Simultaneous Quantification of Human Cardiac α- and β-Myosin Heavy Chain Proteins by MALDI-TOF Mass Spectrometry
Bibliographic record
Abstract
We have developed a novel method for quantifying protein isoforms, in both relative and absolute terms, based on MALDI-TOF mass spectrometry. The utility of the approach is demonstrated by quantifying the alpha and beta protein isoforms of myosin heavy chain (MyHC) in human atrial tissue. Alpha-MyHC (726-741) and beta-MyHC (724-739) were identified as isoform-specific tryptic peptides. A calibration curve was constructed by plotting ion current ratios against molar ratios of the two peptides prepared synthetically. MyHC was digested by trypsin and the ion current ratio determined for the two tryptic peptides. The ion current ratio was converted to the peptide ratio and hence the isoform ratio by reference to the standard curve. The accuracy of the method was confirmed by a comparison between these results and those determined by an established method of MyHC isoform ratio determination. So that the molar ratio could be converted to absolute values, a third peptide, an analogue of the two peptides being measured, was synthesized for use as an internal standard (IS). The measured ion current ratios of synthetic alpha-MyHC (726-741), beta-MyHC (724-739), and IS peptides were used to generate standard curves. A known quantity of the IS was added to the MyHC digests. The measured ion current ratios were converted to the actual quantities of the isoform-specific peptides and hence the actual quantity of each protein isoform by reference to the standard curves. This method is of general applicability, especially when isoform quantification is required.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".