Identification of Secreted Proteins during Skeletal Muscle Development
Bibliographic record
Abstract
The differentiation program of skeletal muscle cells is exquisitely sensitive to secreted proteins. We developed a strategy to maximize the discovery of secreted proteins, using mass spectrometry-based proteomics, from cultured muscle cells, C2C12, grown in a serum-free medium. This strategy led to the identification of 80 nonredundant proteins, of which 27 were secretory proteins that were identified with a minimum of two tryptic peptides. A number of the identified secretory proteins are involved in extracellular matrix remodeling, cellular proliferation, migration, and signaling. A putative network of proteins involving matrix metalloproteinase 2, SPARC, and cystatin C that all interact with TGFβ signaling has been postulated to contribute toward a functional role in the myogenic differentiation program. Keywords: Conditioned media (CM) • One-dimensional gel electrophoresis (1D-SDS-PAGE) • Matrix-assisted laser desorption/ionization quadrupole time-of-fight mass spectrometry (MALDI-QqTOF MS) • Extracelluar matrix (ECM) • Matrix metalloproteinase-2 (MMP2) • Secreted protein rich in cysteine protein (SPARC) • Transforming growth factor-beta (TGFβ)
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".