Evidence map›Paper›PMID 37620815›Full record

ReviewBMC plant biology2023

Mechanisms of systemic resistance to pathogen infection in plants and their potential application in forestry.

S K Wilson, T Pretorius, S Naidoo

Abstract readReview
In one paragraph

Review in BMC plant biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
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

22 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Microbiology (Reading, England) · 2025
    Article
  16. Article
  17. Review
  18. Article
  19. Article
  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

3 authors.

S K WilsonDepartment of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria, 0028, South Africa.
T PretoriusDepartment of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria, 0028, South Africa.
S NaidooDepartment of Biochemistry, Genetics and Microbiology, Forestry and Agricultural Biotechnology Institute, University of Pretoria, Pretoria, 0028, South Africa. sanushka.naidoo@fabi.up.ac.za.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe complex systemic responses of tree species to fight pathogen infection necessitate attention due to the potential for yield protection in forestry.

resultsIn this paper, both the localized and systemic responses of model plants, such as Arabidopsis and tobacco, are reviewed. These responses were compared to information available that investigates similar responses in woody plant species and their key differences were highlighted. In addition, tree-specific responses that have been documented were summarised, with the critical responses still relying on certain systemic acquired resistance pathways. Importantly, coniferous species have been shown to utilise phenolic compounds in their immune responses. Here we also highlight the lack of focus on systemic induced susceptibility in trees, which can be important to forest health.

conclusionsThis review highlights the possible mechanisms of systemic response to infection in woody plant species, their potential applications, and where research may be best focused in future.

Indexed as

ArabidopsisTracheophytaForestryNicotianaTreesPhytohormonesPlant-pathogen interactionsPrimingSystemic resistance

Identifiers

PMID37620815
PMCPMC10463331

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.