Win 55212-2, a cannabinoid receptor agonist, attenuates leukocyte/endothelial interactions in an experimental autoimmune encephalomyelitis model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Multiple sclerosis (MS) is the most common of the immune demyelinating disorders of the central nervous system (CNS). Leukocyte/endothelial interactions are important steps in the progression of the disease and substances that interfere with these activities have been evaluated as potential therapeutic agents. Cannabinoid receptor agonists have been shown to downregulate immune responses and there is preliminary evidence that they may slow the progress of MS. The purpose of this investigation was to determine how cannabinoid receptor agonists interfere with leukocyte rolling and adhesion. This was investigated in an experimental autoimmune encephalomyelitis (EAE) model using six to eight week old C57BL/6 mice. Mouse myelin oligodendrocyte protein and pertussis toxin were used to induce EAE. WIN 55212-2, CB1 and CB2 antagonist were given. By use of in vivo intravital microscopy, leukocyte/endothelial interactions were evaluated via a cranial window implanted two days before. The results demonstrated that EAE increases leukocyte rolling and firm adhesion in the brain, and that this increased leukocyte/endothelial interaction can be attenuated by administration of WIN 55212-2. Furthermore, use of the selective antagonists for the CB1 receptor (SR 141716A) and the CB2 receptor (SR144528) in this study demonstrated that the cannabinoid's inhibitory effects on leukocyte/endothelial interactions can be mediated by activating CB2 receptor.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it