Evidence map›Paper›PMID 34838308›Full record

ReviewJournal of pediatric surgery2022

Building human renal tracts.

Adrian S Woolf

Open access · hybridAbstract readReview
In one paragraph

Review in Journal of pediatric surgery, 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
–field-weighted citation impact, top 90% 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

1 author at 1 institution in 1 country.

Adrian S WoolfDivision of Cell Matrix Biology and Regenerative Medicine, School of Biological Sciences, Michael Smith Building, Faculty of Biology Medicine and Health, University of Manchester, Oxford Road, Manchester, Northern Ireland M13 9PT, United Kingdom; Royal Manchester Children's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Center, Manchester, Northern Ireland, United Kingdom. Electronic address: adrian.woolf@manchester.ac.uk.
Manchester Academic Health Science Centre · GB

Funding

Medical Research Council MR/T016809/1
6 · The paper itself

Abstract

Severe kidney failure affects several million people worldwide. Among these are children born with abnormal renal tracts, and some carry mutations of genes active in renal tract development. Kidney transplants are in short supply, and long term dialysis does not obviate uraemia and its associated harmful effects. It has been envisaged that a combination of stem cell technology, developmental biology, and genetics will revolutionise our understanding of kidney disease and provide novel therapies for kidney failure. Here, we review progress towards making functional kidney tissues from human pluripotent stem cells. Organoids rich in immature glomeruli and tubules can be created in culture from pluripotent stem cells. Moreover, differentiation can be increased by implanting these cells into immunodeficient mice. Challenges remain to be overcome, however, before these tissues can be used for regenerative medicine therapies. Current limitations include the small size of an organoid, the lack of large blood vessels feeding it, and the lack of a urinary tract to plumb the kidney organoid. Pluripotent stem cell technology is also being used to create 'diseases in a dish' to understand the pathobiology underlying human renal tract malformations.

Indexed as

Kidney DiseasesPluripotent Stem CellsAnimalsCell DifferentiationHumansKidneyMiceOrganoidsCollecting ductImplantNephronPluripotent stem cellUreter

Identifiers

PMID34838308
PMCPMC8837266
OpenAlexW3208307879

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.