The Potent Adjuvant Activity of Archaeosomes Correlates to the Recruitment and Activation of Macrophages and Dendritic Cells In Vivo
Bibliographic record
Abstract
The unique glycerolipids of Archaea can be formulated into vesicles (archaeosomes) with potent adjuvant activity. We studied the effect of archaeosomes on APCs to elucidate the mechanism(s) of adjuvant action. Exposure of J774A.1 macrophages to archaeosomes in vitro resulted in up-regulation of B7.1, B7.2, and MHC class II molecules to an extent comparable to that achieved with LPS. Similarly, incubation of bone marrow-derived DCs with archaeosomes resulted in enhanced expression of MHC class II and B7.2 molecules. In contrast, conventional liposomes made from ester phospholipids failed to modulate the expression of these activation markers. APCs treated with archaeosomes exhibited increased TNF production and functional ability to stimulate allogenic T cell proliferation. More interestingly, archaeosomes enhanced APC recruitment and activation in vivo. Intraperitoneal injection of archaeosomes into mice led to recruitment of Mac1alpha(+), F4/80(+) and CD11c(+) cells. The expression of MHC class II on the surface of peritoneal cells was also enhanced. Furthermore, peritoneal cells from archaeosome-injected mice strongly enhanced allo-T cell proliferation and cytokine production. The ability of archaeosome-treated APCs to stimulate T cells was restricted to Mac1alpha(high), B220(-) cells in the peritoneum. These Mac1alpha(high) cells in the presence of GM-CSF gave rise to both F4/80(+) (macrophage) and CD11c(+) (dendritic) populations. Overall, the activation of APCs correlated to the ability of archaeosomes to induce strong humoral, T helper, and CTL responses to entrapped Ag. Thus, the recruitment and activation of professional APCs by archaeosomes constitutes an efficient self-adjuvanting process for induction of Ag-specific responses to encapsulated Ags.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".