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Record W3168056659 · doi:10.1094/mpmi-03-21-0073-cr

Tandem Protein Kinases Emerge as New Regulators of Plant Immunity

2021· review· en· W3168056659 on OpenAlexaff
Valentyna Klymiuk, Gitta Coaker, Tzion Fahima, Curtis Pozniak

Bibliographic record

VenueMolecular Plant-Microbe Interactions · 2021
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsUniversity of Saskatchewan
FundersNational Institute of General Medical SciencesU.S. Department of AgricultureUnited States-Israel Binational Science FoundationNational Science Foundation
KeywordsLeucine-rich repeatBiologyEffectorIntracellularCell biologyGeneExtracellularImmune systemKinaseImmune receptorPathogenPlant ImmunityReceptorR geneImmunityGeneticsPlant disease resistanceArabidopsis

Abstract

fetched live from OpenAlex

Plant–pathogen interactions result in disease development in a susceptible host. Plants actively resist pathogens via a complex immune system comprising both surface-localized receptors that sense the extracellular space as well as intracellular receptors recognizing pathogen effectors. To date, the majority of cloned resistance genes encode intracellular nucleotide-binding leucine-rich repeat receptor proteins. Recent discoveries have revealed tandem kinase proteins (TKPs) as another important family of intracellular proteins involved in plant immune responses. Five TKP genes—barley Rpg1 and wheat WTK1 (Yr15), WTK2 (Sr60), WTK3 (Pm24), and WTK4—protect against devastating fungal diseases. Moreover, a large diversity and numerous putative TKPs exist across the plant kingdom. This review explores our current knowledge of TKPs and serves as a basis for future studies that aim to develop and exploit a deeper understanding of innate plant immunity receptor proteins. [Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.002

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 head0.280
Teacher spread0.246 · 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 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

Citations48
Published2021
Admission routes1
Has abstractyes

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