Evidence map›Paper›PMID 31133880›Full record

ReviewFrontiers in physiology2019

Complex Insect-Pathogen Interactions in Tree Pandemics.

Alberto Santini, Andrea Battisti

Abstract readReview
In one paragraph

Review in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. The novel nematicide chiricanine A suppressesFrontiers in plant science · 2023
    Article
  5. RNA-Seq of Cyst Nematode Infestation of Potato (Plants (Basel, Switzerland) · 2022
    Article
  6. Article
  7. Opinion: Intercepting pandemics through genomics.Proceedings of the National Academy of Sciences of the United States of America · 2020
    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.

Alberto SantiniInstitute for Sustainable Plant Protection, National Research Centre, Sesto Fiorentino, Italy.
Andrea BattistiDepartment of Agronomy, Food, Natural Resources, Animals and the Environment, University of Padua, Padua, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tree pandemics are a major cause of economic and ecological loss in forest and urban ecosystems. They often depend on the introduction of a non-native pathogen, which is occupying the niche of a native, non-aggressive organism. Complex interactions with native insects carrying fungi and nematodes can be established based on the proximity of the aggressive pathogenic agents. Here we review three major pandemics of forest and urban trees in temperate ecosystems at world scale, i.e., the Dutch elm disease, the cypress canker, and the pine wilt disease. For each system, the relationships between aggressive and non-aggressive fungi and nematodes with the native insect vectors are presented. Hidden players such as insects, microorganisms or plants, which may have the role of facilitating or contrasting the performance of the agents, are also considered. Results suggest that pandemics rely on the introduction of a non-native pathogen that exploits well-developed interactions between native non-aggressive organisms and insects associated with trees. The success of the invaders depends on the morpho-physiological proximity of the players and on the mutual benefits resulting from the associations. Deciphering such interactions in native systems may help to predict the outcome of the introduction of new pathogens and the development of new tree pandemics.

Indexed as

antagonistcypress canker diseaseDutch elm diseasefacilitatorpine wilt diseasevector

Identifiers

PMID31133880
PMCPMC6517489

What OpenQuestion holds

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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.