Formation and toxicity of neuronal peripherin inclusions
Bibliographic record
Abstract
Degenerating spinal motor neurons in amyotrophic lateral sclerosis (ALS) are characterized by a reduced expression of neurofilament light (NF-L) mRNA and by the presence of inclusions composed of peripherin and neurofilament (NF) proteins. This thesis examines questions related to the formation and toxicity of inclusions containing peripherin. Transfection studies demonstrated that the organization of the penpherin network is disrupted by the larger NF proteins NF-M and NF-H in context of NF-L deficiency. To further investigate the in vivo assembly of peripherin, transgenic mice overexpressing the mouse peripherin gene were generated and then bred with NF-L null mice. Mice overexpressing peripherin developed a late onset motor neuron disease characterized by the formation of peripherin inclusions and by the degeneration of motor axons in two years old mice. Remarkably, a deficiency of the NF-L protein enhanced the formation of inclusions and accelerated the onset of the peripherin-mediated disease by about 15 months. Transgenic mice overexpressing the human NF-H protein in the absence of NF-L (hH;L-/- mice) were then generated to further examine the impact of a NF-L deficiency upon the formation and toxicity of protein inclusions. These mice were characterized by the formation of large perikaryal inclusions containing peripherin and NF-H. Unlike the axonal and perikaryal inclusions formed in peripherin transgenic mice, the inclusions of hH;L-/- mice were not associated with loss spinal motor neuron, thus suggesting that the toxicity of inclusions in peripherin transgenic mice may be related to their axonal localization. Finally, a last series of experiments demonstrated that stab injuries and ischemia can also trigger the formation of peripherin inclusions in brain neurons that are normally silent for peripherin expression. The combined results suggest that peripherin inclusions may participate to the pathology of ALS and perhaps to neurodegeneration in other dis
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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 | 0.000 | 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 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".