Autosomal dominant HK1-related neurodevelopmental disorder with visual defects and brain anomalies (NEDVIBA): An emerging mitochondrial disorder
Bibliographic record
Abstract
Purpose: ) encodes a ubiquitously expressed hexokinase, which is responsible for the first step of glycolysis, phosphorylation of glucose to glucose-6-phosphate. Both autosomal recessive and dominant variants in this gene have previously been shown to cause human disease, and presently, there are clinical data available for 27 individuals with the monoallelic neurodevelopmental disorder with visual defects and brain anomalies. Delineation of the entire phenotypic spectrum and genotype-phenotype relations will aid in management and counseling decisions. Methods: . We also reviewed data from the published literature. Results: The clinical manifestations of neurodevelopmental disorder with visual defects and brain anomalies include varying degrees of intellectual disability/developmental delay, hypotonia, epileptic encephalopathy, visual deficits, a Leigh syndrome spectrum pattern on brain magnetic resonance imaging, and elevated lactate in blood and cerebrospinal fluid, suggesting mitochondrial dysfunction. Based on severity, individuals can be classified into mild, moderate, severe, or lethal forms. In terms of genotype-phenotype correlation, we find that all individuals carrying a missense variant at the threonine 457 residue have severe clinical features. Conclusion: should be included in mitochondrial disorder gene sequencing panels.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".