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Record W3015071465 · doi:10.3390/plants9040434

Diversity, Function and Regulation of Cell Surface and Intracellular Immune Receptors in Solanaceae

2020· review· en· W3015071465 on OpenAlexafffund
Jong Hum Kim, Christian Danve M. Castroverde

Bibliographic record

VenuePlants · 2020
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsWilfrid Laurier University
FundersNational Research Foundation of KoreaWilfrid Laurier University
KeywordsBiologyReceptorEffectorImmune systemImmune receptorIntracellularLeucine-rich repeatCell biologyFunction (biology)ExtracellularCell surface receptorSolanaceaeComputational biologyGeneticsGene

Abstract

fetched live from OpenAlex

The first layer of the plant immune system comprises plasma membrane-localized receptor proteins and intracellular receptors of the nucleotide-binding leucine-rich repeat protein superfamily. Together, these immune receptors act as a network of surveillance machines in recognizing extracellular and intracellular pathogen invasion-derived molecules, ranging from conserved structural epitopes to virulence-promoting effectors. Successful pathogen recognition leads to physiological and molecular changes in the host plants, which are critical for counteracting and defending against biotic attack. A breadth of significant insights and conceptual advances have been derived from decades of research in various model plant species regarding the structural complexity, functional diversity, and regulatory mechanisms of these plant immune receptors. In this article, we review the current state-of-the-art of how these host surveillance proteins function and how they are regulated. We will focus on the latest progress made in plant species belonging to the Solanaceae family, because of their tremendous importance as model organisms and agriculturally valuable crops.

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 score0.981
Threshold uncertainty score0.243

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 science0.0000.000
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 head0.034
GPT teacher head0.222
Teacher spread0.188 · 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

Citations12
Published2020
Admission routes2
Has abstractyes

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