Evidence map›Paper›PMID 30201502›Full record

ReviewBiomaterials2019

Biomimetic cardiovascular platforms for in vitro disease modeling and therapeutic validation.

Roberto Portillo-Lara, Andrew R Spencer, Brian W Walker, Ehsan Shirzaei Sani, Nasim Annabi

Abstract readReview
In one paragraph

Review in Biomaterials, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. High throughput screening system for engineered cardiac tissues.Frontiers in bioengineering and biotechnology · 2023
    Article
  6. Dynamic and static biomechanical traits of cardiac fibrosis.Frontiers in bioengineering and biotechnology · 2022
    Review
  7. Review
  8. Article
  9. Article
  10. Rebuilding the Vascular Network:Frontiers in cell and developmental biology · 2021
    Review
  11. hiPSC-Derived Cardiac Tissue for Disease Modeling and Drug Discovery.International journal of molecular sciences · 2020
    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

5 authors.

Roberto Portillo-LaraDepartment of Chemical Engineering, Northeastern University, Boston, USA; Tecnologico de Monterrey, Escuela de Ingeniería y Ciencias, Zapopan, JAL, Mexico.
Andrew R SpencerDepartment of Chemical Engineering, Northeastern University, Boston, USA.
Brian W WalkerDepartment of Chemical and Biomolecular Engineering, University of California- Los Angeles, Los Angeles, CA 90095, USA.
Ehsan Shirzaei SaniDepartment of Chemical and Biomolecular Engineering, University of California- Los Angeles, Los Angeles, CA 90095, USA.
Nasim AnnabiDepartment of Chemical and Biomolecular Engineering, University of California- Los Angeles, Los Angeles, CA 90095, USA; Center for Minimally Invasive Therapeutics (C-MIT), University of California-Los Angeles, Los Angeles, CA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA. Electronic address: nannabi@ucla.edu.

Funding

Engineering highly elastic surgical sealants with hemostatic propertiesR01HL140618 · NHLBI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ANNABI, NASIM, KHADEMHOSSEINI, ALI · 2018 to 2021
$2.8M
Engineering a naturally derived and highly adhesive surgical sealantR01EB023052 · NIBIB · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI ANNABI, NASIM, KHADEMHOSSEINI, ALI · 2017 to 2022
$2.4M
American Heart Association-American Stroke Association 16SDG31280010NHLBI NIH HHS R01 HL140618NIBIB NIH HHS R01 EB023052
6 · The paper itself

Abstract

Bioengineered tissues have become increasingly more sophisticated owing to recent advancements in the fields of biomaterials, microfabrication, microfluidics, genetic engineering, and stem cell and developmental biology. In the coming years, the ability to engineer artificial constructs that accurately mimic the compositional, architectural, and functional properties of human tissues, will profoundly impact the therapeutic and diagnostic aspects of the healthcare industry. In this regard, bioengineered cardiac tissues are of particular importance due to the extremely limited ability of the myocardium to self-regenerate, as well as the remarkably high mortality associated with cardiovascular diseases worldwide. As novel microphysiological systems make the transition from bench to bedside, their implementation in high throughput drug screening, personalized diagnostics, disease modeling, and targeted therapy validation will bring forth a paradigm shift in the clinical management of cardiovascular diseases. Here, we will review the current state of the art in experimental in vitro platforms for next generation diagnostics and therapy validation. We will describe recent advancements in the development of smart biomaterials, biofabrication techniques, and stem cell engineering, aimed at recapitulating cardiovascular function at the tissue- and organ levels. In addition, integrative and multidisciplinary approaches to engineer biomimetic cardiovascular constructs with unprecedented human and clinical relevance will be discussed. We will comment on the implementation of these platforms in high throughput drug screening, in vitro disease modeling and therapy validation. Lastly, future perspectives will be provided on how these biomimetic platforms will aid in the transition towards patient centered diagnostics, and the development of personalized targeted therapeutics.

Indexed as

AnimalsBiocompatible MaterialsBioengineeringBiomimeticsCardiovascular DiseasesDrug DiscoveryDrug Evaluation, PreclinicalEquipment DesignHumansLab-On-A-Chip DevicesBiocompatible Materials

Identifiers

PMID30201502
PMCPMC11044891

What OpenQuestion holds

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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.