Evidence map›Paper›PMID 32293708›Full record

ArticleBritish journal of pharmacology2020

Evaluation of the profiles of CB

Xiao Zhu, David B Finlay, Michelle Glass, Stephen B Duffull

Open access · bronzeAbstract read
In one paragraph

Article in British journal of pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.5field-weighted citation impact, top 18% 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

10 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. CB1 Cannabinoid Receptor Signaling and Biased Signaling.Molecules (Basel, Switzerland) · 2021
    Review
  8. Article
  9. Evaluation of the profiles of CBBritish journal of pharmacology · 2020
    Article
  10. 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

4 authors at 2 institutions in 1 country.

Xiao ZhuOtago Pharmacometrics Group, School of Pharmacy, University of Otago, Dunedin, New Zealand.ORCID 0000-0003-3295-619X
David B FinlayDepartment of Pharmacology and Toxicology, University of Otago, Dunedin, New Zealand.ORCID 0000-0002-3160-2931
Michelle GlassDepartment of Pharmacology and Toxicology, University of Otago, Dunedin, New Zealand.ORCID 0000-0002-5997-6898
Stephen B DuffullOtago Pharmacometrics Group, School of Pharmacy, University of Otago, Dunedin, New Zealand.
University of Auckland · NZUniversity of Otago · NZ

Funding

Faculty of Medical and Health Sciences, University of AucklandUniversity of AucklandUniversity of Otago
6 · The paper itself

Abstract

background and purposeBiased agonism describes the ability of ligands to differentially regulate multiple signalling pathways when coupled to a single receptor. Signalling is affected by rapid agonist-induced receptor internalisation. Hence, the conventional use of equilibrium models may not be optimal, because (i) receptor numbers vary with time and, in addition, (ii) some pathways may show non-monotonic profiles over time. EXPERIMENTAL APPROACH: Data were available from internalisation, cAMP inhibition and phosphorylation of ERK (pERK) of the cannabinoid-1 (CB KEY

resultsA joint kinetic model was able to capture the signalling profiles across all pathways for the CB CONCLUSION AND IMPLICATIONS: This is the first joint kinetic assessment of biased agonism at a GPCR (e.g. CB

Indexed as

CannabinoidsSignal TransductionDronabinolKineticsReceptor, Cannabinoid, CB1Receptor, Cannabinoid, CB2Receptors, CannabinoidCannabinoidsDronabinolReceptor, Cannabinoid, CB1Receptor, Cannabinoid, CB2Receptors, Cannabinoid

Identifiers

PMID32293708
PMCPMC7369624
OpenAlexW3015324570

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.