Comparative Analysis of Chitosan, Lipid Nanoparticles, and Alum Adjuvants in Recombinant SARS-CoV-2 Vaccine: An Evaluation of Their Immunogenicity and Serological Efficacy
Bibliographic record
Abstract
Background: Chitosan, a family of polysaccharides composed of glucosamine and N-acetyl glucosamine, is a promising adjuvant candidate for eliciting potent immune response. Methods: This study compared the adjuvant effects of chitosan to those of empty lipid nanoparticles (eLNPs) and aluminum hydroxide (alum) following administration of recombinant SARS-CoV-2 spike immunogen in adult mice. Mice received the adjuvanted recombinant protein vaccine in a prime-boost regimen with four weeks interval. Subsequent analyses included serological assessment of antibody responses, evaluation of T cell activity, immune cell recruitment and cytokine profiles at injection site. Results: Compared to alum, chitosan induced a more balanced Th1/Th2 response, akin to that observed with eLNPs, demonstrating its ability to modulate both the humoral and cellular immune pathways. Chitosan induced a different proinflammatory cytokine (e.g., IL-1⍺, IL-2, IL-6, and IL-7) and chemokine (e.g., Eotaxin, IP-10, MIP-1a) profile compared to eLNPs and alum at the injection site and in the draining lymph nodes. Moreover, chitosan potentiated the recruitment of innate immune cells, with neutrophils accounting for about 40% of the infiltrating cells in the muscle, representing a ~10-fold increase compared to alum and a comparable level to eLNPs. Conclusions: These findings collectively indicate that chitosan has the potential to serve as an effective adjuvant, offering comparable, and potentially superior, properties to those of currently approved adjuvants.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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 teacher head, 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".