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Viral diversity and phloem transcriptional changes in grapevine Shiraz disease infected vines

2025· article· en· W4406332767 on OpenAlexfundno aff
Cristóbal A. Onetto, Dilrukshi S. K. Nagahatenna, Yeniu Mickey Wang, Vinay Pagay, Anthony R. Borneman

Bibliographic record

VenueOENO One · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
FundersWine AustraliaAustralian GovernmentAlberta Water Research Institute
KeywordsPhloemBiologyVineCalloseVirologyGeneVirusPathosystemClosterovirusVitis viniferaPlant virusBotanyGenetics

Abstract

fetched live from OpenAlex

Shiraz disease (SD) is a highly destructive disease of grapevines that is associated with grapevine virus A (GVA) infection of vineyards in Australia and South Africa. However, little is known about the transcriptional modifications in grapevine phloem tissues induced by SD. In this study, we explored the viral diversity and transcriptional changes linked to SD. Vines symptomatic for SD exhibited higher viral abundance and were also shown to be co-infected with both GVA and grapevine leafroll-associated virus (GLRaV-4) strain 9. Differential gene (DE) expression analysis revealed physiological responses of Vitis vinifera to the infection. Similar to other plant pathogen infections, SD upregulated genes associated with the systemic acquired resistance (SAR) mechanism and downregulated genes related to vine immunity. Additionally, upregulated genes suggests that callose deposition and the blocking of phloem sieve elements are likely employed by V. vinifera as a defence strategy to limit the internal spread of SD viruses.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.042
GPT teacher head0.242
Teacher spread0.200 · 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 designObservational
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
Published2025
Admission routes1
Has abstractyes

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