Dystonin loss-of-function leads to impaired autophagosome–endolysosome pathway dynamics
Bibliographic record
Abstract
The neuronal dystonin protein (DST-a) is a large cytoskeletal linker important for integrating the various components of the cytoskeleton. Recessive Dst mutations lead to a sensory neuropathy in mice, known as dystonia musculorum (Dstdt). The disease is characterized by ataxia, autonomic disturbances, and ultimately, death, which are associated with massive degeneration of the sensory neurons in the dorsal root ganglion (DRG). Recent investigation of Dstdt sensory neurons revealed an accumulation of autophagosomes and a disruption in autophagic flux, which was believed to be due to insufficient availability of motor protein. Motor protein levels and the endolysosomal pathway were assessed in pre-symptomatic (postnatal day 5; P5) and symptomatic (P15) stage wild-type and Dstdt DRGs. Levels of mRNA encoding molecular motors were reduced, although no significant reduction in the protein level was detected. An increase in lysosomal marker LAMP1 in medium-large size Dstdt-27J sensory neurons was observed, along with an accumulation of electron-light single-membraned vesicles in Dstdt-27J DRG tissue at the late stages of disease. These vesicles are likely to have been autolysosomes, and their presence in only late-stage Dstdt-27J sensory neurons is suggestive of a pathological defect in autophagy. Further investigation is necessary to confirm vesicle identity, and to determine the role of Dst-a in normal autophagic flux.
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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) | 0.001 | 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 | 0.001 | 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".