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Comparison of DNA Fingerprinting Methods for Use in Investigation of Type E Botulism Outbreaks in the Canadian Arctic

2006· article· en· W2118124254 on OpenAlexafffundabout
Daniel Leclair, Franco Pagotto, Jeffrey M. Farber, Brigitte Cadieux, John W. Austin

Bibliographic record

VenueJournal of Clinical Microbiology · 2006
Typearticle
Languageen
FieldMedicine
TopicBotulinum Toxin and Related Neurological Disorders
Canadian institutionsHealth Canada
FundersHealth Canada
KeywordsPulsed-field gel electrophoresisRibotypingBiologyMicrobiologyTypingDNA profilingRAPDOutbreakSerotypeClostridium botulinumVirologyPolymerase chain reactionGeneticsGenotypeDNAToxinGenetic diversityMedicineGenePopulation

Abstract

fetched live from OpenAlex

Pulsed-field gel electrophoresis (PFGE), randomly amplified polymorphic DNA (RAPD) analysis, and automated ribotyping were compared for epidemiological typing of Clostridium botulinum type E using clinical and food isolates associated with four botulism outbreaks occurring in the Canadian Arctic. All type E strains previously untypeable by PFGE, even with the use of a formaldehyde fixation step, could be typed by the addition of 50 microM thiourea to the electrophoresis running buffer. Digestion with SmaI or XhoI followed by PFGE was used to link food and clinical isolates from four different type E botulism outbreaks and differentiate them from among 39 group II strains. Strain differentiation was unsuccessful with the automated ribotyping system, producing a single characteristic EcoRI fingerprint common to all group II strains. RAPD analysis of C. botulinum group II strains was not consistently reproducible with primer OPJ-6 or OPJ-13, apparently discriminating between epidemiologically related strains. A modified PFGE protocol was judged to be the most useful method for typing epidemiologically related C. botulinum type E strains, based on its ability to type all strains reproducibly and with an adequate level of discrimination.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.151
GPT teacher head0.457
Teacher spread0.306 · 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

Citations59
Published2006
Admission routes3
Has abstractyes

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