Giant axonal neuropathy alters the structure of keratin intermediate filaments in human hair
Bibliographic record
Abstract
Giant axonal neuropathy (GAN) follows an autosomal recessive genetic inheritance and impedes the peripheral and central nervous system due to axonal swellings that are packed with neurofilaments. The patients display a number of phenotypes, including hypotonia, muscle weakness, decreased reflexes, ataxia, seizures, intellectual disability, pale skin and often curled hair. We used X-ray diffraction and tensile testing to determine potential changes to the structure of keratin intermediate filaments (IFs) in the hair of patients with GAN. A statistically significant decrease in the 47 and the 27 Šdiffraction signals were observed. Tensile tests determined that the hair was slightly stiffer, stronger and more extensible in GAN patients. These results suggest that the structure of keratin IFs in hair is altered in GAN, and the findings are compatible with an increased positional disorder of the keratin tetramers within the hair fibres.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".