Characterization of gastrointestinal pathologies in the <i>dystonia musculorum</i> mouse model for hereditary sensory and autonomic neuropathy type VI
Bibliographic record
Abstract
Abstract Background Dystonia musculorum (Dstdt) is a murine disease caused by recessive mutations in the dystonin (Dst) gene. Loss of dorsal root ganglion (DRG) sensory neurons, ataxia, and dystonic postures before death by postnatal day 18 (P18) is a hallmark feature. Recently we observed gas accumulation and discoloration in the small intestine and cecum in Dstdt mice by P15. The human disease resulting from dystonin loss‐of‐function, known as hereditary sensory and autonomic neuropathy type VI (HSAN‐VI), has also been associated with gastrointestinal (GI) symptoms including chronic diarrhea and abdominal pain. As neuronal dystonin isoforms are expressed in the GI tract, we hypothesized that dystonin loss‐of‐function in Dstdt‐27J enteric nervous system (ENS) neurons resulted in neurodegeneration associated with the GI abnormalities. Methods We characterized the nature of the GI abnormalities observed in Dstdt mice through histological analysis of the gut, assessing the ENS for signs of neurodegeneration, evaluation of GI motility and absorption, and by profiling the microbiome. Key results Though gut histology, ENS viability, and GI absorption were normal, slowed GI motility, thinning of the colon mucous layer, and reduced microbial richness/evenness were apparent in Dstdt‐27J mice by P15. Parasympathetic GI input showed signs of neurodegeneration, while sympathetic did not. Conclusions & Inferences Dstdt‐27J GI defects are not linked to ENS neurodegeneration, but are likely a result of an imbalance in autonomic control over the gut. Further characterization of HSAN‐VI patient GI symptoms is necessary to determine potential treatments targeting symptom relief.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".