Liposomal Delivery of CTL Epitopes to Dendritic Cells
Bibliographic record
Abstract
The induction of strong and long lasting T-cell response, CD4+ or CD8+, is a major requirement in the development of efficient vaccines. An important aspect involves delivery of antigens to dendritic cells (DCs) as antigen presenting cells (APCs) for the induction of potent antigen-specific CD8+ T lymphocyte (CTLs) responses. Protein or peptide-based vaccines become an attractive alternative to the use of live cell vaccines to stimulate CTL responses for the treatment of viral diseases or malignancies. However, vaccination with proteins or synthetic peptides representing discrete CTL epitopes have failed in most instances due to the inability for exogenous antigens to be properly presented to T cells via major histocompatibility complex (MHC) class I molecules. Modern vaccines, based on either synthetic or natural molecules, will be designed in order to target appropriately professional APCs and to co-deliver signals able to facilitate activation of DCs. In this review, we describe the recent findings in the development of lipid-based formulations containing a combination of these attributes able to deliver tumor- or viral-associated antigens to the cytosol of DCs. We present in vitro and pre-clinical studies reporting specific immunity to viral, parasitic infection and tumor growth.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.002 |
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".