The necroptosis machinery mediates axonal degeneration in a model of Parkinson disease
Bibliographic record
Abstract
Abstract Parkinson’s disease (PD) is the second most common neurodegenerative condition, characterized by motor impairment due to the progressive degeneration of dopaminergic neurons in the substantia nigra and depletion of dopamine release in the striatum. Accumulating evidence suggest that degeneration of axons is an early event in the disease, involving destruction programs that are independent of the survival of the cell soma. Necroptosis, a programmed cell death process, is emerging as a mediator of neuronal loss in models of neurodegenerative diseases. Here, we demonstrate activation of necroptosis in postmortem brain tissue from PD patients and in a toxin-based mouse model of the disease. Inhibition of key components of the necroptotic pathway resulted in a significant delay of 6-hydroxydopamine dependent axonal degeneration of dopaminergic and cortical neurons in vitro . Genetic ablation of necroptosis mediators MLKL and RIPK3, as well as pharmacological inhibition of RIPK1 in vivo , decreased dopaminergic neuron degeneration, improving motor performance. Together, these findings suggest that axonal degeneration in PD is mediated by the necroptosis machinery, a process here referred to as necroaxoptosis , a druggable pathway to target dopaminergic neuronal loss.
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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 | 0.000 | 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".