Characterization of Dendritic Polyglycerol Amine Layers as Coatings for Improved Neural Cell Growth Surfaces
Bibliographic record
Abstract
Surfaces coated with the hyperbranched dendritic polyglycerol amine, dPGA, a nonprotein macromolecular biomimetic of polylysine, have been shown to provide enhanced support for stable long-term culture of embryonic rat neocortical neurons and human neurons derived from induced pluripotent stem cells (iPSCs). Here, we investigate the physical properties of surface-adsorbed dPGA to understand how it provides better support for cell attachment, survival, and growth. High-molecular-weight dPGA (MW 550 kDa) with ∼30% amine functionalization was deposited on silicon wafers from PBS (pH 7.4) solutions to measure the layer thickness and density by ellipsometry and surface roughness and texture by atomic force microscopy (AFM). Colloidal silica (dia ∼ 100 nm) was used as a substrate to measure surface charge (zeta potential), adsorbed amounts by thermal gravimetric analysis (TGA), and molecular mobility by solid-state NMR spectroscopy. We found that the dPGA film properties were dependent on the immersion time in the dPGA coating solution as well as the storage conditions of dPGA solutions. Upon immobilization, dPGA retains a globular but flattened shape. Chain mobility is reduced but the adsorbed dPGA still can be considered a highly flexible polymer that rearranges to present a higher density of positive surface charges as compared to dPGA in solution. Coated surfaces prepared with different deposition times were tested for the capacity to support cells in culture.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".