Liquid chromatography-mass spectrometric method for the simultaneous analysis of branched-chain amino acids and their ketoacids from dried blood spot as secondary analytes for the detection of maple syrup urine disease
Bibliographic record
Abstract
Background: Maple syrup urine disease (MSUD) is an aminoacidopathy caused by a defective branched-chain alpha-ketoacid dehydrogenase complex, leading to the accumulation of branched-chain amino acids (BCAAs) and their respective keto acids (BCKAs). A comprehensive test was developed to measure BCAAs and BCKAs using LC-MS from dried blood spot (DBS) samples for the diagnosis and prevention of MSUD in newborns and infants. Methods: Analytes were extracted from DBS using a methanol:0.1 % v/v formic acid solution (75:25) containing internal standards and analyzed on a Luna PFP column (150 mm × 4.6 mm, 3 µm) at a flow rate of 0.3 mL/min. The method was validated for linearity, accuracy, precision, recovery, carry-over, matrix effect, hematocrit, blood volume, and punch position effects. Biomarker stability in the matrix and stock solution was assessed. Correlation with the plasma method was determined using Pearson's correlation coefficient and Bland-Altman analysis. The method established reference ranges for the Udupi district population in South India. Results: > 0.99), with a lower limit of detection at 2 µM (BCAA) and 1 µM (BCKA), and acceptable recovery of QC samples. Hematocrit, blood volume, punch position, and storage condition effects were within acceptable limits. Correlation and Bland-Altman analysis showed strong interconvertibility between plasma and DBS assays. Reference ranges for leucine, isoleucine, valine, KIC, KIV, and KMV were established. Conclusion: The developed DBS method, requiring no derivatization and involving simple sample preparation with short run times, is a cost-effective and reliable approach for the confirmatory diagnosis of MSUD.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".