Evidence map›Paper›PMID 42292862›Full record

ArticleMethodsX2026

A reproducible mechano-thermal injury method for reconstructed human epidermis to study wound re-epithelialization.

Thaís C Pereira, Victória S Padilha, José M de Brito Neto, Raquel F Chaves, Vanja Dakic, Ronaldo José F C do Amaral

Abstract read
In one paragraph

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

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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

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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

6 authors.

Thaís C PereiraL'Oréal Research & Innovation, Rio de Janeiro, Brazil.
Victória S PadilhaInstitute of Biomedical Sciences, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil.
José M de Brito NetoInstitute of Biomedical Sciences, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil.
Raquel F ChavesUniversity of Grande Rio (Unigranrio), Rio de Janeiro, RJ, Brazil.
Vanja DakicL'Oréal Research & Innovation, Rio de Janeiro, Brazil.
Ronaldo José F C do AmaralInstitute of Biomedical Sciences, Federal University of Rio de Janeiro (UFRJ), Rio de Janeiro, Brazil.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Reconstructed human epidermis (RHE) models are widely used as an ethical alternative to animal testing and are validated for cutaneous toxicity assessment. However, their application in wound healing research remains limited due to the lack of standardized methods to induce reproducible epidermal injuries. Generating localized lesions while preserving the polycarbonate membrane required for keratinocyte migration remains a technical challenge. Here we describe a method to generate controlled lesions in reconstructed human epidermis suitable for re-epithelialization studies. Several injury strategies were evaluated, including mechanical approaches using pipette tips, punches, microneedles and glass capillaries. These approaches frequently produced inconsistent lesions or disrupted the membrane. A mechano-thermal strategy proved to be the most reliable approach, generating well-defined and reproducible lesions while preserving membrane integrity. Histological analysis confirmed characteristic features of thermal injury. Longitudinal macroscopic and histological analyses, including semi-quantitative scoring, demonstrated progressive epidermal reorganization following injury. This method establishes a reproducible epidermal burn model suitable for studying epidermal regeneration and wound healing.•Comparative evaluation of mechanical and mechano-thermal strategies to induce lesions in reconstructed human epidermis.•Identification of a reproducible injury method that preserves the polycarbonate membrane required for keratinocyte migration.•Development of a standardized epidermal burn model for re-epithelialization studies.

Indexed as

In vitro assayRe-epithelializationRHESkinEthic®

Identifiers

PMID42292862
PMCPMC13254972

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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.