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Machine learning applications in healthcare clinical practice and research.
World J Clin Cases
January 2025
Department of Gastroenterology, Laiko General Hospital, National and Kapodistrian University of Athens, Athens 11527, Greece.
Machine learning (ML) is a type of artificial intelligence that assists computers in the acquisition of knowledge through data analysis, thus creating machines that can complete tasks otherwise requiring human intelligence. Among its various applications, it has proven groundbreaking in healthcare as well, both in clinical practice and research. In this editorial, we succinctly introduce ML applications and present a study, featured in the latest issue of the .
View Article and Find Full Text PDFIncreasing evidence suggests the involvement of metabolic alterations in neurological disorders, including Alzheimer's disease (AD), and highlights the significance of the peripheral metabolome, influenced by genetic factors and modifiable environmental exposures, for brain health. In this study, we examined 1,387 metabolites in plasma samples from 1,082 dementia-free middle-aged participants of the population-based Rotterdam Study. We assessed the relation of metabolites with general cognition (G-factor) and magnetic resonance imaging (MRI) markers using linear regression and estimated the variance of these metabolites explained by genes, gut microbiome, lifestyle factors, common clinical comorbidities, and medication using gradient boosting decision tree analysis.
View Article and Find Full Text PDFDepressive symptoms in older adults are associated with changes in stress-related markers, functional connectivity and brain volume.
Alzheimers Res Ther
January 2025
Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders", NeuroPresage Team, Institut Blood and Brain @ Caen-Normandie, GIP Cyceron, Bd Henri Becquerel, BP 5229, Caen, 14074, France.
Background: Subclinical depressive symptoms increase the risk of developing Alzheimer's disease (AD). The neurobiological mechanisms underlying this link may involve stress system dysfunction, notably related to the hippocampus which is particularly sensitive to AD. We aimed to investigate the links between blood stress markers and changes in brain regions involved in the stress response in older adults with or without subclinical depressive symptoms.
View Article and Find Full Text PDFAssociations of plasma biomarkers with cerebral perfusion and structure in Alzheimer's disease.
Transl Psychiatry
January 2025
Department of Neurology, Tianjin Neurological Institute, Tianjin Medical University General Hospital, Tianjin, China.
Plasma biomarkers have great potential in the screening, diagnosis, and monitoring of Alzheimer's disease (AD). However, findings on their associations with cerebral perfusion and structural changes are inconclusive. We examined both cross-sectional and longitudinal associations between plasma biomarkers and cerebral blood flow (CBF), gray matter (GM) volume, and white matter (WM) integrity.
View Article and Find Full Text PDFDevelopment and Validation of a Green Spectrofluorimetric Method for Nateglinide Quantification: Utilizing AR87 as a Probe With Box-Behnken Optimization and Quantum Mechanical Calculations.
Luminescence
January 2025
Pharmaceutical Analytical Chemistry Department, Faculty of Pharmacy, Al-Azhar University, Cairo, Egypt.
In this study, a sensitive and selective spectrofluorimetric method was developed for the determination of the antidiabetic drug nateglinide based on its reaction with the xanthene dye acid red 87 (AR87). A fluorescence quenching process was observed for the AR87 at 545 nm upon the addition of nateglinide, which was exploited for the quantitative analysis. The reaction mechanism was investigated using quantum mechanical calculations suggesting a transfer between the electron-rich AR87 and the electron-deficient nateglinide.
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