Evidence map›Paper›PMID 41281655›Full record

ArticleMaterials today. Bio2025

Integrated biofabrication of artificial esophageal scaffolds using electrospinning, embedded DLP, and extrusion techniques.

Priya Ranganathan, Seung Hoon Han, In Gul Kim, Dageon Oh, Yewon Kim, Kyung-Noh Yoon, Garin Kim, Young Hwa Lee, Masoud Shirzad, Gyeongmi Lee and 10 more

Abstract read
In one paragraph

Article in Materials today. Bio, 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

20 authors.

Priya RanganathanIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, South Korea.
Seung Hoon HanDepartment of Otorhinolaryngology-Head and Neck Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, 05505, South Korea.
In Gul KimDepartment of Otorhinolaryngology-Head and Neck Surgery, Biomedical Research Institute, Seoul National University Hospital, Seoul, 03080, South Korea.
Dageon OhIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, South Korea.
Yewon KimDepartment of Otorhinolaryngology-Head and Neck Surgery, Biomedical Research Institute, Seoul National University Hospital, Seoul, 03080, South Korea.
Kyung-Noh YoonResearch and Development Institute, ATEMs, Seoul, 05836, South Korea.
Garin KimIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, South Korea.
Young Hwa LeeResearch and Development Institute, ATEMs, Seoul, 05836, South Korea.
Masoud ShirzadIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, South Korea.
Gyeongmi LeeIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, South Korea.
Jungeun ChoiIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, South Korea.
Jin Myoung YooIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, South Korea.
Ganghak LeeIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, South Korea.
Young Jick KimResearch and Development Institute, ATEMs, Seoul, 05836, South Korea.
Jungirl SeokDepartment of Otorhinolaryngology-Head and Neck Surgery, Biomedical Research Institute, Seoul National University Hospital, Seoul, 03080, South Korea.
Ji Youl LeeDepartment of Urology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, 06591, South Korea.
Sang-Hyug ParkIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, South Korea.
Jung-Woog ShinDepartment of Biomedical Engineering, Inje University, Gimhae, 50834, South Korea.
Seung Yun NamIndustry 4.0 Convergence Bionics Engineering, Pukyong National University, Busan, 48513, South Korea.
Eun-Jae ChungDepartment of Otorhinolaryngology-Head and Neck Surgery, Biomedical Research Institute, Seoul National University Hospital, Seoul, 03080, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Esophageal reconstruction faces critical challenges due to limitations in current techniques, including inadequate mechanical properties, poor tissue integration, and insufficient functional regeneration. This study presents a novel biofabrication strategy for developing artificial esophageal scaffolds by integrating electrospinning, embedded digital light processing (DLP), and extrusion-based bioprinting techniques. These scaffolds are composed of flexible electrospun polyurethane (PU) nanofibers wherein silk fibroin methacryloyl (Sil-MA) is embedded within the PU layer to enhance mechanical strength and hydrophilicity. Decellularized esophageal extracellular matrix (EdECM) is deposited onto the scaffolds to promote tissue regeneration. Comprehensive in vitro and in vivo evaluations reveal that the PU/Sil-MA/EdECM scaffolds exhibit superior mechanical properties, enhanced cell adhesion, and significant improvements in smooth muscle and epithelial tissue regeneration. Moreover, in a rat model with partial esophageal defects, the scaffolds demonstrate successful tissue integration, reduced postoperative complications, and restoration of esophageal function, including peristalsis and nerve regeneration. Altogether, this integrated biofabrication approach offers a promising solution for esophageal reconstruction by effectively addressing the current challenges and paving the way for future clinical applications in regenerative medicine.

Indexed as

Artificial esophagusElectrospinningEmbedded DLPEsophageal regenerationExtrusion-based bioprinting

Identifiers

PMID41281655
PMCPMC12639500

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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.