Laforin preferentially binds the neurotoxic starch-like polyglucosans, which form in its absence in progressive myoclonus epilepsy
Bibliographic record
Abstract
Lafora disease (LD) is a fatal and the most common form of adolescent-onset progressive epilepsy. Fulminant endoplasmic reticulum (ER)-associated depositions of starch-like long-stranded, poorly branched glycogen molecules [known as polyglucosans, which accumulate to form Lafora bodies (LBs)] are seen in neuronal perikarya and dendrites, liver, skeletal muscle and heart. The disease is caused by loss of function of the laforin dual-specificity phosphatase or the malin E3 ubiquitin ligase. Towards understanding the pathogenesis of polyglucosans in LD, we generated a transgenic mouse overexpressing inactivated laforin to trap normal laforin's unknown substrate. The trap was successful and LBs formed in liver, muscle, neuronal perikarya and dendrites. Using immunogold electron microscopy, we show that laforin is found in close proximity to the ER surrounding the polyglucosan accumulations. In neurons, it compartmentalizes to perikaryon and dendrites and not to axons. Importantly, it binds polyglucosans, establishing for the first time a direct association between the disease-defining storage product and disease protein. It preferentially binds polyglucosans over glycogen in vivo and starch over glycogen in vitro, suggesting that laforin's role begins after the appearance of polyglucosans and that the laforin pathway is involved in monitoring for and then preventing the formation of polyglucosans. In addition, we show that the laforin interacting protein, EPM2AIP1, also localizes on the polyglucosan masses, and we confirm laforin's intense binding to LBs in human LD biopsy material.
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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 | 0.001 |
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".