Combined photodynamic-chemotherapy investigation of cancer cells using carbon quantum dot-based drug carrier system
Bibliographic record
Abstract
The combined chemotherapy and photodynamic therapy have significant advantages for cancer treatments, which have higher therapeutic effects compared with other medicines. Herein, we focused on the synthesis of carbon quantum dot (CQD) based nanocarrier system. CQD and 5-aminolevulinic acid (5-ALA) were conjugated with mono-(5-BOC-protected-glutamine-6-deoxy) β-cyclodextrin (CQD-Glu-β-CD) moiety, and finally, the anticancer chemotherapy doxorubicin (DOX) drug was loaded in the 5-ALA-CQD-Glu-β-CD system. The stepwise physicochemical changes for the preparation of the DOX loaded 5-ALA-CQD-Glu-β-CD system were investigated by Fourier transform infrared (FT-IR) spectroscopy, X-ray diffraction (XRD), transmission electron microscopy (TEM), atomic force microscopy (AFM), and Raman fluorescence spectroscopy. The encapsulation efficiency of DOX in 5-ALA-CQD-Glu-β-CD was observed at ∼83.0%, and the loading capacity of DOX is ∼20.37%. The in vitro releasing of DOX and 5-ALA was observed through the UV–vis spectroscopy by the λmax value of 487 nm and 253 nm, respectively. By the investigation against the breast MCF-7 cancer cells, the high cytotoxicity and morphological changes of cancer cells were observed by the treating of DOX/5-ALA-CQD-Glu-β-CD. The generation of reactive oxygen species (ROS) upon 635 nm (25 mW cm−2) for 15 min laser irradiation-induced improved the therapeutic effects. In vitro cellular uptake studies recommend the synthesized DOX/5-ALA-CQD-Glu-β-CD nanocarrier could significantly enhance the cell apoptosis and assist in the MCF-7 cell damages. The result suggests a multifunctional therapeutic system for chemo/photodynamic synergistic effects on cancer therapy.
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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".