Neonatal Mass Urine Screening Approach for Early Detection of Mucopolysaccharidoses by UPLC-MS/MS
Bibliographic record
Abstract
Mucopolysaccharidoses (MPSs) are lysosomal storage disorders caused by deficiencies of enzymes involved in the catabolism of glycosaminoglycans (GAGs). Various treatments such as enzyme replacement therapy and/or hematopoietic stem cell transplant are available for MPSs. Early initiation of treatment improves the outcome and delays the onset of symptoms, highlighting the need for newborn screening for MPSs. The main objective of this project was to devise and validate a multiplex urine filter paper method for GAG analysis using a tandem mass spectrometry (MS/MS) approach to screen newborns for MPSs. Eluted urine samples from 21-day-old newborns were evaporated and a methanolysis reaction was performed. Samples were resuspended and analyzed using a UPLC-MS/MS system. A one-minute chromatographic method allowed the absolute quantification of heparan sulfate (HS), dermatan sulfate (DS), and creatinine. Method validation revealed high precision (< 9% relative standard deviation) and accuracy (< 7% bias) for all analytes. The reference values normalized to creatinine obtained by the analysis of five hundred 21-day-old newborn urine samples were 34.6 +/-6.2 mg/mmol of creatinine and 17.3 +/-3.9 mg/mmol of creatinine for HS and DS, respectively. We present a rapid and efficient method for populational newborn urine screening using MS/MS, which could also be applied to high-risk screening.
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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 | 0.001 |
| 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".