Functions of intermediate filaments in neuronal development and disease
Bibliographic record
Abstract
Five major types of intermediate filament (IF) proteins are expressed in mature neurons: the three neurofilament proteins (NF-L, NF-M, and NF-H), alpha-internexin, and peripherin. While the differential expression of IF genes during embryonic development suggests potential functions of these proteins in axogenesis, none of the IF gene knockout experiments in mice caused gross developmental defects of the nervous system. Yet, deficiencies in neuronal IF proteins are not completely innocuous. Substantial developmental loss of motor axons was detected in mice lacking NF-L and in double knockout NF-M;NF-H mice, supporting the view of a role for IFs in axon stabilization. Moreover, the absence of peripherin resulted in approximately 30% loss of small sensory axons. Mice lacking NF-L had a scarcity of IF structures and exhibited a severe axonal hypotrophy, causing up to 50% reduction in conduction velocity, a feature that would be very detrimental for large animal species. Unexpectedly, the NF-M rather than NF-H protein turned out to be required for proper radial growth of large myelinated axons. Studies with transgenic mice suggest that some types of IF accumulations, reminiscent of those found in amyotrophic lateral sclerosis (ALS), can have deleterious effects and even cause neurodegeneration. Additional evidence for the involvement of IFs in pathogenesis came from the recent discovery of neurofilament gene mutations linked to ALS and Charcot-Marie-Tooth disease (CMT2E). Conversely, we discuss how certain types of perikaryal neurofilament aggregates might confer protection in motor neuron disease.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".