Targeted delivery of interleukin‐12 plasmid into <scp>HepG2</scp> cells through folic acid conjugated graphene oxide nanocarrier
Bibliographic record
Abstract
Successful gene therapy relies on carriers to transfer genetic materials with high efficiency and low toxicity in a targeted manner. To enhance targeted cell binding and uptake, we developed and synthesized a new gene delivery vector based on graphene oxide (GO) modified by branched polyethyleneimine (BPEI) and folic acid (FA). The GO-PEI-FA nanocarriers exhibit lower toxicity compared to unmodified PEI, as well as having the potential to efficiently condense and protect pDNA. Interestingly, increasing the polymer content in the polyplex formulation improved plasmid transfer ability. Substituting graphene oxide for PEI at an N/P ratio of 10 in the HepG2 and THP1 cell lines improved hIL-12 expression by up to approximately eightfold compared to simple PEI, which is twice as high as GO-PEI-FA in Hek293 at the same N/P ratio. Therefore, the GO-PEI-FA described in this study may serve as a targeting nanocarrier for the delivery of the hIL-12 plasmid into cells overexpressing folic acid receptors, such as those found in hepatocellular carcinoma.
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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".