Neuromuscular Junction Changes in a Mouse Model of Charcot-Marie-Tooth Disease Type 4C
Bibliographic record
Abstract
The neuromuscular junction (NMJ) appears to be a site of pathology in a number of peripheral nerve diseases. Charcot-Marie-Tooth (CMT) 4C is an autosomal recessive, early onset, demyelinating neuropathy. Numerous mutations in the SH3TC2 gene have been shown to underlie the condition often associated with scoliosis, foot deformities, and reduced nerve conduction velocities. Mice with exon 1 of the Sh3tc2 gene knocked out demonstrate many of the features seen in patients. To determine if NMJ pathology is contributory to the pathomechanisms of CMT4C we examined NMJs in the gastrocnemius muscle of SH3TC2-deficient mice. In addition, we performed proteomic assessment of the sciatic nerve to identify protein factors contributing to the NMJ alterations and the survival of demyelinated axons. Morphological and gene expression analysis of NMJs revealed a lack of continuity between the pre- and post-synaptic apparatus, increases in post-synaptic fragmentation and dispersal, and an increase in expression of the gamma subunit of the acetylcholine receptor. There were no changes in axonal width or the number of axonal inputs to the NMJ. Proteome investigations of the sciatic nerve revealed altered expression of extracellular matrix proteins important for NMJ integrity. Together these observations suggest that CMT4C pathology includes a compromised NMJ even in the absence of changes to the innervating axon.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".