Isopranoid- and dipalmitoyl-aminophospholipid adjuvants impact differently on longevity of CTL immune responses
Bibliographic record
Abstract
The success of lipid membranes as cytotoxic T-cell (CTL) adjuvants requires targeted uptake by antigen-presenting cells (APCs) and delivery of the antigen cargo to the cytosol for processing. To target the phosphatidylserine (PS) receptor of APCs, we prepared antigen-loaded liposomes containing dipalmitoylphosphatidylserine and archaeal lipid liposomes (archaeosomes), containing an equivalent amount of archaetidylserine, and compared their ability to promote short and long-term CTL activity in animals. CTL responses were enhanced by the incorporation of PS into phosphatidylcholine/cholesterol liposomes and, to a lesser extent, into phosphatidylglycerol/cholesterol liposomes, that correlated to the amount of surface amino groups reactive with trinitrobenzoyl sulfonate. Archaeosomes contrasted to the liposome adjuvants by exhibiting higher amounts of surface amino groups and inducing superior shorter and, especially, longer-term CTL responses. The incorporation of dipalmitoyl lipids into archaeosomes induced instability and prevented long-term, but not short-term, CTL responses in mice. The importance of glycero-lipid cores (isopranoid versus dipalmitoyl) to the longevity of the CTL response achieved was shown further by incorporating dipalmitoyl phosphatidylethanolamine (DPPE) or equivalent amounts of synthetic archaetidylethanolamine (AE) into archaeosome adjuvants. Both DPPE and AE at equivalent (5 mol%) concentrations enhanced the rapidity of CTL responses in mice, indicating the importance of the head group in the short term. In the longer term, 5% of DPPE (but not 5% of AE) was detrimental. In addition to head-group effects critical to the potency of short-term CTL responses, the longer term CTL adjuvant properties of archaeosomes may be ascribed to stability imparted by the archaeal isopranoid core lipids.
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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) | 0.001 | 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".