An optimized polymeric delivery system for <i>piggyBac</i> transposition
Bibliographic record
Abstract
The piggyBac transposon/transposase system has been explored for long-term, stable gene expression to execute genomic integration of therapeutic genes, thus emerging as a strong alternative to viral transduction. Most studies with piggyBac transposition have employed physical methods for successful delivery of the necessary components of the piggyBac system into the cells. Very few studies have explored polymeric gene delivery systems. In this short communication, we report an effective delivery system based on low molecular polyethylenimine polymer with lipid substitution (PEI-L) capable of delivering three components, (i) a piggyBac transposon plasmid DNA carrying a gene encoding green fluorescence protein (PB-GFP), (ii) a piggyBac transposase plasmid DNA or mRNA, and (iii) a 2 kDa polyacrylic acid as additive for transfection enhancement, all in a single complex. We demonstrate an optimized formulation for stable GFP expression in two model cell lines, MDA-MB-231 and SUM149 recorded till day 108 (3.5 months) and day 43 (1.4 months), respectively, following a single treatment with very low cell number as starting material. Moreover, the stability of the transgene (GFP) expression mediated by piggyBac/PEI-L transposition was retained following three consecutive cryopreservation cycles. The success of this study highlights the feasibility and potential of employing a polymeric delivery system to obtain piggyBac-based stable expression of therapeutic genes.
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".