134 Encapsulation of antitumor drugs tamoxifen, 4-hydroxytamoxifen and endoxifen by chitosan nanoparticles
Bibliographic record
Abstract
Synthetic polymers are often used as drug delivery systems in vitro and in vivo (1). Here, we used biodegradable chitosan of different sizes to encapsulate antitumor drug tamoxifen (tam) and its metabolites 4-hydroxytamoxifen (hydroxytam) and endoxifen (end). The interactions of tamoxifen and its metabolites with chitosan 15, 100, and 200 KD were investigated in aqueous solution, using FTIR, fluorescence spectroscopic methods, and molecular modeling. The structural analysis showed that tamoxifen and its metabolites bind chitosan via both hydrophilic and hydrophobic contacts with overall binding constants of K tam-ch-15 = 8.7 (±0.5) × 103 M−1 , K tam-ch-100 = 5.9 (±0.4) × 105 M−1, and K tam-ch-200 = 2.4 (±0.4) × 105 M−1; K hydroxytam-ch-15 = 2.6 (±0.3) × 104 M−1, K hydroxytam-ch-100 = 5.2 (±0.7) × 106 M−1, and K hydroxytam-ch-200 = 5.1 (±0.5) × 105 M−1; and K end-ch-15 = 4.1 (±0.4) × 103 M−1 , K end-ch-100 = 1.2 (±0.3) × 106 M−1, and K end-ch-200 = 4.7 (±0.5) × 105 M−1 with the number of drug molecules bound per chitosan (n) 2.8–0.5. The order of binding is ch-100 > 200 > 15 KD with stronger complexes formed with 4-hydroxytamoxifen than with tamoxifen and endoxifen. The molecular modeling showed the participation of polymer charged NH2 residues with drug OH and NH2 groups in the drug–polymer adducts. The free binding energies of -3.46 kcal/mol for tamoxifen, −3.54 kcal/mol for 4-hydroxytamoxifen, and −3.47 kcal/mol for endoxifen were estimated for these drug–polymer complexes. The results show that chitosan 100 KD is a stronger carrier for drug delivery than for chitosan-15 and chitosan-200 KD, which is consistent with our recent report on doxorubicin–chitosan complexes (2).
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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 | 0.000 | 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) | 0.000 | 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".