Amyloid plaques, which are a type of protein deposit, and protein aggregates, known as neurofibrillary tangles, are trademark indications of Alzheimer’s disease. But because there is no ethical way to extract brain tissue from patients to look for clues about how these plaques and tangles proliferate, supplementary techniques are needed to better understand the progression of Alzheimer’s disease.
During the American Crystallographic Association’s 71st annual meeting, Structural Science Awakens, which was held virtually last week, Abdullah Al Bashit, PhD, from Northeastern University, discussed using state-of-the-art computational techniques to help address these challenges in his presentation, “Classification of tissue variations in x-ray scanning microdiffraction from thin sections of human brain.”
“The brain is heterogeneous in structure at every possible length scale, from molecular to cellular to entire regions of the brain,” says Bashit. “Tracking pathological changes that occur at the molecular level across this heterogeneous tissue requires computational tools that can cope with the vast complexity of the brain.”
Though neuropathologists can locate amyloid plaques and neurofibrillary tangles, Bashit’s work demonstrates how the use of both small and wide-angle scattering along with state-of-the-art detection techniques will help probe their molecular structure and proliferation.
Additionally, coupling these with improvements to computational methodologies, like machine learning algorithms and better analysis methods, can lead to a better understanding of how Alzheimer’s disease progresses. “Understanding the molecular mechanisms underlying disease progression may provide a basis for designing therapies that could slow or halt neurodegeneration,” Bashit says.