ArticleBiomaterials2018
A systems mechanobiology model to predict cardiac reprogramming outcomes on different biomaterials.
Article in Biomaterials, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 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
8 citing papers in PubMed.
- Review
- Harnessing cell reprogramming for cardiac biological pacing.Journal of biomedical science · 2023Review
- Reduction of Intracellular Tension and Cell Adhesion Promotes Open Chromatin Structure and Enhances Cell Reprogramming.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Biomaterial-induced conversion of quiescent cardiomyocytes into pacemaker cells in rats.Nature biomedical engineering · 2022Article
- Extracellular matrix-based biomaterials for cardiac regeneration and repair.Heart failure reviews · 2021Review
- Stromal cell identity modulates vascular morphogenesis in a microvasculature-on-a-chip platform.Lab on a chip · 2021Article
- Review
- Biomaterials and Advanced Biofabrication Techniques in hiPSCs Based Neuromyopathic Disease Modeling.Frontiers in bioengineering and biotechnology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
During normal development, the extracellular matrix (ECM) regulates cell fate mechanically and biochemically. However, the ECM's influence on lineage reprogramming, a process by which a cell's developmental cycle is reversed to attain a progenitor-like cell state followed by subsequent differentiation into a desired cell phenotype, is unknown. Using a material mimetic of the ECM, here we show that ligand identity, ligand density, and substrate modulus modulate indirect cardiac reprogramming efficiency, but were not individually correlated with phenotypic outcomes in a predictive manner. Alternatively, we developed a data-driven model using partial least squares regression to relate short-term cell states, defined by quantitative mechanosensitive responses to different material environments, with long-term changes in phenotype. This model was validated by accurately predicting the reprogramming outcomes on a different material platform. Collectively, these findings suggest a means to rapidly screen candidate biomaterials that support reprogramming with high efficiency, without subjecting cells to the entire reprogramming process.
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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.