Null mutations of NEUROG3 are associated with delayed-onset diabetes mellitus
Bibliographic record
Abstract
Biallelic mutations of the gene encoding the transcription factor NEUROG3 are associated with a rare disorder that presents in neonates as generalized malabsorption - due to a complete absence of enteroendocrine cells - followed, in early childhood or beyond, by insulin-dependent diabetes mellitus (IDDM). The commonly delayed onset of IDDM suggests a differential requirement for NEUROG3 in endocrine cell generation in the human pancreas versus the intestine. However, previously identified human mutations were hypomorphic and, hence, may have had residual function in pancreas. We report 2 patients with biallelic functionally null variants of the NEUROG3 gene who nonetheless did not present with IDDM during infancy but instead developed permanent IDDM during middle childhood ages. The variants showed no evidence of function in traditional promoter-based assays of NEUROG3 function and also failed to exhibit function in a variety of potentially novel in vitro and in vivo molecular assays designed to discern residual NEUROG3 function. These findings imply that, unlike in mice, pancreatic endocrine cell generation in humans is not entirely dependent on NEUROG3 expression and, hence, suggest the presence of unidentified redundant in vivo pathways in human pancreas capable of yielding β cell mass sufficient to maintain euglycemia until early childhood.
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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 | 0.001 |
| Research integrity | 0.001 | 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".