Identification and genetic correlation of avian reoviruses to the currently used vaccines in Egypt
Bibliographic record
Abstract
A variety of illnesses, including arthritis, tenosynovitis, stunted growth, and malabsorption syndrome, are caused by Avian Reoviruses (ARVs), which have become more prevalent in Egypt during recent years and resulted in significant economic losses. This study investigated 27 suspected samples collected from 14 broiler breeders and 13 broilers suffering from immunosuppression, decreased body weight, and diarrhea. Fourteen samples tested positive based on RT-PCR, and the virus could be isolated from ten samples in Specific Pathogen Free (SPF) embryonated chicken eggs. Ten isolates were subjected to molecular and genetic analysis of the S1 gene (sigma C) and S2 gene (sigma A). The amino acid identity of the S1 gene revealed that these viruses are closely related to the viruses that were identified in Israel during 2020 (91.8%-97.2% identity) and belonged to the genetic cluster 5 (genotype 5), which also includes some viruses that are circulating in the United States and Canada. They also showed weak similarity (48.9%-50.2%) with the available vaccine strains in the Egyptian field that belong to cluster 1, genotype 1. The S2 gene showed amino acid homology of 91.7%-98.2% with the current vaccine used in Egypt. However, the Egy-Reo-7-2021 virus had the lowest similarity (84.2%-87.6%) to the available vaccine. It is hypothesized that the difference between field and vaccine strains may have contributed to the failure of current vaccinations to produce protective immunity against current ARV strains circulated in Egypt, which made the disease a problem to the poultry industry. Developing homologous vaccines and evaluating their potency and efficacy are required in Egypt.
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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) | 0.001 | 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".