Multidisciplinary Human-Focused Research
2022-07-21



Please can you introduce the DataBrain project – what are the aims of this initiative, and what technologies are you using to achieve them?
The DataBrain project is a project financed by the University of Pisa, and the aim of the project is to use deep imaging techniques like confocal and two-photon microscopy, to image clarified brains, and thereby extract the structural, morphometric information of neuron architecture in its native 3D environment, and then use that information, use specific mathematical algorithms to store that information, and then use it to 3D print the neurons in order to better understand how their architecture modulates their function.
In that way, zooming into the brain architecture, we can see how, for example, diseases or disorders such as autism or Parkinson’s can alter the structure, and therefore the functional connections.
The data has been placed on an open platform so that anybody can use the stored architectures to print neurons themselves, and they can also use the algorithms that we have developed to extract the same type of information from the tissue that the researchers might be interested in.

How do the mathematical and programmatic models capture a digital map of the internal structure of the brain?
The data has been placed on an open platform so that anybody can use the stored architectures to print neurons themselves, and they can also use the algorithms that we have developed to extract the same type of information from the tissue that the researchers might be interested in.
To digitalize a map of the brain, we need to acquire the brain at cellular resolution and deep in the tissue. But the brain is full of lipids, so we need the X-CLARITY to clarify the brain. We’ve demonstrated that the clarification can be regarded as a trade-off between tissue transparency, and protein loss within the tissue – so following this simple rule, you can have the best contrasted images, which allow my algorithms to work.
After the clarification process, I acquire the samples using a confocal microscope. Then, I use my smart region-growing algorithm to reconstruct a single neuron from the forest of the brain. My algorithm works on the pixel intensity of the brain images, and automatically reconstructs, not just traces, single neurons. So, we can have Fourier information about the neuron volume, for example dendrite thickness.
My work can help the scientific community to unravel the mystery of the brain, because the structure of the brain is strongly connected with the function of the brain, so giving the scientific community a high-fidelity map of the brain can help them understand how it works.

What is the importance of tissue clearing techniques for DataBrain and your other projects? Are there insights that would be impossible or much more difficult to achieve without it?
The tissue clearing methodology and the electrophoretic tissue clearing machine that we’re using, the X-CLARITY from Logos Biosystems, has actually been fundamental to the DataBrain project, because without being able to clear tissues of the lipids, we wouldn’t be able to image deep into brains, and so we wouldn’t be able to extract that structural information that is so important to understand the function of mammalian brains.
I think it’s given us a huge advantage, and it’s a great leap forward in imaging, not just of brain tissue, but also of other types of tissue because we can now clarify different organs. Mini-organs as well can now be clarified and therefore visualized in-depth without having to resort to techniques that break down the tissue, which would mean we might lose the structure while we’re trying to investigate it.

What do you hope will be the impact of your work in the longer term?
Well, in the longer term we have a lot of inspirational ideas. I suppose one of the driving forces for the work that I do, personal driving forces, is being able to reduce the number of animals used in scientific experiments, but also to be able to get a better idea of how the human body functions. We obviously can’t do that by using animals; we have to do it by using humans, and if we can build these mini physiological-like systems in vitro, we actually have a super way of approaching themes such as personalized medicine, toxicology, disease models, etc.
I think it’s important for scientists to be aware of the ethical implications of their work, and to be also aware of the impact of their work on society and on the environment. Our work isn’t directly focused on reducing animal testing, and I don’t think that science should be driven by any sort of ideology, such as beliefs that it’s incorrect to use animals in experimental work, or beliefs that humans are superior to animals. So whilst we are working to gain a better understanding of how the human body functions, and the ethical implications of the work are important, I think they should be driven by a rational and illuminated way of approaching science, as well as life in general.

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