Evidence map›Paper›PMID 40266846›Full record

ArticleSTAR protocols2025

Protocol to develop a proximal tubule-on-chip model based on hiPSC-derived kidney organoids for functional analysis of renal transporters.

Cheng Ma, Ramin Banan Sadeghian, Ryosuke Negoro, Kazuya Fujimoto, Toshikazu Araoka, Naoki Ishiguro, Minoru Takasato, Ryuji Yokokawa

Abstract read
In one paragraph

Article in STAR protocols, 2025. 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. Review
  2. Review
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

8 authors.

Cheng MaDepartment of Micro Engineering, Kyoto University, Kyoto 615-8540, Japan. Electronic address: ma.cheng.5z@kyoto-u.ac.jp.
Ramin Banan SadeghianDepartment of Micro Engineering, Kyoto University, Kyoto 615-8540, Japan.
Ryosuke NegoroLaboratory of Molecular Pharmacokinetics, College of Pharmaceutical Sciences, Ritsumeikan University, Kusatsu 525-8577, Japan.
Kazuya FujimotoDepartment of Micro Engineering, Kyoto University, Kyoto 615-8540, Japan.
Toshikazu AraokaCenter for iPS Cell Research and Application (CiRA), Kyoto University, Kyoto 606-8507, Japan.
Naoki IshiguroPharmacokinetics and Non-Clinical Safety Department, Nippon Boehringer Ingelheim Co. Ltd., Kobe, Japan.
Minoru TakasatoRIKEN Center for Biosystems Dynamics Research (BDR), Kobe 650-0047, Japan; Graduate School of Medicine, Osaka University, Suita 565-0871, Japan; Graduate School of Biostudies, Kyoto University, Kyoto 606-8501, Japan.
Ryuji YokokawaDepartment of Micro Engineering, Kyoto University, Kyoto 615-8540, Japan. Electronic address: yokokawa.ryuji.8c@kyoto-u.ac.jp.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Here, we present a protocol for describing the generation of a proximal tubule-on-chip model using human induced pluripotent stem cell (hiPSC)-derived kidney organoids for renal transporter analysis. We describe steps for hiPSC differentiation into kidney organoids, proximal tubule cell isolation, and microfluidic chip seeding. The hiPSC-derived model enhances transporter expression and polarization, with improved uptake and efflux functions compared to conventional immortalized cell-based models. This protocol serves as a platform to assess renal transporter function, nephrotoxicity, and drug-drug interactions. For complete details on the use and execution of this protocol, please refer to Ma et al.

Indexed as

Induced Pluripotent Stem CellsKidney Tubules, ProximalLab-On-A-Chip DevicesOrganoidsCell DifferentiationHumansModels, BiologicalBiotechnology and bioengineeringStem CellsTissue Engineering

Identifiers

PMID40266846
PMCPMC12225029

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.