Acanthopanax senticosus polysaccharide-loaded calcium carbonate nanoparticle as an adjuvant to enhance porcine parvovirus vaccine immune responses
Bibliographic record
Abstract
Recently, the strategy of using positively charged nanoparticles as new vaccine delivery systems has been widely investigated for enhancing the anti-infectious disease immune responses and has been found to efficiently improve the immune response through the targeting and activation of antigen-presenting cells. Acanthopanax senticosus polysaccharide (ASPS) is extracted from Acanthopanax senticosus and functions as an effective immunostimulatory drug. The present work encapsulated the ASPS immunopotentiator to the calcium carbonate (CaCO3) microspheres, and adopted polyethylenimine, a cationic polymer, for coating the microspheres, finally developing the novel nanoparticle (NP) delivery system with positive charge (CaCO3–ASPS–PEI). As a result, our constructed CaCO3–ASPS–PEI remarkably up-regulated CD86 and MHCII and activated macrophages, while increasing TNF-α and IL-1β production via macrophages. Moreover, the mice immunized with porcine parvovirus (PPV) antigen adsorbed onto CaCO3–ASPS–PEI nanoparticles had a significant enhancement in cytokine production, the PPV-specific IgG immune response, and the hybrid Th1/Th2 immune response (dominated by Th1), relative to the remaining groups. Based on the above results, our constructed CaCO3–ASPS–PEI NPs with positive charge may be used as the efficient adjuvant vaccine delivery system for inducing the long-time potent immune responses.
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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) | 0.000 | 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".