Simplified Admix Archaeal Glycolipid Adjuvanted Vaccine and Checkpoint Inhibitor Therapy Combination Enhances Protection from Murine Melanoma
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Archaeosomes are liposomes composed of natural or synthetic archaeal lipids that when used as adjuvants induce strong long-lasting humoral and cell-mediated immune responses against entrapped antigens. However, traditional entrapped archaeosome formulations have only low entrapment efficiency, therefore we have developed a novel admixed formulation which offers many advantages, including reduced loss of antigen, consistency of batch-to-batch production as well as providing the option to formulate the vaccine immediately before use, which is beneficial for next generation cancer therapy platforms that include patient specific neo-antigens or for use with antigens that are less stable. Herein, we demonstrate that, when used in combination with anti-CTLA-4 and anti-PD-1 checkpoint therapy, this novel admixed archaeosome formulation, comprised of preformed sulfated lactosyl archaeol (SLA) archaeosomes admixed with OVA antigen (SLA–OVA (adm)), was as effective at inducing strong CD8+ T cell responses and protection from a B16-OVA melanoma tumor challenge as the traditionally formulated archaeosomes with encapsulated OVA protein. Furthermore, archaeosome vaccine formulations combined with anti-CTLA-4 and anti-PD-1 therapy, induced OVA-CD8+ T cells within the tumor and immunohistochemical analysis revealed the presence of CD8+ T cells associated with dying or dead tumor cells as well as within or around tumor blood vessels. Overall, archaeosomes constitute an attractive option for use with combinatorial checkpoint inhibitor cancer therapy platforms.
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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 it