OVA-PEG-R848 nanocapsules stimulate neonatal conventional and plasmacytoid dendritic cells
Bibliographic record
Abstract
Childhood mortality represents a major issue with 5. 3 million worldwide deaths of children under 5 years of age in 2019. Approximately half of those deaths can be attributed to easily preventable, infectious diseases. Currently approved neonatal vaccines are typically effective only after multiple doses leaving infants especially vulnerable during the first 6 months of life. Survival rates could be improved significantly by developing new and more potent vaccines that are capable of overcoming inherently tolerogenic neonatal immune systems. TLR agonists have garnered a great deal of attention in recent years due to their extensive capacities to activate innate immunity. Herein, the superior capacity of the TLR7/8 agonist, resiquimod (R848), to activate adult and neonatal primary peripheral blood dendritic cells is demonstrated. Moreover, R848 can be conjugated to polyethylene glycol and encapsulated in ovalbumin nanocapsules to efficiently co-deliver antigen and adjuvantin vitro. This study is among the first to demonstrate the capacity of encapsulated R848 to activate neonatal dendritic cells. These findings support the potential incorporation of R848 as adjuvant in neonatal vaccines, making them more effective in eliciting a robust immune response.
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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 | 0.001 |
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".