Regulation of Dopaminergic Loss by Fas in a 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine Model of Parkinson's Disease
Bibliographic record
Abstract
Accumulating evidence suggests that apoptotic and inflammatory factors contribute to the demise of dopaminergic neurons. In this respect, Fas, a member of the tumor necrosis factor receptor family with proapoptotic and inflammatory functions, was reported to be elevated within the striatum and substantia nigra pars compacta (SNc) of Parkinson's disease (PD) patients. Accordingly, the present investigation evaluated the function of Fas in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of PD. Injection of MPTP increased nigral Fas expression, and mice lacking Fas displayed attenuated MPTP-induced SNc dopaminergic loss and microglial activation. In addition, Fas induction was blocked by expression of a dominant-negative c-Jun adenovirus that also protected dopamine neurons from MPTP-induced damage. Together, these data suggest the critical nature of the c-Jun-Fas signaling pathway in MPTP-induced neuronal loss. Although critical for degeneration of the soma, Fas deficiency did not significantly prevent the reduction of dopaminergic terminal fibers within the striatum or normalize the activation of striatal microglia and elevation of the postsynaptic activity marker DeltaFosB induced by denervation. Interestingly, Fas-deficient mice displayed a pre-existing reduction in striatal dopamine levels and locomotor behavior when compared with wild-type mice. Despite the reduced terminals, dopamine levels were not further suppressed by MPTP treatment in mutant mice, raising the possibility of a compensatory response in basal ganglia function in Fas-deficient mice.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".