ReviewTrends in biotechnology2012
Imaging cardiac extracellular matrices: a blueprint for regeneration.
Review in Trends in biotechnology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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.
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.
Who cites it
14 citing papers in PubMed.
- Integrating Bioprinting and Increased Throughput: Next-Generation Models for Cardiac Research.International journal of molecular sciences · 2025Review
- Harnessing native blueprints for designing bioinks to bioprint functional cardiac tissue.iScience · 2025Review
- Biomimetic Approaches in Cardiac Tissue Engineering: Replicating the Native Heart Microenvironment.Cureus · 2023Review
- Laminin 411 mediates endothelial specification via multiple signaling axes that converge on β-catenin.Stem cell reports · 2022Article
- Machine intelligence for nerve conduit design and production.Journal of biological engineering · 2020Review
- Engineering hiPSC cardiomyocyte in vitro model systems for functional and structural assessment.Progress in biophysics and molecular biology · 2019Review
- Engineering Tissue Fabrication With Machine Intelligence: Generating a Blueprint for Regeneration.Frontiers in bioengineering and biotechnology · 2019Review
- 3D bioprinting for cardiovascular regeneration and pharmacology.Advanced drug delivery reviews · 2018Review
- Solid organ fabrication: comparison of decellularization to 3D bioprinting.Biomaterials research · 2016Review
- Porous, Ventricular Extracellular Matrix-Derived Foams as a Platform for Cardiac Cell Culture.BioResearch open access · 2015Article
- Decellularized scaffolds as a platform for bioengineered organs.Current opinion in organ transplantation · 2014Review
- Single-cell analysis of embryoid body heterogeneity using microfluidic trapping array.Biomedical microdevices · 2014Article
- ECM-incorporated hydrogels cross-linked via native chemical ligation to engineer stem cell microenvironments.Biomacromolecules · 2013Article
- Spatial and temporal analysis of extracellular matrix proteins in the developing murine heart: a blueprint for regeneration.Tissue engineering. Part A · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Once damaged, cardiac tissue does not readily repair and is therefore a primary target of regenerative therapies. One regenerative approach is the development of scaffolds that functionally mimic the cardiac extracellular matrix (ECM) to deliver stem cells or cardiac precursor populations to the heart. Technological advances in micro/nanotechnology, stem cell biology, biomaterials and tissue decellularization have propelled this promising approach forward. Surprisingly, technological advances in optical imaging methods have not been fully utilized in the field of cardiac regeneration. Here, we describe and provide examples to demonstrate how advanced imaging techniques could revolutionize how ECM-mimicking cardiac tissues are informed and evaluated.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.