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Record W2107223272 · doi:10.1139/b10-039

Non-host resistance responses of <i>Arabidopsis thaliana</i> to the coffee leaf rust fungus (<i>Hemileia vastatrix</i>)

2010· article· en· W2107223272 on OpenAlexvenueno aff
Helena G. Azinheira, Maria do Céu Silva, Pedro Talhinhas, Clara Medeira, Isabel Maia, Anne‐Sophie Petitot, Diana Fernandez

Bibliographic record

VenueBotany · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsnot available
FundersFundação para a Ciência e a Tecnologia
KeywordsBiologyHaustoriumCalloseRust (programming language)AppressoriumArabidopsis thalianaBotanyInoculationPlant disease resistanceFungusHost (biology)HorticultureGeneCell wall

Abstract

fetched live from OpenAlex

Leaf rust, caused by Hemileia vastatrix Berk &amp; Broome, is the most destructive fungal disease of coffee. In the absence of a suitable gene validation system in coffee, the objective of this study was to investigate whether the model plant Arabidopsis thaliana (L.) Heynh. may be used as a heterologous system for the molecular dissection of coffee responses to leaf rust. Histological examination of A. thaliana (Col-0) leaves inoculated with H. vastatrix (race II) showed that by 24 h after inoculation (hai), H. vastatrix uredospores differentiated appressoria and penetrated the stomata, but failed to form haustoria. Arabidopsis thaliana cellular resistance responses included hypersensitive-like response (HR) of stomata guard cells together with accumulation of phenolic compounds and callose deposition in walls of epidermal and mesophyll cells. Results indicate that H. vastatrix infection triggered the induction of a set of defence-related genes peaking at 18 and 42 hai. The non-host HR triggered by H. vastatrix in the model plant A. thaliana makes it usable to infer the function of coffee genes involved in pre-haustorial rust resistance.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.231
Teacher spread0.217 · 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 teacher head, 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

Citations27
Published2010
Admission routes1
Has abstractyes

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