Proteomic Identification of Cellular Protease Substrates Using Isobaric Tags for Relative and Absolute Quantification (iTRAQ)
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it