Development of an SRM method for absolute quantitation of MYDGF/C19orf10 protein
Bibliographic record
Abstract
PURPOSE: To develop a MS-based selected reaction monitoring (SRM) assay for quantitation of myeloid-derived growth factor (MYDGF) formerly chromosome 19 open reading frame (C19orf10). EXPERIMENTAL DESIGN: Candidate reporter peptides were identified in digests of recombinant MYDGF. Isotopically labeled forms of these reporter peptides were employed as internal standards for assay development. Two reference peptides were selected SYLYFQTFFK and GAEIEYAMAYSK with respective LOQ of 42 and 380 attomole per injection. RESULTS: Application of the assay to human serum and synovial fluid determined that the assay sensitivity was reduced and quantitation was not achievable. However, the partial depletion of albumin and immunoglobulin from synovial fluids provided estimates of 300-650 femtomoles per injection (0.7-1.6 nanomolar (nM) fluid concentrations) in three of the six samples analyzed. CONCLUSIONS AND CLINICAL RELEVANCE: A validated sensitive assay for the quantitation of MYDGF in biological fluids was developed. However, the endogenous levels of MYDGF in such fluids are at or below the current levels of quantitation. The levels of MYDGF are lower than those previously reported using an ELISA. The current results suggest that additional steps may be required to remove high abundance proteins or to enrich MYDGF for SRM-based quantitation.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".