CpG ODN and ISCOMATRIX Adjuvant: A Synergistic Adjuvant Combination Inducing Strong T-Cell IFN-<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M1"><mml:mrow><mml:mi>γ</mml:mi></mml:mrow></mml:math>Responses
Bibliographic record
Abstract
For the induction of robust humoral and cellular immune responses, a strong rationale exists to use vaccine-adjuvant combinations possessing both immune modulatory and enhanced delivery capabilities. Herein, we evaluated the combination of 2 different adjuvants, a TLR9 agonist, composed of synthetic oligodeoxynucleotides (ODN) containing immunostimulatory CpG motifs (CpG), and ISCOMATRIX adjuvant (ISCOMATRIX), composed of saponin, phospholipid, and cholesterol, which possesses both immunostimulatory and delivery properties. While both individual adjuvants have been shown effective in numerous preclinical and clinical studies, it is likely that for optimal adjuvant activity a combined adjuvant approach will be necessary. Herein, using three different antigens, namely, hepatitis B surface antigen (HBsAg), ovalbumin (OVA), and influenza A haemagglutinin antigen (HA), we show in mice that some adjuvant effects of CpG and ISCOMATRIX are further enhanced if they are used in combination. In particular, with all three antigens, IFN-γ levels were greatly increased with the CpG/ISCOMATRIX combination. The ability of the CpG/ISCOMATRIX combination to induce antitumor responses when administered with OVA following administration to mice of a highly metastatic OVA-secreting tumor cell line (B16-OVA melanoma) was also demonstrated. Thus the CpG/ISCOMATRIX combination may prove to be a valuable tool in the development of novel or improved vaccines.
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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 | 0.000 |
| 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 | 0.000 |
| 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".