AIMC Topic: Neurodegenerative Diseases

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Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging.

Nature communications
The process of protein aggregation, central to neurodegenerative diseases like Huntington's, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in d...

Public hesitancy for AI-based detection of neurodegenerative diseases in France.

Scientific reports
Recent advances in artificial intelligence (AI) have made it possible to detect neurodegenerative diseases (NDDs) earlier, potentially improving patient outcomes. However, AI-based detection tools remain underutilized. We studied individual valuation...

Advancing rare neurological disorder diagnosis: Addressing challenges with systematic reviews and AI-driven MRI meta-trans learning framework for neurodegenerative disorders.

Ageing research reviews
Neurological Disorders (ND) affect a large portion of the global population, impacting the brain, spinal cord, and nerves. These disorders fall into categories such as NeuroDevelopmental (NDD), NeuroBiological (NBD), and NeuroDegenerative (ND) disord...

Biomarkers and therapeutic strategies targeting microglia in neurodegenerative diseases: current status and future directions.

Molecular neurodegeneration
Recent advances in our understanding of non-cell-autonomous mechanisms in neurodegenerative diseases (NDDs) have highlighted microglial dysfunction as a core driver of disease progression. Conditions such as Alzheimer's disease (AD), amyotrophic late...

Integrative machine learning and molecular simulation approaches identify GSK3β inhibitors for neurodegenerative disease therapy.

Scientific reports
Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are a growing global health concern, especially among the elderly, posing significant challenges to well-being and survival. GSK3β, a serine/threonine...

Ultradeep N-glycoproteome atlas of mouse reveals spatiotemporal signatures of brain aging and neurodegenerative diseases.

Nature communications
The current depth of site-specific N-glycoproteomics is insufficient to fully characterize glycosylation events in biological samples. Herein, we achieve an ultradeep and precision analysis of the N-glycoproteome of mouse tissues by integrating multi...

Regional free-water diffusion is more strongly related to neuroinflammation than neurodegeneration.

Journal of neurology
INTRODUCTION: Recent research has suggested that neuroinflammation may be important in the pathogenesis of neurodegenerative diseases. Free-water diffusion (FWD) has been proposed as a non-invasive neuroimaging-based biomarker for neuroinflammation.

Uncovering injury-specific proteomic signatures and neurodegenerative risks in single and repetitive traumatic brain injury.

Signal transduction and targeted therapy
Traumatic brain injury (TBI) is a major public health concern associated with an increased risk of neurodegenerative diseases including Alzheimer's disease (AD), Parkinson's disease (PD), and chronic traumatic encephalopathy, yet the underlying molec...

Machine learning-enhanced SERS diagnostics: Accelerating the AI-powered transition from laboratory discoveries to clinical practice.

Computers in biology and medicine
Surface-enhanced Raman spectroscopy (SERS) has emerged as a transformative analytical tool in disease diagnostics, offering unparalleled sensitivity and molecular fingerprinting capabilities. However, its clinical translation is hindered by the inher...

EEG-based neurodegenerative disease diagnosis: comparative analysis of conventional methods and deep learning models.

Scientific reports
In the context of lifestyle changes, stress and other environmental factors have resulted in the sudden hike in dementia globally. This necessitates investigations with respect to every horizon of the due cause for it; further on, the diagnosis and t...