Polycationic Block Copolymers of Poly(ethylene oxide) and Poly(propylene oxide) for Cell Transfection
Bibliographic record
Abstract
A facile, one-step synthesis of cationic block copolymers of poly(2-N-(dimethylaminoethyl) methacrylate) (pDMAEMA) and copolymers of poly(propylene oxide) (PPO) and poly(ethylene oxide) (PEO) has been developed. The PEO-PPO-PEO-pDMAEMA (L92-pDMAEMA) and PEO-pDMAEMA copolymers were obtained via free radical polymerization of DMAEMA initiated by polyether radicals generated by cerium(IV). Over 95% of the copolymer fraction was of molecular mass ranging from 6.9 to 7.1 kDa in size, indicating the prevalence of the polyether-monoradical initiation mechanism. The L92-pDMAEMA copolymers possess parent surfactant-like surface activity. In contrast, the PEO-pDMAEMA copolymers lack significant surface activity. Both copolymers can complex with DNA. Hydrodynamic radii of the complexes of the L92-pDMAEMA and PEO-pDMAEMA with plasmid DNA ranged in size from 60 to 400 nm, depending on the copolymer/DNA ratio. Addition of Pluronic P123 to the L92-pDMAEMA complexes with DNA masked charges and decreased the tendency of the complex to aggregate, even at stoichiometric polycation/DNA ratios. The transfection efficiency of the L92-pDMAEMA copolymer was by far greater than that of the PEO-pDMAEMA copolymer. An extra added Pluronic P123 further increased the transfecton efficacy of L92-pDMAEMA, but did not affect that of PEO-pDMAEMA.
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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 | 0.001 |
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".