Normal role of the low‐molecular‐weight neurofilament protein in mitochondrial dynamics and disruption in Charcot‐Marie‐Tooth disease
Bibliographic record
Abstract
Intermediate filaments serve important structural roles, but other cellular functions are increasingly recognized. This study demonstrated normal function of the low-molecular-weight neurofilament protein (NFL) in mitochondrial dynamics and disruption in Charcot-Marie-Tooth disease (CMT) due to mutations in the Nefl gene. In motor neurons of spinal cord cultured from Nefl-knockout mice, mitochondrial length and the rate of fusion were decreased concomitant with increased motility. These parameters were normalized after expression of NFL(wt) on the Nefl(-/-) background, but not by overexpression of the profusion protein, mitofusin 2 (MFN2). The effects of CMT-causing NFL mutants bore similarities to and differences from Nefl knockout. In the early phase of toxicity before disruption of the neurofilament network, NFL(Q333P) and NFL(P8R) integrated into neurofilaments and had effects on mitochondria similar to those with Nefl knockout. The reduction of fusion rate by NFL(Q333P) was partly due to interference with the function of the profusion protein MFN2, which is mutated in CMT2A, functionally linking these forms of CMT. In the later phase of toxicity, mitochondria essentially stopped moving in neurons expressing NFL mutants, probably a consequence of cytoskeletal disruption. Overall, the data point to important functions of neurofilaments in mitochondrial dynamics as well as primary involvement in CMT2E/1F.
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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 | 0.001 | 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 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".