A Mechanistic Study on the Destabilization of Whole Inactivated Influenza Virus Vaccine in Gastric Environment
Bibliographic record
Abstract
Oral immunization using whole inactivated influenza virus vaccine promises an efficient vaccination strategy. While oral vaccination was hampered by harsh gastric environment, a systematic understanding about vaccine destabilization mechanisms was not performed. Here, we investigated the separate and combined effects of temperature, retention time, pH, and osmotic stress on the stability of influenza vaccine by monitoring the time-dependent morphological change using stopped-flow light scattering. When exposed to osmotic stress, clustering of vaccine particles was enhanced in an acidic medium (pH 2.0) at ≥25°C. Fluorescence spectroscopic studies showed that hyper-osmotic stress at pH 2.0 and 37°C caused a considerable increase in conformational change of antigenic proteins compared to that in acidic iso-osmotic medium. A structural integrity of membrane was destroyed upon exposure to hyper-osmotic stress, leading to irreversible morphological change, as observed by undulation in stopped-flow light scattering intensity and transmission electron microscopy. Consistent with these analyses, hemagglutination activity decreased more significantly with an increasing magnitude of hyper-osmotic stress than in the presence of the hypo- and iso-osmotic stresses. This study shows that the magnitude and direction of the osmotic gradient has a substantial impact on the stability of orally administrated influenza vaccine.
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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) | 0.001 | 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".