Multiple anthelmintic drug resistance in hookworms (Ancylostoma caninum) in a Labrador breeding and training kennel in Georgia, USA
Bibliographic record
Abstract
OBJECTIVE: To evaluate the efficacy of the 3 major classes of anthelmintics used for the treatment of hookworms in dogs in the US and an extralabel treatment with an FDA-approved product for use in cats in a Labrador kennel with a history of persistent hookworm infections. ANIMALS: 22 dogs housed in a single kennel comprised of the following breeds: 19 Labrador Retrievers, 1 English Cocker Spaniel, 1 Chesapeake Bay Retriever, and 1 Boykin Spaniel. PROCEDURES: We performed a fecal egg count (FEC) reduction test using 22 dogs that were allocated randomly to 1 of 5 treatment groups: pyrantel pamoate (Pyrantel pamoate suspension), fenbendazole (Safe-Guard suspension 10%), milbemycin oxime (Interceptor), moxidectin plus imidacloprid (Advantage Multi), and emodepside plus praziquantel (Profender topical solution for cats). FEC was performed on samples collected on days 0 and 11. RESULTS: FEC reductions for the milbemycin oxime, moxidectin plus imidacloprid, and emodepside plus praziquantel groups were 43.9%, 57.4%, and 100%, respectively. The FEC increased following treatment for the pyrantel and fenbendazole groups. CLINICAL RELEVANCE: These data demonstrate that the Ancylostoma caninum infecting the dogs in this kennel are highly resistant to all major anthelmintic classes approved for use in dogs in the US but are susceptible to emodepside. This was the first report of multiple anthelmintic drug-resistant A caninum in a dog kennel that does not involve 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".