Topical CpG Adjuvantation of a Protein-Based Vaccine Induces Protective Immunity to Listeria monocytogenes
Bibliographic record
Abstract
Robust CD8(+) T cell responses are essential for immune protection against intracellular pathogens. Using parenteral administration of ovalbumin (OVA) protein as a model antigen, the effect of the Toll-like receptor 9 (TLR9) agonist, CpG oligodeoxynucleotide (ODN) 1826, as an adjuvant delivered either topically, subcutaneously, or intramuscularly on antigen-specific CD8(+) T cell responses in a mouse model was evaluated. Topical CpG adjuvant increased the frequency of OVA-specific CD8(+) T cells in the peripheral blood and in the spleen. The more effective strategy to administer topical CpG adjuvant to enhance CD8(+) T cell responses was single-dose administration at the time of antigen injection with a prime-boost regimen. Topical CpG adjuvant conferred both rapid and long-lasting protection against systemic challenge with recombinant Listeria monocytogenes expressing the cytotoxic T lymphocyte (CTL) epitope of OVA(257-264) (strain Lm-OVA) in a TLR9-dependent manner. Topical CpG adjuvant induced a higher proportion of CD8(+) effector memory T cells than parenteral administration of the adjuvant. Although traditional vaccination strategies involve coformulation of antigen and adjuvant, split administration using topical adjuvant is effective and has advantages of safety and flexibility. Split administration of topical CpG ODN 1826 with parenteral protein antigen is superior to other administration strategies in enhancing both acute and memory protective CD8(+) T cell immune responses to subcutaneous protein vaccines. This vaccination strategy induces rapid and persistent protective immune responses against the intracellular organism L. monocytogenes.
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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".