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Record W2007555612 · doi:10.1111/lam.12173

A fluorescence-based method coupled with Disruptor filtration for rapid detection of F <b>+</b> RNA phages

2013· article· en· W2007555612 on OpenAlexafffund
Yongheng Yang, Mansel W. Griffiths

Bibliographic record

VenueLetters in Applied Microbiology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicFecal contamination and water quality
Canadian institutionsUniversity of Guelph
FundersMcGill UniversityU.S. Department of AgricultureU.S. Environmental Protection Agency
KeywordsRNALytic cycleFiltration (mathematics)FluorescenceBiologyChromatographyBacteriophageContaminationDetection limitMicrobiologyMolecular biologyChemistryVirologyEscherichia coliBiochemistryGeneVirusPhysics

Abstract

fetched live from OpenAlex

UNLABELLED: F + RNA phages are commonly used as indicators of faecal contamination. This study evaluated a fluorescent method for the detection of F + RNA phages based on testing the phage-mediated release of β-galactosidase. Factors that may potentially interfere with phage detection were investigated, and the assay was optimized. Low numbers of F + RNA phages were detected by the fluorescent method coupled with a concentration step using a Disruptor filter. The fluorescent method, when used alone, detected 1 log PFU ml(-1) of F+RNA phages within 3 h, while 0.01 PFU ml(-1) was detected within 5 h when the method was combined with the concentration step. This is the first time to combine a fluorescent method with a filtration step by the use of Disruptor filter for rapid detection of low numbers of F + RNA phages, and this method can be adapted to detect other lytic phages infecting host cells that produce measurable enzyme activity. SIGNIFICANCE AND IMPACT OF THE STUDY: A fluorescent method coupled with Disruptor filtration was evaluated for the first time to rapidly detect low numbers of F + RNA phages. Rapid detection of F + RNA phages provides an effective way to monitor faecal contamination of environmental water and thus helps prevent contamination of fresh produce via irrigation.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.256
Threshold uncertainty score0.351

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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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

Citations1
Published2013
Admission routes2
Has abstractyes

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