Evidence map›Paper›PMID 27279908›Full record

ArticleTheranostics2016

Synthesis and Preclinical Evaluation of Sulfonamido-based [(11)C-Carbonyl]-Carbamates and Ureas for Imaging Monoacylglycerol Lipase.

Lu Wang, Wakana Mori, Ran Cheng, Joji Yui, Akiko Hatori, Longle Ma, Yiding Zhang, Benjamin H Rotstein, Masayuki Fujinaga, Yoko Shimoda and 8 more

Open access · goldAbstract read
In one paragraph

Article in Theranostics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing papers in PubMed
6.4field-weighted citation impact, top 4% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

29 citing papers in PubMed, 55 citations in OpenAlex.

  1. Article
  2. Review
  3. Development of a novelActa pharmaceutica Sinica. B · 2025
    Article
  4. Radiopharmaceuticals and their applications in medicine.Signal transduction and targeted therapy · 2025
    Review
  5. Article
  6. Potential forBrain communications · 2024
    Article
  7. Review
  8. Evaluation of [Pharmaceuticals (Basel, Switzerland) · 2023
    Article
  9. Endocannabinoid System Biomarkers in Alzheimer's Disease.Cannabis and cannabinoid research · 2023
    Article
  10. Review
  11. A novel monoacylglycerol lipase-targetedActa pharmacologica Sinica · 2022
    Article
  12. Article
  13. Article
  14. Article
  15. Development of a highly-specificActa pharmaceutica Sinica. B · 2021
    Article
  16. Review
  17. Article
  18. Review
  19. Design, Synthesis, and Evaluation ofJournal of medicinal chemistry · 2019
    Article
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors at 3 institutions in 3 countries.

Lu Wang1. Gordon Center of Medical Imaging, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA.
Wakana Mori2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Ran Cheng1. Gordon Center of Medical Imaging, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA.; 3. School of Pharmaceutical Science and Technology, Tianjin University, Tianjin, 300072, China.
Joji Yui2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Akiko Hatori2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Longle Ma1. Gordon Center of Medical Imaging, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA.
Yiding Zhang2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Benjamin H Rotstein1. Gordon Center of Medical Imaging, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA.
Masayuki Fujinaga2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Yoko Shimoda2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Tomoteru Yamasaki2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Lin Xie2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Yuji Nagai2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Takafumi Minamimoto2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Makoto Higuchi2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Neil Vasdev1. Gordon Center of Medical Imaging, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA.
Ming-Rong Zhang2. Molecular Imaging Center, National Institute of Radiological Sciences, Chiba, 263-8555, Japan.
Steven H Liang1. Gordon Center of Medical Imaging, Division of Nuclear Medicine and Molecular Imaging, Massachusetts General Hospital & Department of Radiology, Harvard Medical School, Boston, MA, 02114, USA.
Chiba Hospital · JPGordon Center for Medical Imaging · USTianjin University of Science and Technology · CN

Funding

New PET tracers for neuroimaging of FAAH in endocannabinoid signalingK01DA038000 · NIDA · MASSACHUSETTS GENERAL HOSPITAL · PI LIANG, STEVEN H · 2014 to 2018
$927k
NIDA NIH HHS K01 DA038000
6 · The paper itself

Abstract

Monoacylglycerol lipase (MAGL) is a 33 kDa member of the serine hydrolase superfamily that preferentially degrades 2-arachidonoylglycerol (2-AG) to arachidonic acid in the endocannabinoid system. Inhibition of MAGL is not only of interest for probing the cannabinoid pathway but also as a therapeutic and diagnostic target for neuroinflammation. Limited attempts have been made to image MAGL in vivo and a suitable PET ligand for this target has yet to be identified and is urgently sought to guide small molecule drug development in this pathway. Herein we synthesized and evaluated the physiochemical properties of an array of eleven sulfonamido-based carbamates and ureas with a series of terminal aryl moieties, linkers and leaving groups. The most potent compounds were a novel MAGL inhibitor, N-((1-(1H-1,2,4-triazole-1-carbonyl)piperidin-4-yl) methyl)-4-chlorobenzenesulfonamide (TZPU; IC50 = 35.9 nM), and the known inhibitor 1,1,1,3,3,3-hexafluoropropan-2-yl 4-(((4-chlorophenyl)sulfonamido) methyl)piperidine-1-carboxylate (SAR127303; IC50 = 39.3 nM), which were also shown to be selective for MAGL over fatty acid amide hydrolase (FAAH), and cannabinoid receptors (CB1 & CB2). Both of these compounds were radiolabeled with carbon-11 via [(11)C]COCl2, followed by comprehensive ex vivo biodistribution and in vivo PET imaging studies in normal rats to determine their brain permeability, specificity, clearance and metabolism. Whereas TZPU did not show adequate specificity to warrant further evaluation, [(11)C]SAR127303 was advanced for preliminary PET neuroimaging studies in nonhuman primate. The tracer showed good brain permeability (ca. 1 SUV) and heterogeneous regional brain distribution which is consistent with the distribution of MAGL.

Indexed as

AnimalsCarbamatesCarbon RadioisotopesMonoacylglycerol LipasesNeuroimagingPositron-Emission TomographyRatsSulfonamidesUreaCarbamatesCarbon RadioisotopesMonoacylglycerol LipasesSulfonamidesUreacarbon-11MAGLmonoacylglycerol lipasenonhuman primatepositron emission tomographySAR127303.

Identifiers

PMID27279908
PMCPMC4893642
OpenAlexW2415867517

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.