The combination of stabilized plasmid lipid particles and lipid nanoparticle encapsulated CpG containing oligodeoxynucleotides as a systemic genetic vaccine
Bibliographic record
Abstract
BACKGROUND: DNA vaccines offer unique potential for generating protective and therapeutic immunity against infectious and malignant diseases. Unfortunately, rapid degradation and poor cellular uptake has significantly limited the efficacy of 'naked' plasmid DNA vaccines. We have previously described stabilized plasmid lipid particles (SPLP) as effective nonviral gene delivery vehicles for the transfection of tumours at distal sites following intravenous administration. Based on their low toxicity and favourable transfection profile following systemic administration, we investigate SPLP as gene delivery vehicles for the generation of a systemically administered genetic vaccine. METHODS: The uptake of SPLP and their ability to transfect splenic antigen presenting cells (APC) following systemic administration is assessed through fluorescently-labelled SPLP in combination with phenotype markers and a very sensitive flow cytometry-based assay for the detection of the transgene, beta-galactosidase. The priming of antigen-specific adaptive and humoural immune responses following vaccination with SPLP alone or in combination with liposomal nanoparticle encapsulated CpG-ODN containing oligodeoxynucleotides (LN CpG-ODN) is characterized through the use of antigen-specific cytotoxicity assays, interferon-gamma secretion assays and enzyme-linked immunosorbant assay. RESULTS: We demonstrate that SPLP are taken up by and transfect APC in the spleen following intravenous administration and that, in the presence of a strong immunostimulatory signal provided by LN CpG-ODN, are able to prime transgene-specific humoural and cellular immune responses. CONCLUSIONS: SPLP represent an effective candidate for the nonviral delivery of a systemic genetic vaccine when combined with additional immune stimulation provided by LN CpG-ODN.
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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 | 0.000 |
| 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 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".