Poly(Oligo(Ethylene Glycol) Methacrylate)-Based Polymers in Biomedical Applications: Preparation and Applications
Bibliographic record
Abstract
While poly(ethylene glycol) (PEG) has been widely applied in a host of biomedical applications due to its antifouling properties, its limited potential for functionalization and emerging concerns over potential immunogenicity have inspired the development of PEG alternatives. Herein, we review the use of poly(oligo(ethylene glycol) methacrylate) (POEGMA) as a PEG alternative that can provide significantly more synthetic versatility, minimize immunogenicity, and open up additional applications (e.g., thermoresponsive devices) based on precise control over the (co)polymer composition, the backbone molecular weight, and the side chain molecular weight. The synthetic pathways and applications of POEGMA as a surface or biomolecular grafting agent, a hydrogel, a microgel/nanogel, and a nanoparticle stabilizer are comprehensively summarized, with applications in drug delivery, tissue engineering/wound healing, and biosensing particularly highlighted to show how the unique properties of POEGMA can impart improved or unique application performance. Future directions to better leverage the properties of POEGMA in diverse applications are also proposed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".