Genotyping USA laboratory-maintained isolates and European clinical isolates of Dirofilaria immitis to assess macrocyclic lactone susceptibility or resistance at predictive SNP sites using droplet digital PCR
Bibliographic record
Abstract
Dirofilaria immitis is a parasitic nematode that causes cardiovascular dirofilariosis ("heartworm disease") primarily in canids. The principal approach for mitigating heartworm infection involves the use of macrocyclic lactone (ML) for prophylaxis. Recent research has substantiated the emergence of D. immitis displaying resistance to MLs in the USA. Numerous factors, such as the mobility of companion animals and competent vectors could impact the spread of drug resistance. Genomic analysis has unveiled that isolates resistant to ML exhibit unique genetic profiles when compared to their wild-type (susceptible) counterparts. Out of the ten single nucleotide polymorphism (SNP) markers validated in clinical samples of D. immitis from the USA, four have demonstrated their effectiveness in distinguishing between isolates with varying ML efficacy phenotypes. This study explores the potential of these confirmed SNPs for conducting surveillance studies. Genotypic analysis using SNP markers emerges as a valuable tool for carrying out surveys and evaluating individual clinical isolates. Two USA laboratory-maintained isolates (Berkeley, WildCat) and twenty-five random European clinical samples of either adult worms or microfilariae (mf) pools isolated from domestic dogs, were tested by droplet digital PCR (ddPCR)-based duplex assay. This approach elucidates genetic evidence pertaining to the development of drug resistance and provides baseline data on resistance related genotypes in Europe. The data on these clinical samples suggests genotypes consistent with the continued efficacy of ML treatment regimens in Europe. In addition, this assay can be significant in discriminating cases of drug-resistance from those possibly due to non-compliance to the recommended preventive 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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".