Evidence map›Paper›PMID 24668880›Full record

ReviewHepatology (Baltimore, Md.)2014

Engineering liver.

Linda G Griffith, Alan Wells, Donna B Stolz

Abstract readReview
In one paragraph

Review in Hepatology (Baltimore, Md.), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Liver 'organ on a chip'.Experimental cell research · 2018
    Review
  13. Microphysiological Systems to Assess Nonclinical Toxicity.Current protocols in toxicology · 2017
    Article
  14. Review
  15. Article
  16. Liver metastases: Microenvironments and ex-vivo models.Experimental biology and medicine (Maywood, N.J.) · 2016
    Review
  17. Article
  18. Article
  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

3 authors.

Linda G GriffithDepartment of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA.
Alan Wells
Donna B Stolz

Funding

Systems Biology of Cell Decision ProcessesP50GM068762 · NIGMS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI YAFFE, MICHAEL B · 2003 to 2012
$32.3M
TOXICOLOGY CORE UNITP30ES002109 · NIEHS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI LEVINE, STUART S · 1985 to 2020
$25.6M
Perfused 3D Tissue Surrogates for Complex Cell-Cell Communication SystemsR01EB010246 · NIBIB · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GRIFFITH, LINDA G · 2009 to 2013
$3.3M
Bioengineering partnership to improve chemical hazard testing paradigmsR01ES015241 · NIEHS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI RUSYN, IVAN · 2008 to 2012
$3.1M
All-Human Microphysical Model of Metastasis TherapyUH2TR000496 · NCATS · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI GRIFFITH, LINDA G · 2012 to 2013
$2.3M
NCATS NIH HHS UH2 TR000496NCATS NIH HHS UH2TR000496NIBIB NIH HHS R01 EB010246NIBIB NIH HHS R01-EB 010246NIEHS NIH HHS P30 ES002109NIEHS NIH HHS P30-ES002109NIEHS NIH HHS R01 ES015241NIEHS NIH HHS R01-ES015241NIGMS NIH HHS P50 GM068762
6 · The paper itself

Abstract

Interest in "engineering liver" arises from multiple communities: therapeutic replacement; mechanistic models of human processes; and drug safety and efficacy studies. An explosion of micro- and nanofabrication, biomaterials, microfluidic, and other technologies potentially affords unprecedented opportunity to create microphysiological models of the human liver, but engineering design principles for how to deploy these tools effectively toward specific applications, including how to define the essential constraints of any given application (available sources of cells, acceptable cost, and user-friendliness), are still emerging. Arguably less appreciated is the parallel growth in computational systems biology approaches toward these same problems-particularly in parsing complex disease processes from clinical material, building models of response networks, and in how to interpret the growing compendium of data on drug efficacy and toxicology in patient populations. Here, we provide insight into how the complementary paths of engineering liver-experimental and computational-are beginning to interplay toward greater illumination of human disease states and technologies for drug development.

Indexed as

AnimalsBioengineeringComputer SimulationDisease Models, AnimalHumansLiverLiver DiseasesSystems Biology

Identifiers

PMID24668880
PMCPMC4176555

What OpenQuestion holds

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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.