Immunomodulatory Microgels Support Proregenerative Macrophage Activation and Attenuate Fibroblast Collagen Synthesis
Bibliographic record
Abstract
Abstract Scars composed of fibrous connective tissues are natural consequences of injury upon incisional wound healing in soft tissues. Hydrogels that feature a sustained presentation of immunomodulatory cytokines are known to modulate wound healing. However, existing immunomodulatory hydrogels lack interconnected micropores to promote cell ingrowth. Other limitations include invasive delivery procedures and harsh synthesis conditions that are incompatible with drug molecules. Here, hybrid nanocomposite microgels containing interleukin‐10 (IL‐10) are reported to modulate tissue macrophage phenotype during wound healing. The intercalation of laponite nanoparticles in the polymer network yields microgels with tissue‐mimetic elasticity (Young's modulus in the range of 2–6 kPa) and allows the sustained release of IL‐10 to promote the differentiation of macrophages toward proregenerative phenotypes. The porous interstitial spaces between microgels promote fibroblast proliferation and fast trafficking (an average speed of ≈14.4 µm h −1 ). The incorporation of hyaluronic acid further enhances macrophage infiltration. The coculture of macrophages and fibroblasts treated with transforming growth factor‐beta 1 resulted in a twofold reduction in collagen‐I production for microgels releasing IL‐10 compared to the IL‐10 free group. The new microgels show potential toward regenerative healing by harnessing the antifibrotic behavior of host macrophages.
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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 | 0.001 | 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) | 0.000 | 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".