One is familiar with the disturbance in the circadian rhythm or the 24-hour biological cycle, which handles almost all aspects of metabolism, from sleep-wake cycles to body temperature and digestion.
Every cell in the body has a circadian clock, but researchers are not clear about how cell networks connect with each other over time and how those time-varying connections affect network functions. Researchers at the University of Washington developed a unified and data-driven computational method, called the ICON method (inferred network connections), to infer and reveal these connections in biological and chemical oscillatory networks, known as the topology of these complex networks, based on Your time series data.
Abnormal synchrony has been linked to a variety of brain disorders, such as epilepsy, Alzheimer diseaseand Parkinson's disease.
The researchers first tested their method on a simulated network of different sizes they created. Then, they tested the method on a network of oscillators (populations of dynamic units that are activated several times together, silenced and then re-lit together) created in the laboratory. When they applied the algorithm to the network of interactions between the synthetic oscillators, the results coincided with the previous experiments, finding the same connections in a network of 15 chemical oscillators. Such a prediction of this dynamic topology was not possible previously, the researchers said.
"The connection at one time may be strong, but at another time it may be stronger or weaker, so we can use this data to recover functional connectivity." If we know this, then we know the network, we can study and investigate more over time if this network will be synchronized or if specific dynamic patterns will emerge, "said Jr-Shin Li, researcher.
They also stated that ICON would help them and other scientists to understand the principles that allow systems to synchronize efficiently.
In another experiment, the researchers tested the method in seven groups of five mice that were housed together over a period of time as social networks. They measured the oscillations of the mice at the end of the experiment and then applied the algorithm to infer the results of the data. In the end, the researchers found that four of the groups of mice had social synchronization because they had the same body temperature at the end of their time together.
The findings appeared in the Journal of Proceedings of the National Academy of Sciences.
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Reference: https://www.thehealthsite.com/news/cell-connections-may-impact-your-biological-cycle-says-study-ag0818/, by ANI