Giant axonal neuropathy–associated gigaxonin mutations impair intermediate filament protein degradation
Bibliographic record
Abstract
Giant axonal neuropathy (GAN) is an early-onset neurological disorder caused by mutations in the GAN gene (encoding for gigaxonin), which is predicted to be an E3 ligase adaptor. In GAN, aggregates of intermediate filaments (IFs) represent the main pathological feature detected in neurons and other cell types, including patients' dermal fibroblasts. The molecular mechanism by which these mutations cause IFs to aggregate is unknown. Using fibroblasts from patients and normal individuals, as well as Gan-/- mice, we demonstrated that gigaxonin was responsible for the degradation of vimentin IFs. Gigaxonin was similarly involved in the degradation of peripherin and neurofilament IF proteins in neurons. Furthermore, proteasome inhibition by MG-132 reversed the clearance of IF proteins in cells overexpressing gigaxonin, demonstrating the involvement of the proteasomal degradation pathway. Together, these findings identify gigaxonin as a major factor in the degradation of cytoskeletal IFs and provide an explanation for IF aggregate accumulation, the subcellular hallmark of this devastating human disease.
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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) | 0.001 | 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".