Structural Characterization of Cis– and Trans–Pt(NH3)2Cl2 Conjugations with Chitosan Nanoparticles
Bibliographic record
Abstract
The conjugation of chitosan 15 and 100 KD with anticancer drugs cis– and trans–Pt (NH3)2Cl2 (abbreviated cis–Pt and trans–Pt) were studied at pH 5–6. Using multiple spectroscopic methods and thermodynamic analysis to characterize the nature of drug–chitosan interactions and the potential application of chitosan nanoparticles in drug delivery. Analysis showed that both hydrophobic and hydrophilic contacts are involved in drug–polymer interactions, while chitosan size and charge play a major role in the stability of drug–polymer complexes. The overall binding constants are Kch–15–cis–Pt = 1.44 (±0.6) × 105 M−1, Kch–100–cis–Pt = 1.89 (±0.9) × 105 M−1 and Kch–15–trans–Pt = 9.84 (±0.5) × 104 M−1, and Kch–100–trans–Pt = 1.15 (±0.6) × 105 M−1. More stable complexes were formed with cis–Pt than with trans–Pt–chitosan adducts, while stronger binding was observed for chitosan 100 in comparison to chitosan 15 KD. This study indicates that polymer chitosan 100 is a stronger drug carrier than chitosan 15 KD in vitro.
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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".