Evidence mapPaperPMID 41214197Full record

ReviewNature reviews. Nephrology2026

Advances and continuing challenges in differentiation of stem cells to human kidney tissue.

Melissa H Little, Sean B Wilson

Abstract readReview
PubMed Publisher
In one paragraph

Review in Nature reviews. Nephrology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

2 authors.

Melissa H LittleNovo Nordisk Foundation Centre for Stem Cell Medicine, Murdoch Children's Research Institute, Melbourne, Victoria, Australia. melissa.little@mcri.edu.au.ORCID http://orcid.org/0000-0003-0380-2263
Sean B WilsonNovo Nordisk Foundation Centre for Stem Cell Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.ORCID http://orcid.org/0000-0002-8994-0781

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The capacity to generate a human model of the kidney via the directed differentiation of human pluripotent stem cells is a remarkable advance. Such three-dimensional multicellular tissues can accurately recapitulate certain kidney disease phenotypes in vitro, enabling the development of novel therapies for inherited kidney disease. These models also suggest the future possibility of engineering kidney tissue for kidney replacement therapy. Here, we focus on the latest advances in the field, including protocols for generating ureteric organoids and their combination with nephron-forming organoids to create integrated assembloid models, as well as examining the challenges in the application of these protocols. Although current protocols are modelled on differentiation in vivo, gaps in this knowledge remain, as well as challenges in recapitulating such complex events in vitro. The scale and complexity of the transcriptional analyses required to evaluate these models can also prove difficult to interpret. The genuine application of stem-cell-derived kidney tissue will require a deep understanding of what cells should not be present, what cell types are missing, how to increase the level of maturity of the component cells and whether organoids can reach a degree of maturation that can replicate postnatal kidney disease. Finally, the development of cellular therapies will require quality-controlled protocols to ensure both safety and efficacy.

Indexed as

Cell DifferentiationKidneyKidney DiseasesPluripotent Stem CellsTissue EngineeringHumansOrganoids

Identifiers

What Socratic holds

Textmetadata
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 Socratic graph.