Evidence map›Paper›PMID 36794396›Full record

ReviewVirulence2023

Extracellular vesicles in bacterial and fungal diseases - Pathogenesis to diagnostic biomarkers.

Jnana A, Sadiya S S, Satyamoorthy K, Murali T S

Open access · goldFull text readReview
In one paragraph

Review in Virulence, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.4field-weighted citation impact, top 7% 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

18 citing papers in PubMed, 22 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

4 authors at 1 institution in 1 country.

Jnana ADepartment of Biotechnology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India.
Sadiya S SDepartment of Biotechnology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India.
Satyamoorthy KDepartment of Cell and Molecular Biology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India.
Murali T SDepartment of Biotechnology, Manipal School of Life Sciences, Manipal Academy of Higher Education, Manipal, India.ORCID 0000-0003-1563-8077
Manipal Academy of Higher Education · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intercellular communication among microbes plays an important role in disease exacerbation. Recent advances have described small vesicles, termed as "extracellular vesicles" (EVs), previously disregarded as "cellular dust" to be vital in the intracellular and intercellular communication in host-microbe interactions. These signals have been known to initiate host damage and transfer of a variety of cargo including proteins, lipid particles, DNA, mRNA, and miRNAs. Microbial EVs, referred to generally as "membrane vesicles" (MVs), play a key role in disease exacerbation suggesting their importance in pathogenicity. Host EVs help coordinate antimicrobial responses and prime the immune cells for pathogen attack. Hence EVs with their central role in microbe-host communication, may serve as important diagnostic biomarkers of microbial pathogenesis. In this review, we summarize current research regarding the roles of EVs as markers of microbial pathogenesis with specific focus on their interaction with host immune defence and their potential as diagnostic biomarkers in disease conditions.

Indexed as

Extracellular VesiclesMicroRNAsMycosesBiomarkersHumansVirulenceBiomarkersMicroRNAsBiomarkersextracellular vesiclesinfection diagnosismicrobial pathogenesis

Identifiers

PMID36794396
PMCPMC10012962
OpenAlexW4321003930

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read4
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.