Encapsulation of Antitumor Drug Doxorubicin and Its Analogue by Chitosan Nanoparticles
Bibliographic record
Abstract
Biodegradable chitosan of different sizes were used to encapsulate antitumor drug doxorubicin (Dox) and its N-(trifluoroacetyl) doxorubicin (FDox) analogue. The complexation of Dox and FDox with chitosan 15, 100, and 200 KD was investigated in aqueous solution, using FTIR, fluorescence spectroscopic methods, and molecular modeling. The structural analysis showed that Dox and FDox bind chitosan via both hydrophilic and hydrophobic contacts with overall binding constants of K(Dox-ch-15) = 8.4 (±0.6) × 10(3) M(-1), K(Dox-ch-100) = 2.2 (±0.3) × 10(5) M(-1), K(Dox-ch-200) = 3.7 (±0.5) × 10(4) M(-1), K(FDox-ch-15) = 5.5 (±0.5) × 10(3) M(-1), K(FDox-ch-100) = 6.8 (±0.6) × 10(4) M(-1), and K(FDox-ch-200) = 2.9 (±0.5) × 10(4) M(-1), with the number of drug molecules bound per chitosan (n) ranging from 1.2 to 0.5. The order of binding is ch-100 > 200 > 15 KD, with stronger complexes formed with Dox than FDox. The molecular modeling showed the participation of polymer charged NH(2) residues with drug OH and NH(2) groups in the drug-polymer adducts. The presence of the hydrogen-bonding system in FDox-chitosan adducts stabilizes the drug-polymer complexation, with the free binding energy of -3.89 kcal/mol for Dox and -3.76 kcal/mol for FDox complexes. The results show chitosan 100 KD is a more suitable carrier for Dox and FDox delivery.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".