The researchers report that the behavior of cell networks, called "arrays," conforms to a branch of mathematics known as non-linear dynamics—also known as "the butterfly effect." Image Credit: Melanie Allan/Flickr
Scientists have figured out how to use channel-blocking drugs to set off a “wave” of poor communication among healthy heart cells.
The work combines principles of the butterfly effect and computer simulation to explore new ways of predicting and controlling the beginnings of heart disease. The findings suggest that a similar approach could one day be used to restore order to disrupted heart cells.
Christopher George, a molecular cardiologist from the Cardiff University School of Medicine, describes healthy hearts as being totally dependent on the synchronization of huge networks of cells working together for a common purpose. He says disease, on the other hand, can be defined as a loss of synchronicity whereby communication between individual cells is either very poor or lost altogether.
The ‘butterfly effect’
“Much like a murmuration of starlings in flight, the synchronization and behavior of thousands of birds gives rise to complex patterns that also have an amazing simplicity to them,” explains George.
“If a few birds don’t conform to these patterns, it wouldn’t make a great deal of difference—the overall collective behavior would remain.
“As in the butterfly effect, small changes can lead to drastic changes: if, over time, more birds become uncoupled from the dominant flight pattern, either a new pattern of communication would emerge, or the entire network would collapse into disarray.
“Our research shows that this is what happens to human cells in heart disease: the well-ordered behavior of coupled cells unravels and the synchronization is lost. Along this route though, there are points at which it is possible to halt, or reverse, this de-synchronization. We call these the ‘crisis points.'”
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Dimitris Parthimos, a mathematician based in the university’s Wales Heart Research Institute, developed the mathematical models that were used to perform the computer simulations.
“In knowing how to decode the patterns of cell communication, we can now begin using this information to design new ways of modulating cell behavior, to delay the onset of heart disease, and ultimately develop methods to reverse the process if disease is already established,” says Parthimos.
“Since all organs within the human body depend on communication networks built by cell-to-cell coupling, this work has implications for other diseases from cancer and neurodegeneration to diabetes.”
Finding the ‘crisis points’
According to the paper, the behavior of cell networks, called “arrays,” conforms to a branch of mathematics known as non-linear dynamics—also known as “the butterfly effect.”
It has two key features:
- If a sufficiently detailed picture of cell signaling can be constructed then the outcome of cell behavior, in response to a “crisis point,” can be predicted.
- If scientists understand the nature of these crisis points, which trigger the progression of disease, it should be possible to reverse it.
“Everything we are and everything that we do results from well-orchestrated biological signals or—’switches’—that use very few components,” explains George.
“What we’re trying to do now is to identify the ‘on’ and ‘off’ switches that turn health into disease, so as to understand the very early events that cause disease. This will help make it possible to intervene early, even before symptoms appear. We can then look to design ‘switches’ that turn disease back into health.”
The research team envisions that developments in imaging technologies will soon help to construct detailed 3D maps of entire human hearts, giving them an even more accurate picture of how heart cells communicate with each other, and the telltale signs of when things go wrong.
The findings are published in the Annals of Biomedical Engineering.
The British Heart Foundation (BHF), the Wellcome Trust, Heart Research UK, the Cardiac Research Development Fund, and Ser Cymru’s Engineering National Research Network (NRN) supported the work.
Source: Cardiff University
This article was originally published on futurity.org.