Multiple Drug Resistance in the canine hookworm <i>Ancylostoma caninum</i> : an Emerging Threat
Bibliographic record
Abstract
Abstract In the past few years, diagnoses by veterinarians of recurrent canine hookworm infections have dramatically increased, suggesting that anthelmintic resistance (AR) may have evolved in the parasite Ancylostoma caninum . To investigate this, we established three “suspected-resistant” and two susceptible A. caninum isolates in research dogs for further study. The egg hatch assay (EHA) and the larval development assay (LDA) were used for detecting resistance to benzimidazoles, and macrocyclic lactones, respectively. Resistance ratios ranged from 6.0 to >100 and 5.5-69.8 for the EHA and LDA, respectively. Following treatments with fenbendazole, pyrantel and milbemycin oxime, reduction in faecal egg counts ranged from 64–86%, 0–72% and 58–92%, respectively. Deep amplicon sequencing of the isotype-1 β tubulin gene identified a high frequency of resistance-associated single nucleotide polymorphisms at codon 167 in the resistant isolates and clinical cases.. These data conclusively demonstrate multiple anthelmintic resistance in A. caninum , and provide pivotal evidence that this is an emerging problem in the United States. Consequently, these findings should provide some concern to the global health community, as the scale-up of mass drug administration for soil-transmitted helminths (STH) is now placing similar selection pressures for benzimidazole resistance in human hookworms.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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".