An Eight-Segment Swine Influenza Virus Harboring H1 and H3 Hemagglutinins Is Attenuated and Protective against H1N1 and H3N2 Subtypes in Pigs
Bibliographic record
Abstract
Swine influenza virus (SIV) infections continue to cause production losses in the agricultural industry in addition to being a human public health concern. The primary method of controlling SIV is through vaccination. The killed SIV vaccines currently in use must be closely matched to the challenge virus, and their protective efficacy is limited. Live attenuated influenza vaccines (LAIV) provide strong, long-lived cell-mediated and humoral immunity against different influenza virus subtypes with no need for antigen matching. Here we report the generation of a new potential LAIV, an eight-segment SIV harboring two different SIV hemagglutinins (HAs), H1 and H3, in the genetic background of H1N1 SIV. This mutant SIV was generated by fusing the H3 HA ectodomain from A/Swine/Texas/4199-2/98 (H3N2) to the cytoplasmic tail, transmembrane domain, and stalk region of neuraminidase (NA) from A/Swine/Saskatchewan/18789/02 (H1N1) SIV. While this H1-H3 chimeric SIV, when propagated in vitro in the presence of exogenous neuraminidase, showed kinetics and growth properties similar to those of the parental wild-type virus, in vivo it was highly attenuated in pigs, demonstrating a great potential for serving as a dual LAIV. Furthermore, vaccination with the H1-H3 virus elicited robust immune responses, which conferred complete protection against infections with both H1 and H3 SIV subtypes in pigs.
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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 | 0.000 | 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 | 0.000 |
| 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".