Evidence map›Paper›PMID 31772214›Full record

ArticleScientific reports2019

Effective reconstruction of functional organotypic kidney spheroid for in vitro nephrotoxicity studies.

Hyun Mi Kang, Jung Hwa Lim, Kyung Hee Noh, Dongmin Park, Hyun-Soo Cho, Katalin Susztak, Cho-Rok Jung

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.0field-weighted citation impact, top 23% 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

18 citing papers in PubMed, 27 citations in OpenAlex.

  1. Beyond monolayers: a comparative analysis of 2D cell cultures and 3DFrontiers in bioengineering and biotechnology · 2026
    Review
  2. Review
  3. Article
  4. Review
  5. Article
  6. Kidney Disease Modeling with Organoids and Organs-on-Chips.Annual review of biomedical engineering · 2024
    Review
  7. Article
  8. Article
  9. Porcine Kidney Organoids Derived from Naïve-like Embryonic Stem Cells.International journal of molecular sciences · 2024
    Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Review
  15. Article
  16. Article
  17. Article
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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

7 authors at 2 institutions in 2 countries.

Hyun Mi KangLaboratory of Disease Modeling and Therapeutics, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea.
Jung Hwa LimLaboratory of Disease Modeling and Therapeutics, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea.
Kyung Hee NohLaboratory of Disease Modeling and Therapeutics, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea.
Dongmin ParkLaboratory of Disease Modeling and Therapeutics, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea.
Hyun-Soo ChoStem Cell Research Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea.
Katalin SusztakDivision of Nephrology, Department of Medicine, Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. ksusztak@pennmedicine.upenn.edu.ORCID http://orcid.org/0000-0002-1005-3726
Cho-Rok JungLaboratory of Disease Modeling and Therapeutics, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea. crjung@kribb.re.kr.
Korea Research Institute of Bioscience and Biotechnology · KRUniversity of Pennsylvania · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stable and reproducible kidney cellular models could accelerate our understanding of diseases, help therapeutics development, and improve nephrotoxicity screenings. Generation of a reproducible in vitro kidney models has been challenging owing to the cellular heterogeneity and structural complexity of the kidney. We generated mixed immortalized cell lines that stably maintained their characteristic expression of renal epithelial progenitor markers for the different lineages of kidney cellular compartments via the BMP7 signaling pathway from a mouse and a human whole kidney. These cells were used to generate functional and matured kidney spheroids containing multiple renal lineages, such as the proximal tubule, loop of Henle, distal tubules, and podocytes, using extracellular matrix and physiological force, named spheroid-forming unit (SFU). They expressed all apical and basolateral transporters that are important for drug metabolism and displayed key functional aspects of the proximal tubule, including protein endocytosis and increased gamma-glutamyltransferase activity, and cyclic AMP responded to external cues, such as parathyroid hormone. Following exposure, cells fluxed and took up drugs via proximal tubule-specific apical or basolateral transporters, and displayed increased cell death and expression of renal injury marker. Here, we developed a new differentiation method to generate kidney spheroids that structurally recapitulate important features of the kidney effectively and reproducibly using mixed immortalized renal cells, and showed their application for renal toxicity studies.

Indexed as

Spheroids, CellularAcyclovirAnimalsBiological TransportBiomarkersBone Morphogenetic Protein 7Carrier ProteinsCell Culture TechniquesCell LineageCell Line, TransformedCimetidineCisplatinCyclic AMPCyclosporineDigoxinDoxorubicinAcyclovirBiomarkersBMP7 protein, humanbmp7 protein, mouseBone Morphogenetic Protein 7Carrier ProteinsCimetidineCisplatinCyclic AMPCyclosporineDigoxinDoxorubicingamma-Glutamyltransferasegamma-glutamyltransferase, humanVerapamil

Identifiers

PMID31772214
PMCPMC6879515
OpenAlexW2989619306

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.