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The goal of this observational study is to evaluate the detection ability of α-Synuclein Ultrafine Fluorescence Detection Method for body fluids (Such as saliva, urine, cerebrospinal fluid, and blood, etc.) and skin in Parkinson's patients.
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Social benefits: This technology has minimal harm (skin sampling diameter of 1mm), rather than surgical traumatic brain biopsy, which meets the minimum harm and maximum benefit; 1) Clear clinical diagnosis and differential diagnosis of diseases at once, avoiding repetitive examinations, effectively saving medical expenses and medical insurance funds; 2) Beneficial for early diagnosis and intervention, reducing social and economic burden; 3) Enhance the disease diagnosis and treatment capabilities of the region, enhance basic medical research, and enhance the medical level of the region. Clinical advantage: This technology belongs to extracranial tissues α-Syn aggregate testing can replace brain biopsy procedures that are difficult to carry out clinically, thus breaking through the limitations of clinical experience in diagnosing a-synuclein lineage diseases and greatly improving the diagnostic and differential diagnostic level of this group of diseases.
Clinical needs: α-Synaptic nucleoprotein lineage diseases (Parkinson's disease, multisystem atrophy, and Lewy body dementia) have complex early symptoms, making diagnosis and differential diagnosis difficult. Early diagnosis is crucial for disease prognosis. Authoritative theories suggest that brain tissue biopsy is necessary for the diagnosis of this group of diseases, but it is difficult to generalize in clinical practice. Therefore, there is a 20% misdiagnosis and missed diagnosis rate in the clinical diagnosis of α-synaptic nuclear protein spectrum diseases. The α-Synuclein Ultrafine Fluorescence Detection Method for body fluids and skin in Parkinson's patients can truly reflect the degree of pathological aggregation in synapses, which is helpful for early diagnosis and evaluation of diseases.
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600 participants in 5 patient groups
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Yousheng Xiao, professor
Data sourced from clinicaltrials.gov
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