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Record W2186950625 · doi:10.3389/fpls.2015.00995

Elevated Temperature Differentially Influences Effector-Triggered Immunity Outputs in Arabidopsis

2015· article· en· W2186950625 on OpenAlexafffund
Alexandra Menna, Dang Nguyen, David S. Guttman, Darrell Desveaux

Bibliographic record

VenueFrontiers in Plant Science · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPseudomonas syringaeArabidopsisEffectorVirulenceBiologyPlant ImmunityArabidopsis thalianaAbiotic componentHypersensitive responseImmunityInnate immune systemPathogenPlant defense against herbivoryMicrobiologyCell biologyImmune systemGeneticsPlant disease resistanceMutantGeneEcology

Abstract

fetched live from OpenAlex

Pseudomonas syringae is a Gram-negative bacterium that infects multiple plant species by manipulating cellular processes via injection of type three secreted effectors (T3SEs) into host cells. Nucleotide-binding leucine-rich repeat (NLR) resistance (R) proteins recognize specific T3SEs and trigger a robust immune response, called effector-triggered immunity (ETI), which limits pathogen proliferation and is often associated with localized programmed cell death, known as the hypersensitive response (HR). In this study, we examine the influence of elevated temperature on two ETI outputs: HR and pathogen virulence suppression. We found that in the Arabidopsis thaliana accession Col-0, elevated temperatures suppress the HR, but have minimal influence on ETI-associated P. syringae virulence suppression, thereby uncoupling these two ETI responses. We also identify accessions of Arabidopsis that exhibit impaired P. syringae virulence suppression at elevated temperature, highlighting the natural variation that exists in coping with biotic and abiotic stresses. These results not only reinforce the influence of abiotic factors on plant immunity but also emphasize the importance of carefully documented environmental conditions in studies of plant immunity.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.340

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.223
Teacher spread0.207 · 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 designObservational
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

Citations60
Published2015
Admission routes2
Has abstractyes

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