Wolcott-Rallison Syndrome
Bibliographic record
Abstract
Wolcott-Rallison syndrome (WRS) is a rare autosomal-recessive disorder characterized by the association of permanent neonatal or early-infancy insulin-dependent diabetes, multiple epiphyseal dysplasia and growth retardation, and other variable multisystemic clinical manifestations. Based on genetic studies of two inbred families, we previously identified the gene responsible for this disorder as EIF2AK3, the pancreatic eukaryotic initiation factor 2alpha (eIF2alpha) kinase. Here, we have studied 12 families with WRS, totalling 18 cases. With the exception of one case, all patients carried EIF2AK3 mutations resulting in truncated or missense versions of the protein. Exclusion of EIF2AK3 mutations in the one patient case was confirmed by both linkage and sequence data. The activities of missense versions of EIF2AK3 were characterized in vivo and in vitro and found to have a complete lack of activity in four mutant proteins and residual kinase activity in one. Remarkably, the onset of diabetes was relatively late (30 months) in the patient expressing the partially defective EIF2AK3 mutant and in the patient with no EIF2AK3 involvement (18 months) compared with other patients (<6 months). The patient with no EIF2AK3 involvement did not have any of the other variable clinical manifestations associated with WRS, which supports the idea that the genetic heterogeneity between this variant form of WRS and EIF2AK3 WRS correlates with some clinical heterogeneity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".