Molecular epidemiology of Giardia duodenalis and Cryptosporidium spp on swine farms in Ontario, Canada
Bibliographic record
Abstract
A subset of swine farms in Ontario, Canada have been monitored for Cryptosporidium and Giardia.Fecal samples were collected from different stages of production as well as from manure pits.G. duodenalis cysts and Cryptosporidium spp.oocysts were detected in the manure samples using immunofluorescence microscopy.A nested PCR and sequencing method was performed to determine the genotypes.A mixed multivariable method was used to compare the prevalence of Cryptosporidium and Giardia in samples from different sources.Cryptosporidium oocysts and Giardia cysts were recovered from 51.0% and 44.3% of samples, respectively.However, using PCR, 66.4% of fecal samples were positive for Giardia and 55.7% for Cryptosporidium.Cryptosporidium was more likely detected in manure pits and weaners compared to finisher pigs but it was less frequent in sows than in finishers (P < 0.05).Prevalence of Giardia was less frequent among sows and weaners compared to finisher pigs (P < 0.05).In total, 92% of the Giardia isolates were Assemblage B and 8% were Assemblage E. The most prevalent Cryptosporidium genotypes were C. parvum (55%) and pig genotype II (38%).Only one (2%) of the Cryptosporidium spp.isolates was determined to be C. suis.These findings indicate that the occurrence of zoonotic G. duodenalis and Cryptosporidium are very high on swine farms in southern Ontario, and that there is a potential for transmission between swine and humans by means of cyst and oocyst contaminated water or foods.
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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 | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".