Quantification of Urinary Albumin by Using Protein Cleavage and LC-MS/MS
Bibliographic record
Abstract
BACKGROUND: Urinary albumin excretion is a sensitive diagnostic and prognostic marker for renal disease. Therefore, measurement of urinary albumin must be accurate and precise. We have developed a method to quantify intact urinary albumin with a low limit of quantification (LOQ). METHODS: We constructed an external calibration curve using purified human serum albumin (HSA) added to a charcoal-stripped urine matrix. We then added an internal standard, (15)N-labeled recombinant HSA ((15)NrHSA), to the calibrators, controls, and patient urine samples. The samples were reduced, alkylated, and digested with trypsin. The concentration of albumin in each sample was determined by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and linear regression analysis, in which the relative abundance area ratio of the tryptic peptides (42)LVNEVTEFAK(51) and (526)QTALVELVK(534) from albumin and (15)NrHSA were referenced to the calibration curve. RESULTS: The lower limit of quantification was 3.13 mg/L, and the linear dynamic range was 3.13-200 mg/L. Replicate digests from low, medium, and high controls (n = 5) gave intraassay imprecision CVs of 2.8%-11.0% for the peptide (42)LVNEVTEFAK(51), and 1.9%-12.3% for the (526)QTALVELVK(534) peptide. Interassay imprecision of the controls for a period of 10 consecutive days (n = 10) yielded CVs of 1.5%-14.8% for the (42)LVNEVTEFAK(51) peptide, and 6.4%-14.1% for the (526)QTALVELVK(534) peptide. For the (42)LVNEVTEFAK(51) peptide, a method comparison between LC-MS/MS and an immunoturbidometric method for 138 patient samples gave an R(2) value of 0.97 and a regression line of y = 0.99x + 23.16. CONCLUSIONS: Urinary albumin can be quantified by a protein cleavage LC-MS/MS method using a (15)NrHSA internal standard. This method provides improved analytical performance in the clinically relevant range compared to a commercially available immunoturbidometric assay.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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 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".