Injectable Superparamagnets: Highly Elastic and Degradable Poly(<i>N</i>-isopropylacrylamide)–Superparamagnetic Iron Oxide Nanoparticle (SPION) Composite Hydrogels
Bibliographic record
Abstract
Injectable, in situ-gelling magnetic composite materials have been fabricated by using aldehyde-functionalized dextran to cross-link superparamagnetic nanoparticles surface-functionalized with hydrazide-functionalized poly(N-isopropylacrylamide) (pNIPAM). The resulting composites exhibit high water contents (82-88 wt.%) while also displaying significantly higher elasticities (G' >60 kPa) than other injectable hydrogels previously reported. The composites hydrolytically degrade via slow hydrolysis of the hydrazone cross-link at physiological temperature and pH into degradation products that show no significant cytotoxicity. Subcutaneous injections indicate only minor chronic inflammation associated with material degradation, with no fibrous capsule formation evident. Drug release experiments indicate the potential of these materials to facilitate pulsatile, "on-demand" changes in drug release upon the application of an external oscillating magnetic field. The injectable but high-strength and externally triggerable nature of these materials, coupled with their biological degradability and inertness, suggest potential biological applications in tissue engineering and drug delivery.
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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".