Evidence map›Paper›PMID 42125408›Full record

ArticleRegenerative therapy2026

Accelerated diabetic wound healing via microenvironmental modulation treated by hydrogel encapsulated with neural stem cells.

Junying Song, Yifu Zhu, Yufei Zhang, Zhou Yu, Baoqiang Song

Abstract read
In one paragraph

Article in Regenerative therapy, 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

5 authors.

Junying SongDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, People's Republic of China.
Yifu ZhuDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, People's Republic of China.
Yufei ZhangDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, People's Republic of China.
Zhou YuDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, People's Republic of China.
Baoqiang SongDepartment of Plastic Surgery, Xijing Hospital, Fourth Military Medical University, Xi'an, 710032, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Diabetic wound healing is a highly coordinated, multi-stage process that relies critically on the pro-regenerative microenvironment. Recently, stem cell-based therapies have emerged as a promising paradigm in regenerative medicine, largely attributable to their inherent self-renewal capacity, multilineage differentiation potential, and pro-repair secretome. Despite these advances, the therapeutic potential of neural stem cells (NSCs) in cutaneous wound repair remains largely unexplored. Methods: We systematically evaluated the pro-angiogenic, antioxidant, and mitochondrial modulatory effects of NSCs on endothelial cells. A bio-inspired hydrogel was designed for NSC encapsulation with favorable preliminary biocompatibility. The Results: NSCs enhanced angiogenesis, antioxidant capacity, and mitochondrial function in endothelial cells. The engineered hydrogel exhibited favorable preliminary biocompatibility for the encapsulation of NSCs. This platform accelerated diabetic wound healing by regulating inflammation, promoting angiogenic, and exerting neural-supportive effects. Conclusions: This NSC-loaded hydrogel platform offers a promising and clinically relevant strategy for diabetic wound repair.

Indexed as

Diabetic woundHydrogelMicroenvironmental modulationNeural stem cells

Identifiers

PMID42125408
PMCPMC13158421

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Registered trials

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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.