Safety and Biocompatibility of a Spray-Dried Influenza Microparticle Vaccine in Mice
Bibliographic record
Abstract
Abstract: Influenza virus is a persistent source of morbidity and moribundity, and effective disease control requires ever-evolving effective vaccines. In this work, we evaluate the safety and biocompatibility of two novel polymeric particle-based influenza vaccines. Mice were immunized either intranasally or subcutaneously with these two formulations and examined at 1 h, 1 day, and 14 days post-immunization for histopathology in liver, kidneys, and lungs and serum biomarker analysis. Mice that received an intranasal vaccination were also observed for pulmonary disruption via whole body plethysmography. Examination of tissues post-immunization found only limited inflammation, with no difference observed in plethysmography measurements and no serum biomarkers (e.g., AST, AlkPhos) indicating tissue damage. Collectively, these data support the conclusion that these polymeric particle-based influenza vaccine formulations were well tolerated by the animals and did not induce any adverse side effects. Lay summary: Particle-based influenza vaccines were safety tolerated by mice and did not induce any adverse side effects. Supplementary Information: The online version contains supplementary material available at 10.1007/s40883-025-00473-2.
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 | 0.000 |
| 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 | 0.001 | 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".