Evidence map›Paper›PMID 30867877›Full record

ArticleBiomicrofluidics2019

A human proximal tubule-on-a-chip to study renal disease and toxicity.

Courtney M Sakolish, Brian Philip, Gretchen J Mahler

Abstract read
In one paragraph

Article in Biomicrofluidics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. An AOP-guidedNAM journal · 2026
    Article
  5. Review
  6. Review
  7. Review
  8. Review
  9. A Cell Pre-Wrapping Seeding Technique for Hydrogel-Based Tubular Organ-On-A-Chip.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  10. Article
  11. Review
  12. Article
  13. Article
  14. Review
  15. Article
  16. Organs-on-chip technology: a tool to tackle genetic kidney diseases.Pediatric nephrology (Berlin, Germany) · 2022
    Review
  17. Article
  18. Review
  19. Article
  20. Toward Human Models of Cardiorenal SyndromeFrontiers in cardiovascular medicine · 2022
    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

3 authors.

Courtney M Sakolish
Brian PhilipDepartment of Biomedical Engineering, Binghamton University, Binghamton, New York 13902, USA.
Gretchen J MahlerDepartment of Biomedical Engineering, Binghamton University, Binghamton, New York 13902, USA.ORCID 0000-0002-7286-8920

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Renal disease is a global problem with unsustainable health-care costs. There currently exists a lack of accurate human renal disease models that take into account the complex microenvironment of these tissues. Here, we present a reusable microfluidic model of the human proximal tubule and glomerulus, which allows for the growth of renal epithelial cells in a variety of conditions that are representative of renal disease states including altered glomerular filtration rate, hyperglycemia, nephrolithiasis, and drug-induced nephrotoxicity (cisplatin and cyclosporine). Cells were exposed to these conditions under fluid flow or in traditional static cultures to determine the effects of a dynamic microenvironment on the pathogenesis of these renal disease states. The results indicate varying stress-related responses (α-smooth muscle actin (α-SMA) expression, alkaline phosphatase activity, fibronectin, and neutrophil gelatinase-associated lipocalin secretion) to each of these conditions when comparing cells that had been grown in static and dynamic conditions, potentially indicating more realistic and sensitive predictions of human responses and a requirement for a more complex "fit for purpose" model.

Identifiers

PMID30867877
PMCPMC6404920

What OpenQuestion holds

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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.