Fabricating Degradable Thermoresponsive Hydrogels on Multiple Length Scales via Reactive Extrusion, Microfluidics, Self-assembly, and Electrospinning
Bibliographic record
Abstract
While various smart materials have been explored for a variety of biomedical applications (e.g., drug delivery, tissue engineering, bioimaging, etc.), their ultimate clinical use has been hampered by the lack of biologically-relevant degradation observed for most smart materials. This is particularly true for temperature-responsive hydrogels, which are almost uniformly based on polymers that are functionally non-degradable (e.g., poly(N-isopropylacrylamide) (PNIPAM) or poly(oligoethylene glycol methacrylate) (POEGMA)). As such, to effectively translate the potential of thermoresponsive hydrogels to the challenges of remote-controlled or metabolism-regulated drug delivery, cell scaffolds with tunable cell-material interactions, theranostic materials with the potential for both imaging and drug delivery, and other such applications, a method is required to render the hydrogels (if not fully degradable) at least capable of renal clearance following the required lifetime of the material. To that end, this protocol describes the preparation of hydrolytically-degradable hydrazone-crosslinked hydrogels on multiple length scales based on the reaction between hydrazide and aldehyde-functionalized PNIPAM or POEGMA oligomers with molecular weights below the renal filtration limit. Specifically, methods to fabricate degradable thermoresponsive bulk hydrogels (using a double barrel syringe technique), hydrogel particles (on both the microscale through the use of a microfluidics platform facilitating simultaneous mixing and emulsification of the precursor polymers and the nanoscale through the use of a thermally-driven self-assembly and cross-linking method), and hydrogel nanofibers (using a reactive electrospinning strategy) are described. In each case, hydrogels with temperature-responsive properties similar to those achieved via conventional free radical cross-linking processes can be achieved, but the hydrazone cross-linked network can be degraded over time to re-form the oligomeric precursor polymers and enable clearance. As such, we anticipate these methods (which may be generically applied to any synthetic water-soluble polymer, not just smart materials) will enable easier translation of synthetic smart materials to clinical applications.
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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 | 0.001 | 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".