Evidence map›Paper›PMID 34582025›Full record

ArticleAdvances in experimental medicine and biology2021

Extracellular Matrix Scaffold Using Decellularized Cartilage for Hyaline Cartilage Regeneration.

Seyed Mostafa Monzavi, Abdol-Mohammad Kajbafzadeh, Shabnam Sabetkish, Alexander Seifalian

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Article in Advances in experimental medicine and biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

4 authors.

Seyed Mostafa MonzaviPediatric Urology and Regenerative Medicine Research Center, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran.
Abdol-Mohammad KajbafzadehPediatric Urology and Regenerative Medicine Research Center, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran.
Shabnam SabetkishPediatric Urology and Regenerative Medicine Research Center, Children's Medical Center, Tehran University of Medical Sciences, Tehran, Iran.
Alexander SeifalianNanotechnology and Regenerative Medicine Commercialization Centre (NanoRegMed Ltd.), The London BioScience Innovation Centre, London, UK. a.seifalian@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The repair of osteochondral defects is among the top ten medical needs of humans in the 21st centuries with many countries facing rapidly aging population involved with osteoarthritis as a major contributor to global disease burden. Tissue engineering methods have offered new windows of hope to treat such disorders and disabilities. Regenerative approaches to cartilage injuries require careful replication of the complex microenvironment of the native tissue. The decellularized hyaline cartilage derived from human allografts or xenografts is potentially an ideal scaffold, simulating the mechanical and biochemical properties, as well as biological microarchitecture of the hyaline cartilage. There have been many attempts to regenerate clinically viable hyaline cartilage tissue using decellularized cartilage-derived extracellular matrix with stem cell technology. This chapter describes the reproducible methods for hyaline cartilage decellularization and recellularization. In addition, quality control and characterization requirements of the product at each step, as well as the clinical applications of final product have been discussed.

Indexed as

Cartilage, ArticularHyaline CartilageAgedExtracellular MatrixHumansTissue EngineeringTissue ScaffoldsDecellularizationHyaline CartilageRecellularizationRegenerative MedicineTissue EngineeringTissue Scaffolds

Identifiers

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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.