Poly[N-(2-aminoethyl)ethyleneimine] as a New Non-Viral Gene Delivery Carrier: The Effect of Two Protonatable Nitrogens in the Monomer Unit on Gene Delivery Efficiency
Bibliographic record
Abstract
PURPOSE: The aim of this study was to investigate the in vitro gene delivery efficiency of poly[N-(2-aminoethyl)ethylene-imine](PAEEI), a polymer with a linear Polyethyleneimine (LPEI) backbone and with aminoethyl side groups that has two protonatable nitrogen atoms per monomer unit instead of one as in LPEI (an established gene delivery polymer). Method. PAEEI (Mn=4.5 kDa, Mw= 10 kDa) was synthesized by ring-opening polymerization of N-(2-(1'-aziridino)ethyl)formamide followed by hydrolysis of the amide groups. The buffering capacity of the resulting polymer was determined by acid-base titration and consequently the percentage of the protonated nitrogen atoms was calculated. Polyplexes were prepared separately in buffers with different ionic strength including Hepes buffered saline (150 mM NaCl) and Hepes buffered glucose (5% glucose) and their zeta-potential, hydrodynamic diameter and colloidal stability were measured. Transfection activity (and toxicity in Hela cells) of the polyplexes were done in HeLa, CHO and HEK293T cells. Cell incubations with polyplexes were done both in the presence and absence (HeLa cells) of serum. Results. PAEEEI showed two times more buffering capacity than LPEI. PAEEI-based Polyplexes had about the same size and zeta-potential as those of LPEI, with a higher colloidal stability in saline buffer in continuous particle size measurement. Their transfection activity was slightly higher than 22-kDa LPEI polyplexes whereas their toxicity profiles were similar in cell lines studied. The PAEEI polyplexes showed gene expression activity both in the presence and absence of serum. Conclusion. Paying attention to the fact that LPEI molecules with smaller sizes than 22 kDa show less transfection efficiency than LPEI 22, the effect of smaller size of PAEEI (10 kDa) on the gene delivery efficiency was compensated by its higher buffering capacity due to carrying more protonatable nitrogen per monomeric unit comparing with LPEI (22 kDa). Having slightly higher transfection efficiency and better colloidal stability than PEI-based systems, PAEEI is an attractive candidate for future in vivo gene delivery studies.
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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 | 0.000 |
| 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 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".