Laser-Induced Axonal Injury Reveals Gene Dosage-Dependent Mitochondrial Vulnerability in CMT2B Sensory Neurons
Bibliographic record
Abstract
Charcot-Marie-Tooth type 2B (CMT2B) is an inherited peripheral neuropathy characterized by axonal degeneration, progressive muscle weakness, and loss of pain sensation [1].The disease is caused by missense mutations in the Rab7a gene, which disrupt vesicular transport, mitochondrial dynamics, and axonal stability [2].While previous research has established a role for Rab7a-mediated mitochondrial dysfunction in CMT2B pathogenesis, the mechanisms underlying axonal vulnerability and response to injury remain insufficiently understood [3].In this study, we applied laser nano-surgery to dorsal root ganglion (DRG) neurons derived from wild-type and CMT2B mutant mice to model and analyze axonal injury responses.A 740 nm femtosecond laser beam was focused at 120 mW to generate submicron axonal lesions, and neurons were monitored for 60 minutes post-ablation using phase-contrast microscopy.Damage was scored by morphology-based classification into three levels: level 0 (neuropraxia), level 1 (axonotmesis), and level 2 (neurotmesis).To examine the contribution of mitochondrial fission, select cultures were pretreated with Mdivi-1, a Drp1 inhibitor, at 100 M for 60 minutes before laser exposure.Results demonstrated that Mdivi-1 significantly reduced the frequency of severe axonal damage in heterozygous CMT2B neurons (fln/+), with level 2 injury rates decreasing from 26% to 3%.In homozygous neurons (fln/fln), level 2 injury decreased from 32% to 26%, suggesting a gene dosage effect in treatment efficacy.These data indicate that mitochondrial fission plays a critical role in the damage response of CMT2B neurons, and that Drp1 inhibition may have therapeutic potential.This study establishes laser nano-surgery as a powerful and reproducible tool for inducing and analyzing axonal injury in vitro, and highlights mitochondrial dysfunction as a key contributor to axonal pathology in CMT2B.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".