ReviewBMC plant biology2024
Pine wilt disease: what do we know from proteomics?
Review in BMC plant biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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.
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.
Who cites it
9 citing papers in PubMed.
- An antifungal effector from a plant-parasitic nematode modulates host fungal community composition and supports ecological fitness.NPJ biofilms and microbiomes · 2026Article
- Amino Acid-Optimized Medium Improves Long-Term Growth, Conidiation, Stress Tolerance, and Biocontrol Performance ofJournal of fungi (Basel, Switzerland) · 2026Article
- A Three-Tier In Vitro Strategy for Accelerated Pine Breeding and Resistance Research Against Pine Wilt Disease.Plants (Basel, Switzerland) · 2026Article
- Effects of Dominant Associated BacteriaMicroorganisms · 2025Article
- Molecular Mechanisms of the Biological Control of Pine Wilt Disease Using Microorganisms.Microorganisms · 2025Review
- Transcriptomic, metabonomic and proteomic analyses reveal that terpenoids and flavonoids are required for Pinus koraiensis early defence against Bursaphelenchus xylophilus infection.BMC plant biology · 2025Article
- Establishment of a Sensitive and Reliable Droplet Digital PCR Assay for the Detection ofPlants (Basel, Switzerland) · 2024Article
- Prediction of protein interactions between pine and pine wood nematode using deep learning and multi-dimensional feature fusion.Frontiers in plant science · 2024Article
- The impact of pine wilt disease on the endophytic microbial communities structure ofFrontiers in microbiology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pine wilt disease (PWD) is a devastating forest disease caused by the pinewood nematode (PWN), Bursaphelenchus xylophilus, a migratory endoparasite that infects several coniferous species. During the last 20 years, advances have been made for understanding the molecular bases of PWN-host trees interactions. Major advances emerged from transcriptomic and genomic studies, which revealed some unique features related to PWN pathogenicity and constituted fundamental data that allowed the development of postgenomic studies. Here we review the proteomic approaches that were applied to study PWD and integrated the current knowledge on the molecular basis of the PWN pathogenicity. Proteomics has been useful for understanding cellular activities and protein functions involved in PWN-host trees interactions, shedding light into the mechanisms associated with PWN pathogenicity and being promising tools to better clarify host trees PWN resistance/susceptibility.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.