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Record W4297969090 · doi:10.5423/ppj.rw.07.2022.0090

Versatile Roles of Microbes and Small RNAs in Rice and Planthopper Interactions

2022· review· en· W4297969090 on OpenAlexaff
Abdelaziz Mansour, Mohamed Mannaa, Omar A. Hewedy, Mostafa G. Ali, Hyejung Jung, Young‐Su Seo

Bibliographic record

VenueThe Plant Pathology Journal · 2022
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsUniversity of Guelph
FundersRural Development Administration
KeywordsBiologyBrown planthopperPlanthopperTranscriptomeHost (biology)MetagenomicsMicrobiomeGeneGeneticsEcologyGene expression

Abstract

fetched live from OpenAlex

Planthopper infestation in rice causes direct and indirect damage through feeding and viral transmission. Host microbes and small RNAs (sRNAs) play essential roles in regulating biological processes, such as metabolism, development, immunity, and stress responses in eukaryotic organisms, including plants and insects. Recently, advanced metagenomic approaches have facilitated investigations on microbial diversity and its function in insects and plants, highlighting the significance of microbiota in sustaining host life and regulating their interactions with the environment. Recent research has also suggested significant roles for sRNA-regulated genes during rice-planthopper interactions. The response and behavior of the rice plant to planthopper feeding are determined by changes in the host transcriptome, which might be regulated by sRNAs. In addition, the roles of microbial symbionts and sRNAs in the host response to viral infection are complex and involve defense-related changes in the host transcriptomic profile. This review reviews the structure and potential functions of microbes and sRNAs in rice and the associated planthopper species. In addition, the involvement of the microbiota and sRNAs in the rice-planthopper-virus interactions during planthopper infestation and viral infection are discussed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.113
GPT teacher head0.304
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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