Increasing levels of the endocannabinoid 2-AG is neuroprotective in the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine mouse model of Parkinson's disease
Bibliographic record
Abstract
Parkinson's disease (PD) is a common chronic neurodegenerative disorder, usually of idiopathic origin. Symptoms including tremor, bradykinesia, rigidity and postural instability are caused by the progressive loss of dopaminergic neurons in the nigrostriatal region of the brain. Symptomatic therapies are available but no treatment slows or prevents the loss of neurons. Neuroinflammation has been implicated in its pathogenesis. To this end, the present study utilises the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) neurotoxin to reproduce the pattern of cell death evident in PD patients. Herein, the role of a potential regulator of an immune response, the endocannabinoid system (ECS), is investigated. The most prevalent endocannabinoid, 2-arachidonoylglycerol (2-AG) (3 and 5mg/kg), was added exogenously and its enzymatic degradation inhibited to provide protection against MPTP-induced cell death. Furthermore, the addition of DFU (25mg/kg), a selective inhibitor of inflammatory mediator cyclooxygenase-2 (COX-2), potentiated these effects. Levels of 2-AG were shown to be upregulated in a time- and region-specific manner following MPTP administration, indicating that the ECS represents a natural defence mechanism against inflammation, potentiation of which could provide therapeutic benefits. The results expand the current understanding of the role that this signalling system has and its potential influence in PD.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".