Neurodegeneration with Brain Iron Accumulation and a Brief Report of the Disease in Iran
Bibliographic record
Abstract
Neurodegeneration with brain iron accumulation (NBIA) is a term used for a group of hereditary neurological disorders with abnormal accumulation of iron in basal ganglia. It is clinically and genetically heterogeneous with symptoms such as dystonia, dysarthria, Parkinsonism, intellectual disability, and spasticity. The age at onset and rate of progression are variable among individuals. Current therapies are exclusively symptomatic and unable to hinder the disease progression. Approximately 16 genes have been identified and affiliated to such condition with different functions such as iron metabolism (only two genes: Ferritin Light Chain (FTL) Ceruloplasmin (CP)), lipid metabolism, lysosomal functions, and autophagy process, but some functions have remained unknown so far. Subgroups of NBIA are categorized based on the mutant genes. Although in the last 10 years, the development of whole-exome sequencing (WES) technology has promoted the identification of disease-causing genes, there seem to be some unknown genes and our knowledge about the molecular aspects and pathogenesis of NBIA is not complete yet. There is currently no comprehensive study about the NBIA in Iran; however, one of the latest discovered NBIA genes, GTP-binding protein 2 (GTPBP2), has been identified in an Iranian family, and there are some patients who have genetically remained unknown.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".