Antigenic Relatedness of Norovirus GII.4 Variants Determined by Human Challenge Sera
Bibliographic record
Abstract
The GII.4 noroviruses (NoVs) are a single genotype that is responsible for over 50% of NoV gastroenteritis epidemics worldwide. However, GII.4 NoVs have been found to undergo antigenic drifts, likely selected by host herd immunity, which raises an issue for vaccine strategies against NoVs. We previously characterized GII.4 NoV antigenic variations and found significant levels of antigenic relatedness among different GII.4 variants. Further characterization of the genetic and antigenic relatedness of recent GII.4 variants (2008b and 2010 cluster) was performed in this study. The amino acid sequences of the receptor binding interfaces were highly conserved among all GII.4 variants from the past two decades. Using serum samples from patients enrolled in a GII.4 virus challenge study, significant cross-reactivity between major GII.4 variants from 1998 to 2012 was observed using enzyme-linked immunosorbent assays and HBGA receptor blocking assays. The overall abilities of GII.4 NoVs to bind to the A/B/H HBGAs were maintained while their binding affinities to individual ABH antigens varied. These results highlight the importance of human HBGAs in NoV evolution and how conserved antigenic types impact vaccine development against GII.4 variants.
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 | 0.000 | 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 | 0.000 | 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".