Doxorubicin-Conjugated Terbium-Doped Carbon Dots for Site-Specific Colon Cancer Theranostics
Bibliographic record
Abstract
This work focuses on synthesizing fluorescent rare earth terbium-doped carbon dots (CD-Tb) as a nanodrug carrier for doxorubicin (DOX) drug moieties using the hydrothermal method. The nature of CD-Tb nanoparticles in the absence and presence of DOX was evaluated using various spectroscopic and microscopic techniques, namely, X-ray diffraction (XRD), high-resolution transmission electron microscopy (HR-TEM), Zeta potential analyzer, Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), UV–visible, fluorescence emission, and lifetime spectroscopy. The synthesized CD-Tb nanoparticles were found to be approximately 7 nm in size and spherical, with a surface charge of −20.7 mV. They are biocompatible with electron-rich amino groups on their surface and are used for the bioconjugation of DOX, an anticancer drug. The photophysical characterization shows 92.5% of adsorption and 89% of in vitro release of DOX from CD-Tb nanoparticles. This might be due to the presence of carboxyl and amino groups on the DOX surface and CD-Tb nanoparticles. The effective concentration of CD-Tb nanoparticles and DOX was achieved at a stoichiometric ratio of 1:1.5. Further, the Stern–Volmer quenching rate constant ( K q ) of CD-Tb-DOX was calculated as 4.9 × 10 10 L/mol·s –1, and the binding of nanoparticles with various concentrations of DOX is found to be static. In addition, the in vitro antitumoral activity of free DOX and the CD-Tb-DOX against Caco-2 cancer cell lines (human colon cancer) and L929 cell lines (mouse fibroblast cells) was evaluated as the healthy cell model. CD-Tb-DOX’s in vitro cytotoxic evaluation result shows higher cytotoxicity and morphological changes at Caco-2 colon cancer tumor sites than free DOX. In brief, this study confirms that the synthesized CD-Tb-DOX nanocarriers could significantly enhance the metabolic damage in the Caco-2 cancer cell lines (human colon cancer) and facilitate the action of cellular apoptosis, which might be helpful in site-specific targeting drug delivery applications.
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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 | 0.001 | 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".