Stabilized Plasmid–Lipid Particles: Pharmacokinetics and Plasmid Delivery to Distal Tumors following Intravenous Injection
Bibliographic record
Abstract
A previous study has shown that plasmid DNA can be encapsulated in lipid particles (SPLP, "stabilized plasmid lipid particles") of approximately 70 nm diameter composed of 1,2-dioleoyl-3-phosphatidyl-ethanolamine (DOPE), the cationic lipid N,N-dioleoyl-N,N-dimethylammonium chloride (DODAC) and poly(ethylene glycol) conjugated to ceramide (PEG-Cer) using a detergent dialysis process (Wheeler et al. (1999) Gene Therapy 6, 271-281). In this work we evaluated the potential of these SPLPs as systemic gene therapy vectors, determining their pharmacokinetics and the biodistribution of the plasmid and lipid components. It is shown that the blood clearance and the biodistribution of the SPLPs can be modulated by varying the acyl chain length of the ceramide group used as lipid anchor for the PEG polymer. Circulation lifetimes observed for SPLPs with PEG-CerC14 and PEG-CerC20 were t(1/2) = approximately 1 and approximately 10 h, respectively. The SPLPs are stable while circulating in the blood and the encapsulated DNA is fully protected from degradation by serum nucleases. The accelerated clearance of SPLPs with PEG-CerC14 is accompanied by increased accumulation in liver and spleen as compared to PEG-CerC20 SPLPs. Delivery of intact plasmid to liver and spleen was detected. Significant accumulation (approximately 10% of injected dose) of the long circulating SPLPs with PEG-CerC20 in a distal tumor (Lewis lung tumor in the mouse flank) was observed following i.v. application and delivery of intact plasmid to tumor tissue at approximately 6% injected dose/g tissue is demonstrated.
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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 | 0.001 |
| 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".