Hierarchical Self-Assembly Route to “Polyplex-in-Hydrophobic-Core” Micelles for Gene Delivery
Bibliographic record
Abstract
Hierarchical block copolymer self-assembly is used to produce “polyplex-in-hydrophobic-core” (PIHC) micelles for gene delivery. The unique PIHC micelle structure provides nuclease protection and controlled release by embedding nucleic acids in the micelle core surrounded by condensed hydrophobic polymer chains. PIHC micelles are generated through a simple, two-step process using commercially available polymers: (1) electrostatic binding between the nucleic acid cargo and poly(ε-caprolactone)- block -poly(2-vinyl pyridine) (PCL- b -P2VP) (SA1), followed by (2) microprecipitation of the polyplex with poly(ε-caprolactone)- block -poly(ethylene glycol) (SA2). The resulting vectors possess poly(ethylene glycol) (PEG) coronae and nucleic acid–P2VP polyplexes embedded within condensed PCL hydrophobic cores. Using a two-phase microfluidic reactor for the SA2 step, we produce mainly spherical PIHC micelles with ∼30 nm PCL cores and ∼15 nm PEG shells. Plasmids encapsulated in PIHC micelles show resistance to DNase I degradation compared to plasmids located outside the micelle cores. PIHC micelles containing pUC18 show enhanced transformation efficiencies in competent Escherichia coli with a linear time dependence over 8 h associated with slow plasmid release via hydrolytic degradation of PCL cores. Finally, we show that PIHC micelles are readily taken into the cytosol of MDA-MB-231 (human breast cancer) cells.
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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".