Defective Fas expression exacerbates neurotoxicity in a model of Parkinson's disease
Bibliographic record
Abstract
Fas (CD95), a member of the tumor necrosis factor-receptor superfamily, has been studied extensively as a death-inducing receptor in the immune system. However, Fas is also widely expressed in a number of other tissues, including in neurons. Here, we report that defects in the Fas/Fas ligand system unexpectedly render mice highly susceptible to neural degeneration in a model of Parkinson's disease. We found that Fas-deficient lymphoproliferative mice develop a dramatic phenotype resembling clinical Parkinson's disease, characterized by extensive nigrostriatal degeneration accompanied by tremor, hypokinesia, and loss of motor coordination, when treated with the neurotoxin 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) at a dose that causes no neural degeneration or behavioral impairment in WT mice. Mice with generalized lymphoproliferative disease, which express a mutated Fas ligand, display an intermediate phenotype between that of lymphoproliferative and WT mice. Moreover, Fas engagement directly protects neuronal cells from MPTP/1-methyl-4-phenylpyridinium ion toxicity in vitro. Our data show that decreased Fas expression renders dopaminergic neurons highly susceptible to degeneration in response to a Parkinson-causing neurotoxin. These findings constitute the first evidence for a neuroprotective role for Fas in vivo.
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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) | 0.001 | 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 | 0.001 |
| 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".