Contribution of tandem mass spectrometry to the diagnosis of lysosomal storage disorders
Bibliographic record
Abstract
Tandem mass spectrometry (MS/MS) is a highly sensitive and specific technique. Thanks to the development of triple quadrupole analyzers, it is becoming more widely used in laboratories working in the field of inborn errors of metabolism. We review here the state of the art of this technique applied to the diagnosis of lysosomal storage disorders (LSDs) and how MS/MS has changed the diagnostic rationale in recent years. This fine technology brings more sensitive, specific, and reliable methods than the previous biochemical ones for the analysis of urinary glycosaminoglycans, oligosaccharides, and sialic acid. In sphingolipidoses, the quantification of urinary sphingolipids (globotriaosylceramide, sulfatides) is possible. The measurement of new plasmatic biomarkers such as oxysterols, bile acids, and lysosphingolipids allows the screening of many sphingolipidoses and related disorders (Niemann-Pick type C), replacing tedious biochemical techniques. Applied to amniotic fluid, a more reliable prenatal diagnosis or screening of LSDs is now available for fetuses presenting with antenatal manifestations. Applied to enzyme measurements, it allows high throughput assays for the screening of large populations, even newborn screening. The advent of this new method can modify the diagnostic rationale behind LSDs.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".