Evidence map›Paper›PMID 38784062›Full record

ArticleFrontiers in plant science2024

Exploring the putative microRNAs cross-kingdom transfer in

Paola Leonetti, Debora Dallera, Davide De Marchi, Pamela Candito, Lorenzo Pasotti, Anca Macovei

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Frontiers in plant science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Paola LeonettiInstitute for Sustainable Plant Protection of the National Research Council, Unit of Bari, Bari, Italy.
Debora DalleraLaboratory of Bioinformatics, Mathematical Modelling, and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering - Centre for Health Technology, University of Pavia, Pavia, Italy.
Davide De MarchiLaboratory of Bioinformatics, Mathematical Modelling, and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering - Centre for Health Technology, University of Pavia, Pavia, Italy.
Pamela CanditoLaboratory of Bioinformatics, Mathematical Modelling, and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering - Centre for Health Technology, University of Pavia, Pavia, Italy.
Lorenzo PasottiLaboratory of Bioinformatics, Mathematical Modelling, and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering - Centre for Health Technology, University of Pavia, Pavia, Italy.
Anca MacoveiPlant Biotechnology Laboratory, Department of Biology and Biotechnology "L. Spallanzani", University of Pavia, Pavia, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Plant-pathogen interaction is an inexhaustible source of information on how to sustainably control diseases that negatively affect agricultural production. Methods: Here, we propose a bioinformatics pipeline to highlight potential miRNA-dependent cross-kingdom interactions between tomato and Results: The obtained data show that nematode miRNAs putatively targeting tomato genes are mostly related to detrimental effects on plant development and defense. Similarly, tomato miRNAs putatively targeting Discussions: Therefore, the current study expands the knowledge related to the cross-kingdom miRNAs involvement in host-parasite interactions and could pave the way for the application of exogenous plant miRNAs as tools to control nematode infection.

Indexed as

bioinformatics pipelinecross-species target predictionmiRNAsplant-pathogen interactionroot-knot nematodetomato

Identifiers

PMID38784062
PMCPMC11114104

What Socratic holds

Textmetadata
LicenceCC BY
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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 Socratic graph.