Role of Positive Selection Pressure on the Evolution of H5N1 Hemagglutinin
Bibliographic record
Abstract
The surface glycoprotein hemagglutinin (HA) helps the influenza A virus to evade the host immune system by antigenic variation and is a major driving force for viral evolution. In this study, the selection pressure on HA of H5N1 influenza A virus was analyzed using bioinformatics algorithms. Most of the identified positive selection (PS) sites were found to be within or adjacent to epitope sites. Some of the identified PS sites are consistent with previous experimental studies, providing further support to the biological significance of our findings. The highest frequency of PS sites was observed in recent strains isolated during 2005-2007. Phylogenetic analysis was also conducted on HA sequences from various hosts. Viral drift is almost similar in both avian and human species with a progressive trend over the years. Our study reports new mutations in functional regions of HA that might provide markers for vaccine design or can be used to predict isolates of pandemic potential.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.001 | 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".