DEPDC1B is a key regulator of myoblast proliferation in mouse and man
Bibliographic record
Abstract
OBJECTIVES: DISHEVELLED, EGL-10, PLECKSTRIN (DEP) domain-containing 1B (DEPDC1B) promotes dismantling of focal adhesions and coordinates detachment events during cell cycle progression. DEPDC1B is overexpressed in several cancers with expression inversely correlated with patient survival. Here, we analysed the role of DEPDC1B in the regulation of murine and human skeletal myogenesis. MATERIALS AND METHODS: Expression dynamics of DEPDC1B were examined in murine and human myoblasts and rhabdomyosarcoma cells in vitro by RT-qPCR and/or immunolabelling. DEPDC1B function was mainly tested via siRNA-mediated gene knockdown. RESULTS: DEPDC1B was expressed in proliferating murine and human myoblasts, with expression then decreasing markedly during myogenic differentiation. SiRNA-mediated knockdown of DEPDC1B reduced myoblast proliferation and induced entry into myogenic differentiation, with deregulation of key cell cycle regulators (cyclins, CDK, CDKi). DEPDC1B and β-catenin co-knockdown was unable to rescue proliferation in myoblasts, suggesting that DEPDC1B functions independently of canonical WNT signalling during myogenesis. DEPDC1B can also suppress RHOA activity in some cell types, but DEPDC1B and RHOA co-knockdown actually had an additive effect by both further reducing proliferation and enhancing myogenic differentiation. DEPDC1B was expressed in human Rh30 rhabdomyosarcoma cells, where DEPDC1B or RHOA knockdown promoted myogenic differentiation, but without influencing proliferation. CONCLUSION: DEPDC1B plays a central role in myoblasts by driving proliferation and preventing precocious myogenic differentiation during skeletal myogenesis in both mouse and human.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.004 | 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".