Evidence map›Paper›PMID 42666826›Full record

ReviewRegenerative biomaterials2026

Smart hydrogel systems for skin fibrosis: rational design, mechanisms and therapeutic applications.

Ranyu Sun, Zhaojian Wang, Xiao Long

Abstract readReview
In one paragraph

Review in Regenerative biomaterials, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ranyu SunDepartment of Plastic and Aesthetic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China.
Zhaojian WangDepartment of Plastic and Aesthetic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China.
Xiao LongDepartment of Plastic and Aesthetic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China.ORCID https://orcid.org/0000-0003-0136-2508

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Skin fibrosis is a pathological process characterized by excessive extracellular matrix (ECM) deposition and tissue remodeling following chronic injury or inflammation. Current treatments remain limited, highlighting the need for more effective therapeutic strategies. Tissue-engineered hydrogels (TEHs) have emerged as promising platforms for fibrosis intervention due to their biocompatibility and tunable physicochemical properties. This review summarizes recent advances in TEH-based approaches for skin fibrosis, with a focus on the design of smart hydrogels. Unlike conventional scaffolds, smart hydrogels can sense pathological changes in the fibrotic microenvironment and respond to disease-associated cues, including pH changes, elevated reactive oxygen species (ROS), enzymatic activity and mechanical alterations. These adaptive systems enable controlled cargo delivery and local microenvironment regulation. We further discuss multifunctional hydrogel platforms incorporating bioactive molecules, nucleic acids and nanomaterials to modulate key fibrotic pathways. Finally, we highlight current challenges in clinical translation and future perspectives for developing safer and more effective responsive hydrogel therapies for skin fibrosis.

Indexed as

biomimetic designcontrolled cargo deliverymicroenvironment remodelingskin fibrosissmart hydrogel systems

Identifiers

PMID42666826
PMCPMC13524228

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.