Proteome Dynamics during C2C12 Myoblast Differentiation
Bibliographic record
Abstract
Mouse-derived C2C12 myoblasts serve as an experimentally tractable model system for investigating the molecular basis of skeletal muscle cell specification and development. To examine the biochemical adaptations associated with myocyte formation comprehensively, we used large scale gel-free tandem mass spectrometry to monitor global proteome alterations throughout a time course analysis of the myogenic C2C12 differentiation program. The relative abundance of approximately 1,800 high confidence proteins was tracked across multiple time points using capillary scale multidimensional liquid chromatography coupled to high throughput shotgun sequencing. Hierarchical clustering of the resulting profiles revealed differential waves of expression of proteins linked to intracellular signaling, transcription, cytoarchitecture, adhesion, metabolism, and muscle contraction across the early, mid, and late stages of differentiation. Several hundred previously uncharacterized proteins were likewise detected in a stage-specific manner, suggesting novel roles in myogenesis and/or muscle function. These proteomic data are complementary to recent microarray-based studies of gene expression patterns in developing myotubes and provide a holistic framework for understanding how diverse biochemical processes are coordinated at the cellular level during skeletal muscle development.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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".