Pluronics as crosslinking agents for collagen: novel amphiphilic hydrogels
Bibliographic record
Abstract
Abstract A series of Pluronic samples (L61, L121, F68, F108) were investigated as collagen crosslinking agents to determine their ability to improve the Young's modulus of a collagen hydrogel, while simultaneously serving as surfactants for single‐walled carbon nanotubes (SWNTs). The crosslinked collagen matrices were prepared by blending type I bovine collagen with either Pluronics or SWNTs dispersed in an aqueous Pluronic solution and crosslinked utilizing carbodiimide chemistry. The resulting material was a crosslinked collagen hydrogel with sufficient mechanical strength to be manipulated and transferred without damaging the matrix. Differential scanning calorimetry confirmed a change in the denaturation temperature for hydrogels prepared using Pluronic or Pluronic/SWNT solutions. Water uptake analysis confirmed the crosslinked matrices to be hydrogels. These collagen hydrogels produced with Pluronics as the crosslinking agents exhibited a Young's modulus 3 to 9 times greater than collagen hydrogels produced in the absence of any crosslinking agent, regardless of polymer molecular weight. However, non‐covalent incorporation of SWNTs was not found to affect the Young's modulus of the resulting collagen hydrogels at the incorporation levels achieved with the Pluronics surfactants. Copyright © 2010 Society of Chemical Industry
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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) | 0.000 | 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 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".