PET Imaging of Fatty Acid Amide Hydrolase with [<sup>18</sup>F]DOPP in Nonhuman Primates
Bibliographic record
Abstract
Fatty acid amide hydrolase (FAAH) regulates endocannabinoid signaling. [(11)C]CURB, an irreversibly binding FAAH inhibitor, has been developed for clinical research imaging with PET. However, no fluorine-18 labeled radiotracer for FAAH has yet advanced to human studies. [(18)F]DOPP ([(18)F]3-(4,5-dihydrooxazol-2-yl)phenyl (5-fluoropentyl)carbamate) has been identified as a promising (18)F-labeled analogue based on rodent studies. The goal of this work is to evaluate [(18)F]DOPP in nonhuman primates to support its clinical translation. High specific activity [(18)F]DOPP (5-6 Ci·μmol(-1)) was administered intravenously (iv) to three baboons (2M/1F, 3-4 years old). The distribution and pharmacokinetics were quantified following a 2 h dynamic imaging session using a simultaneous PET/MR scanner. Pretreatment with the FAAH-selective inhibitor, URB597, was carried out at 200 or 300 μg/kg iv, 10 min prior to [(18)F]DOPP administration. Rapid arterial blood sampling for the first 3 min was followed by interval sampling with metabolite analysis to provide a parent radiotracer plasma input function that indicated ∼95% baseline metabolism at 60 min and a reduced rate of metabolism after pretreatment with URB597. Regional distribution data were analyzed with 1-, 2-, and 3-tissue compartment models (TCMs), with and without irreversible trapping since [(18)F]DOPP covalently links to the active site of FAAH. Consistent with previous findings for [(11)C]CURB, the 2TCM with irreversible binding was found to provide the best fit for modeling the data in all regions. The composite parameter λk3 was therefore used to evaluate whole brain (WB) and regional binding of [(18)F]DOPP. Pretreatment studies showed inhibition of λk3 across all brain regions (WB baseline: 0.112 mL/cm(3)/min; 300 μg/kg URB597: 0.058 mL/cm(3)/min), suggesting that [(18)F]DOPP binding is specific for FAAH, consistent with previous rodent data.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".