Scientists have grown a neural network from human stem cells
The study of the nervous system of higher animals is an extremely difficult task. Especially when it comes to the study of the human brain. Get the required material is very rare. Recently, however, neuroscientists have learned quite well how to handle stem cells, and it is precisely because of this that a team of experts from Tufts University (Medford, Massachusetts) has grown one of the most advanced biological neural networks today.
The new work is based on the previous one, during which scientists, researching rodent neurons, successfully raised a 3D model of the brain. To do this, they used induced pluripotent stem cells, which made it possible to create a variety of tissue cultures, including not only normal neurons, but also astroglial cells, which, interacting with each other, formed a neural network.
We found suitable conditions for stem cells to differentiate into different subtypes that support the growth and development of neural networks. This model has been tested on stem cells obtained from both healthy people and Alzheimer’s and Parkinson’s patients. We observed similar growth and gene expression.
– Kaplan DL, study coauthor
The new approach is based on the creation of a “framework” in the form of fibrin and fibrinogen threads, over which the cell distribution takes place. This allows you to directly integrate pluripotent stem cells into a three-dimensional design, bypassing the early stages of neural differentiation, getting long-lived cultures.
This method of creating neural networks can be used not only for a more detailed study of the neurophysiological characteristics of the organism, but also to identify biomarkers of neurodegenerative diseases in the early stages, which, in turn, will contribute to the early diagnosis and development of new therapies. With further improvement of technology, experts do not exclude the possibility of creating target cells for drugs against neurodegenerative diseases of the brain. And this will further accelerate the production of medicines.