Pain Perception in Acute Model Mice of Parkinson's Disease Induced by 1-Methyl-4-Phenyl-1,2,3,6-Tetrahydropyridine (MPTP)
Bibliographic record
Abstract
BACKGROUND: Pain is the most prominent non-motor symptom observed in patients with Parkinson's disease (PD). However, the mechanisms underlying the generation of pain in PD have not been well studied. We used a 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP)-induced mouse model of PD to analyze the relationship between pain sensory abnormalities and the degeneration of dopaminergic neurons. RESULTS: The latency to fall off the rotarod and the total distance traveled in round chamber were significantly reduced in MPTP-induced PD mice, consistent with motor dysfunction. MPTP-treated mice also showed remarkably shorter nociceptive response latencies compared to saline-treated mice and the subcutaneous injection of L-3,4-dihydroxyphenylalanine (L-DOPA) partially reversed pain hypersensitivity induced by MPTP treatment. We found that degeneration of cell bodies and fibers in the substantia nigra pars compacta and the striatum of MPTP-treated mice. In addition, astrocytic and microglial activation was seen in the subthalamic nucleus and neuronal activity was significantly increased in the striatum and globus pallidus. However, we did not observe any changes in neurons, astrocytes, and microglia of both the dorsal and ventral horns in the spinal cord after MPTP treatment. CONCLUSIONS: These results suggest that the dopaminergic nigrostriatal pathway may have a role in inhibiting noxious stimuli, and that abnormal inflammatory responses and neural activity in basal ganglia is correlated to pain processing in PD induced by MPTP treatment.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".