A Versatile Bifunctional Dendritic Cell Targeting Vaccine Vector
Bibliographic record
Abstract
We have developed an efficient versatile in vivo dendritic cell (DC) targeting vector for delivering different classes of antigens such as proteins, peptide, glycolipids and naked DNA for vaccine applications. A single chain antibody (scFv) that recognizes DEC-205 receptor of DC was fused with a core-streptavidin domain and expressed in Escherichia coli using the T7 expression system. The bifunctional fusion protein (bfFp) was expressed as a periplasmic soluble protein and affinity-purified in its monomeric form. The bifunctional activity against DEC-205 and biotin was characterized by ELISA and Western blot. In vivo DC targeting of a diverse group of biotinylated antigens such as viral and bacterial proteins, a cancer peptide, gangliosides and DNA of certain infectious diseases was conducted in mice. Results show that in the presence of bfFp and costimulatory anti-CD40 mAb, both humoral and cell-mediated responses were augmented in either the single antigen or multiple antigen targeting strategy. Lastly, bfFp based DC targeting of antigens in low doses may be a useful strategy for the design of monovalent or polyvalent vaccines for the masses.
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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 | 0.001 |
| 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".