Carbon dots in drug delivery and therapeutic applications
Bibliographic record
Abstract
Carbon dots (CDs) are recently introduced carbon nanomaterials showing diverse properties. They show unique fluorescent behavior, low production cost, ecofriendliness, electron mobility, potent antioxidant and antibacterial capabilities, good biocompatibility, and abundant functional groups providing opportunities in functionalization for desired properties such as targeted drug delivery, diagnostics, and therapeutics. In this review, we provide a general overview of their synthesis processes, including top-down and bottom-up approaches and their associated benefits and drawbacks. Together with their pros and cons, we also explore the structural and optical properties, photoluminescence mechanisms, free radicals scavenging behavior, toxicity and biological behavior, surface chemistry, and functionalization for drug delivery and therapeutic effects. Furthermore, significant advances in the applicability of CDs such as bioimaging, cellular labelings, cell tracking, biosensing, bioanalytical assays, and therapeutic behavior, like antibacterial properties, tissue engineering, drug delivery system, gene delivery, cancer therapy, photothermal therapy (PTT), photodynamic therapy (PDT), and combinatorial (theranostic) applications are also discussed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".