Evidence map›Paper›PMID 34975803›Full record

ReviewFrontiers in microbiology2021

Secretion Systems in Gram-Negative Bacterial Fish Pathogens.

Sophanit Mekasha, Dirk Linke

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in microbiology, 2021. 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
1.6field-weighted citation impact, top 17% 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, 29 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. IsJournal of veterinary research · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Synergistic Antibacterial Effect ofJournal of microbiology and biotechnology · 2024
    Article
  12. Review
  13. Article
  14. Article
  15. Genomic Characterization ofAntibiotics (Basel, Switzerland) · 2023
    Article
  16. Article
  17. Article
  18. Inhibitory Effect of Polydatin AgainstFrontiers in veterinary science · 2022
    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 1 institution in 1 country.

Sophanit MekashaSection for Genetics and Evolutionary Biology, Department of Biosciences, University of Oslo, Oslo, Norway.
Dirk LinkeSection for Genetics and Evolutionary Biology, Department of Biosciences, University of Oslo, Oslo, Norway.
University of Oslo · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Bacterial fish pathogens are one of the key challenges in the aquaculture industry, one of the fast-growing industries worldwide. These pathogens rely on arsenal of virulence factors such as toxins, adhesins, effectors and enzymes to promote colonization and infection. Translocation of virulence factors across the membrane to either the extracellular environment or directly into the host cells is performed by single or multiple dedicated secretion systems. These secretion systems are often key to the infection process. They can range from simple single-protein systems to complex injection needles made from dozens of subunits. Here, we review the different types of secretion systems in Gram-negative bacterial fish pathogens and describe their putative roles in pathogenicity. We find that the available information is fragmented and often descriptive, and hope that our overview will help researchers to more systematically learn from the similarities and differences between the virulence factors and secretion systems of the fish-pathogenic species described here.

Indexed as

aquaculturefish diseasefish pathogenGram-negativesecretion systemvirulence factor

Identifiers

PMID34975803
PMCPMC8714846
OpenAlexW4200154291

What Socratic 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 Socratic graph.