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Record W2399096442 · doi:10.1099/jmmcr.0.005045

First reported case of Campylobacter lanienae enteritis in a human

2016· article· en· W2399096442 on OpenAlexaff
Simon Lévesque, Frédéric Lemay, Sadjia Békal, Éric Frost, Sophie Michaud

Bibliographic record

VenueJMM Case Reports · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsCentre Hospitalier Universitaire de SherbrookeUniversité de SherbrookeInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsEnteritisCampylobacterMicrobiologyBiologyBacteriaGenetics

Abstract

fetched live from OpenAlex

Introduction: Campylobacters are the most frequently identified bacteria causing diarrhoea in humans worldwide. Campylobacter lanienae was isolated for the first time in 2000 from faecal samples of two asymptomatic abattoir workers in Switzerland during a routine hygiene screen, but has never been associated with human disease. Case presentation: At hospital admission, the patient reported diarrhoea, lower abdominal cramps, nausea, one episode of bilious vomiting and low-grade fever of 38 °C. The patient was having 10 or more diarrheic stools per day as well as during the night, and had noticed blood mixed with the stools on several occasions. Stool cultures were negative for species of Salmonella and Shigella , Escherichia coli O157:H7 and Yersinia enterocolitica , but were positive for C. lanienae . Identification was made by classical biochemical testing, as well as 16S rRNA gene and cpn60 sequencing. The patient slowly improved without antibiotic treatment and was discharged nine days after admission with complete resolution of symptoms. Conclusion: On the whole it seems very likely that C. lanienae was the causative agent. Clinical microbiologists should be aware of this micro-organism which can be identified by phenotypic and molecular methods. The real burden of C. lanienae infection in humans might be underestimated and should be further investigated as a potential cause of human diarrhoea disease.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.111
Threshold uncertainty score1.000

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.030
GPT teacher head0.264
Teacher spread0.234 · 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 designCase report
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

Citations15
Published2016
Admission routes1
Has abstractyes

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