Evidence map›Paper›PMID 33375539›Full record

ReviewCancers2020

(Endo)Cannabinoids and Gynaecological Cancers.

Anthony H Taylor, Daniel Tortolani, Thangesweran Ayakannu, Justin C Konje, Mauro Maccarrone

Open access · goldAbstract readReview
In one paragraph

Review in Cancers, 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
0.9field-weighted citation impact, top 24% 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, 13 citations in OpenAlex.

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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

5 authors at 4 institutions in 2 countries.

Anthony H TaylorEndocannabinoid Research Group, Reproductive Sciences Section, Department of Cancer Studies and Molecular Medicine, University of Leicester, Leicester LE1 7RH, UK.ORCID 0000-0003-3260-256X
Daniel TortolaniEuropean Centre for Brain Research, IRCCS Santa Lucia Foundation, 00164 Rome, Italy.
Thangesweran AyakannuEndocannabinoid Research Group, Reproductive Sciences Section, Department of Cancer Studies and Molecular Medicine, University of Leicester, Leicester LE1 7RH, UK.
Justin C KonjeEndocannabinoid Research Group, Reproductive Sciences Section, Department of Cancer Studies and Molecular Medicine, University of Leicester, Leicester LE1 7RH, UK.
Mauro MaccarroneEuropean Centre for Brain Research, IRCCS Santa Lucia Foundation, 00164 Rome, Italy.ORCID 0000-0002-3990-2963
University of Leicester · GBEuropean Brain Research Institute · ITUniversity of L'Aquila · ITUniversity of Liverpool · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gynaecological cancers can be primary neoplasms, originating either from the reproductive tract or the products of conception, or secondary neoplasms, representative of metastatic disease. For some of these cancers, the exact causes are unknown; however, it is recognised that the precise aetiopathogeneses for most are multifactorial and include exogenous (such as diet) and endogenous factors (such as genetic predisposition), which mutually interact in a complex manner. One factor that has been recognised to be involved in the pathogenesis and progression of gynaecological cancers is the endocannabinoid system (ECS). The ECS consists of endocannabinoids (bioactive lipids), their receptors, and metabolic enzymes responsible for their synthesis and degradation. In this review, the impact of plant-derived (

Indexed as

cannabinoidscervical cancerendocannabinoidsendometrial cancerenzymesgynaecological cancerovarian cancerreceptorssignal transductiontransport

Identifiers

PMID33375539
PMCPMC7795647
OpenAlexW3117815659

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.