AIMC Topic: Biomarkers

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Assessing prospective molecular biomarkers and functional pathways in severe asthma based on a machine learning method and bioinformatics analyses.

The Journal of asthma : official journal of the Association for the Care of Asthma
BACKGROUND: Severe asthma, which differs significantly from typical asthma, involves specific molecular biomarkers that enhance our understanding and diagnostic capabilities. The objective of this study is to assess the biological processes underlyin...

Identification of key biomarkers for predicting atherosclerosis progression in polycystic ovary syndrome via bioinformatics analysis and machine learning.

Computers in biology and medicine
OBJECTIVE: Polycystic ovary syndrome (PCOS) is one of the most significant cardiovascular risk factors, playing vital roles in various cardiovascular diseases such as atherosclerosis (AS). This study attempted to explore key biomarkers for predicting...

Machine learning interpretability methods to characterize the importance of hematologic biomarkers in prognosticating patients with suspected infection.

Computers in biology and medicine
OBJECTIVE: To evaluate the effectiveness of Monocyte Distribution Width (MDW) in predicting sepsis outcomes in emergency department (ED) patients compared to other hematologic parameters and vital signs, and to determine whether routine parameters co...

Combining bioinformatics and machine learning to identify diagnostic biomarkers of TB associated with immune cell infiltration.

Tuberculosis (Edinburgh, Scotland)
OBJECTIVE: The asymptomatic nature of tuberculosis (TB) during its latent phase, combined with limitations in current diagnostic methods, makes accurate diagnosis challenging. This study aims to identify TB diagnostic biomarkers by integrating gene e...

Knowledge-driven multi-graph convolutional network for brain network analysis and potential biomarker discovery.

Medical image analysis
In brain network analysis, individual-level data can provide biological features of individuals, while population-level data can provide demographic information of populations. However, existing methods mostly utilize either individual- or population...

Integrated approach of machine learning, Mendelian randomization and experimental validation for biomarker discovery in diabetic nephropathy.

Diabetes, obesity & metabolism
AIM: To identify potential biomarkers and explore the mechanisms underlying diabetic nephropathy (DN) by integrating machine learning, Mendelian randomization (MR) and experimental validation.

Serum metabolite biomarkers for the early diagnosis and monitoring of age-related macular degeneration.

Journal of advanced research
INTRODUCTION: Age-related macular degeneration (AMD) is a leading cause of irreversible blindness worldwide, with significant challenges for early diagnosis and treatment.

The Bioprotective Effects of Marigold Tea Polyphenols on Obesity and Oxidative Stress Biomarkers in High-Fat-Sugar Diet-Fed Rats.

Cardiovascular therapeutics
The research is aimed at exploring the potential of marigold petal tea (MPT), rich in polyphenol contents, against oxidative stress and obesity in a rat model following a high-fat-sugar diet (HFSD). The MPT was prepared through the customary method...

Peripheral Blood Mononuclear Cell Biomarkers for Major Depressive Disorder: A Transcriptomic Approach.

Depression and anxiety
Major depressive disorder (MDD) is a complex condition characterized by persistent depressed mood, loss of interest or pleasure, loss of energy or fatigue, and, in severe case, recurrent thoughts of death. Despite its prevalence, reliable diagnostic...

The role of lactylation in plasma cells and its impact on rheumatoid arthritis pathogenesis: insights from single-cell RNA sequencing and machine learning.

Frontiers in immunology
INTRODUCTION: Rheumatoid arthritis (RA) is a chronic autoimmune disorder characterized by persistent synovitis, systemic inflammation, and autoantibody production. This study aims to explore the role of lactylation in plasma cells and its impact on R...