Detection of Hepatitis E virus in swine using real-time RT-PCR
Bibliographic record
Abstract
The zoonotic transmtsswn potential of Hepatitis E virus (HEY) is now widely recognized. Swine represents the main animal reservoir for this virus in many countries, including Canada. In recent years, different real-time RT-PCR assays were developed and proposed as reliable and sensitive detection methods. However, the quality of extracted RNA, presence of inhibitors and RN ase contamination of the samples may impact on the detection results obtained with these molecular methods. The aim of this study was to evaluate the use of a sample process control (SPC) within a real-time RT-PCR assay for the detection ofHEV. This TaqMan multiplex assay was afterwards used to evaluate the viral load ofHEV in organs, tissues and excreta of normal pigs at slaughter. HEY RNA was detected in at least one sample from 14 out of the 43 animals tested (32.6 %). HEV was present in lymph nodes (25.6%), bladder (23.3%), liver (20.9%), bile (18.6%), feces (13.9%), tonsils (7.0%) and plasma (2.3%) but was undetected in loins.
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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".