Detection of border disease virus (BDV) in goat herds suffering diarrhea in eastern China
Bibliographic record
Abstract
BACKGROUND: Border disease virus (BDV) is an important pathogen in sheep and goat production. Neither epidemiological investigation nor any reports of BDV infection was available in China. During Jan to Apr, 2012, several herd goats in Anhui and Jiangsu provinces in eastern China suffered unremitting diarrhea, with morbidity and mortality of about 28-37% and 10-15%, respectively. In the present study, sera and tissue samples from diseased goats of four farms were taken for BDV detection, isolation and identification. RESULTS: Panpesti generic primers and border disease virus (BDV)-specific primers targeting the 5'-UTR region produced RT-PCR positive bands for sera (24/28) and tissue samples (7/30). Twenty positive sera and tissue samples were inoculated onto Madin-Darby bovine kidney (MDBK) cells for virus isolation. Finally, three different strains of BDV, named AH12-01, AH12-02 and JS12/04, were successfully isolated as identified by RT-PCR using 5'-UTR and N(pro) gene primers, sequencing and electron microscopy. Sequences of 5'-UTR and N(pro) genes of them were used for phylogenetic analysis and comparison to other reference sequences available in GenBank. The results indicated AH12-01, AH12-02 and JS12/04 possess high relationship with the BDV 3 group viruses and differed with each other. CONCLUSION: This is the first detection of BDV from goats with diarrhea and confirmation of BDV infection in China.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".