Abstract
BACKGROUND: Mice lacking MyoD exhibit delayed skeletal muscle regeneration and markedly enhanced numbers of satellite cells. Myoblasts isolated from MyoD-/- myoblasts proliferate more rapidly than wild type myoblasts, display a dramatic delay in differentiation, and continue to incorporate BrdU after serum withdrawal. METHODS: Primary myoblasts isolated from wild type and MyoD-/- mutant mice were examined by microarray analysis and further characterized by cell and molecular experiments in cell culture. RESULTS: We found that NF-κB, a key regulator of cell-cycle withdrawal and differentiation, aberrantly maintains nuclear localization and transcriptional activity in MyoD-/- myoblasts. As a result, expression of cyclin D is maintained during serum withdrawal, inhibiting expression of muscle-specific genes and progression through the differentiation program. Sustained nuclear localization of cyclin E, and a concomitant increase in cdk2 activity maintains S-phase entry in MyoD-/- myoblasts even in the absence of mitogens. Importantly, this deficit was rescued by forced expression of IκBαSR, a non-degradable mutant of IκBα, indicating that inhibition of NF-κB is sufficient to induce terminal myogenic differentiation in the absence of MyoD. CONCLUSION: MyoD-induced cytoplasmic relocalization of NF-κB is an essential step in linking cell-cycle withdrawal to the terminal differentiation of skeletal myoblasts. These results provide important insight into the unique functions of MyoD in regulating the switch from progenitor proliferation to terminal differentiation.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.004 |
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".