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Biological pacemaker: from biological experiments to computational simulation

  • Yacong Li
  • , Kuanquan Wang
  • , Qince Li
  • , Henggui Zhang*
  • *Corresponding author for this work
  • School of Computer Science and Technology, Harbin Institute of Technology
  • Peng Cheng Laboratory
  • University of Manchester

Research output: Contribution to journalReview articlepeer-review

Abstract

Pacemaking dysfunction has become a significant disease that may contribute to heart rhythm disorders, syncope, and even death. Up to now, the best way to treat it is to implant electronic pacemakers. However, these have many disadvantages such as limited battery life, infection, and fixed pacing rate. There is an urgent need for a biological pacemaker (bio-pacemaker). This is expected to replace electronic devices because of its low risk of complications and the ability to respond to emotion. Here we survey the contemporary development of the bio-pacemaker by both experimental and computational approaches. The former mainly includes gene therapy and cell therapy, whilst the latter involves the use of multi-scale computer models of the heart, ranging from the single cell to the tissue slice. Up to now, a bio-pacemaker has been successfully applied in big mammals, but it still has a long way from clinical uses for the treatment of human heart diseases. It is hoped that the use of the computational model of a bio-pacemaker may accelerate this process. Finally, we propose potential research directions for generating a bio-pacemaker based on cardiac computational modeling.

Translated title of the contribution生物起搏器: 从生物实验到计算机模拟
Original languageEnglish
Pages (from-to)524-536
Number of pages13
JournalJournal of Zhejiang University: Science B
Volume21
Issue number7
DOIs
StatePublished - 1 Jul 2020
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Biological pacemaker
  • Cardiac simulation
  • Cell therapy
  • Computational modeling
  • Gene therapy
  • Q81

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