Absolute Quantitation of NAPQI-Modified Rat Serum Albumin by LC–MS/MS: Monitoring Acetaminophen Covalent Binding<i>in Vivo</i>
Bibliographic record
Abstract
Acetaminophen is known to cause hepatoxicity via the formation of a reactive metabolite, N-acetyl p-benzoquinone imine (NAPQI), as a result of covalent binding to liver proteins. Serum albumin (SA) is known to be covalently modified by NAPQI and is present at high concentrations in the bloodstream and is therefore a potential biomarker to assess the levels of protein modification by NAPQI. A newly developed method for the absolute quantitation of serum albumin containing NAPQI covalently bound to its active site cysteine (Cys34) is described. This optimized assay represents the first absolute quantitation of a modified protein, with very low stoichiometric abundance, using a protein-level standard combined with isotope dilution. The LC-MS/MS assay is based on a protein standard modified with a custom-designed reagent, yielding a surrogate peptide (following digestion) that is a positional isomer to the target peptide modified by NAPQI. To illustrate the potential of this approach, the method was applied to quantify NAPQI-modified SA in plasma from rats dosed with acetaminophen. The resulting method is highly sensitive (capable of quantifying down to 0.0006% of total RSA in its NAPQI-modified form) and yields excellent precision and accuracy statistics. A time-course pharmacokinetic study was performed to test the usefulness of this method for following acetaminophen-induced covalent binding at four dosing levels (75-600 mg/kg IP), showing the viability of this approach to directly monitor in vivo samples. This approach can reliably quantify NAPQI-modified albumin, allowing direct monitoring of acetaminophen-related covalent binding.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".