Improved diagnostics lead to identification of three new patients with congenital disorder of glycosylation-Ip
Bibliographic record
Abstract
Congenital disorders of glycosylation (CDG) comprise a clinically and biochemically heterogeneous group of monogenetic-inherited, multisystemic diseases that affect the biosynthesis of N- and/or O-glycans linked to glycoconjugates. Recently, we identified the first patient with a defect in the cytosolic-orientated GDP-mannose:Man(3-4) GlcNAc(2)-PP-dolichol alpha-1,2-mannosyltransferase (ALG11), who presented an accumulation of shortened dolichol-linked oligosaccharides leading to CDG-Ip (ALG11-CDG). Here we describe an improved metabolic labeling method that allowed the identification of three new CDG-Ip cases that were missed so far in routine diagnostics. Although all CDG-Ip patients carry different mutations in the ALG11 gene, they share a variety of clinical syndromes like an unremarkable prenatal period followed by developmental delay, psychomotor, and mental retardation, strabismus convergens and seizures occurring in the first year of life.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".