The buildup of abnormal tau proteins in the brain in neurofibrillary tangles is a feature of Alzheimer's disease, but it also accumulates in other neurodegenerative diseases, such as chronic traumatic encephalopathy and additional age-related conditions. Accurate diagnosis of neurodegenerative diseases is challenging and requires a highly-trained specialist. Researchers at the Center for Computational and Systems Pathology at Mount Sinai developed and used the Precise Informatics Platform to apply powerful machine learning approaches to digitized microscopic slides prepared using tissue samples from patients with a spectrum of neurodegenerative diseases. Applying deep learning, these images were used to create a convolutional neural network capable of identifying neurofibrillary tangles with a high degree of accuracy directly from digitized images. "Utilizing artificial intelligence has great potential to improve our ability to detect and quantify neurodegenerative diseases, representing a major advance over existing labor-intensive and poorly reproducible approaches," said lead investigator John Crary, MD, PhD, Professor of Pathology and Neuroscience at the Icahn School of Medicine at Mount Sinai.
NFL team helmets are displayed at the NFL headquarters in New York in 2015. Weeks before the NFL season begins, new research reminds us of the physical cost of America's most popular sport. A new study of 111 former NFL players found all but one had a degenerative brain disease as known as chronic traumatic encephalopathy (CTE). These injuries may have started early in the players' careers, based on the findings published in the Journal of the American Medical Association. The results also suggest those who play American football have a higher chance of developing long-term neurological conditions, like CTE. "This is the largest study to date on CTE," Michael Alosco, a clinical neuropsychology fellow Boston University and study co-author said.
The specter of neurodegenerative disease, particularly Alzheimer's disease, haunts the developed world and exacts a poorly documented toll on underdeveloped countries. With so little progress made toward finding a cure--or, better, a prevention--it is time to rethink the path to progress. This requires a change in perspective on the type of research that will make a difference. The lesson learned from cancer research is that a new commitment means rethinking the fundamental approach to the disease. Cancer research moved from taking potshots with, usually, cytotoxic drugs to a bottom-up, mechanism-based approach in which newly acquired genetic knowledge played the largest role.
The role of specific subsets of immune cell in the onset and progression of Alzheimer's disease (AD) is poorly understood. Keren-Shaul et al. profiled the entire immune cell population in the brains of wild-type and AD-transgenic (Tg-AD) mice. They identified a microglial cell type (DAM) that is associated with neurodegenerative diseases. The DAM cells contained internalized amyloid-β--presumably promoting its clearance. One key player was the AD-associated risk factor Trem2. Single-cell analysis of DAM in Tg-AD and Trem2 / Tg-AD mice suggested that activating the DAM program involved two steps.
Neurological disorders affect millions of patients worldwide. The inaccessibility of the brain to physical examination and the complexity of clinical evaluation for such conditions represent major challenges. Subjective symptoms such as chronic pain, for example, can be difficult to confirm, while cognitive impairment can result from a range of different pathologies. In the absence of clear biological markers indicating a particular pathology, it can be difficult to provide a rapid, definitive diagnosis. These challenges are particularly pertinent in neurodegenerative diseases, as few effective treatments for slowing or stopping such conditions are currently available.