HydrogelsPaper

Smart Hydrogel Systems for Skin Fibrosis: Rational Design, Mechanisms, and Therapeutic Applications

Ranyu Sun, Zhaojian Wang, Xiao Long · Oxford University Press (OUP) · 2026

This review discusses the design and therapeutic potential of smart hydrogels for treating skin fibrosis.

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Plain English summary

Skin fibrosis is a condition caused by excessive tissue remodeling, and current treatments are limited. Smart hydrogels, which can adapt to changes in their environment, show promise for improving treatment outcomes. This review highlights recent advancements in these hydrogels, focusing on their ability to respond to specific disease cues and deliver therapeutic agents effectively.

Why this matters

The research addresses a significant medical challenge—skin fibrosis—by exploring innovative hydrogel systems that can adapt to the disease environment. These smart materials could lead to more effective treatments, improving patient outcomes and advancing the field of regenerative medicine.

Key findings

  • Smart hydrogels can sense and respond to changes in the fibrotic microenvironment.
  • They enable controlled delivery of therapeutic agents.
  • Incorporation of bioactive molecules and nanomaterials enhances their effectiveness.
  • Current challenges in clinical translation are discussed.
  • Future perspectives for safer and more effective therapies are outlined.

What's new

The review emphasizes the unique capabilities of smart hydrogels to adapt to pathological changes, distinguishing them from conventional scaffolds.

Limitations

The abstract mentions challenges in clinical translation but does not provide specific details on these challenges or the extent of current limitations.

Commercial context

The abstract does not provide information on the commercial status of the technologies discussed.

Publication

Publisher
Oxford University Press (OUP)
Publication date
July 31, 2026
Research type
Paper
License
https://creativecommons.org/licenses/by/4.0/

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Method note: Summaries and ratings on this page are generated by AI from the abstract only. Read the original paper for full context. · Model: gpt-4o-mini-2024-07-18