Evidence map›Paper›PMID 40918441›Full record

ArticleFrontiers in bioengineering and biotechnology2025

Engineering a 3D wounded skin equivalent to study early inflammatory and regenerative responses

Rima Nuwayhid, Nguyen Ngoc-Huyen, Dmitry Notov, Stefan Langer, Olga Kurow

Abstract read
In one paragraph

Article in Frontiers in bioengineering and biotechnology, 2025. 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

5 authors.

Rima Nuwayhid *Department of Orthopaedic, Trauma and Plastic Surgery, University Hospital Leipzig, Leipzig, Germany.
Nguyen Ngoc-Huyen *Department of Upper Extremity Surgery and Microsurgery, Institute of Traumatology, Orthopedics and Plastic Surgery of Central Hospital 108, Hanoi, Vietnam.
Dmitry NotovDepartment of Orthopaedic, Trauma and Plastic Surgery, University Hospital Leipzig, Leipzig, Germany.
Stefan LangerDepartment of Orthopaedic, Trauma and Plastic Surgery, University Hospital Leipzig, Leipzig, Germany.
Olga KurowDepartment of Orthopaedic, Trauma and Plastic Surgery, University Hospital Leipzig, Leipzig, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Traditional models for studying wound healing, including 2D cell cultures and animal models, present substantial limitations in mimicking human skin physiology. In this study, we present a three-dimensional wounded skin equivalent (3DWoundSE) composed of human cells as a physiologically relevant Methods: The model builds upon a previously established 3D skin equivalent (3DSE) and incorporates a reproducible partial-thickness dermal punch wound. We characterised the 3DWoundSE using histology, cytotoxicity assays, immunofluorescence staining, and pro-inflammatory cytokine profiling at multiple time points post-wounding. Results: Results revealed hallmark wound responses, including increased lactate dehydrogenase (LDH) and apoptosis-inducing factor (AIF) expression, dynamic Ki-67 proliferation changes, and a pro-inflammatory cytokine response, notably elevated IL-6, IL-8, IL-33 and TNF-α levels. Discussion: Compared to the intact 3DSE, this 3DWoundSE demonstrated enhanced responsiveness to injury and cytotoxic stimuli, confirming its utility for early wound response assessment. This platform offers a reproducible and ethically sound alternative to animal models, with potential applications in dermatological research, drug development, and therapeutic screening.

Indexed as

3D skin equivalentbioengineered skincytokinesin vitro modelwound healingwound model

Identifiers

PMID40918441
PMCPMC12412330

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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.