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Record W2084627784 · doi:10.1128/jvi.01151-09

Identification of Proteins from<i>Prunus persica</i>That Interact with Peach Latent Mosaic Viroid

2009· article· en· W2084627784 on OpenAlexafffund
Audrey Dubé, Martin Bisaillon, Jean‐Pierre Perreault

Bibliographic record

VenueJournal of Virology · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsUniversité de Sherbrooke
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiologyViroidRNAPrunusPlant virusCucumber mosaic virusVirologyGeneticsMolecular biologyGeneBotanyVirus

Abstract

fetched live from OpenAlex

Peach latent mosaic viroid (PLMVd) is a small, single-stranded, circular RNA pathogen that infects Prunus persica trees. As with all other known viroids, the PLMVd genome does not encode any proteins. Consequently, it must interact with host cellular factors in order to ensure its life cycle. With the objective of identifying cellular proteins that interact with PLMVd, Northwestern hybridizations were performed using partially purified peach leaf extracts. Mass spectrometric analysis of the detected RNA-protein complexes led to the identification of six putative RNA-binding proteins. One of these was found to be elongation factor 1-alpha (eEF1A), and because of its known involvement in the replication and translation of various RNA viruses, further characterizations were performed. Initially, the existence of this interaction received support from an experiment that immunoprecipitated the eEF1A from a crude extract of infected peach leaves, coupled with reverse transcription-PCR detection of the PLMVd. Subsequently, eEF1A interaction with PLMVd strands of both polarities was confirmed in vitro by electrophoresis mobility shift assays, fluorescence spectroscopy, and the prediction of an altered PLMVd RNase mapping profile in the presence of the protein. The potential contribution of eEF1A to the molecular biology of PLMVd, including for viroid replication, is discussed.

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 score0.790
Threshold uncertainty score0.131

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 head0.026
GPT teacher head0.254
Teacher spread0.228 · 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

Citations35
Published2009
Admission routes2
Has abstractyes

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