Dendritic surface functionalization of biodegradable polymer assemblies
Bibliographic record
Abstract
Abstract The functionalization of nanomaterials with dendritic surface moieties was recently demonstrated to be an effective means of displaying biological ligands and potentially modulating the biological properties of these materials. With the aim of extending this surface functionalization approach to biodegradable polymer assemblies, poly(ethylene oxide)‐polycaprolactone (PEO‐PCL) block copolymers with terminal azide or methoxy groups were prepared and were assembled to form micelles or vesicles with varying loadings of surface azides. Dendrons bearing peripheral amines, guanidines, or hydroxyls were prepared and conjugated to the assemblies, and the conjugation yields were measured and compared as a function of azide loading and assembly type (micelle versus vesicle). A small molecule rhodamine derivative was also conjugated, allowing the effect of sterics to be studied. The effects of the surface functionalization on the aggregation state of the assemblies were studied by light scattering and transmission electron microscopy. Overall, the results revealed interesting differences between the two systems with respect to both the reaction yields and the stabilities. Furthermore, micelles functionalized with dendrons bearing peripheral guanidines were found to exhibit enhanced cell uptake relative to control micelles, demonstrating that this approach can be used to modulate the biological properties of the materials. © 2011 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem, 2011
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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".