Enhancement of the priming efficacy of DNA vaccines encoding dendritic cell-targeted antigens by synergistic toll-like receptor ligands

Abstract Background Targeting of protein antigens to dendritic cells (DC) via the DEC205 receptor enhances presentation of antigen-derived peptides on MHC-I and MHC-II molecules and, in the presence of costimulatory signals, antigen-specific immune responses. The immunogenicity and efficacy of DNA vaccination can also be enhanced by fusing the encoded antigen to single chain antibodies directed against DEC205. To further improve this strategy, we evaluated different toll-like receptor ligands (TLR) and CD40 ligands (CD40L) as adjuvants for DNA vaccines encoding a DEC205-single-chain antibody fused to the ovalbumin model antigen or HIV-1 Gag and assessed the priming efficacy of DNA in a DNA prime adenoviral vector boost immunization regimen. Results Mice were primed with the adjuvanted DEC-205 targeted DNA vaccines and boosted with adenoviral vectors encoding the same antigens. CD8+ T cell responses were determined after the adenoviral booster immunization, to determine how well the different DNA immunization regimens prime for the adenoviral boost. In the absence of adjuvants, targeting of DNA-encoded ovalbumin to DCs suppressed CD8+ T-cell responses after the adenoviral booster immunization. CD8+ T-cell responses to the DEC205 targeted DNA vaccines increased only slightly by adding either the TLR-9 ligand CpG, the TLR-3 ligand Poly I:C, or CD40 ligand expression plasmids. However, the combination of both TLR-ligands led to a strong enhancement of CD8+ T-cell responses compared to a non-targeted DNA vaccine. This finding was confirmed using HIV Gag as antigen. Conclusion Although DNA prime adenoviral vector boost immunizations belong to the strongest inducers of cytotoxic T cell responses in different animal models and humans, the CD8+ T cell responses can be further improved by targeting the DNA encoded antigen to DEC205 in the presence of synergistic TLR ligands CpG and Poly I:C

Enhancement of the priming efficacy of DNA vaccines encoding dendritic cell-targeted antigens by synergistic toll-like receptor ligands

Abstract Background Targeting of protein antigens to dendritic cells (DC) via the DEC205 receptor enhances presentation of antigen-derived peptides on MHC-I and MHC-II molecules and, in the presence of costimulatory signals, antigen-specific immune responses. The immunogenicity and efficacy of DNA vaccination can also be enhanced by fusing the encoded antigen to single chain antibodies directed against DEC205. To further improve this strategy, we evaluated different toll-like receptor ligands (TLR) and CD40 ligands (CD40L) as adjuvants for DNA vaccines encoding a DEC205-single-chain antibody fused to the ovalbumin model antigen or HIV-1 Gag and assessed the priming efficacy of DNA in a DNA prime adenoviral vector boost immunization regimen. Results Mice were primed with the adjuvanted DEC-205 targeted DNA vaccines and boosted with adenoviral vectors encoding the same antigens. CD8+ T cell responses were determined after the adenoviral booster immunization, to determine how well the different DNA immunization regimens prime for the adenoviral boost. In the absence of adjuvants, targeting of DNA-encoded ovalbumin to DCs suppressed CD8+ T-cell responses after the adenoviral booster immunization. CD8+ T-cell responses to the DEC205 targeted DNA vaccines increased only slightly by adding either the TLR-9 ligand CpG, the TLR-3 ligand Poly I:C, or CD40 ligand expression plasmids. However, the combination of both TLR-ligands led to a strong enhancement of CD8+ T-cell responses compared to a non-targeted DNA vaccine. This finding was confirmed using HIV Gag as antigen. Conclusion Although DNA prime adenoviral vector boost immunizations belong to the strongest inducers of cytotoxic T cell responses in different animal models and humans, the CD8+ T cell responses can be further improved by targeting the DNA encoded antigen to DEC205 in the presence of synergistic TLR ligands CpG and Poly I:C.</p

Is one annotation enough? A data-centric image classification benchmark for noisy and ambiguous label estimation

High-quality data is necessary for modern machine learning. However, the acquisition of such data is difficult due to noisy and ambiguous annotations of humans. The aggregation of such annotations to determine the label of an image leads to a lower data quality. We propose a data-centric image classification benchmark with ten real-world datasets and multiple annotations per image to allow researchers to investigate and quantify the impact of such data quality issues. With the benchmark we can study the impact of annotation costs and (semi-)supervised methods on the data quality for image classification by applying a novel methodology to a range of different algorithms and diverse datasets. Our benchmark uses a two-phase approach via a data label improvement method in the first phase and a fixed evaluation model in the second phase. Thereby, we give a measure for the relation between the input labeling effort and the performance of (semi-)supervised algorithms to enable a deeper insight into how labels should be created for effective model training. Across thousands of experiments, we show that one annotation is not enough and that the inclusion of multiple annotations allows for a better approximation of the real underlying class distribution. We identify that hard labels can not capture the ambiguity of the data and this might lead to the common issue of overconfident models. Based on the presented datasets, benchmarked methods, and analysis, we create multiple research opportunities for the future directed at the improvement of label noise estimation approaches, data annotation schemes, realistic (semi-)supervised learning, or more reliable image collection