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Record W4200530105 · doi:10.1177/10406387211065501

Characterization of 2 <i>Klebsiella pneumoniae</i> carbapenemase–producing Enterobacterales isolated from canine rectal swabs

2021· article· en· W4200530105 on OpenAlexaboutno aff
Stephen D. Cole, Shelley C. Rankin

Bibliographic record

VenueJournal of Veterinary Diagnostic Investigation · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
FundersU.S. Food and Drug Administration
KeywordsKlebsiella pneumoniaeBiologyMicrobiologyPlasmidOutbreakWhole genome sequencingKlebsiellaEscherichia coliVirologyGeneGenomeGenetics

Abstract

fetched live from OpenAlex

Globally, carbapenemase-producing Enterobacterales (CPE) cause life-threatening, hospital-acquired infections in people, and have been reported recently among veterinary patients. Organisms that produce a Klebsiella pneumoniae carbapenemase (KPC) are one of the most common CPE isolated from people but have been reported only rarely in animals. We characterized 2 KPC-producing Enterobacterales isolated from companion animal rectal swabs during the response to an outbreak caused by a strain of bla NDM-5 Escherichia coli. Both isolates were characterized by whole-genome sequencing (WGS) and analysis. The first isolate (case A) was from an immunosuppressed 6-y-old Yorkshire Terrier and was identified as E. coli (ST372) with a bla KPC-18 gene and an IncFII plasmid. The second isolate (case B) was from a 3-y-old Labrador Retriever with acute diarrhea and was identified as Citrobacter koseri with a bla KPC-2 gene, multiple plasmids (ColRNAI, pKPC-CAV1193), and a putative enterotoxin gene ( senB). Further research is needed to determine what role animals might play in the epidemiology of CPE in communities. It is imperative that all CPE isolated from companion animals be fully characterized by WGS and the associated case examined. All veterinary isolates should be sequenced and shared for surveillance, monitoring, and investigation purposes.

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)0.001
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 score0.181
Threshold uncertainty score0.725

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.013
GPT teacher head0.236
Teacher spread0.223 · 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

Citations8
Published2021
Admission routes1
Has abstractyes

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