Characterization of innate immune response to «Nicotiana benthamiana»-derived Influenza H5 virus-like particles
Bibliographic record
Abstract
Current influenza vaccine manufacturing processes using chicken-embryonated egg technology is a time-consuming and laborious process, and is currently the major drawback in counteracting pandemic influenza strain. One solution to that problem is the use of plants to generate vaccine antigen. Virus-like particles (VLP), produced from the tobacco plant Nicotiana benthamiana, represent a cost-effective, alternative platform for influenza vaccine production. Previous studies have shown that the immunization with VLP expressing the hemagglutinin (HA) protein from influenza virus H5N1 (H5-VLP) produced in N. benthamianainduce protective immunity against challenge of cross-clade virus in mice and ferrets. In this study, we used human peripheral blood mononuclear cells (PBMC) to characterize the innate immune response to plant-derived influenza H5-VLP ex vivo. We successfully demonstrate the mitogenic property of H5-VLP on PBMC ex vivo. Furthermore, we detect up-regulation of activation marker in B cells and NK cells, and some T cells. Cytokine profile of the supernatant from VLP-stimulated sample suggests that inflammatory response dominates the innate immunity within first 48 hours and is produced by CD14+ monocytes. Our study demonstrates that tobacco plant-derived influenza VLP are capable of generating innate immune responses in naïve human PBMC, helping us to better understand the immunostimulatory nature of this potential vaccine candidate.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Immunology study of plant-derived influenza virus-like particles.
The study examines immune responses to a vaccine candidate, not research itself.
Vaccine immunology of plant-derived influenza VLPs, domain biomedical science.
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".