Insight Into the Molecular Parameters of PEI Promoting an Efficient Gene Delivery into Cells
Bibliographic record
Abstract
Abstract The development of natural or synthetic polycations able to interact with nucleic acids and condense them into nanoparticles known as polyplexes, faces several unresolved challenges at the cellular level. Key issues include the intracellular trafficking of polyplexes, the endosomal escape and the release of nucleic acids into the cytosol, which are considered major bottlenecks for efficient protein expression. Here, we aim at gaining fundamental insights into the stability of polyplexes in biological media and their uptake and intracellular trafficking, while correlating data of the expression of reporter protein with both the molecular characteristics of various poly(ethylenimines) (PEI) and the physicochemical characteristics of PEI/peGFP-C3 polyplexes. For this, we chosen four samples of PEI, selected as a model polycation, with different molecular weights (Mw = 0.8, 20, 25 and 60 kg/mol) and structures (linear and branched). We found that the in vitro and in vivo stability of PEI/peGFP-C3 polyplexes, their cell internalization and transfection efficiency is dependent on the variation of polycation Mw and structure, as well as the intrinsic properties of polyplexes, such as the charge ratio (R=[N + ]/[P − ]). A relation between the percentage of positive cells to green fluorescent protein (GFP) and the amount of internalized nucleic acid (cyanine 5-peGFP-C3) allowed revealing the molecular characteristics of PEI promoting both higher both cell internalization and GFP expression on HEK293T cells. In the long term, the outcome of this work will be to propose guidelines to help design more effective, and less cytotoxic non-viral gene carriers with a great potential for new therapeutic applications.
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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".