Evidence map›Paper›PMID 34582017›Full record

ArticleAdvances in experimental medicine and biology2021

The Renal Extracellular Matrix as a Supportive Scaffold for Kidney Tissue Engineering: Progress and Future Considerations.

Shabnam Sabetkish, Abdol-Mohammad Kajbafzadeh

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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. 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, top 71% of its field
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

0 citing papers in PubMed, 0 citations in OpenAlex.

No citing paper in PubMed yet.

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

2 authors at 1 institution in 1 country.

Shabnam SabetkishPediatric Urology and Regenerative Medicine Research Center, Section of Tissue Engineering and Stem Cells Therapy, Children's Medical Center, Pediatric Center of Excellence, Tehran University of Medical Sciences, No. 62, Dr. Gharib's Street, Keshavarz Boulevard, 1419433151, Tehran, Iran.
Abdol-Mohammad KajbafzadehPediatric Urology and Regenerative Medicine Research Center, Section of Tissue Engineering and Stem Cells Therapy, Children's Medical Center, Pediatric Center of Excellence, Tehran University of Medical Sciences, No. 62, Dr. Gharib's Street, Keshavarz Boulevard, 1419433151, Tehran, Iran. kajbafzd@sina.tums.ac.ir.
Tehran University of Medical Sciences · IR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the past decades, diverse methods have been used toward renal tissue engineering in order to replace renal function. The goals of all these techniques included the recapitulation of renal filtration, re-absorptive, and secretary functions, and replacement of endocrine/metabolic activities. It is also imperative to develop a reliable, up scalable, and timely manufacturing process. Decellularization of the kidney with intact ECM is crucial for in-vivo compatibility and targeted clinical application. Contemporarily there is an increasing interest and research in the field of regenerative medicine including stem cell therapy and tissue bioengineering in search for new and reproducible sources of kidneys. In this chapter, we sought to determine the most effective method of renal decellularization and recellularization with emphasis on biologic composition and support of stem cell growth. Current barriers and limitations of bioengineered strategies will be also discussed, and strategies to overcome these are suggested.

Indexed as

Tissue EngineeringTissue ScaffoldsExtracellular MatrixKidneyRegenerative MedicineDecellularizationKidney matricesRecellularizationRenal stem cellsScaffold

Identifiers

PMID34582017
OpenAlexW3203098220

What OpenQuestion holds

Textmetadata
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Registered trials

None linked

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.