Suppressing Subcapsular Sinus Macrophages Enhances Transport of Nanovaccines to Lymph Node Follicles for Robust Humoral Immunity
Bibliographic record
Abstract
Nanovaccines need to be transported to lymph node follicles to induce humoral immunity and generate neutralizing antibodies. Here, we discovered that subcapsular sinus macrophages play a barrier role to prevent nanovaccines from accessing lymph node follicles. This is illustrated by measuring the humoral immune responses after removing or functionally altering these cells in the nanovaccine transport process. We achieved up to 60 times more antigen-specific antibody production after suppressing subcapsular sinus macrophages. The degree of the enhanced antibody production is dependent on the nanovaccine dose and size, formulation, and administration time. We further found that pharmacological agents that disrupt the macrophage uptake function can be considered as adjuvants in vaccine development. Immunizing mice using nanovaccines formulated with these agents can induce more than 30 times higher antigen-specific antibody production compared to nanovaccines alone. These findings suggest that altering transport barriers to enable more of the nanovaccine to be delivered to the lymph node follicles for neutralizing antibody production is an effective strategy to boost vaccination.
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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) | 0.001 | 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".