Absolute quantitation of acetaminophen‐modified human serum albumin in acute liver failure patients by liquid chromatography/tandem mass spectrometry
Bibliographic record
Abstract
RATIONALE: Acetaminophen (APAP) is a well-known analgesic, deemed a very safe over-the-counter medication. However, it is also the main cause of acute liver failure (ALF) in the Western world, via the formation of its reactive metabolite, N-acetyl p-benzoquinone imine (NAPQI), and its covalent attachment to liver proteins. The aim of this study was to develop a sensitive and robust quantitative assay to monitor APAP-protein binding to human serum albumin (HSA) in patient samples. METHODS: A combination of isotope dilution, peptic digestion and solid-phase extraction coupled to liquid chromatography/multiple reaction monitoring (LC/MRM) was employed. An external calibration curve with surrogate modified protein spiked into blank serum was used for absolute quantitation. Samples were analyzed by LC/MRM to measure the modified active site peptide of HSA. The LC/MRM assay was validated and successfully applied to serum samples from patients suffering from APAP-induced ALF. RESULTS: Accuracy ranged from 83.8-113.3%, within-run coefficient of variation (CV) ranged from 0.3-6.9%, and total CVs from 1.6-10.6%. Patient samples ranged from 0.12-3.91 nmol/mL NAPQI-HSA; in-between the assay dynamic range of 0.11-50.13 nmol/mL serum. In vivo median concentrations were found to be 0.62 nmol/mL and 0.91 nmol/mL for non-spontaneous survivors (n = 25) and individuals with irreversible liver damage (n = 10), respectively (p-value = 0.028), demonstrating significant potential as a biomarker for ALF outcome. CONCLUSIONS: A fast and sensitive assay was developed to accurately quantify NAPQI-HSA as a biomarker for APAP-related covalent binding in human serum.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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".