The Next Generation of Aging Insights
A New Way To Understand Aging
Electrical signals serve as one of the silent messengers orchestrating intercellular cooperation and communication within every complex organism. While conventional wisdom among health practitioners often perceives the bioelectric system solely as conduits for these signals, recent breakthroughs in scientific research have illuminated a new frontier of understanding.
Far beyond mere conduits, the patterns and intricacies of our body's bioelectric networks offer profound insights into our health, encompassing crucial aspects such as aging and regeneration. Emerging studies have unveiled that these electrical networks harbour unique learnings and memories, distinct from other biological processes like the nervous system and genome.
Dr. Dan Turner (High Performance Scientist & Program Manager, Red Bull High Performance) using the Aycoutay research prototype with Kate Courtney (World Champion Mountain Biker)
Ion Channels Simplified
Diagram of synapse between two neurons - a process commonly effected by aging.
At the cellular level, electrical activity originates from the movement of charges (ions) across cell surface membranes at synaptic junctions between cells.
Embedded within the cell membrane are various ion protein channels that regulate the flow of ions across the membrane. This creates an ionic imbalance, with certain ions preferring to remain inside the cell while others gravitate outside, establishing an electrical gradient—the foundation of bioelectricity.
Intercellular communication is facilitated through a process called action potential, wherein cells rapidly depolarize and repolarize upon stimulation by neighbouring cells' electrical output. This sequential activation of cells forms chains of electrical actions, contributing to larger bioelectrical patterns that offer profound insights into whole-organism function.
Electrophysiology & Aging
Embedded within the intricate patterns of our body's bioelectric signals lie crucial insights into the aging process and longevity. Numerous peer-reviewed studies (referenced below) have identified a clear relationship between ion channel malfunction and various aging processes within the body.
The widespread malfunction of ion channels associated with aging leaves a distinct footprint on the aggregate bioelectric network, measurable through modern electrophysiology techniques and analyzable via artificial intelligence.
Notably, a study published in Frontiers of Cardiovascular Medicine by Baek et al. demonstrated the development of an accurate artificial intelligence model predicting the biological age of the heart using electrocardiogram (ECG) data. Significantly, this age prediction correlated strongly with mortality and cardiovascular disease.
Supporting Literature
Learn more about the incredible research that is helping us understand the way our bodies operate like never before.
Ion Channels in Aging & Age-related Diseases
Rao et al. (2016)
Relationships Between Ion Channels, Mitochondrial Functions, and Inflammation in Humans
Strickland et al. (2019)
Essential Roles of Intracellular Calcium Release Channels in Muscle, Brain, Metabolism, and Aging
Santulli & Marks (2015)
Oxidation of Ion Channels in the Aging Nervous System
Patel & Sesi (2016)
It is within this paradigm of discovery and innovation that Aycoutay stands, driven by the mission to decipher these signals and unlock transformative insights that empower individuals to lead longer and healthier lives.
Aycoutay Technology's Biological Aging Platform
With compelling scientific evidence supporting the feasibility of measuring aging through electrophysiology, Aycoutay has pioneered the world’s first whole-body electrophysiology device that measures biological aging.
This innovative technology empowers health practitioners to predict a person's whole-body biological age and receive a comprehensive breakdown across seven major biological systems. Leveraging a clinical dataset of over 10,000 measurements, Aycoutay’s team of data scientists has developed models providing informative aging insights within just 30 seconds, a significant improvement over the typical six-week timeframe required by most other biological age clocks.
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