Biodegradable Polyurethane Hydrogels for Sustained Growth Factor Delivery Intended for Treatment of Ischemic Conditions
Bibliographic record
Abstract
The development of a treatment for ischemic conditions has been hindered by the lack of appropriate growth factor delivery vehicles, the limited number of effective agents, and the inability to assess the efficacy of the agent in clinical trials. An MRI-trackable injectable microsphere growth factor delivery vehicle, containing low-inflammatory polyurethanes, referred to as D-PHI polymers, is proposed for treating ischemic conditions in this thesis. The carriers were developed with the design challenge that growth factors have short half-lives in the body but are necessary for a few weeks to ensure cell survival, proliferation, and migration. In order to avoid rapid uptake by phagocytic cells and to facilitate the extracellular delivery of growth factors, microspheres of specific sizes and morphologies were fabricated. The chemistry of the D-PHI polymer was modified to achieve a fast bioresorption rate, whereby it can be quickly reabsorbed once the growth factor has been released. In order to predict the biodegradation of a family of novel crosslinked D-PHI hydrogels, an accelerated erosion test was developed. In vitro methods for evaluating the encapsulation, stability, and release of proteins from such hydrogels were developed and validated. Specific steps were taken to maintain the activity of the protein (i.e. vascular endothelial growth factor (VEGF)) during fabrication, storage, and use of the growth factor carriers. A sustained release of VEGF was observed over a two-week period from the hydrogels, and the released VEGF increased the proliferation of cells. To dampen the inflammation associated with a foreign body response in tissue and prepare it for revascularization, polyurethane-based D-PHI materials were used. These materials exhibited inherent immune-modulatory properties. For the purpose of tracking the hydrogel in rodents non-invasively, an MRI contrast agent was developed. The T1 contrast of manganese porphyrins bound to hydrogels was measured using this strategy. This thesis contributed to the development of an injectable polyurethane D-PHI hydrogel, which facilitates the slow release of pro-angiogenic VEGF and provides a versatile MRI-active platform. The combination of these technologies can provide a specific set of growth factor carriers that may be applied to the treatment of ischemic conditions and other soft tissue injuries where pro-regenerative immune control is important.
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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".