Benzimidazole F167Y polymorphism in the canine hookworm, Ancylostoma caninum: Widespread geographic, seasonal, age, and breed distribution in United States and Canada dogs
Bibliographic record
Abstract
Surveillance data for Ancylostoma spp. and the A. caninum benzimidazole treatment resistance associated F167Y polymorphism using molecular diagnostics was obtained in a large population of dogs from the United States and Canada. Real-time PCR (qPCR) for Ancylostoma spp. and allele-specific qPCR detecting a single nucleotide polymorphism (SNP) F167Y was used in 262,872 canine stool samples collected between March and December of 2022. Ancylostoma spp. was found at an overall prevalence of 2.5% (6538/262,872), with the highest prevalence in the Southern US, 4.4% (4490/103,095), and the lowest prevalence in Canada 0.6% (101/15,829). The A. caninum F167Y polymorphism was found with the highest prevalence (13.4%, n = 46/343) in the Western US and the lowest in Canada at 4.1% (4/97). The F167Y polymorphism was detected every month over the 10-month collection period. Seasonal distribution showed a peak in June for both Ancylostoma spp. (3.08%, 547/17,775) and A. caninum F167Y (12.25%, 67/547). However, the A. caninum F167Y polymorphism prevalence was highest in September (13.9%, 119/856). Age analysis indicates a higher prevalence of both hookworm infections and occurrence of resistant isolates in puppies. The breeds with the highest F167Y polymorphism prevalence in Ancylostoma spp. detected samples were poodles (28.9%), followed by Bernese Mountain dogs (25%), Cocker spaniels (23.1%), and greyhounds (22.4%). Our data set describes widespread geographic distribution of the A. caninum benzimidazole resistance associated F167Y polymorphism in the United States and Canada, with no clear seasonality compared to the Ancylostoma spp. prevalence patterns. The F167 polymorphism was present in all geographic areas with detected hookworms, including Canada. Our study highlights that the F167Y polymorphism is represented in many dog breeds, including greyhounds.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".