Intracellular Barriers to Non-Viral Gene Transfer
Bibliographic record
Abstract
Non-viral vector mediated gene transfer, compared to viral vector mediated one, is a promising tool for the safe delivery of therapeutic DNA in genetic and acquired human diseases. Although the lack of specific immune response favor the clinical application of non-viral vectors, comprising of an expression cassette complexed to cationic liposome or cationic polymer, the limited efficacy and short duration of transgene expression impose major hurdles in the widespread application of non-viral gene therapy. The trafficking of transgene, complexed with chemical vectors, has been the subject of intensive investigations to improve our understanding of cellular and extracellular barriers impeding gene delivery. Here, we review those physical and metabolic impediments that account, at least in part, for the inefficient translocation of transgene into the nucleus of target cells. Following the internalization of the DNA-polycation complex by endocytosis, a large fraction is targeted to the lysosomal compartment by default. Since the cytosolic release of heterelogous DNA is a prerequisite for nuclear translocation, entrapment and degradation of plasmid DNA in endo-lysosomes constitute a major impediment to efficient gene transfer. Only a small fraction of internalized plasmid DNA penetrates the cytoplasm. Plasmid DNA encounters the diffusional and metabolic barriers of the cytoplasm, further decreasing the number of intact plasmid molecules reaching the nuclear pore complex (NPC), the gateway of nucleosol. Nuclear translocation of DNA requires either the disassembly of the nuclear envelope or active nuclear transport via the NPC. Comparison of viral and plasmid DNA cellular trafficking should reveal strategies that viruses have developed to overcome those cellular barriers that impede non-viral DNA delivery in gene therapy attempts.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".