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Record W2314881324 · doi:10.1021/es502794h

Insertion/Deletion-Based Approach for the Detection of <i>Escherichia coli</i> O157:H7 in Freshwater Environments

2014· article· en· W2314881324 on OpenAlexafffund
Shirley Wong, Athanasios Paschos, Radhey S. Gupta, Herb E. Schellhorn

Bibliographic record

VenueEnvironmental Science & Technology · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEscherichia coli research studies
Canadian institutionsMcMaster University Medical CentreMcMaster University
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and Science
KeywordsEscherichia coliBiologyTaqManPathogenSerotypeMicrobiologyPolymerase chain reactionPlasmidEnterobacteriaceaeGenomeGeneDNAHeterologousGeneticsVirologyMolecular biology

Abstract

fetched live from OpenAlex

Enterohemorrhagic Escherichia coli O157:H7 is responsible for many outbreaks of gastrointestinal illness and hemolytic uremic syndrome worldwide. Monitoring this pathogen in food and water supplies is an important public health issue. Highly conserved genetic markers, which are characteristic for specific strains, can provide direct identification of target pathogens. In this study, we examined a new detection strategy for pathogenic strains of E. coli O157:H7 serotype based on a conserved signature insertion/deletion (CSI) located in the ybiX gene using TaqMan-probe-based quantitative PCR (qPCR). The qPCR assay was linear from 1.0 × 10(2) to 1.0 × 10(7) genome copies and was specific to O157:H7 when tested against a panel of 15 non-O157:H7 E. coli. The assay also maintained detection sensitivity in the presence of competing E. coli K-12, heterologous nontarget DNA spiked in at a 1000-fold and 800-fold excess of target DNA, respectively, demonstrating the assay's ability to detect E. coli O157:H7 in the presence of high levels of background DNA. This study thus validates the use of strain-specific CSIs as a new class of diagnostic marker for pathogen detection.

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)0.001
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 score0.073
Threshold uncertainty score0.657

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.006
GPT teacher head0.220
Teacher spread0.214 · 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

Citations43
Published2014
Admission routes2
Has abstractyes

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