DLin-MC3-Containing mRNA Lipid Nanoparticles Induce an Antibody Th2-Biased Immune Response Polarization in a Delivery Route-Dependent Manner in Mice
Bibliographic record
Abstract
mRNA-based vaccines have made a leap forward since the SARS-CoV-2 pandemic and are currently used to develop anti-infectious therapies. If the selection of a delivery system and an optimized mRNA sequence are two key factors to reach in vivo efficacy, the optimal administration route for those vaccines remains unclear. We investigated the influence of lipid components and immunization route regarding the intensity and quality of humoral immune responses in mice. The immunogenicity of HIV-p55Gag encoded mRNA encapsulated into D-Lin-MC3-DMA or GenVoy-ionizable lipid-based LNPs was compared after intramuscular or subcutaneous routes. Three sequential mRNA vaccines were administrated followed by a heterologous boost composed of p24-HIV protein antigen. Despite equivalent IgG kinetic profiles of general humoral responses, IgG1/IgG2a ratio analysis showed a Th2/Th1 balance toward a Th1-biased cellular immune response when both LNPs were administrated via the intramuscular route. Surprisingly, a Th2-biased antibody immunity was observed when DLin-containing vaccine was injected subcutaneously. A protein-based vaccine boost appeared to reverse this balance to a cellular-biased response correlated to an increase in antibody avidity. Our finding suggests that the intrinsic adjuvant effect of ionizable lipids appears to be dependent on the delivery route used, which could be relevant to reach potent and long-lasting immunity after mRNA-based immunization.
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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) | 0.000 | 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 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".