CpG Oligodeoxynucleotides with Hepatitis B Surface Antigen (HBsAg) for Vaccination in HBsAg-Transgenic Mice
Bibliographic record
Abstract
DNA motifs containing unmethylated CpG dinucleotides within the context of certain flanking sequences enhance both innate and antigen-specific immune responses, due in part to the enhanced production of Th1-type cytokines. Here we explored the ability of CpG-containing oligodeoxynucleotides combined with recombinant hepatitis B surface antigen (HBsAg) to induce Th1 responses in mice that are transgenic for this antigen and that represent a model for asymptomatic hepatitis B virus chronic carriers. This was compared to hepatitis B virus-specific DNA-mediated immunization, which we have previously shown to induce the clearance of the transgene expression product and the down-regulation of hepatitis B virus mRNA in this transgenic mouse lineage. In control nontransgenic C57BL/6 mice, three immunizations with HBsAg and CpG triggered the production of anti-HBs antibodies and of HBs-specific T cells that secrete gamma interferon but do not display any HBsAg-specific cytotoxic activity. In the HBsAg-transgenic mice, immunization with HBsAg and CpG oligodeoxynucleotides, but not with CpG alone, induced the clearance of HBsAg circulating in the sera, with a concomitant appearance of specific antibodies, and was able to regulate the hepatitis B virus mRNA constitutively expressed in the liver. Finally, adoptive transfer experiments with CD8(+) T cells primed in C57BL/6 mice with HBsAg and CpG oligodeoxynucleotide-based immunization show that these cells were able to partially control transgene expression in the liver and to clear the HBsAg from the sera of recipient transgenic mice without an antibody requirement. CpG oligodeoxynucleotides motifs combined with HBsAg could therefore represent a potential therapeutic approach with which to treat chronically infected patients.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".