Evidence map›Paper›PMID 39682918›Full record

ArticleFoods (Basel, Switzerland)2024

Plant Microbe Interaction-Predicting the Pathogen Internalization Through Stomata Using Computational Neural Network Modeling.

Linze Li, Shakeel Ahmed, Mukhtar Iderawumi Abdulraheem, Fida Hussain, Hao Zhang, Junfeng Wu, Vijaya Raghavan, Lulu Xu, Geng Kuan, Jiandong Hu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Foods (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Identification ofFrontiers in plant science · 2025
    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

10 authors.

Linze LiCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China.
Shakeel AhmedCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China.ORCID 0000-0003-1317-6956
Mukhtar Iderawumi AbdulraheemCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China.ORCID 0000-0002-6745-378X
Fida HussainCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China.
Hao ZhangCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China.
Junfeng WuCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China.
Vijaya RaghavanDepartment of Bioresource Engineering, Faculty of Agriculture and Environmental Studies, McGill University, Sainte-Anne-de-Bellevue, QC H9X 3V9, Canada.ORCID 0000-0003-1819-6710
Lulu XuCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China.ORCID 0009-0008-8445-1402
Geng KuanCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China.
Jiandong HuCollege of Mechanical and Electrical Engineering, Henan Agricultural University, Zhengzhou 450002, China.ORCID 0000-0002-1944-2840

Funding

Henan Center for Outstanding Overseas Scientists GZS2021007Major Science and Technology projects of Henan Province 221100320200National Natural Science Foundation of China 32071890
6 · The paper itself

Abstract

Foodborne disease presents a substantial challenge to researchers, as foliar water intake greatly influences pathogen internalization via stomata. Comprehending plant-pathogen interactions, especially under fluctuating humidity and temperature circumstances, is crucial for formulating ways to prevent pathogen ingress and diminish foodborne hazards. This study introduces a computational model utilizing neural networks to anticipate pathogen internalization via stomata, contrasting with previous research that emphasized biocontrol techniques. Computational modeling assesses the likelihood and duration of internalization for bacterial pathogens such as

Indexed as

computational modelingfoliar water uptakefoodborne illnessneural networkingplant–pathogen interaction

Identifiers

PMID39682918
PMCPMC11640189

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.