Genomic signature and toxicogenomics comparison of polycationic gene delivery nanosystems in human alveolar epithelial A549 cells
Bibliographic record
Abstract
"nBackground and the purpose of the study: Of the gene delivery systems, non-viral polycationic gene delivery nanosystems have been alternatively exploited as a relatively safe delivery reagents compared to viral vectors. However, little is known about the genomic impacts of these delivery systems in target cells/tissues. In this study, the toxicogenomics and genotoxicity potential of some selected polycationic lipid/polymer based nanostructures (i.e., Oligofectamine® (OF), starburst polyamidoamine Polyfect® (PF) and diaminobutane (DAB) dendrimers) were investigated in human alveolar epithelial A549 cells. "nMethods: To study the nature and the ontology of the gene expression changes in A549 cells upon treatment with polycationic nanostructures, MTT assay and microarray gene expression profiling methodology were employed. For microarray analysis, cyanine (Cy3/Cy5) labeled cDNA samples from treated and untreated cells were hybridized on target arrays housing 200 genes. "nResults and major conclusions: The polycationic nanosystems induced significant gene expression changes belonging to different genomic ontologies such as cell defence and apoptosis pathways. These data suggest that polycationic nanosystems can elicit multiple gene expression changes in A549 cells upon their chemical structures and interactions with cellular/subcellular components. Such impacts may interfere with the main goals of the desired genemedicine.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".