Novel dendrimer based polyurethanes for PEO incorporation
Bibliographic record
Abstract
A series of segmented polyurethanes based on methylene diisocyanate/poly (tetramethylene oxide) and chain extended with either ethylene diamine or butane diol in combination with a generation 2 polypropylenimine octaamine dendrimer were synthesized. For polymer synthesis, the dendrimers were protected with either t-boc or Fmoc groups and were incorporated into the polyurethane microstructure to permit further functionalization with biologically active groups. Following deprotection, the dendrimers were reacted with succinimidyl propionate polyethylene oxide (SPA-PEO) to improve the protein resistance of the polymers and to examine the potential of this technique for polymer functionalization. Different synthesis techniques were examined to optimize the incorporation of the PEO into the polymer microstructure. Incorporation of the dendrimers and the PEO were confirmed by NMR and FTIR. Gel permeation chromatography was used to examine the molecular weights of the various polyurethanes. The dendrimer incorporated polymers had significantly lower molecular weights than the ED or BDO chain extended controls, likely due to lower reactivity of the dendrimers as a result of steric factors. Following PEO reaction, the molecular weights of the resultant polymers were consistent with the levels of PEO incorporation noted by comparison of peak intensities in the NMR spectra. Due to the highly hydrophilic nature of the PEO, some migration to the polymer surface was expected. Water contact angles and XPS, used to characterize the surfaces, suggest that there was some PEO enrichment at the surface of the polymers. Adsorption of radiolabeled fibrinogen to the polymer surfaces was decreased by a factor of approximately 40% in some of the PEO incorporated polymers. There were also differences in the patterns of plasma protein adsorption on the various surfaces as evaluated by SDS PAGE and immunoblotting. Therefore, the use of dendrimers in biomaterials for incorporation of a large number of functional groups seems to be promising.
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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".