A NEW CAPILLARY ZONE ELECTROPHORESIS METHOD FOR THE SCREENING OF CONGENITAL DISORDERS OF GLYCOSYLATION (CDG)
Bibliographic record
Abstract
Background The Congenital Disorders of Glycosylation (CDG) are an expanding group of metabolic diseases with a broad clinical presentation. We sought to validate a new Capillary Zone Electrophoresis (CZE) method (Sebia CAPILLARYS™ CDT) to screen for CDG. Methods We analyzed 119 serum samples from children of varying ages and of both sexes to establish a reference range of transferrin glycoforms including CDT (Carbohydrate Deficient Transferrin). We then studied serums from 8 known CDG patients and compared the CZE results to the isoelectric focusing (IEF) profiles. We also analyzed serums after extraction from spotted Guthrie cards. Results The mean (SD) percentage of transferrin glycoforms is 18.5 (4.4), 78.5 (4.2), 2.5 (1.3) and 0.6 (0.3) for penta-, tetra-, trisialotransferrin and CDT, respectively. There is no statistically significant difference between the different age groups analyzed (0-5, 6-11, 12-15, 16-18, and > 18 years) or between sexes. We observed a good correlation between the CZE and IEF profiles with both fresh serum and serum extracted from Guthrie cards. Conclusions The Sebia CAPILLARYS™ CDT system is a simple and reliable method to screen for CDG in pediatric and adult patients with an unexplained clinical syndrome, particularly when the nervous system is involved.
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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 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".