Synthesis and evaluation of diethylethylamine–chitosan for gene delivery: composition effects on the<i>in vitro</i>transfection efficiency
Bibliographic record
Abstract
Chitosan has been indicated as a safe and promising polycation vector for gene delivery. However its low transfection efficiency has been a challenging obstacle for its application. To address this limitation, we synthesized chitosan derivatives which had increasing amounts of diethylethylamine groups (DEAE) attached to the chitosan main chain. The plasmid DNA VR1412 (pDNA), encoding the ß-galactosidase (ß-gal) reporter gene was used to prepare nanoparticles with the chitosan derivatives, and the transfection studies were performed with HeLa cells. By means of dynamic light scattering and zeta potential measurements, it was shown that diethylethylamine-chitosan derivatives (DEAE(x)-CH) were able to condense DNA into small particles having a surface charge depending on the polymer/DNA ratio (N/P ratio). Nanoparticles prepared with derivatives containing 15 and 25% of DEAE groups (DEAE(15)-CH and DEAE(25)-CH) exhibited transfection efficiencies ten times higher than that observed with deacetylated chitosan (CH). For derivatives with higher degrees of substitution (DS), transfection efficiency decreased. The most effective carriers showed low cytotoxicity and good transfection activities at low charge ratios (N/P). Vectors with low DS were easily degraded in the presence of lysozyme at physiological conditions in vitro and the nontoxicity displayed by these vectors opens up new opportunities in the design of DEAE-chitosan-based nanoparticles for gene delivery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".