Evidence map›Paper›PMID 30793851›Full record

ArticleJournal of tissue engineering and regenerative medicine2019

Scaffolding kidney organoids on silk.

Ashwani Kumar Gupta, Jeannine M Coburn, Jessica Davis-Knowlton, Erica Kimmerling, David L Kaplan, Leif Oxburgh

Open access · greenAbstract read
In one paragraph

Article in Journal of tissue engineering and regenerative medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.7field-weighted citation impact, top 9% 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

27 citing papers in PubMed, 48 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
  4. A review of 3D bioprinting for organoids.Medical review (2021) · 2025
    Review
  5. Article
  6. Review
  7. Review
  8. Engineered organoids for biomedical applications.Advanced drug delivery reviews · 2023
    Review
  9. Review
  10. Review
  11. Review
  12. Review
  13. Article
  14. Stem cells for organoids.Smart medicine · 2022
    Review
  15. Review
  16. Review
  17. Next-generation cancer organoids.Nature materials · 2022
    Review
  18. Review
  19. Review
  20. 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

6 authors at 3 institutions in 1 country.

Ashwani Kumar GuptaCenter for Molecular Medicine, Maine Medical Center Research Institute, Scarborough, Maine.
Jeannine M CoburnBiomedical Engineering, Worcester Polytechnic Institute.
Jessica Davis-KnowltonCenter for Molecular Medicine, Maine Medical Center Research Institute, Scarborough, Maine.
Erica KimmerlingDepartment of Biomedical Engineering, Tufts University School of Engineering, Medford, Massachusetts.
David L KaplanDepartment of Biomedical Engineering, Tufts University School of Engineering, Medford, Massachusetts.ORCID 0000-0002-9245-7774
Leif OxburghCenter for Molecular Medicine, Maine Medical Center Research Institute, Scarborough, Maine.ORCID 0000-0002-2825-7663
Tufts University · USMaine Medical Center Research Institute · USWorcester Polytechnic Institute · US

Funding

Understanding Factors Influencing COVID-19 Testing and Vaccination in Immigrant Low-income and Homeless Populations and Testing Targeted InterventionsU54GM115516 · NIGMS · MAINEHEALTH · PI Kimberly Luebbers · 2017 to 2026
$51.6M
Translational Bioreactors - Engineering Complex TissuesP41EB002520 · NIBIB · TUFTS UNIVERSITY MEDFORD · PI KAPLAN, DAVID L. · 2004 to 2018
$16.7M
Engineering erythropoietin-producing cellsR24DK106743 · NIDDK · ROGOSIN INSTITUTE · PI CARROLL, THOMAS JOSEPH, CLEAVER, ONDINE B · 2015 to 2019
$7.0M
Three-dimensional Human Kidney Tissue System for Studying Renal DiseasesF32DK098877 · NIDDK · TUFTS UNIVERSITY MEDFORD · PI COBURN, JEANNINE · 2013 to 2015
$151k
NIBIB NIH HHS P41 EB002520NIDDK NIH HHS F32 DK098877NIDDK NIH HHS R24 DK106743NIGMS NIH HHS U54 GM115516
6 · The paper itself

Abstract

End stage kidney disease affects hundreds of thousands of patients in the United States. The therapy of choice is kidney replacement, but availability of organs is limited, and alternative sources of tissue are needed. Generation of new kidney tissue in the laboratory has been made possible through pluripotent cell reprogramming and directed differentiation. In current procedures, aggregates of cells known as organoids are grown either submerged or at the air-liquid interface. These studies have demonstrated that kidney tissue can be generated from pluripotent stem cells, but they also identify limitations. The first is that perfusion of cell aggregates is limited, restricting the size to which they can be grown. The second is that aggregates lack the structural integrity required for convenient engraftment and suturing or adhesion to regions of kidney injury. In this study, we evaluated the capacity of silk to serve as a support for the growth and differentiation of kidney tissue from primary cells and from human induced pluripotent stem cells. We find that cells can differentiate to epithelia characteristic of the developing kidney on this material and that these structures are maintained following engraftment under the capsule of the adult kidney. Blood vessel investment can be promoted by the addition of vascular endothelial growth factor to the scaffold, but the proliferation of stromal cells within the graft presents a challenge, which will require some readjustment of cell growth and differentiation conditions. In summary, we find that silk can be used to support growth of stem cell derived kidney tissue.

Indexed as

Induced Pluripotent Stem CellsKidneyOrganoidsAnimalsCell LineFibroinsHumansMiceTissue ScaffoldsFibroinsdirected differentiationengraftmentfibroin

Identifiers

PMID30793851
PMCPMC6529243
OpenAlexW2916378491

What OpenQuestion holds

Textmetadata
LicenceTDM
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.