Study on the role of polyethylenimine as gene delivery carrier using molecular dynamics simulations
Bibliographic record
Abstract
Polyethylenimine (PEI) is known to be one of the most promising polymers to serve as a delivery carrier in gene therapy. Complexation between PEI molecules and nucleic acids results in nanoparticles that can subsequently enter cells for therapeutic treatment. Design of the carrier molecules for stabler complexation, better cell uptake, and lower cytotoxicity remains to be a challenge. Molecular dynamics (MD) simulations allow atomistic level examination of the complexation between PEI and nucleic acids, as well as the interaction of the complexes formed with other entities in the delivery path. It is a powerful tool in revealing the role of carrier molecules and guiding the design of more effective delivery systems. In this work, we first review the current status in studying complexation of PEI with nucleic acids and interaction between the complex formed and cell membrane. We have conducted preliminary MD simulations on several aspects of complexation between PEI and DNA. These results are presented to demonstrate how MD simulations can help understand the role of PEI in serving as a gene delivery carrier.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".