Intracellular Fate and Impact on Gene Expression of Doxorubicin/Cyclodextrin-Graphene Nanomaterials at Sub-Toxic Concentration
Bibliographic record
Abstract
The graphene road in nanomedicine still seems very long and winding because the current knowledge about graphene/cell interactions and the safety issues are not yet sufficiently clarified. Specifically, the impact of graphene exposure on gene expression is a largely unexplored concern. Herein, we investigated the intracellular fate of graphene (G) decorated with cyclodextrins (CD) and loaded with doxorubicin (DOX) and the modulation of genes involved in cancer-associated canonical pathways. Intracellular fate of GCD@DOX, tracked by FLIM, Raman mapping and fluorescence microscopy, evidenced the efficient cellular uptake of GCD@DOX and the presence of DOX in the nucleus, without graphene carrier. The NanoString nCounter™ platform provided evidence for 34 (out of 700) differentially expressed cancer-related genes in HEp-2 cells treated with GCD@DOX (25 µg/mL) compared with untreated cells. Cells treated with GCD alone (25 µg/mL) showed modification for 16 genes. Overall, 14 common genes were differentially expressed in both GCD and GCD@DOX treated cells and 4 of these genes with an opposite trend. The modification of cancer related genes also at sub-cytotoxic G concentration should be taken in consideration for the rational design of safe and effective G-based drug/gene delivery systems. The reliable advantages provided by NanoString® technology, such as sensibility and the direct RNA measurements, could be the cornerstone in this field.
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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".