Diurnal Variation of Urinary Fabry Disease Biomarkers during Enzyme Replacement Therapy Cycles
Bibliographic record
Abstract
Fabry disease is an X-linked lysosomal storage disorder caused by mutations in the GLA gene encoding the α-galactosidase A enzyme. This enzyme cleaves the last sugar unit of glycosphingolipids, including globotriaosylceramide (Gb3), globotriaosylsphingosine (lyso-Gb3), and galabiosylceramide (Ga2). Enzyme impairment leads to substrate accumulation in different organs, vascular endothelia, and biological fluids. Enzyme replacement therapy (ERT) is a commonly used treatment. Urinary analysis of Gb3 isoforms (different fatty acid moieties), as well as lyso-Gb3 and its analogues, is a reliable way to monitor treatment. These analogues correspond to lyso-Gb3 with chemical modifications on the sphingosine moiety (−C2H4, −C2H4+O, −H2, −H2+O, +O, +H2O2, and +H2O3). The effects of sample collection time on urinary biomarker levels between ERT cycles were not previously documented. The main objective of this project was to analyze the aforementioned biomarkers in urine samples from seven Fabry disease patients (three treated males, three treated females, and one ERT-naïve male) collected twice a day (morning and evening) for 42 days (three ERT cycles). Except for one participant, our results show that the biomarker levels were generally more elevated in the evening. However, there was less variability in samples collected in the morning. No cyclic variations in biomarker levels were observed between ERT infusions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".