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Record W3102250328 · doi:10.3390/tropicalmed5040173

Microbiome Composition and Borrelia Detection in Ixodes scapularis Ticks at the Northwestern Edge of Their Range

2020· article· en· W3102250328 on OpenAlexafffundabout
Janet L. H. Sperling, Daniel T. Fitzgerald, Felix A. H. Sperling, Katharine E. Magor

Bibliographic record

VenueTropical Medicine and Infectious Disease · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaAlberta Innovates - Technology FuturesAlberta Conservation Association
KeywordsIxodes scapularisBorrelia burgdorferiBorreliaLyme diseaseTickBiologyIxodesIxodidaeMicrobiomeBorrelia gariniiMicrobiologyTick-borne diseaseZoologyEcologyVirologyImmunologyAntibody

Abstract

fetched live from OpenAlex

Lyme disease-causing Borrelia burgdorferi has been reported in 10–19% of Ixodes ticks from Alberta, Canada, where the tick vector Ixodes scapularis is at the northwestern edge of its range. However, the presence of Borrelia has not been verified independently, and the bacterial microbiome of these ticks has not been described. We performed 16S rRNA bacterial surveys on female I. scapularis from Alberta that were previously qPCR-tested in a Lyme disease surveillance program. Both 16S and qPCR methods were concordant for the presence of Borrelia. The 16S studies also provided a profile of associated bacteria that showed the microbiome of I. scapularis in Alberta was similar to other areas of North America. Ticks that were qPCR-positive for Borrelia had significantly greater bacterial diversity than Borrelia-negative ticks, on the basis of generalized linear model testing. This study adds value to ongoing tick surveillance and is a foundation for deeper understanding of tick microbial ecology and disease transmission in a region where I. scapularis range expansion, induced by climate and land use changes, is likely to have increasing public health implications.

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)0.000
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 score0.160
Threshold uncertainty score0.521

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.011
GPT teacher head0.229
Teacher spread0.218 · 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

Citations19
Published2020
Admission routes3
Has abstractyes

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