Evidence map›Paper›PMID 41783591›Full record

ArticleFrontiers in cell and developmental biology2026

AI and big data driven knowledge mapping of exosome-hydrogel research in orthopedic regeneration and tissue engineering.

Qinghan Li, Liming Lou, Shuaishuai Wang, Minglei Zhang

Abstract read
In one paragraph

Article in Frontiers in cell and developmental biology, 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
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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

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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

4 authors.

Qinghan LiDepartment of Xinmin Orthopedic, China-Japan Union Hospital of Jilin University, Changchun, China.
Liming LouSchool of Technology, Beijing Forestry University, Beijing, China.
Shuaishuai WangDepartment of Xinmin Orthopedic, China-Japan Union Hospital of Jilin University, Changchun, China.
Minglei ZhangDepartment of Xinmin Orthopedic, China-Japan Union Hospital of Jilin University, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Exosome-hydrogel complexes have great potential in regenerative medicine, being able to combine biological signals with structural support. But overall, the knowledge structure and translational connections between academic discoveries and patent deployment are not clear. Methods: A dual-source analysis framework was established to analyze academic papers and patents, illustrating the landscape of exosome-hydrogel research from 2016 to 2025. An interdisciplinary knowledge graph was constructed using topic modeling, entity-relation extraction, and evidence-ranking methods to quantify temporal trends, thematic differences, and translational gaps. Results: The core components include mesenchymal stem cell-derived exosomes and hydrogels based on gelatin methacrylate (GelMA) or collagen, which form a well-established research foundation. Academic research focuses on osteogenesis, and recent progress mentions angiogenesis and immune regulation. The research application has strong temperature dependence, and patent activities lag behind academic publications. Several high-evidence yet unpatented propositions, such as "hydrogel-encapsulated exosomes" and "exosome-enhanced angiogenesis," represent potential innovation opportunities. Conclusion: This study employs a data-driven framework to connect scientific research with transformation. The integration of semantic models and cross - source evidence reflects the evaluation logic of exosome - hydrogel research, and provides support for future research in the field of regenerative biomaterials and the priority of patent strategies.

Indexed as

artificial intelligencebig data analyticsbone regeneration and tissue engineeringexosome–hydrogel systemsknowledge graph

Identifiers

PMID41783591
PMCPMC12953459

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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.