Evidence map›Paper›PMID 29619754›Full record

ReviewPurinergic signalling2018

The involvement of purinergic signalling in obesity.

Geoffrey Burnstock, Daniela Gentile

Open access · hybridAbstract readReview
In one paragraph

Review in Purinergic signalling, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
4.3field-weighted citation impact, top 6% 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

27 citing papers in PubMed, 44 citations in OpenAlex.

  1. AMetabolites · 2026
    Article
  2. Review
  3. Review
  4. Review
  5. Article
  6. Review
  7. Article
  8. Article
  9. Review
  10. Review
  11. Article
  12. Review
  13. Purinergic signaling in diabetes and metabolism.Biochemical pharmacology · 2021
    Review
  14. Review
  15. Article
  16. The P2XFrontiers in molecular neuroscience · 2021
    Article
  17. The Role of a Selective P2YBioMed research international · 2020
    Article
  18. P2YFrontiers in endocrinology · 2020
    Article
  19. Review
  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

2 authors at 2 institutions in 3 countries.

Geoffrey BurnstockDepartment of Pharmacology and Therapeutics, The University of Melbourne, Parkville, Melbourne, Victoria, 3010, Australia. g.burnstock@ucl.ac.uk.ORCID 0000-0001-8152-7979
Daniela GentileDepartment of Clinical and Experimental Medicine, University of Pisa, Via Roma 55, 56126, Pisa, Italy.
The University of Melbourne · AUUniversity of Pisa · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Obesity is a growing worldwide health problem, with an alarming increasing prevalence in developed countries, caused by a dysregulation of energy balance. Currently, no wholly successful pharmacological treatments are available for obesity and related adverse consequences. In recent years, hints obtained from several experimental animal models support the notion that purinergic signalling, acting through ATP-gated ion channels (P2X), G protein-coupled receptors (P2Y) and adenosine receptors (P1), is involved in obesity, both at peripheral and central levels. This review has drawn together, for the first time, the evidence for a promising, much needed novel therapeutic purinergic signalling approach for the treatment of obesity with a 'proof of concept' that hopefully could lead to further investigations and clinical trials for the management of obesity.

Indexed as

AnimalsHumansObesityReceptors, PurinergicSignal TransductionReceptors, PurinergicAdenosineATPBrown and white adipocytesHypothalamusObesityPurinergic receptors

Identifiers

PMID29619754
PMCPMC5940632
OpenAlexW2801512241

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.