Effects of size and topology of DNA molecules on intracellular delivery with non-viral gene carriers
Bibliographic record
Abstract
BACKGROUND: Efforts to improve the efficiency of non-viral gene delivery require a better understanding of delivery kinetics of DNA molecules into clinically relevant cells. Towards this goal, three DNA molecules were employed to investigate the effects of DNA properties on cellular delivery: a circular plasmid DNA (c-DNA), a linearized plasmid DNA (l-DNA) formulated by single-site digestion of c-DNA, and smaller linear gene cassette generated by PCR (pcr-DNA). Four non-viral gene carriers were investigated for DNA delivery: polyethyleneimine (PEI), poly-L-Lysine (PLL), palmitic acid-grafted PLL (PLL-PA), and Lipofectamine-2000. Particle formation, binding and dissociation characteristics, and DNA uptake by rat bone marrow stromal cells were investigated. RESULTS: For individual carriers, there was no discernible difference in the morphology of particles formed as a result of carrier complexation with different DNA molecules. With PEI and PLL carriers, no difference was observed in the binding interaction, dissociation characteristics, and DNA uptake among the three DNA molecules. The presence of serum in cell culture media did not significantly affect the DNA delivery by the polymeric carriers, unlike other lipophilic carriers. Using PEI as the carrier, c-DNA was more effective for transgene expression as compared to its linear equivalent (l-DNA) by using the reporter gene for Enhanced Green Fluorescent Protein. pcr-DNA was the least effective despite being delivered into the cells to the same extent. CONCLUSION: We conclude that the nature of gene carriers was the primary determinant of cellular delivery of DNA molecules, and circular form of the DNA was more effectively processed for transgene expression.
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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 | 0.001 | 0.002 |
| 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".