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Quantitative study of persistence of human norovirus genome in water using TaqMan real-time RT-PCR

2007· article· en· W1994632990 on OpenAlexafffund
E.S. Ngazoa, Ismaı̈l Fliss, Julie Jean

Bibliographic record

VenueJournal of Applied Microbiology · 2007
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTaqManNorovirusReal-time polymerase chain reactionBiologyPersistence (discontinuity)SewageVirologyViral loadDigital polymerase chain reactionRNAMolecular biologyPolymerase chain reactionVirusGeneticsEnvironmental scienceGeneEnvironmental engineering

Abstract

fetched live from OpenAlex

AIMS: To evaluate the persistence of human norovirus (NoV) in different types of water at various temperatures using conventional and TaqMan real-time reverse transcription-PCR (RT-PCR). METHODS AND RESULTS: Water from different sources was spiked with NoV and incubated at different temperatures over a 3-month period. NoV viral RNA was amplified by one-step TaqMan real-time RT-PCR and by conventional two-step RT-PCR. NoV persisted in mineral and tap water for over 2 months at all tested temperatures but disappeared after 100 days. At 4 and -20 degrees C, viral degradation was slower than that at 25 degrees C. In river water and effluent from primary sewage treatment, a slight reduction in viral load was observed after 1 month at 4 degrees C. This is the first demonstration of medium-to-long-term survival of human NoVs in different types of water using TaqMan real-time detection. CONCLUSIONS: NoV genome may persist for long periods of time in different types of water. Quantitative TaqMan real-time RT-PCR is a sensitive system that allows accurate evaluation of the persistence of human NoVs in different water samples. SIGNIFICANCE AND IMPACT OF THE STUDY: Our study is one of the few to demonstrate the ability of NoV to survive for a long time in water.

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)0.002
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.391
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
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 head0.062
GPT teacher head0.353
Teacher spread0.292 · 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

Citations73
Published2007
Admission routes2
Has abstractyes

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