This is the era of artificial intelligence and machine learning. These two, along with other advanced technologies, are making ripples, one of which is in the area of muscle development. Using machine learning, we now have a clearer understanding of how muscles grow. Dr. Ori Abinoam of the Weizmann Institute of Science, in collaboration with Dr. Asaf Zaritsky of Ben-Gurion University of the Negev, unraveled the mystery behind the transformation of stem cells into muscle fibers.
Stem cells are like the building blocks of our bodies and can transform into different types of cells, such as muscle cells. But how exactly does this happen? Two scientists have created a computer model that tracks the entire process.
The model gave each cell a score, which was based on the process it took to become a muscle fiber. It turns out that not all cells change at the same rate. This was a surprise to them because each had their own path and they had previously thought that they all changed at the same time.
It was also discovered that there are important checkpoints in the process. We know that before stem cells can become muscle fibers, we need to make sure they are ready to do so. An enzyme called p38 helps with this. When these block the enzymes, the cells are unable to complete their transformation into muscle fibers.
Computer models showed that without the enzyme, cells enter a kind of “fusion-ready” stage. These had all the right parts to become muscle fibers. However, these could not be combined perfectly.
This discovery isn't just about muscles. At the same time, it reveals how machine learning can help understand complex biological processes. This could help monitor diseases such as cancer in real time in the future.
