Evidence map›Paper›PMID 22654992›Full record

ArticleSystems and synthetic biology2011

Extracellular matrix bioengineering and systems biology approaches in liver disease.

Natalia Nieto, Matthias P Lutolf

Open access · bronzeAbstract read
In one paragraph

Article in Systems and synthetic biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.6field-weighted citation impact, top 32% 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

5 citing papers in PubMed, 11 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Engineering liver.Hepatology (Baltimore, Md.) · 2014
    Review
  5. 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

2 authors at 2 institutions in 2 countries.

Natalia Nieto
Matthias P Lutolf
École Polytechnique Fédérale de Lausanne · CHIcahn School of Medicine at Mount Sinai · US

Funding

Project 2P20AA017067 · NIAAA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI FRIEDMAN, SCOTT L. · 2008 to 2012
$2.5M
ASS, NOS2, AND ALCOHOLIC LIVER DISEASER01AA017733 · NIAAA · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI NIETO, NATALIA · 2008 to 2012
$2.0M
Communication between Kupffer cells and stellate cellsR01DK069286 · NIDDK · MOUNT SINAI SCHOOL OF MEDICINE OF NYU · PI NIETO, NATALIA · 2005 to 2009
$1.2M
NIAAA NIH HHS P20 AA017067NIAAA NIH HHS R01 AA017733NIDDK NIH HHS R01 DK069286
6 · The paper itself

Abstract

The extracellular matrix (ECM) in the liver as well as in many organs comprises a peripheral network linking numerous macromolecules typically classified into collagens, microfibrillar proteins, proteoglycans, chemokines, growth factors and glycoproteins. In addition to its role as an essential structural and physiological component, it plays a vital role in driving key cellular events such as cell adhesion, migration, proliferation, differentiation and survival. Any structural inherited or acquired defect and/or metabolic or pathologic alteration in the hepatic ECM may cause cellular and organ responses leading to the development or progression of liver disease. Therefore, the ECM molecules are key players in tissue engraftment and in the pathophysiology of liver disease. In this review we provide a snapshot on current efforts for understanding its role in physiological and non-physiological states, by describing how tissue engineering platforms can enhance in vitro and in vivo models of liver disease, by providing examples where bioengineered ECM can serve as systems biology approaches to study the ECM, and then by evaluating pathological protein regulatory networks in the liver using systems biology tools. These approaches hold great promise for future research.

Indexed as

Collagen-INetworksScaffolds

Identifiers

PMID22654992
PMCPMC3159691
OpenAlexW1983197276

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.