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Record W4410427605 · doi:10.1126/sciadv.adu6722

The microRNA OsmiR393 regulates rice brown planthopper resistance by modulating the auxin–ROS signaling cross-talk

2025· article· en· W4410427605 on OpenAlexaff
Haichao Li, Zhihuan Tao, Feilong Ma, Shujun Wu, Xuexia Miao, Liming Cao, Zhenying Shi

Bibliographic record

VenueScience Advances · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsMinistry of Agriculture
Fundersnot available
KeywordsBrown planthopperAuxinReactive oxygen speciesCell biologySignal transductionBiologyFunction (biology)GeneGenetics

Abstract

fetched live from OpenAlex

Auxin plays critical roles in plant development and stress response. However, the roles of auxin and the immune signaling factor, reactive oxygen species (ROS), in resistance to the brown planthopper (BPH), a notorious rice-specific piercing-sucking insect that causes severe yield losses, remain unclear. We revealed that moderate naphthalene acetic acid treatment activates rice resistance to BPH, BPH infestation induces ROS accumulation, and increase in ROS content promotes BPH resistance. Underlying these phenomena, the auxin receptors OsTIR1 and OsAFB2 positively, whereas the posttranscriptional regulator OsmiR393 negatively, regulate BPH resistance. Downstream of the OsmiR393/OsTIR1 module, through successive genetic function analysis of each gene, solid genetic relationship analysis, and various biochemical assays, we established an OsmiR393/OsTIR1-OsIAA10-OsARF12-OsRbohB genetic pathway that mediates BPH resistance, in which ROS are integral. Such cross-talk between auxin and ROS reveals the intricate signaling network underlying BPH resistance, which might assist with BPH resistance breeding.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.008
GPT teacher head0.251
Teacher spread0.243 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations5
Published2025
Admission routes1
Has abstractyes

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