Well-Controlled Cationic Water-Soluble Phospholipid Polymer−DNA Nanocomplexes for Gene Delivery
Bibliographic record
Abstract
The facile synthesis of biocompatible and nontoxic gene delivery vectors has been the focus of research in recent years due to the high potential in treating genetic diseases. 2-Methacryloxyethyl phosphorylcholine (MPC) copolymers were recently studied for their ability to produce nontoxic and biocompatible materials. The synthesis of well-defined and water-soluble MPC polymer based cationic vectors for gene delivery purposes was therefore attractive, due to the potential excellent biocompatibility of the resulting copolymers. Herein, cationic MPC copolymers of varying architectures (block versus random) were produced by the reversible addition--fragmentation chain transfer (RAFT) polymerization technique. The copolymers produced were evaluated for their gene delivery efficacy in the presence and absence of serum. It was found that copolymer architectures and molecular weights do affect their gene delivery efficacy. The statistical copolymers produced larger particles, and showed poor gene transfection efficiency as compared to the diblock copolymers. The diblock copolymers served as efficient gene delivery vectors, in both the presence and absence of serum in vitro. To the best of our knowledge, this is the first report where the effect of architecture of MPC based copolymer on gene delivery efficacy has been studied.
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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) | 0.001 | 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".