Evidence map›Paper›PMID 29802256›Full record

ArticleNature communications2018

Fibrotic microtissue array to predict anti-fibrosis drug efficacy.

Mohammadnabi Asmani, Sanjana Velumani, Yan Li, Nicole Wawrzyniak, Isaac Hsia, Zhaowei Chen, Boris Hinz, Ruogang Zhao

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 76 papers.

0numbers the graph read from it
0cells of the map it votes in
76citing papers in PubMed
7.3field-weighted citation impact, top 2% 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

76 citing papers in PubMed, 139 citations in OpenAlex.

  1. A practical toolbox for modelling fibrosis in vitro.Nature biomedical engineering · 2026
    Review
  2. Article
  3. Article
  4. Review
  5. Physiomimetic culture bias durotaxis toward soft environments.bioRxiv : the preprint server for biology · 2026
    Article
  6. Article
  7. Tools of the trade: leveraging 3DFrontiers in pharmacology · 2026
    Review
  8. Review
  9. Article
  10. Article
  11. Review
  12. Article
  13. Suspended Tissue Open Microfluidic Patterning (STOMP).Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  14. Review
  15. Suspended Tissue Open Microfluidic Patterning (STOMP).bioRxiv : the preprint server for biology · 2025
    Article
  16. Review
  17. Article
  18. Review
  19. Article
  20. Review

16 more citing papers are in PubMed but not listed here.

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 at 2 institutions in 2 countries.

Mohammadnabi AsmaniDepartment of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.ORCID http://orcid.org/0000-0003-0570-6208
Sanjana VelumaniDepartment of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.ORCID http://orcid.org/0000-0002-4577-2472
Yan LiDepartment of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.
Nicole WawrzyniakDepartment of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.ORCID http://orcid.org/0000-0001-6514-4791
Isaac HsiaDepartment of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.ORCID http://orcid.org/0000-0002-1996-5043
Zhaowei ChenDepartment of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA.
Boris HinzLaboratory of Tissue Repair and Regeneration, Matrix Dynamics Group, Faculty of Dentistry, University of Toronto, Toronto, ON, M5S 3E2, Canada.ORCID http://orcid.org/0000-0002-0526-393X
Ruogang ZhaoDepartment of Biomedical Engineering, University at Buffalo, The State University of New York, Buffalo, NY, 14260, USA. rgzhao@buffalo.edu.ORCID http://orcid.org/0000-0002-5351-0843
University at Buffalo, State University of New York · USUniversity of Toronto · CA

Funding

Fibrotic microtissue chips for screening of anti-fibrotic therapiesR01EB019411 · NIBIB · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI ZHAO, RUOGANG · 2015 to 2018
$1.4M
NIBIB NIH HHS R01 EB019411
6 · The paper itself

Abstract

Fibrosis is a severe health problem characterized by progressive stiffening of tissues which causes organ malfunction and failure. A major bottleneck in developing new anti-fibrosis therapies is the lack of in vitro models that recapitulate dynamic changes in tissue mechanics during fibrogenesis. Here we create membranous human lung microtissues to model key biomechanical events occurred during lung fibrogenesis including progressive stiffening and contraction of alveolar tissue, decline in alveolar tissue compliance and traction force-induced bronchial dilation. With these capabilities, we provide proof of principle for using this fibrotic tissue array for multi-parameter, phenotypic analysis of the therapeutic efficacy of two anti-fibrosis drugs recently approved by the FDA. Preventative treatments with Pirfenidone and Nintedanib reduce tissue contractility and prevent tissue stiffening and decline in tissue compliance. In a therapeutic treatment regimen, both drugs restore tissue compliance. These results highlight the pathophysiologically relevant modeling capability of our novel fibrotic microtissue system.

Indexed as

Anti-Inflammatory Agents, Non-SteroidalCells, CulturedDrug Evaluation, PreclinicalFibroblastsFibrosisHumansIndolesLungLung CompliancePrimary Cell CulturePulmonary FibrosisPyridonesTissue Culture TechniquesTissue ScaffoldsTreatment OutcomeAnti-Inflammatory Agents, Non-SteroidalIndolesnintedanibpirfenidonePyridones

Identifiers

PMID29802256
PMCPMC5970268
OpenAlexW2804064570

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.