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Record W4396230787 · doi:10.1093/plcell/koae131

From algae to apples: The structural and functional conservation of NLRs

2024· editorial· en· W4396230787 on OpenAlexaff
Michael Busche, Bradley Laflamme

Bibliographic record

VenueThe Plant Cell · 2024
Typeeditorial
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsBiologyInnate immune systemFunction (biology)NOD1EffectorImmune systemCell biologyImmunityEvolutionary biologyGeneticsComputational biology

Abstract

fetched live from OpenAlex

Plant species have been warding off microbial infections throughout their evolutionary history, which has led to the development of innate immune systems tailored to sensing and responding to pathogens.In plants, the intracellular immune response is spearheaded by Nucleotide-Binding Leucine-Rich-Repeat Receptors, or NLRs, which often detect "effector" virulence proteins used by pathogens to evade or subvert host defenses.Upon activation, NLRs induce a suite of defense responses, including accumulation of defense hormones, induction of immune-related genes, and activation of programmed cell death (Adachi et al. 2019).A key to the function of NLRs is oligomerization driven by the nucleotide-binding domain upon binding of ATP.Such oligomers are referred to as "resistosomes", but the function of resistosomes differs between subclasses of NLRs and is determined by their N-terminal domains and subcellular localization.The oldest group of NLRs in terms of evolution contain an N-terminal coiled-coil (CC) domain, some of which have been shown to form calcium channels upon oligomerization.(Hu and Chai 2023).While the field of NLR biology in plants has received an enormous amount of attention in the last five years, this attention has been focused almost entirely on angiosperms (or flowering plants).In this issue, Khong-Sam Chia and colleagues (Chia et al. 2024) expand our understanding of NLR biology in non-flowering plant lineages, identifying immunity-related mechanisms that have likely been in place for hundreds of millions of years.

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: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.375
Threshold uncertainty score0.998

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 head0.017
GPT teacher head0.204
Teacher spread0.187 · 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
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

Citations0
Published2024
Admission routes1
Has abstractyes

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