Evidence map›Paper›PMID 35365192›Full record

ReviewParasites & vectors2022

Worms and bugs of the gut: the search for diagnostic signatures using barcoding, and metagenomics-metabolomics.

Marina Papaiakovou, D Timothy J Littlewood, Stephen R Doyle, Robin B Gasser, Cinzia Cantacessi

Open access · goldAbstract readReview
In one paragraph

Review in Parasites & vectors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
6.1field-weighted citation impact, top 3% 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

13 citing papers in PubMed, 31 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.

Marina PapaiakovouDepartment of Veterinary Medicine, University of Cambridge, Cambridge, CB3 0ES, UK.
D Timothy J LittlewoodDepartment of Life Sciences, Natural History Museum, Cromwell Road, London, SW7 5BD, UK.
Stephen R DoyleWellcome Sanger Institute, Hinxton, Cambridge, CB10 1SA, UK.
Robin B GasserMelbourne Veterinary School, The University of Melbourne, Parkville, VIC, 3010, Australia.
Cinzia CantacessiDepartment of Veterinary Medicine, University of Cambridge, Cambridge, CB3 0ES, UK. cc779@cam.ac.uk.ORCID http://orcid.org/0000-0001-6863-2950
Natural History Museum · GBThe University of Melbourne · AUUniversity of Cambridge · GBWellcome Sanger Institute · GB

Funding

Medical Research Council MR/T020733/1
6 · The paper itself

Abstract

Gastrointestinal (GI) helminth infections cause significant morbidity in both humans and animals worldwide. Specific and sensitive diagnosis is central to the surveillance of such infections and to determine the effectiveness of treatment strategies used to control them. In this article, we: (i) assess the strengths and limitations of existing methods applied to the diagnosis of GI helminth infections of humans and livestock; (ii) examine high-throughput sequencing approaches, such as targeted molecular barcoding and shotgun sequencing, as tools to define the taxonomic composition of helminth infections; and (iii) discuss the current understanding of the interactions between helminths and microbiota in the host gut. Stool-based diagnostics are likely to serve as an important tool well into the future; improved diagnostics of helminths and their environment in the gut may assist the identification of biomarkers with the potential to define the health/disease status of individuals and populations, and to identify existing or emerging anthelmintic resistance.

Indexed as

Gastrointestinal MicrobiomeMicrobiotaAnimalsGastrointestinal TractMetabolomicsMetagenomics

Identifiers

PMID35365192
PMCPMC8973539
OpenAlexW4220875359

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.