Robotics & Machine Learning Daily News2024,Issue(Sep.9) :43-44.

Federal University Alfenas Reports Findings in Parkinson’s Disease (Metabolomics Unveils Disrupted Pathways in Parkinson’s Disease: Toward Biomarker-Based Diagn osis)

Robotics & Machine Learning Daily News2024,Issue(Sep.9) :43-44.

Federal University Alfenas Reports Findings in Parkinson’s Disease (Metabolomics Unveils Disrupted Pathways in Parkinson’s Disease: Toward Biomarker-Based Diagn osis)

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Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New research on Neurodegenerative Dise ases and Conditions - Parkinson’s Disease is the subject of a report. According to news reporting from Alfenas, Brazil, by NewsRx journalists, research stated, “Parkinson’s disease (PD) is a neurodegenerative disorder characterized by diver se symptoms, where accurate diagnosis remains challenging. Traditional clinical observation methods often result in misdiagnosis, highlighting the need for biom arker-based diagnostic approaches.” The news correspondents obtained a quote from the research from Federal Universi ty Alfenas, “This study utilizes ultraperformance liquid chromatography coupled to an electrospray ionization source and quadrupole time-of-flight untargeted me tabolomics combined with biochemometrics to identify novel serum biomarkers for PD. Analyzing a Brazilian cohort of serum samples from 39 PD patients and 15 hea lthy controls, we identified 15 metabolites significantly associated with PD, wi th 11 reported as potential biomarkers for the first time. Key disrupted metabol ic pathways include caffeine metabolism, arachidonic acid metabolism, and primar y bile acid biosynthesis. Our machine learning model demonstrated high accuracy, with the Rotation Forest boosting model achieving 94.1% accuracy in distinguishing PD patients from controls. It is based on three new PD biomark ers (downregulated: 1-lyso-2-arachidonoylphosphatidate and hypoxanthine and upr egulated: ferulic acid) and surpasses the general 80% diagnostic a ccuracy obtained from initial clinical evaluations conducted by specialists. Bes ides, this machine learning model based on a decision tree allowed for visual an d easy interpretability of affected metabolites in PD patients. These findings c ould improve the detection and monitoring of PD, paving the way for more precise diagnostics and therapeutic interventions.”

Key words

Alfenas/Brazil/South America/Basal Ga nglia Diseases and Conditions/Biomarkers/Brain Diseases and Conditions/Centra l Nervous System Diseases and Conditions/Cyborgs/Diagnostics and Screening/Em erging Technologies/Health and Medicine/Machine Learning/Movement Disorders/Nervous System Diseases and Conditions/Neurodegenerative Diseases and Condition s/Parkinson’s Disease/Parkinsonian Disorders

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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