FAAH inhibition as a preventive treatment for migraine: A pre-clinical study
Bibliographic record
Abstract
BACKGROUND: Fatty-acid amide hydrolase (FAAH) is an intracellular serine hydrolase that catalyzes the cleavage of endogenous fatty-acid amides, including the endocannabinoid anandamide (AEA). We previously reported that the peripherally restricted FAAH inhibitor URB937, which selectively increases AEA levels outside the central nervous system, reduces hyperalgesia and c-Fos expression in the trigeminal nucleus caudalis (TNC) and the locus coeruleus in an animal model of migraine based on nitroglycerin (NTG) administration. AIM: To further investigate the relevance of FAAH inhibition in the NTG animal model of migraine by testing the effects of the globally active FAAH inhibitor URB597. METHODS: Our experimental approach involved mapping neuronal c-Fos protein expression, measurement of AEA levels in brain areas and in trigeminal ganglia, evaluation of pain-related behavior and quantification of molecular mediators in rats that received URB597 (2 mg/kg i.p.) either before or after NTG administration (10 mg/kg, i.p.). RESULTS: Pre-treatment with URB597 significantly reduced c-Fos immunoreactivity in the TNC and inhibited NTG-induced hyperalgesia in the orofacial formalin test. This behavioral response was associated with a decrease in neuronal nitric oxide synthase, calcitonin gene-related peptide and cytokine gene expression levels in central and peripheral structures. Administration of URB597 after NTG had no such effect. CONCLUSIONS: The findings suggest that global FAAH inhibition may offer a therapeutic approach to the prevention, but not the abortive treatment, of migraine attacks. Further studies are needed to elucidate the exact cellular and molecular mechanisms underlying the protective effects of FAAH inhibition.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.004 | 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".