Designing Hydrogels for 3D Cell Culture Using Dynamic Covalent Crosslinking
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Designing simple biomaterials to replicate the biochemical and mechanical properties of tissues is an ongoing challenge in tissue engineering. For several decades, new biomaterials have been engineered using cytocompatible chemical reactions and spontaneous ligations via click chemistries to generate scaffolds and water swollen polymer networks, known as hydrogels, with tunable properties. However, most of these materials are static in nature, providing only macroscopic tunability of the scaffold mechanics, and do not reflect the dynamic environment of natural extracellular microenvironment. For more complex applications such as organoids or co-culture systems, there remain opportunities to investigate cells that locally remodel and change the physicochemical properties within the matrices. In this review, advanced biomaterials where dynamic covalent chemistry is used to produce stable 3D cell culture models and high-resolution constructs for both in vitro and in vivo applications, are discussed. The implications of dynamic covalent chemistry on viscoelastic properties of in vitro models are summarized, case studies in 3D cell culture are critically analyzed, and opportunities to further improve the performance of biomaterials for 3D tissue engineering are discussed.
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it