Structural Characterization of Archaeal Lipid Mucosal Vaccine Adjuvant and Delivery (AMVAD) Formulations Prepared by Different Protocols and Their Efficacy Upon Intranasal Immunization of Mice
Bibliographic record
Abstract
Intranasal administration of ovalbumin (OVA) formulated in an archaeal lipid mucosal vaccine adjuvant and delivery (AMVAD) system prepared by the addition of CaCl2 to small unilamellar archaeosomes (liposomes made from archaeal polar lipids) containing encapsulated OVA, was recently shown to elicit strong and sustained OVA-specific mucosal and systemic immune responses. In this study, we show that the centrifugation/washing and antigen quantization steps required in the standard protocol for obtaining OVA/AMVAD model vaccine formulations can be eliminated by using simpler protocols such as admixing OVA with preformed empty archaeosomes, or by changing the starting ratio (w/w) of archaeal lipid to antigen at the archaeosome preparation stage, prior to the addition of CaCl2 to convert to the AMVAD structures. Irrespective of the vaccine preparation protocol, the AMVAD particle typically comprised of larger spherical structures that had aggregated like a bunch of grapes, and it contained aqueous compartment(s). The anti-OVA IgA antibody responses in vaginal wash, nasal wash, serum, and bile samples, and the anti-OVA IgG antibody responses in sera, in mice intranasally immunized with the OVA/AMVAD formulations prepared by the simplified or the standard protocols, were comparable.
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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 | 0.000 |
| 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 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".