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Record W2768768191 · doi:10.1094/pdis-01-17-0107-re

Development of a Real-Time RT-PCR for the Universal Detection of LChV1 and Study of the Seasonal Fluctuation of the Viral Titer in Sweet Cherry Cultivars

2017· article· en· W2768768191 on OpenAlexfundno aff
Asimina Katsiani, Polyxeni G. Pappi, Antonio Olmos, Konstantinos Efthimiou, Varvara I. Maliogka, Nikolaos I. Katis

Bibliographic record

VenuePlant Disease · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsnot available
FundersEuropean Social FundAgriculture and Agri-Food CanadaUniversität HamburgAristotle University of ThessalonikiConsiglio Nazionale delle RicercheEuropean Commission
KeywordsBiologyTaqManPrunusTiterVirologyReal-time polymerase chain reactionGeminiviridaeReverse transcription polymerase chain reactionPlant virusPolymerase chain reactionVirusCapsidCultivarHorticultureGeneGeneticsGene expressionBegomovirus

Abstract

fetched live from OpenAlex

Little cherry virus 1 (LChV1) is a sweet cherry pathogen which has lately been reported in other Prunus spp. LChV1 variability makes reliable detection a challenging undertaking. The objective of this work was to develop a rapid, sensitive, and reliable one-tube, real-time reverse-transcription polymerase chain reaction (RT-PCR) for the detection and quantification of LChV1. Primers and a TaqMan probe were designed, using conserved regions of the capsid protein gene. Detection range was evaluated using several divergent viral isolates. The amplification efficiency of the method was estimated at 96.7%, whereas the detection limit was about 100 RNA copies. The protocol was applied in the study of virus fluctuation within leaves and phloem tissue throughout the year and the best periods to test and plant tissues to sample were determined. Comparative analysis of this method with a previously published nested RT-PCR revealed the higher analytical and diagnostic sensitivity of the new test, making it a reliable tool that can be used in routine testing and certification programs.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.936
Threshold uncertainty score0.156

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 head0.037
GPT teacher head0.261
Teacher spread0.224 · 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 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

Citations16
Published2017
Admission routes1
Has abstractyes

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