A neurotoxic peripherin splice variant in a mouse model of ALS
Bibliographic record
Abstract
Peripherin, a neuronal intermediate filament (nIF) protein found associated with pathological aggregates in motor neurons of patients with amyotrophic lateral sclerosis (ALS) and of transgenic mice overexpressing mutant superoxide dismutase-1 (SOD1G37R), induces the selective degeneration of motor neurons when overexpressed in transgenic mice. Mouse peripherin is unique compared with other nIF proteins in that three peripherin isoforms are generated by alternative splicing. Here, the properties of the peripherin splice variants Per 58, Per 56, and Per 61 have been investigated in transfected cell lines, in primary motor neurons, and in transgenic mice overexpressing peripherin or overexpressing SOD1G37R. Of the three isoforms, Per 61 proved to be distinctly neurotoxic, being assembly incompetent and inducing degeneration of motor neurons in culture. Using isoform-specific antibodies, Per 61 expression was detected in motor neurons of SOD1G37R transgenic mice but not of control or peripherin transgenic mice. The Per 61 antibody also selectively labeled motor neurons and axonal spheroids in two cases of familial ALS and immunoprecipitated a higher molecular mass peripherin species from disease tissue. This evidence suggests that expression of neurotoxic splice variants of peripherin may contribute to the neurodegenerative mechanism in ALS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".