Paclitaxel conjugate block copolymer nanoparticle formation by flash NanoPrecipitation
Bibliographic record
Abstract
Block copolymer drug nanoparticles have been explored for their potential in solubilizing hydrophobic drugs, reducing drug toxicity, and extending drug circulation times in vivo. Key factors in such applications involve the control of stability and nanoparticle size. Flash NanoPrecipitation, which was introduced recently, is an easily scalable technique that provides high solute loading, and controlled size nanoparticles using amphiphilic diblock copolymer stabilization. Using this technology, the anticancer drug paclitaxel conjugated to vitamin E succinate was formulated into stable and controlled size nanoparticles. Conjugation of the drug to vitamin E succinate to form a paclitaxel conjugate prior to mixing by Flash Nanoprecipitation reduces its solubility, and allows for the drug release rate to be controlled through the linker chemistry used to conjugate the drug to the nanoparticle.
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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 | 0.001 |
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".