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Record W3011195431 · doi:10.1093/cid/ciaa245

First European Haplotype of <i>Echinococcus multilocularis</i> Identified in the United States: An Emerging Disease?

2020· article· en· W3011195431 on OpenAlexaboutno aff
Louis B. Polish, Bobbi S. Pritt, Thomas F.E. Barth, Bruno Gottstein, Elise M. O’Connell, Pamela Church Gibson

Bibliographic record

VenueClinical Infectious Diseases · 2020
Typearticle
Languageen
FieldMedicine
TopicParasitic infections in humans and animals
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of Health
KeywordsEchinococcus multilocularisHaplotypeEchinococcusEchinococcosisMedicineParasitic diseaseDiseaseZoonotic diseaseEnvironmental healthGenotypeGeneticsBiologyPathologyGene

Abstract

fetched live from OpenAlex

BACKGROUND: Echinococcus multilocularis is one of the most severe and lethal parasitic diseases of humans, most often reported in Europe and Asia. Only 1 previous case has been documented in the contiguous United States from Minnesota in 1977. European haplotypes have been identified in carnivores and domestic dogs as well as recently in patients in western and central Canada. METHODS: We used immunohistochemical testing with the monoclonal antibody Em2G11 and a species-specific enzyme-linked immunosorbent assay affinity-purified antigen Em2, as well as COX1 gene sequencing. RESULTS: Using pathology, immunohistochemical staining, specific immunodiagnostic testing, and COX1 gene sequencing, we were able to definitively identify E. multilocularis as the causative agent of our patient's liver and lung lesions, which clustered most closely with the European haplotype. CONCLUSIONS: We have identified the first case of a European haplotype E. multilocularis in the United States and the first case of this parasitic infection east of the Mississippi River. Given the identification of this haplotype in Canada, this appears to be an emerging infectious disease in North America.

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)0.002
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 score0.009
Threshold uncertainty score0.582

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.101
GPT teacher head0.401
Teacher spread0.300 · 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

Citations30
Published2020
Admission routes1
Has abstractyes

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