Evidence map›Paper›PMID 42502899›Full record

ReviewMacromolecular rapid communications2026

Dynamic Biomaterial: A Platform for Biomedical Applications With Multiple Preparation Strategies.

Hanbing Duan, Shuo Feng, Yonggang Lv

Abstract readReview
In one paragraph

Review in Macromolecular rapid communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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.

Hanbing DuanState Key Laboratory of New Textile Materials and Advanced Processing, Wuhan Textile University, Wuhan, P. R. China.
Shuo FengState Key Laboratory of New Textile Materials and Advanced Processing, Wuhan Textile University, Wuhan, P. R. China.
Yonggang LvState Key Laboratory of New Textile Materials and Advanced Processing, Wuhan Textile University, Wuhan, P. R. China.ORCID https://orcid.org/0000-0003-3966-8975

Funding

National Natural Science Foundation of China U23A2070
6 · The paper itself

Abstract

Conventional static biomaterials possess relatively stable physicochemical properties after fabrication or implantation, which limits their ability to adapt to dynamically changing physiological microenvironments. In contrast, dynamic biomaterials can undergo controllable or programmable changes to regulate their physicochemical properties in response to external or endogenous stimuli, thereby providing improved spatiotemporal adaptability for biomedical applications. In this review, dynamic biomaterials are systematically discussed from a physical-cue-centered perspective, focusing on stimulus-responsive changes in stiffness, surface morphology, and shape programmability rather than classification solely by stimulus type or material composition. The responsive mechanisms, preparation strategies, and representative stimuli, including light, temperature, pH, ions, and magnetic fields, are summarized and critically analyzed. Recent biomedical applications in tissue engineering, drug delivery, minimally invasive therapy, and intelligent biomedical devices are further highlighted. Finally, current challenges involving long-term biosafety, mechanical durability, manufacturability, and clinical translation are discussed, together with future perspectives for multifunctional, multi-stimuli-responsive, and spatiotemporally programmable dynamic biomaterials.

Indexed as

Biocompatible MaterialsAnimalsDrug Delivery SystemsHumansHydrogen-Ion ConcentrationTemperatureTissue EngineeringBiocompatible Materialsbiomedical applicationsdynamic biomaterialsmorphologyshape morphingstiffness

Identifiers

PMID42502899
PMCPMC13542758

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.