In vivo targeting of protein antigens to dendritic cells using anti‐DEC‐205 single chain antibody improves HIV Gag specific CD4<sup>+</sup> T cell responses protecting from airway challenge with recombinant vaccinia‐gag virus
Bibliographic record
Abstract
Abstract Introduction Targeting antigens to dendritic cells (DCs) in vivo via a DC‐restricted endocytic receptor, DEC205, has been validated to enhance immunity in several vaccine platforms. Particularly atttractive is selected delivery of proteins to DCs in vivo because it enables proteins to be more immunogenic and provides a cheaper and effective way for repeated immunizations. Methods In this study, we tested the efficacy of a single chain antibody to DEC205 (scDEC) to deliver protein antigens selectively to DCs in vivo and to induce protective immunity. Results In comparison to soluble Ovalbumin (OVA) antigen, when recombinant scDEC:OVA protein was injected subcutaneously (s.c.) into mice, the OVA protein was selectively presented by DCs to both TCR transgenic CD8+ and CD4+ T cells approximately 500 and 100 times more efficient than soluble OVA, respectively, and could persist for seven days following s.c. injection of the scDEC205:OVA. Similarly selective targeting of HIV Gag P24 to DCs in vivo using scDEC‐Gag protein plus polyICLC vaccine resulted in strong, long lasting, polyfuntional CD4+ T cells in mice which were protective against airway challenge by a recombinant vaccinia‐gag virus. Conclusion Thus targeting protein antigens to DCs using scDEC can be used either alone or in combination with other strategies for effective immunization.
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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 | 0.000 |
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".