Nonswelling, Ultralow Content Inverse Electron‐Demand Diels–Alder Hyaluronan Hydrogels with Tunable Gelation Time: Synthesis and In Vitro Evaluation
Bibliographic record
Abstract
Abstract Hyaluronan (HA) is a major component of the extracellular matrix and is particularly attractive for cell‐based assays; yet, common crosslinking strategies of HA hydrogels are not fully tunable and bioorthogonal, and result in gels subject to swelling, which affects their physicochemical properties. To overcome these limitations, HA hydrogels based on the inverse electron‐demand Diels–Alder (IEDDA) “click” reaction are designed. By crosslinking two modified HA components together, as opposed to using telechelic components, tunable gelation times as fast as 4.4 ± 0.4 min and as slow as 46.2 ± 1.8 min are achieved for facile use. By optimizing HA molar mass, ultralow polymer content hydrogels of 0.5% (w/v), resulting in minimal (<3–5% mass variation) to nonswelling (<1%), transparent and biodegradable hydrogels are synthesized. To demonstrate their versatility, the newly designed hydrogels are tested as matrices for 3D cell culture and retinal explant imaging where transparency is important. IEDDA hydrogels are cytocompatible with primary photoreceptors and enable multiphoton imaging of embedded retinal explants for double the time (>38 h) than agarose thermogels (<20 h). IEDDA HA hydrogels constitute a new hydrogel platform. They have low polymer content, tunable gelation time, and are stable, thereby making them suitable for a diversity of 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 | 0.000 | 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 | 0.001 |
| 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".