Negative regulation of reassortant canine influenza virus replication and key site identification in porcine and ferret bronchial epithelial cell lines
Bibliographic record
Abstract
The segmented nature and high mutability of the influenza virus RNA genome facilitate rapid mutation and reassortment, allowing the virus to breach host barriers and migrate between different species, potentially leading to unpredictable influenza outbreaks. With dogs emerging as new natural hosts for influenza virus, vigilant surveillance and scientific prevention strategies are imperative. Here, based on our previous isolation of 21 strains, which are reassortments of the canine influenza virus (CIV) H3N2 (KR/07) with gene segments from the influenza A pandemic (H1N1) 2009 virus strain (CA/09), the replication kinetics of these reassortants in immortalized mammalian respiratory epithelial cell lines from swine and ferret named hTERT-PBECs and hTERT-FBECs, alongside induced changes in cytokine expression, were investigated. Reverse genetics was utilized to generate the reassortment H3N2 canine influenza rKR/07-PB2/NP, which contains the PB2 and NP segments from CA/09. The viral titer of rKR/07-PB2/NP was significantly lower than those of the parental viruses KR/07 and CA/09. In addition, rKR/07-PB2/NP notably decreased expression levels of interleukin-1β (IL-1β) and interleukin-10 (IL-10) in both immortal cells, particularly in hTERT-PBECs. Our findings not only contribute to the understanding and exploring cross-species transmission mechanisms of influenza virus, but also provide new ideas for prevention and treatment of CIV.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| 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".