Bioprinted Recombinant Human-Collagen-Based In Vitro Skin Models for Assessing Effects of Nano-ZnO on Dermis.

Ting Yu, Yang Xu, Xinyue Zhang, Chenkai Zhu, Jianfeng Zhao, Yang Yang, Min Jiang

Abstract read

In one paragraph

Article in Gels (Basel, Switzerland), 2025. 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

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3 · Its place in the literature

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0 citing papers in PubMed.

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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

7 authors.

Ting YuState Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing 211800, China.

Yang XuState Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing 211800, China.

Xinyue ZhangState Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing 211800, China.

Chenkai ZhuNingbo Institute of Technology, Beihang University, 399 Kangda Road, Ningbo 315832, China.

Jianfeng ZhaoZhejiang Zhuji Jland Biotechnology Co., Ltd., No.69 Youyi North Road, Zhuji 311800, China.

Yang YangState Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing 211800, China.

Min JiangState Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing 211800, China.

Funding

National Key Research and Development Project of China 2022YFC2403105National Natural Science Foundation of China 32201119

6 · The paper itself

Abstract

Collagen types I and III are primary structural proteins that maintain human skin integrity, and their ratio is disrupted during aging. In this study, we developed a biomimetic 3D skin model with vascularization potential to evaluate the effects of nano-zinc oxide (nano-ZnO) in a physiologically relevant context. The model used methacrylated recombinant human collagen (RHC-MA) bioinks with tunable collagen I/III ratios that mimic the skin of children and adults. The bioinks exhibited excellent printability and mechanical properties that enabled the 3D bioprinting of full-thickness skin products, including dermal layers with human skin fibroblasts (HSFs) and human umbilical vein endothelial cells (HUVECs), as well as epidermal layers with keratinocytes (KCs). The model recapitulated native skin architecture, and key markers such as keratin 10 (K10), keratin 14 (K14), and cluster of differentiation 31 (CD31) were determined. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis showed that nano-ZnO significantly modulated genes associated with apoptosis, inflammation, and oxidative stress in skin cells.

Indexed as

3D bioprintingin vitro skin modelnano-zinc oxiderecombinant human collagenvascularization potential

Identifiers

PMID41441133

DOI10.3390/gels11120977

PMCPMC12732388

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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.