Evaluation of Adjuvant Activity and Bio-Distribution of Archaeosomes Prepared Using Microfluidic Technology
Bibliographic record
Abstract
Archaeosomes, composed of sulfated lactosyl archaeol (SLA) glycolipids, have been proven to be an effective vaccine adjuvant in multiple preclinical models of infectious disease or cancer. They have classically been prepared using a thin-film hydration method with an average particle size of 100–200 nm. In this study, we developed methods to generate SLA archaeosomes at different sizes, i.e., 30 nm and 100 nm, via microfluidic mixing technology and evaluated their physicochemical characteristics, as well as adjuvant activity and in vivo biodistribution in mice. Archaeosomes, prepared using thin-film and microfluidic mixing techniques, had similar nanostructures and physicochemical characteristics, with both appearing stable during the course of this study when stored at 4 °C or 37 °C. They also demonstrated similar adjuvant activity when admixed with ovalbumin antigen and used to immunize mice, generating equivalent antigen-specific immune responses. Archaeosomes, labeled with CellVueTM NIR815, had an equivalent biodistribution with both sizes, namely the highest signal at the injection site at 24 h post injection, followed by liver, spleen and inguinal lymph node. The presence of SLA archaeosomes of either size helped to retain OVA antigen (OVA-Cy5.5) longer at the injection site than unadjuvanted OVA. Overall, archaeosomes of two sizes (30 nm and 100 nm) prepared using microfluidic mixing maintained similar physicochemical properties, adjuvant activity and biodistribution of antigen, in comparison to those compared by the conventional thin film hydration method. This suggests that microfluidics based approaches could be applied to generate consistently sized archaeosomes for use as a vaccine adjuvant.
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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 | 0.000 | 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 | 0.000 |
| 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 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".