Evaluation of the drug-resistance genotypes of Dirofilaria immitis infections in Ontario dogs (2015–2016)
Bibliographic record
Abstract
For more than 3 decades, macrocyclic lactone (ML) heartworm preventives have been extremely effective at preventing Dirofilaria immitis infections in dogs. Reports of loss of efficacy (LOE) of the MLs in the early 2000s led to in-depth research which identified the presence of resistant strains of D. immitis in the Southeast United States. Detailed genetic analysis of such parasites identified genetic markers for resistance. In order to evaluate the prevalence of these markers in Ontario infections, microfilariae (MF) from 39 Ontario dogs, 22 from a ML-naïve population and 17 from a ML-exposed population, were collected in 2015-2016, analyzed and compared. The ML-naïve population comprised stray dogs from an area near Caledonia, Ontario where heartworm preventives have historically been rarely used. The ML-exposed population comprised client-owned dogs from veterinary practices across Ontario where preventives are commonly used. Overall, MF with resistant markers (two single nucleotide polymorphisms [SNPs]) were found in 3/39 dogs. However, in only one of those infections were both SNPs associated with ML resistance present. There was no significant difference in prevalence of these genetic markers for resistance between the ML-naïve population and the ML-exposed population of dogs (n = 22 genotyped and n = 17 genotyped, respectively). Despite the low prevalence of infections with ML-resistant genotypes, the fact that none of the dogs in this study had traveled outside Ontario suggests that the infections with ML-resistant genotypes were locally acquired.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".