Detection of HEV in naturally infected swine from central Argentina by an optimized HEV/MS2 duplex RT‐qPCR
Bibliographic record
Abstract
Hepatitis E virus (HEV) is currently considered as a global health concern due to the recognition of its zoonotic transmission to humans, mainly from swine, and its association with the development of severe cases of hepatitis in human risk populations. The lack of updated data on HEV state of infection in swineherds of Argentina, and the necessity of robust technologies for its detection in complex biological samples, positions HEV as an emerging issue in public health. Here, we have optimized a RT-qPCR with internal control for a more precise and accurate HEV RNA detection in swine stool samples. We implemented this optimized molecular tool to analyse the current epidemiological scenario of HEV infection in swine from the core region of commercial activity of Argentina. A total of 135 stool samples were collected from 16 different farms and tested for HEV presence, resulting in 11 positive cases (8.1%). Phylogenetic analysis demonstrated that all of them correspond to HEV genotype 3 and that different subtypes circulate in the region. Moreover, two of the detected strains presented a high nucleotide similarity with a previously identified isolate from human sewage discharges, suggesting the zoonotic transmission of HEV to humans. Collectively, this work provides a better understanding of HEV epidemiology in Argentina while contributes to the improvement of HEV detection technologies.
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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 | 0.001 | 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) | 0.000 | 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 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".