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Record W4404066770 · doi:10.1139/gen-2024-0088

Plant immune resilience to a changing climate: molecular insights and biotechnological roadmaps

2024· review· en· W4404066770 on OpenAlexafffundvenue
Christian Danve M. Castroverde, Chi Kuan, Jong Hum Kim

Bibliographic record

VenueGenome · 2024
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Parasitism and Resistance
Canadian institutionsWilfrid Laurier University
FundersNatural Sciences and Engineering Research Council of CanadaGraduate School, Duke UniversityNational Research FoundationWilfrid Laurier UniversityNational Research Foundation of KoreaCanada Foundation for InnovationHoward Hughes Medical Institute
KeywordsBiologyChromatinImmune systemEpigeneticsPlant ImmunityComputational biologyPlant disease resistanceDiseasePsychological resilienceResistance (ecology)Resilience (materials science)SignallingBiotechnologyGeneArabidopsisGeneticsCell biologyEcology

Abstract

fetched live from OpenAlex

Successful resistance to disease-causing pathogens is underpinned by properly regulated immune signalling and defence responses in plants. The plant immune system is controlled at multiple levels of gene and protein regulation-from chromatin-associated epigenetic processes to protein post-translational modifications. Optimal fine-tuning of plant immune signalling and responses is important to prevent plant disease development, which is being exacerbated by a globally changing climate. In this review, we focus on how changing climatic factors mechanistically intercept plant immunity at different levels of regulation (chromatin, transcriptional, post-transcriptional, translational, and post-translational). We specifically highlight recent studies that have provided molecular insights into critically important climate-sensitive nodes and mechanisms of the plant immune system. We then propose several potential future directions to build climate-resilient plant disease resistance using cutting-edge biotechnology. Overall, this conceptual understanding and promising biotechnological advances provide a foundational platform towards novel approaches to engineer plant immune resilience.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.019
GPT teacher head0.245
Teacher spread0.227 · 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 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
Published2024
Admission routes3
Has abstractyes

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