A Streamlined Method for Quantification of Apolipoprotein A1 in Human Plasma by LC-MS/MS
Bibliographic record
Abstract
To the Editor: Apolipoprotein A1 (apoA1) is the major protein component of high-density lipoprotein particles in blood, and its concentration in serum and plasma is a marker of atherosclerotic cardiovascular diseases. Clinical laboratories commonly use immunometric methods to measure apoA1; however, an alternative approach, LC-MS/MS, has been proposed (1–3). Uptake of these LC-MS/MS methods for routine testing in a clinical setting has been challenging owing to complex and time-intensive sample preparation work flows. Overnight digestion has been previously applied for quantification of apoA1 by use of proteolytic peptides VQPYLDDFQK, DYVSQFEGSALGK, and THLAPYSDELR (1, 2) and a 3-h digest using peptide VQPYLDDFQK (3). Toward the design of a streamlined work flow for implementation in a clinical laboratory, we simplified sample preparation by using only additive steps and eliminating the use of chemical denaturants, reduction, and alkylation. Herein we demonstrate that such a simple and rapid work flow, targeting a fast-forming proteolytic peptide, can be used to develop a quantitative apoA1 LC-MS/MS assay in agreement with an established immunonephelometric method.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 0.010 |
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".