ArticleEJNMMI research2022
Target occupancy study and whole-body dosimetry with a MAGL PET ligand [
Article in EJNMMI research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 6 citations in OpenAlex.
- Radiopharmaceuticals and their applications in medicine.Signal transduction and targeted therapy · 2025Review
- Evaluation of [EJNMMI research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
20 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMonoacylglycerol lipase (MAGL) is a key serine hydrolase which terminates endocannabinoid signaling and regulates arachidonic acid driven inflammatory responses within the central nervous system. To develop [
methodsSeven cynomolgus monkeys were enrolled for brain PET measurements. Two PET measurements along with arterial blood sampling were performed in each NHP: one baseline and one pretreatment condition with intravenous administration of PF-06818883, a pro-drug of a selective MAGL inhibitor (total of seven doses between 0.01 and 1.27 mg/kg). Kinetic parameters K
resultsRadioactivity retention was decreased in all brain regions following pretreatment with PF-06818883. Occupancy was measured as 25.4-100.5% in a dose dependent manner. Whole-body PET showed high radioactivity uptake values in the liver, small intestine, kidney, and brain. The effective dose of [
conclusions[
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.