Proteomic Identification of Cellular Protease Substrates Using Isobaric Tags for Relative and Absolute Quantification (iTRAQ)
Bibliographic record
Abstract
Identification of protease substrates is essential to identify and understand the functional consequences of normal and dysregulated proteolysis in disease on the proteome. Isobaric tags for relative and absolute quantification (iTRAQ) can be used to identify novel protease substrates in the cellular context. An amine-targeted iTRAQ tag labels tryptic peptides generated from the proteins and protease cleavage products of secreted proteins, as well as protein domains shed from the cell membrane or pericellular matrix of protease-transfected cells that have accumulated in conditioned medium; a second iTRAQ tag is used for control cells. MS/MS fragmentation enables sequencing of the pooled pairs of differently labeled but identical peptides and generates a low mass signature ion peak unique for each label. This signature ion peak identifies the peptides originating from the protease-transfected or control cells; comparison of the peak areas enables relative quantitation of the peptide between the samples.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".