Combined Newborn Screening for Succinylacetone, Amino Acids, and Acylcarnitines in Dried Blood Spots
Bibliographic record
Abstract
BACKGROUND: Tyrosinemia type I (TYR 1) is a disorder causing early death if left untreated. Newborn screening (NBS) for this condition is problematic because determination of the diagnostic marker, succinylacetone (SUAC), requires a separate first-tier or only partially effective second-tier analysis based on tyrosine concentration. To overcome these problems, we developed a new assay that simultaneously determines acylcarnitines (AC), amino acids (AA), and SUAC in dried blood spots (DBS) by flow injection tandem mass spectrometry (MS/MS). METHODS: We extracted 3/16-inch DBS punches with 300 microL methanol containing AA and AC stable isotope-labeled internal standards. This extract was derivatized with butanol-HCl. In parallel, we extracted SUAC from the residual filter paper with 100 microL of a 15 mmol/L hydrazine solution containing the internal standard 13C5-SUAC. We combined the derivatized aliquots in acetonitrile for MS/MS analysis of AC and AA with additional SRM experiments for SUAC (m/z 155-137) and 13C5-SUAC (m/z 160-142). Analysis time was 1.2 min. RESULTS: SUAC was increased in retrospectively analyzed NBS samples of 11 TYR 1 patients (length of storage, 52 months to 1 week; SUAC range, 13-81 micromol/L), with Tyr concentrations ranging from 65 to 293 micromol/L in the original NBS analysis. The mean concentration of SUAC in 13 521 control DBS was 1.25 micromol/L. CONCLUSION: The inclusion of SUAC analysis into routine analysis of AC and AA allows for rapid and cost-effective screening for TYR 1 with no tangible risk of false-negative results.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".