Immunity toward H1N1 influenza hemagglutinin of historical and contemporary strains suggests protection and vaccine failure
Bibliographic record
Abstract
Evolution of H1N1 influenza A outbreaks of the past 100 years is interesting and significantly complex and details of H1N1 genetic drift remains unknown. Here we investigated the clinical characteristics and immune cross-reactivity of significant historical H1N1 strains. We infected ferrets with H1N1 strains from 1943, 1947, 1977, 1986, 1999, and 2009 and showed each produced a unique clinical signature. We found significant cross-reactivity between viruses with similar HA sequences. Interestingly, A/FortMonmouth/1/1947 antisera cross-reacted with A/USSR/90/1977 virus, thought to be a 1947 resurfaced virus. Importantly, our immunological data that didn't show cross-reactivity can be extrapolated to failure of past H1N1 influenza vaccines, ie. 1947, 1986 and 2009. Together, our results help to elucidate H1N1 immuno-genetic alterations that occurred in the past 100 years and immune responses caused by H1N1 evolution. This work will facilitate development of future influenza therapeutics and prophylactics such as influenza vaccines.
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 | 0.001 |
| 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 | 0.001 |
| 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".