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Record W3134596640 · doi:10.1111/jph.12989

Host autophagy is a shared target of virulence factors of <i>Phytophthora infestans</i> and <i>Plasmodium</i> parasite

2021· article· en· W3134596640 on OpenAlexaff
Wenxian Wu, Raju Datla, Maozhi Ren

Bibliographic record

VenueJournal of Phytopathology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsGlobal Institute for Water SecurityUniversity of Saskatchewan
FundersNational Natural Science Foundation of China
KeywordsPhytophthora infestansBiologyEffectorVirulencePlasmodium (life cycle)GeneGeneticsPathogenGenomeVirulence factorSecretionCell biologyParasite hosting

Abstract

fetched live from OpenAlex

Abstract Phytophthora infestans and Plasmodium are extremely harmful and economically important pathogens. Although they belong to distinct groups and infect very different hosts, P. infestans and Plasmodium display some common similarities. Such as they are closely related phylogenetically and have similarities in the strategies they use for the evasion or suppression of host defences, etc. In addition, both pathogens produce abundant effector proteins that confer enhanced pathogenicity and adaptability. The P. infestans RxLR (Arg‐X‐Leu‐Arg) effector protein shares a conserved host‐targeting motif with the Plasmodium PEXEL‐containing export protein. In this review, we focused on the common distribution features of P. infestans RxLR genes and Plasmodium virulence factor genes in genomes, comparative analysis of the both types of virulence proteins secretion and translocation processes, and description of their molecular functions. We highlight the convergent evolutionary characteristics of P. infestans RxLR effector protein and Plasmodium virulence factor in mediating the autophagy process of host cells. This review will present and discuss current research challenges and opportunities for future research to get better understanding and insights by investigating pathogen effector–host interactions.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.265

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.026
GPT teacher head0.265
Teacher spread0.240 · 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 designBench or experimental
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
Published2021
Admission routes1
Has abstractyes

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