NON-VIRAL GENE DELIVERY WITH pH-SENSITIVE GEMINI NANOPARTICLES: SYNTHESIS OF GEMINI SURFACTANT BUILDING BLOCKS, CHARACTERIZATION AND IN VITRO SCREENING OF TRANSFECTION EFFICIENCY AND TOXICITY
Bibliographic record
Abstract
Research on self-assembling gemini surfactants and other amphiphiles for potential gene delivery applications in research as well as in clinical practice, and as alternatives to viral gene delivery vectors, is beginning to focus more on 'structure-activity relationships' to address the current low gene delivery efficiencies of amphiphiles.Some underlying structure-activity relations are beginning to emerge.But, as a better understanding of the factors that govern the transfection abilities of amphiphile molecules emerges, development of improved non-viral vectors with clinical potential may also emerge.The research conducted for this thesis was aimed at the design, synthesis and in vitro investigation of gemini surfactants as one of a family of novel amphiphiles being investigated for gene therapeutic applications.The properties of these compounds can be controlled as well as allowed to vary naturally.Gemini surfactant-based gene delivery systems were prepared and characterized for transfer of Luciferase plasmid (pMASIA.Luc) to both COS-7 and PAM 212 cells.Characterization was accomplished using microscopy, dynamic light scattering (DLS) and zeta (ζ) potential analysis.In vitro gene expression and toxicities were evaluated in COS-7 cell and PAM 212 keratinocyte cultures.The level of in vitro transfection in general was found to correlate strongly with the structure of the gemini surfactants.Among the 12-spacer-12 surfactants, incorporation of a pH-sensitive aza (N-CH 3 ) group, which is also steric hindrance-imposing, in the spacer chain yielded increased transfection, particularly for the 12-7N-12 surfactant.In iii comparison, the incorporation of the more pH-sensitive imino (N-H) group in the 12-7NH-12 surfactant yielded the highest increase in transfection among the 12-spacer-12 surfactants.The deleterious effect of steric hindrance due to the aza group is more evident when comparing the transfection efficiency of 12-5N-12 (1 × aza, higher) vs. 12-8N-12 (2 × aza, lower transfection).Another highlighted structural feature is provided by the fact that both the 12-7NH-12 and 12-7N-12 surfactants had higher transfection efficiencies than 12-5N-12 and 12-8N-12 surfactants; the first pair has trimethylene spacing, which constitutes an optimal separation between nitrogen centres, while the second pair has shorter dimethylene spacings.After expanding the structure of surfactants, transfection efficiencies were found to increase in response to increase in hydrocarbon tail length, but were much lower for surfactants with no amino functional groups, those that lacked the optimal trimethylene spacing, or those having both of these limitations in the gemini surfactant spacer.The 18-7NH-18 surfactant had the highest overall transfection in both COS-7 and PAM 212 cells.Gemini surfactant-based gene delivery systems capable of adopting both polymorphic structural phases and which could undergo pH-induced structural transition demonstrated high transfection efficiencies.Gemini surfactants with both characteristics (e.g., 12-7NH-12-based complexes are both polymorphic and pH-sensitive) had higher transfection than gemini surfactants with only one (e.g., 12-3-12-based complexes are only polymorphic).Overall, the m-7NH-m surfactants, the most efficient surfactants studied, had transfection efficiencies similar to that of the commercial Lipofectamine Plus™ reagent and imposed no higher toxicity on cells relative to the less efficient surfactants.Thus, the design of the m-7NH-m surfactants to enhance their transfection abilities also
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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 | 0.000 |
| 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".