Molecular Dynamics Studies for Optimization of Noncovalent Loading of Vinblastine on Single-Walled Carbon Nanotube
Bibliographic record
Abstract
Carbon nanotubes (CNTs) have become one of the most promising candidates for transporting drugs to target sites because of their size scale, huge surface area, and high cellular uptake. Many experimental studies of carbon nanotube drug delivery have been performed in the past decade. However, interactions with one of the essential antimitotic agents—vinblastine—and carbon nanotubes have yet to be investigated. Here we present computational studies of the interactions between vinblastine and carbon nanotubes under different conditions. We studied vinblastine–carbon nanotube interactions with one to three vinblastine molecules loaded, with armchair, chiral, and zigzag tube structures, with nonfunctionalized and ester-functionalized carbon nanotubes at 277 and 300 K. Terminal esterification of carbon nanotubes strengthened the drug–carrier interactions of all systems at 300 K. The functionalized carbon nanotubes of armchair type were suitable for drug delivery at both 277 and 300 K due to the strong drug–carrier interactions. The functionalized chiral nanotubes have been shown to be especially effective for the drug transportation at 277 K due to the enhanced drug–carrier interactions at the low temperature.
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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) | 0.002 | 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".