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Association of Brain Age With Physical Disability and Cognitive Impairment in People With Multiple Sclerosis of the Same Age.

Neurology
BACKGROUND AND OBJECTIVES: The brain-predicted age difference (brain-PAD) is a novel marker of neurodegeneration in multiple sclerosis (MS). Brain-PAD has been associated with clinical disability in heterogeneous MS patient cohorts of varying ages an...

Comparison of machine learning classification and regression models for prediction of academic performance among postgraduate public health students.

Scientific reports
Machine learning (ML) is an artificial intelligence tool that focuses on learning by generating models using established algorithms that represent a given dataset. It can be used as a predictive tool for students' academic performance (AP) at both un...

Detection of cortical arousals in sleep using multimodal wearable sensors and machine learning.

Scientific reports
Cortical arousals are brief brain activations that disrupt sleep continuity and contribute to cardiovascular, cognitive, and behavioral impairments. Although polysomnography is the gold standard for arousal detection, its cost and complexity limit us...

Association between stress hyperglycemia ratio and all-cause mortality in critically ill patients with mitral valve disease.

Scientific reports
The study of stress hyperglycemia ratio (SHR) aims to further investigate the relationship between chronic glucose factors and adverse clinical events, particularly cardiovascular outcomes, in critically ill patients. However, prior research has not ...

Dual-channel TRCA-net based on cross-subject positive transfer for SSVEP-BCI.

Biomedical physics & engineering express
. To enhance the decoding accuracy and information transfer rate of steady-state visual evoked potential-based brain-computer interface (SSVEP-BCI) systems and to reduce inter-subject variability for broader SSVEP-BCI applications, a dual-channel TRC...

Incorporating multi-modal prompt learning into foundation models enhances predictability of visual fMRI responses to dynamic natural stimuli.

Journal of neural engineering
. Modeling neural encoding of visual stimuli often uses deep neural networks (DNNs) to predict human brain response to external stimuli. However, each DNN depends on networks tailored for computer vision tasks, resulting in suboptimal brain correspon...

Unraveling the Mechanisms of Osteoporosis Triggered by Methylparaben and Monomethyl Phthalate through Integrated Mendelian Randomization, In Silico Simulations, and Experimental Validation.

Environmental science & technology
Endocrine-disrupting chemicals (EDCs) are pervasive environmental hazards that have been linked to osteoporosis (OP), though causal mechanisms remain elusive. Employing an integrated multiomics framework, this study combined bidirectional Mendelian r...

Thyroid Function Effects of Mixed Exposure to Urinary Trihalomethanes and Haloacetic Acids: Based on an Integrated Framework of Exposure Assessment, Qualitative Association, and Quantitative Attribution.

Environmental science & technology
Toxicological studies have demonstrated that disinfection byproducts (DBPs) can disrupt thyroid function; however, human epidemiological evidence remains limited. The existing studies focus on a limited number of compounds and lack detailed investiga...

A Framework for Identifying Serum Exosomal Lipid Biomarkers in Alzheimer's Disease.

ACS chemical neuroscience
The escalating global burden of Alzheimer's disease (AD), projected to reach $16.9 trillion by 2050 with disproportionate impacts on low- and middle-income countries and racial minorities, underscores an urgent need for accessible early detection too...