A simple and robust LC‐MS/MS method for quantification of free 3‐nitrotyrosine in human plasma from patients receiving on‐pump CABG surgery
Bibliographic record
Abstract
We have developed a simple, sensitive, and robust liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) method to determine free 3-nitrotyrosine concentrations in human plasma of patients receiving on-pump coronary artery bypass grafting surgery. A one-step solid-phase extraction protocol was optimized to enrich the analyte at low nanomolar concentrations. The processed samples were analyzed by LC-MS/MS with a 2.1 × 100 mm Kinetex PFP column and a triple quadrupole mass spectrometer. The method was validated for 3-nitrotyrosine concentrations close to real patient plasma levels. The relative standard deviations or relative errors of the intraday and interday determinations were all within 10%. Limit of detection and limit of quantitation were determined to be 0.034 nM and 0.112 nM, respectively, while lower limit of quantitation was below 0.625 nM. No deterioration of the column performance was noticed after running a large number of patient samples. The results showed that the 3-nitrotyrosine concentrations in coronary sinus plasma samples were elevated after cardiopulmonary bypass (CPB) procedure. The pre-CPB and post-CPB concentrations of 3-nitrotyrosine in patient plasmas were 1.494 ± 0.107 nM and 2.167 ± 0.177 nM (mean ± SEM), respectively. Application of this method to more patients in clinical studies may help validate 3-nitrotyrosine as a meaningful biomarker for nitrosative stress and link patient characteristics, clinical outcomes, and cardioprotective treatments to endogenous nitrosative stress levels.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".