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Record W2368121580

Establishment of Reverse Transcription Helicase-Dependent Isothermal Amplification for Rapid Detection of Foot-and-Mouth Disease Virus

2014· article· en· W2368121580 on OpenAlexaff
Sun Yat

Bibliographic record

VenueXumu yu shouyi · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Disease Management and Epidemiology
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsVirologyFoot-and-mouth disease virusVirusClassical swine feverBiologyReverse Transcription Loop-mediated Isothermal AmplificationReverse transcriptaseLoop-mediated isothermal amplificationHelicaseFoot-and-mouth diseaseVesicular stomatitis virusRNADNAMolecular biologyGeneGenetics
DOInot available

Abstract

fetched live from OpenAlex

A rapid detection method of foot- and- mouth disease virus( FMDV) was established based on reverse transcription helicase- dependent isothermal amplification( RT- HAD). Its sensitivity and specificity were assessed and compared with RT- PCR method. The results showed that target fragment of FMDV RNA could be amplified by incubating at 65 ℃ for 120 minutes using a pair of primers designed based on the conservative sequence of foot- and- mouth disease virus genome. The detection limit of this method was 0. 2 ng of RNA sample which was 10 fold higher than that of RT- PCR.The specificity of this method is also high. We couldn't detection swine vesicular disease virus( SVDV) 、porcine reproductive and respiratory syndrome virus( PRRSV) 、swine fever virus( CSFV) 、porcine parvo virus( PPV) and vesicular stomatitis virus( VSV) by this method with the primers of FMDV.RT- HDA detection method of FMDV not only has high sensitivity and specificity,but also does not require expensive equipment. These properties offer a great potential for the development of simple portable DNA diagnostic devices to be used in the field and at the point- of- care.

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 score0.883
Threshold uncertainty score0.194

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 head0.033
GPT teacher head0.240
Teacher spread0.208 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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