Hyperbranched polyglycerols: recent advances in synthesis, biocompatibility and biomedical applications
Why this work is in the frame
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Bibliographic record
Abstract
In the pursuit of dendrimer alternatives, hyperbranched polymers have found increasing interest from academia and industry in a broad range of fields due to their topological and synthetic advantages. Hyperbranched polyglycerol (HPG), as the name implies, is a hyperbranched polymer with about 50-65% dendrimeric structure. Due to its ease in synthesis, globular nature, versatility in terms of functionalization, and superb biocompatibility profiles HPG provides a promising class of materials suitable for numerous applications in nanomedicine and biomedical technologies. The structural features of HPG can be easily tailored by adopting different synthetic methodologies. In this review, we briefly explore the synthesis of HPGs starting from the traditional Lewis acid based approaches to recent advances including the development of high MW HPGs, biodegradable HPGs, co-block HPGs and sustainable or 'green' HPG synthesis. The robust history of HPG biocompatibility is extensively reviewed giving examples of both in vitro and in vivo models. In particular, HPG showed very minimal polymer accumulation in vital organs after intravenous injection compared to other polymers widely used for various biomedical applications. HPG is well tolerated in mice and rats, and has been found to be non-immunogenic to date. Due to its demonstrated safety profile and multifunctionality, HPG has been extensively studied for different biomedical applications including as macromolecular therapeutics, multivalent inhibitors/scavengers, in controlled drug delivery systems, in organ preservation, dialysis and cell surface engineering, as imaging agents and theranostics, in the development of anti-fouling surfaces and proteomics reagents. We highlight these applications along with its advantages. Finally, we conclude by providing a future prospective of HPG as one of the promising PEG alternatives with a great potential to enter clinical trials in the near future.
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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 | 0.000 |
| 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 it