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Record W4412988917 · doi:10.1016/j.ijpddr.2025.100604

Surveillance of single nucleotide polymorphisms correlated to macrocyclic lactone resistance in Dirofilaria immitis from client-owned dogs across the United States

2025· article· en· W4412988917 on OpenAlexafffundabout
Emily Curry, David C. Tack, Jessica Rodriguez, Danielle Brehm-Lowe, John Letherer, Megan W. Lineberry, Roger K. Prichard, Tobias Clark

Bibliographic record

VenueInternational Journal for Parasitology Drugs and Drug Resistance · 2025
Typearticle
Languageen
FieldMedicine
TopicParasitic Diseases Research and Treatment
Canadian institutionsMcGill University
FundersGénome Québec
KeywordsDirofilaria immitisSingle-nucleotide polymorphismGeneticsNucleotideResistance (ecology)MedicineBiologyGeneHelminthsGenotypeImmunologyEcology

Abstract

fetched live from OpenAlex

Dirofilaria immitis is a parasitic filarial nematode and the causative agent of heartworm disease in canids and other species. Heartworm disease is predominantly managed via macrocyclic lactone (ML) - based chemoprophylactics. Through opportunistic sampling, genotypically and phenotypically confirmed ML-resistant D. immitis isolates have been isolated in the Lower Mississippi River Valley region (LMRV); however, the pervasiveness of resistant isolates in the USA has not been evaluated. This study aimed to evaluate the geographic distribution and prevalence of genotypically ML-resistant heartworms in client-owned dogs across the USA over a 3-year period. Owner consent was obtained to collect microfilaremic blood samples from heartworm-positive dogs from participating clinics. Veterinarians completed a questionnaire on the known history of each dog, including treatment and travel history. A total of 310 microfilaremic blood samples were collected from 45 geographically diverse veterinary clinics located in 22 states. Microfilariae were filtered from blood, DNA extracted utilizing the QIAGEN QIAamp DNA Micro Kit and samples sequenced by the Génome Québec Innovation Centre to determine allele frequencies at nine SNP sites previously correlated with ML resistance. The highly predictive 2-SNP model was used to identify genotypically susceptible, mixed, and resistant populations. Computational analysis indicated 111 (35.8 %) were genotypically susceptible, 96 (31.0 %) were genotypically resistant, and 103 (33.2 %) were genotypically mixed. The genotypically mixed and ML-resistant infections were located within and outside of the endemic LMRV, as far north as Michigan, which indicates canine populations outside of the LMRV are at increased risk for transmission of potentially ML-resistant heartworm infections than previously hypothesized. Veterinary practitioners across the USA need to be aware of the potential risks of ML resistance heartworm infections and ensure patient compliance with recommended prevention protocols.

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 score0.025
Threshold uncertainty score0.612

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 studies0.0000.000
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 head0.010
GPT teacher head0.350
Teacher spread0.339 · 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

Citations3
Published2025
Admission routes3
Has abstractyes

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