Evidence map›Paper›PMID 28260890›Full record

ArticleInternational journal of nanomedicine2017

Preparation of a nano- and micro-fibrous decellularized scaffold seeded with autologous mesenchymal stem cells for inguinal hernia repair.

Yinlong Zhang, Yuanyuan Zhou, Xu Zhou, Bin Zhao, Jie Chai, Hongyi Liu, Yifei Zheng, Jinling Wang, Yaozong Wang, Yilin Zhao

Abstract read
In one paragraph

Article in International journal of nanomedicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Review
  3. Review
  4. Article
  5. Article
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

10 authors.

Yinlong ZhangMedical College, Xiamen University.
Yuanyuan ZhouMedical College, Xiamen University.
Xu ZhouDepartment of Oncology and Vascular Intervention Radiology.
Bin ZhaoMedical College, Xiamen University.
Jie ChaiMedical College, Xiamen University.
Hongyi LiuMedical College, Xiamen University.
Yifei ZhengMedical College, Xiamen University.
Jinling WangDepartment of Emergency.
Yaozong WangDepartment of Orthopaedics, Zhongshan Hospital, Xiamen University, Xiamen, People's Republic of China.
Yilin ZhaoDepartment of Oncology and Vascular Intervention Radiology.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prosthetic meshes used for hernioplasty are usually complicated with chronic pain due to avascular fibrotic scar or mesh shrinkage. In this study, we developed a tissue-engineered mesh (TEM) by seeding autologous bone marrow-derived mesenchymal stem cells onto nanosized fibers decellularized aorta (DA). DA was achieved by decellularizing the aorta sample sequentially with physical, mechanical, biological enzymatic digestion, and chemical detergent processes. The tertiary structure of DA was constituted with micro-, submicro-, and nanosized fibers, and the original strength of fresh aorta was retained. Inguinal hernia rabbit models were treated with TEMs or acellular meshes (AMs). After implantation, TEM-treated rabbit models showed no hernia recurrence, whereas AM-treated animals displayed bulges in inguinal area. At harvest, TEMs were thicker, have less adhesion, and have stronger mechanical strength compared to AMs (

Indexed as

Mesenchymal Stem Cell TransplantationWound HealingAnimalsAortaCell ProliferationCollagenDNAExtracellular MatrixHernia, InguinalHerniorrhaphyHumansL-Lactate DehydrogenaseMaleMaterials TestingMesenchymal Stem CellsNanoparticlesCollagenDNAL-Lactate Dehydrogenasedecellularized aortahernioplastyinguinal herniananobiomaterialtissue engineering

Identifiers

PMID28260890
PMCPMC5327914

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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.