Folic Acid‐Functionalized Albumin/Graphene Oxide Nanocomposite to Simultaneously Deliver Curcumin and 5‐Fluorouracil into Human Colorectal Cancer Cells: An <i>In Vitro</i> Study
Bibliographic record
Abstract
Background: Nowadays, due to various inherent properties, graphene-based nanoparticles are widely used in drug delivery research. On the other hand, folate receptors are highly expressed on the surface of human tumor cells. In this work, to enhance the 5-fluorouracil (5FU) and curcumin (Cur) effects on colon cancer, we constructed a folic acid- (FA-) modified codelivery carrier based on graphene nanoparticles (GO-Alb-Cur-FA-5FU). Materials and Methods: The HUVEC and HT-29 were selected for evaluating the antitumor effect of the prepared nanocarriers. The structure of nanocarriers was characterized by FTIR spectroscopy, X-ray diffraction analysis, TEM microscopy, and a DLS analyzer. The efficiency of the prepared carrier was evaluated by fluorescence microscopy using Annexin V and the PI kit. The cytotoxicity of the carrier's component individually and the efficacy of the drug carrier GO-Alb-Cur-FA-5FU were assessed by MTT. Results: The results of the pharmacological tests indicated that the new nanoparticles cause increased apparent toxicity in HT-29 cells. The apoptosis rate of the HT-29 and HUVEC cells treated with IC50 values of GO-Alb-Cur-FA-5FU for 48 h was higher than the cells treated with IC50 values of 5FU and Cur individually, which indicated the greater inhibitory efficacy of GO-Alb-Cur-FA-5FU than free drugs. Conclusion: The designed GO-Alb-CUR-FA-5FU delivery system can be applied for targeting colon cancer cells and can be severe as a potential candidate for future drug development.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".