Volume 2 Issue 12, December 2018

Volume 2 Issue 12

Tissue-engineered heart ventricles

This issue highlights low-noise polymer-coated glucose sensors, endovascular stents for focal stimulation of the motor cortex, implantable pre-metastatic niches, tissue-engineered models of the human ventricle, self-repairing engineered skeletal muscle incorporating macrophages, and the modelling of mutation-related cardiomyopathies with engineered cardiac microtissues.

The cover illustrates a scale model of the human left ventricle made of nanofibrous scaffolds and human stem-cell-derived cardiomyocytes, for the study of contractile function and the modelling of arrhythmia induced by structural defects.

See MacQueen et al.

Image: Michael Rosnach. Cover Design: Alex Wing.


  • Editorial |

    Research on disease mechanisms will increasingly be supported by progressively more sophisticated engineered tissues serving as in vitro models of human disease.


News & Views

  • News & Views |

    Coating continuous glucose-monitoring sensors with zwitterionic polymer reduces early inflammatory responses and signal noise after sensor implantation in live animals, and improves the performance of the sensors without the need for additional recalibration.

    • Ershuai Zhang
    •  & Zhiqiang Cao
  • News & Views |

    Minimally invasive intravascular electrodes chronically implanted via the superior sagittal sinus can stimulate the motor cortex of sheep, and elicit muscular activity.

    • Robert S. Fisher
  • News & Views |

    A humanized biomaterial microenvironment that mimics the pre-metastatic niche captures disseminated tumour cells and recapitulates metastatic progression after implantation in xenografted mice.

    • Irina Matei
    • , Sham Rampersaud
    •  & David Lyden


  • News & Views |

    A tissue-engineered scale model of the human ventricle made of nanofibrous scaffolds and human-stem-cell-derived cardiomyocytes enables the modelling of arrhythmia.

    • Wolfram-Hubertus Zimmermann


  • News & Views |

    A machine-learning algorithm reliably predicts Cas9-edited genotypes arising from the repair of DNA double-strand breaks in mouse cells and human cells.

    • Sangsu Bae
    •  & Jin-Soo Kim


Amendments & Corrections