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Record W2130279784 · doi:10.3389/fpls.2012.00308

Hijack it, change it: how do plant viruses utilize the host secretory pathway for efficient viral replication and spread?

2013· article· en· W2130279784 on OpenAlexaff
Camilo Patarroyo, Jean‐François Laliberté, Huanquan Zheng

Bibliographic record

VenueFrontiers in Plant Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsInstitut National de la Recherche ScientifiqueMcGill University
Fundersnot available
KeywordsHost (biology)Replication (statistics)Viral replicationBiologyPlant virusVirologyCell biologyVirusGenetics

Abstract

fetched live from OpenAlex

The secretory pathway of eukaryotic cells has an elaborated set of endomembrane compartments involved in the synthesis, modification, and sorting of proteins and lipids. The secretory pathway in plant cells shares many features with that in other eukaryotic cells but also has distinct characteristics important for fundamental cell and developmental processes and for proper immune responses. Recently, there has been evidence that the remodeling of this pathway, and often the formation of viral-induced organelles, play an important role in viral replication and spread. The modification of the host secretory pathway seems to be a common feature among most single-stranded positive ss(+)RNA and even some DNA viruses. In this review, we will present the recent advances in the understanding of the organization and dynamics of the plant secretory pathway and the molecular regulation of membrane trafficking in the pathway. We will also discuss how different plant viruses may interact with the host secretory pathway for their efficient replication and spread, with a focus on tobacco mosaic virus and turnip mosaic virus.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0040.007
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0010.002

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 head0.066
GPT teacher head0.264
Teacher spread0.198 · 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 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

Citations43
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueFrontiers in Plant ScienceSame topicPlant Virus Research StudiesFrench-language works237,207