Evidence map›Paper›PMID 35096071›Full record

ArticleStem cells international2022

Fabrication and Characterization of Alveolus-Like Scaffolds with Control of the Pore Architecture and Gas Permeability.

Lanxin Lü, Hongxian Shen, Daichi Kasai, Ying Yang

Abstract read
In one paragraph

Article in Stem cells international, 2022. 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

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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

4 authors.

Lanxin LüEmergency Center of the Affiliated Hospital of Xuzhou Medical University, Laboratory of Emergency Medicine, Xuzhou Medical University, Xuzhou 221002, China.ORCID https://orcid.org/0000-0001-7454-6768
Hongxian ShenEmergency Center of the Affiliated Hospital of Xuzhou Medical University, Laboratory of Emergency Medicine, Xuzhou Medical University, Xuzhou 221002, China.
Daichi KasaiSchool of Pharmacy and Bioengineering, Keele University, Stoke-on-Trent ST4 7QB, UK.
Ying YangSchool of Pharmacy and Bioengineering, Keele University, Stoke-on-Trent ST4 7QB, UK.ORCID https://orcid.org/0000-0002-1362-6040

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The micrometer scale sac-like alveoli are the most important and essential unit for gas exchange in the lung. Thus, design and fabrication of scaffolds for alveoli regeneration by tissue engineering approach should meet a few topography and functional requests such as large surface area, flexibility, and high gas permeability to their native counterpart. Testing the gas permeability of scaffolds through a fast and simple technique is also highly demanded to assist new scaffold development. This study fabricated alveolus-like scaffolds with regular pore shape, high pore connectivity, and high porosity produced by inverse opal technique alongside randomly distrusted porous scaffolds by salt leaching technique from two different materials (polyurethane and poly(L-lactic acid)). The scaffold surface was modified by immobilization of VEGF. A facile and new technique based on the bubble meter principle enabling to measure the gas permeability of porous scaffolds conveniently has been developed specifically. The cellular response of the scaffolds was assessed by culturing with bone marrow mesenchymal stem cells and coculturing with lung epithelial NL20 and endothelial HUVECs. Our results showed that the newly designed gas permeability device provided rapid, nondestructive, reproducible, and accurate assessment of gas permeability of different scaffolds. The porous polyurethane scaffolds made by inverse opal method had much better gas permeability than other scaffolds used in this study. The cellular work indicated that with VEGF surface modification, polyurethane inverse opal scaffolds induced alveolus-like tissues and have promising application in lung tissue engineering.

Identifiers

PMID35096071
PMCPMC8794699

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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.