Evidence map›Paper›PMID 24564863›Full record

ReviewStem cell research & therapy2013

Innovations in preclinical biology: ex vivo engineering of a human kidney tissue microperfusion system.

Edward J Kelly, Zhican Wang, Jenna L Voellinger, Cathy K Yeung, Danny D Shen, Kenneth E Thummel, Ying Zheng, Giovanni Ligresti, David L Eaton, Kimberly A Muczynski and 7 more

Open access · goldAbstract readReview
In one paragraph

Review in Stem cell research & therapy, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
2.5field-weighted citation impact, top 11% 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

19 citing papers in PubMed, 35 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Article
  6. Tissue Chips in Space-Challenges and Opportunities.Clinical and translational science · 2020
    Article
  7. Article
  8. Review
  9. Review
  10. Review
  11. Inhibition ofJournal of the American Society of Nephrology : JASN · 2017
    Article
  12. Article
  13. Review
  14. Abundance of Drug Transporters in the Human Kidney Cortex as Quantified by Quantitative Targeted Proteomics.Drug metabolism and disposition: the biological fate of chemicals · 2016
    Article
  15. Review
  16. Article
  17. Review
  18. A Quantitative Approach to Screen for Nephrotoxic Compounds In Vitro.Journal of the American Society of Nephrology : JASN · 2016
    Article
  19. Tissue-engineered microenvironment systems for modeling human vasculature.Experimental biology and medicine (Maywood, N.J.) · 2014
    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

17 authors at 3 institutions in 1 country.

Edward J Kelly
Zhican Wang
Jenna L Voellinger
Cathy K Yeung
Danny D Shen
Kenneth E Thummel
Ying Zheng
Giovanni Ligresti
David L Eaton
Kimberly A Muczynski
Jeremy S Duffield
Thomas Neumann
Anna Tourovskaia
Mark Fauver
Greg Kramer
Elizabeth Asp
Jonathan Himmelfarb
University of Washington · USNortis (United States) · USSeattle University · US

Funding

XENOBIOTIC BIOTRANSFORMATION AND DISPOSITIONP30ES007033 · NIEHS · UNIVERSITY OF WASHINGTON · PI Sheela Sathyanarayana · 1995 to 2026
$42.5M
Vector and Transgenic Mouse CoreP30DK017047 · NIDDK · UNIVERSITY OF WASHINGTON · PI Karin E Bornfeldt · 1986 to 2026
$41.4M
Pharmacological Sciences SupplementT32GM007750 · NIGMS · UNIVERSITY OF WASHINGTON · PI ATKINS, WILLIAM M · 1985 to 2023
$12.6M
Institute of Translational Health SciencesKL2TR000421 · NCATS · UNIVERSITY OF WASHINGTON · PI DISIS, MARY L. · 2012 to 2016
$12.6M
Using iPSCs to model patient outcomes in nephrotic syndromeUH3TR000504 · NCATS · UNIVERSITY OF WASHINGTON · PI HIMMELFARB, JONATHAN · 2014 to 2016
$6.1M
A Tissue Engineered Human Kidney Microphysiological SystemUH2TR000504 · NCATS · UNIVERSITY OF WASHINGTON · PI HIMMELFARB, JONATHAN · 2012 to 2013
$2.1M
NCATS NIH HHS 1UH2TR000504NCATS NIH HHS KL2 TR000421NCATS NIH HHS UH2 TR000504NCATS NIH HHS UH3 TR000504NIDDK NIH HHS P30 DK017047NIEHS NIH HHS ES007033NIGMS NIH HHS T32 GM007750
6 · The paper itself

Abstract

Kidney disease is a public health problem that affects more than 20 million people in the US adult population, yet little is understood about the impact of kidney disease on drug disposition. Consequently there is a critical need to be able to model the human kidney and other organ systems, to improve our understanding of drug efficacy, safety, and toxicity, especially during drug development. The kidneys in general, and the proximal tubule specifically, play a central role in the elimination of xenobiotics. With recent advances in molecular investigation, considerable information has been gathered regarding the substrate profiles of the individual transporters expressed in the proximal tubule. However, we have little knowledge of how these transporters coupled with intracellular enzymes and influenced by metabolic pathways form an efficient secretory and reabsorptive mechanism in the renal tubule. Proximal tubular secretion and reabsorption of xenobiotics is critically dependent on interactions with peritubular capillaries and the interstitium. We plan to robustly model the human kidney tubule interstitium, utilizing an ex vivo three-dimensional modular microphysiological system with human kidney-derived cells. The microphysiological system should accurately reflect human physiology, be usable to predict renal handling of xenobiotics, and should assess mechanisms of kidney injury, and the biological response to injury, from endogenous and exogenous intoxicants.

Indexed as

Cell Culture TechniquesCell SurvivalEndothelial CellsEpithelial CellsHumansKidney TubulesMicrofluidic Analytical TechniquesPericytesXenobioticsXenobiotics

Identifiers

PMID24564863
PMCPMC4029535
OpenAlexW2103047489

What OpenQuestion 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 OpenQuestion graph.