Immune based detection of Angiostrongylus vasorum infection in dogs and molecular characterization of the antigen
Bibliographic record
Abstract
Angiostrongylus vasorum (French heartworm) is a metastrongylid nematode which infects the pulmonary artery and right ventricle of wild and domestic canids and can lead to fatal cardiopulmonary disease in infected dogs. In North America, there is an endemic focus of infection in Newfoundland, Canada. Diagnosis is made by detection of first-stage larvae by Baermann fecal examination, however, fecal diagnosis can lack sensitivity due to intermittent shedding of larvae. In this study we developed serological tests to detect French Heartworm similar to those used for the diagnosis of North American Heartworm (Dirofilaria immitis) infection. An initial attempt to use an enzyme-linked immunosorbent assay (ELISA) to detect antibodies to the parasite was confounded by significant cross-reactivity to antigens of Crenosoma vulpis, which is a metastrongylid nematode that is also common in Atlantic Canada. We therefore developed a sandwich ELISA to detect circulating antigens of A. vasorum using rabbit polyclonal antiserum prepared against whole-worm adult antigen. A test positive cut-off value and test sensitivity and specificity were determined by two-graph receiver operating characteristic curve (ROC) analysis using sera from 24 Baermann positive A. vasorum dogs from Newfoundland and sera from 52 Baermann negative A. vasorum dogs from non endemic areas. An optical density of 0.19 was used as the positive cutoff and the test specificity was 100% with a sensitivity of 92%. Furthermore, sera from 30 Crenosoma vulpis positive dogs were tested and found to be negative on the sandwich ELISA. A survey of dogs from Newfoundland with signs of cardiopulmonary disease compared Baermann fecal results with the sandwich ELISA and indicated that fecal testing may have missed almost half of the infections. To standardize the test, increase sensitivity, and develop a dependable source of diagnostic antigen(s), this study characterized some immunoreactive antigen(s) detected in the sandwich ELISA test. We developed a cDNA library from adult A. vasorum and after screening with rabbit anti-A. vasorum serum we identified 8 immunoreactive clones. Sequence analysis showed these clones to contain sequences homologous to 3 proteins, which shared homology to similar proteins in other parasites: vitellogenin, tropomyosin and heat shock protein 70 (Hsp70).
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".