Effective gene delivery of <i>sh</i>BMP-9 using polyethyleneimine-based core–shell nanoparticles in an animal model of insulin resistance
Bibliographic record
Abstract
Bone morphogenetic protein (BMP)-9 has been associated with insulin resistance and type 2 diabetes mellitus. However, methods for delivering exogenous BMP-9 genes in vivo are lacking. In this study, we developed a gene delivery system using polyethyleneimine (PEI)-based core-shell nanoparticles (PCNs) as gene delivery carriers, and investigated the effectiveness and safety for delivery of the shBMP-9 gene. PCNs possessed a well-defined core-shell nanostructure with hydrophobic polymer cores and dense PEI shells of uniform particle size and highly positively charged surfaces. In vitro evaluation suggested that PCNs had high loading capacity for exogenous genes and low cytotoxicity toward hepatocytes. The transfection efficiency of PCNs/pENTR-shBMP9 complexes was higher than that of commercial lipofectamine 2000/shBMP9. In vivo studies showed that PCNs/pENTR-shBMP9 transfection led to a significant decrease in hepatic BMP9 expression compared with pENTR-shBMP9 transfection. Under high fat diet (HFD) feeding, PCNs/pENTR-shBMP9 mice exhibited aggravated glucose and insulin tolerance. At a molecular level, PCNs/pENTR-shBMP9 mice displayed elevated PEPCK protein levels and lower levels of InsR and Akt phosphorylation than pENTR-shBMP9 mice. These results suggest that the biological effects of PCNs/pENTR-shBMP9 in vivo are much more effective than those of pENTR-shBMP9. Therefore, the polyethyleneimine (PEI)-based core-shell nanoparticle can be applied as promising nanocarriers for effective and safe gene delivery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".