Assessment of Viral Vaccine N-Glycosylation via Orthogonal Capillary Electrophoresis-Based Methods
Bibliographic record
Abstract
Despite global vaccination programs, seasonal influenza continues to pose a significant economic burden and strain on healthcare systems worldwide.Annual reformulation of influenza vaccines is required due to the high mutation rates of surface glycoproteins on influenza viruses.Although vaccination is the most effective preventative measure against influenza viruses, reduced vaccine efficacy in recent years has become an increasing concern.Egg-adaptations incurred through the manufacturing process of influenza vaccines result in antigenic mismatches, whereby vaccine strains differ from the wild-type circulating viruses.In 2017, low vaccine efficacy was attributed to altered glycosylation characteristics of the H3N2 vaccine strain whereby an eggadaptation resulted in the deletion of a single N-glycosylation site.However, even with these implications on immunogenicity, influenza glycosylation is not a well-implemented critical quality attribute and therefore not optimally controlled or regulated during vaccine manufacturing due to assay limitations.Furthermore, current potency evaluation methods are not sensitive enough to capture differences in glycosylation.In this study, capillary zone electrophoresis with laser induced fluorescence (CZE-LIF) and sheathless capillary electrophoresis-mass spectrometry (CESI-MS) methods were developed for the assessment of influenza vaccine N-glycosylation.A magnetic bead-based sample preparation approach was adapted and modified for the fluorescent labeling and CZE-LIF analysis of enzymatically released N-glycans derived from three influenza vaccine monovalent bulk manufacturers.A filter-aided dual hydrazide labeling strategy was developed and elucidation of N-glycan structures was achieved using an untargeted sheathless CESI-MS/MS approach.There is currently a lack of standardized methods for analyzing Nglycosylation; therefore, this study highlights the utility of capillary electrophoresis-based methods for analysis of influenza vaccine N-glycosylation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".