Dogs as victims of their own worms: Serodiagnosis of canine alveolar echinococcosis
Bibliographic record
Abstract
BACKGROUND: Besides acting as definitive hosts for Echinococcus multilocularis, dogs can become infected by the larval form of this parasite and thereby develop life-threatening alveolar echinococcosis (AE). Although AE is a zoonotic disease, most therapeutic and diagnostic approaches have been developed for human patients. In dogs, AE is typically diagnosed in the advanced stage of the disease when the parasitic mass has already caused abdominal distension. At that stage, complete resection of the parasitic mass is often impossible, leaving a guarded prognosis for the affected dogs. For humans, sensitive and specific diagnostic protocols relying on serology have been validated and are now widely used. In contrast, sensitive and specific laboratory diagnostic tools that would enable early diagnosis of canine AE are still lacking. The aim of the current study was to establish a serological protocol specifically adapted to dogs. METHODS: We tested several native and recombinant antigens (EmVF, Em2, recEm95, recEm18) in in-house ELISA, an in-house Western blot (WB), as well as a commercially available WB developed for serodiagnosing human AE (Anti-Echinococcus EUROLINE-WB®), using a panel of known status dog sera. RESULTS: RecEm95-antigen was revealed to be the most promising antigen for use in ELISA, demonstrating 100% (95% CI: 72-100%) sensitivity and 100% (95% CI: 93-100%) specificity in our study. The in-house WB using EmVF antigen performed as well as the recEm95-ELISA. The commercial WB also correctly identified all infected dogs, coupled with a specificity of 98% (95% CI: 91-100%). CONCLUSION: The recEm95-ELISA alone or in combination with either the in-house WB or the Anti-Echinococcus EUROLINE-WB® (IgG) with a minor modification should be considered as the best current approach for the serological diagnosis of dogs infected with the larval stage of E. multilocularis. However, larger studies with a focus on potentially cross-reacting sera should be undertaken to verify these findings.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 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 teacher head, 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".