Structural and transfection properties of amine‐substituted gemini surfactant‐based nanoparticles
Bibliographic record
Abstract
BACKGROUND: Increases in DNA transfection efficiencies for non-viral vectors can be achieved through rational design of novel cationic building blocks. Based on previous results examining DNA condensation by polyamines, novel gemini surfactants have been designed that incorporate aza or imino substituents within the spacer group in order to increase interactions with DNA and potentially improve their DNA transfection ability. METHODS: Transfection efficiencies and cell toxicity of gemini nanoparticles constructed from plasmid DNA, gemini surfactant, and a neutral lipid were measured in COS7 cells using a luciferase assay. Structural properties of nanoparticles were examined by using circular dichroism, particle size, zeta potential, and small-angle X-ray scattering (SAXS) measurements. RESULTS: The incorporation of aza and imino substituents within the spacer group was observed to enhance the transfection ability of gemini surfactants. Incorporation of an imino group in the structure of the 1,9-bis(dodecyl)-1,1,9,9-tetramethyl-5-imino-1,9-nonanediammonium dibromide surfactant (12-7NH-12) resulted in a statistically significant (p < 0.01) 9-fold increase in transfection compared to an unsubstituted gemini surfactant and a 3-fold increase compared to the corresponding aza-substituted compound. A pH-dependent transition in size and zeta potential was observed to occur at pH 5.5 for complexes formed from the 12-7NH-12 compound. SAXS results show weakly ordered structures and the presence of multiple phases. CONCLUSIONS: The incorporation of a pH-active imino group within the spacer of the gemini surfactant results in a significant increase in transfection efficiency that can be related to both pH-induced changes in nanoparticle structure and the formation of multiple phases that more readily allow for membrane fusion that may facilitate DNA release.
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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 | 0.001 | 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".