Targeted comparative proteomics by liquid chromatography/matrix‐assisted laser desorption/ionization triple‐quadrupole mass spectrometry
Bibliographic record
Abstract
Here we report the first application of a matrix-assisted laser desorption/ionization (MALDI) triple-quadrupole mass spectrometer for targeted proteomics. Employing an amine-specific isotopic labelling approach, the technique was validated using five randomly selected bovine serum albumin peptides differentially labelled at known ratios. An indirect benefit of the isotopic labelling technique is a significant enhancement of the a1 ion in tandem mass (MS/MS) spectra of all peptides studied. Therefore, the a1 ion was selected as the fragment ion for multiple reaction monitoring (MRM) in all cases, eliminating tedious method development and optimization. Accurate quantification was achieved with an average relative standard deviation (RSD) of 5% (n = 5) and a detection limit of 14 amol. The technique was then applied to validate an important virulence biomarker of the fungal pathogen Candida albicans, which was not accurately quantified using global proteomics experiment employing two-dimensional liquid chromatography/electrospray ionization tandem mass spectrometry (2D-LC/ESI)-MS/MS. Using LC/MALDI-MRM analysis of five tryptic peptides, the protein PHR1 was found to be upregulated in the hyphal (pathogenic) form of C. albicans by a factor of 7.7 +/- 0.8.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".