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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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 teacher head, 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".