Transmission of H9N2 Low Pathogenicity Avian Influenza Virus (LPAIV) in a Challenge-Transmission Model
Bibliographic record
Abstract
Migratory birds are major reservoirs for avian influenza viruses (AIV), which can be transmitted to poultry and mammals. The H9N2 subtype of AIV has become prevalent in poultry over the last two decades. Despite that, there is a scarcity of detailed information on how this virus can be transmitted. The current study aimed to establish a direct contact model using seeder chickens infected with H9N2 AIV as a source of the virus for transmission to recipient chickens. Seeder chickens were inoculated with two different inoculation routes either directly or via the aerosol route. The results indicate that inoculation via the aerosol route was more effective at establishing infection compared to the direct inoculation route. Shedding was observed to be higher in aerosol-inoculated seeder chickens, with a greater percentage of chickens being infected at each time point. In terms of transmission, the recipient chickens exposed to the aerosol-inoculated seeder chickens had higher oral and cloacal virus shedding compared to the recipient chickens of the directly inoculated group. Furthermore, the aerosol route of infection resulted in enhanced antibody responses in both seeder and recipient chickens compared to the directly inoculated group. Overall, the results confirmed that the aerosol route is a preferred inoculation route for infecting seeder chickens in a direct contact transmission model.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".