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Record W4313475525 · doi:10.3390/jof9010012

Progress and Challenges in Elucidating the Functional Role of Effectors in the Soybean-Phytophthora sojae Interaction

2022· review· en· W4313475525 on OpenAlexafffund
Mst Hur Madina, Parthasarathy Santhanam, Yanick Asselin, Rajdeep Jaswal, Richard R. Bélanger

Bibliographic record

VenueJournal of Fungi · 2022
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicPlant-Microbe Interactions and Immunity
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhytophthora sojaeEffectorBiologyContext (archaeology)Cell biologyPhytophthoraApoplastHost (biology)GeneticsCell wallBotany

Abstract

fetched live from OpenAlex

Phytophthora sojae, the agent responsible for stem and root rot, is one of the most damaging plant pathogens of soybean. To establish a compatible-interaction, P. sojae secretes a wide array of effector proteins into the host cell. These effectors have been shown to act either in the apoplastic area or the cytoplasm of the cell to manipulate the host cellular processes in favor of the development of the pathogen. Deciphering effector-plant interactions is important for understanding the role of P. sojae effectors in disease progression and developing approaches to prevent infection. Here, we review the subcellular localization, the host proteins, and the processes associated with P. sojae effectors. We also discuss the emerging topic of effectors in the context of effector-resistance genes interaction, as well as model systems and recent developments in resources and techniques that may provide a better understanding of the soybean-P. sojae interaction.

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)0.001
metaresearch head score (Gemma)0.001
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
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.109
GPT teacher head0.302
Teacher spread0.193 · 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

Citations2
Published2022
Admission routes2
Has abstractyes

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