AIMC Topic: Biomarkers

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A novel potential biomarker panel to diagnose depression derived from big proteomic data.

Journal of affective disorders
BACKGROUND: There is still no clinical biomarker to diagnose depression. Given the complexity of a multifactorial disease like depression, a single biomarker is unlikely to capture the full heterogeneity of the disease and be applicable in clinical p...

Development and validation of a machine learning model integrating BUN/Cr ratio for mortality prediction in critically ill atrial fibrillation patients.

Scientific reports
Atrial fibrillation (AF), the most prevalent critical care arrhythmia, demonstrates substantial mortality associations where renal dysfunction management plays a pivotal therapeutic role. We examined the prognostic capacity of admission blood urea ni...

Associations of the intestinal microbiota with plasma bile acids and inflammation markers in Crohn's disease and ulcerative colitis.

Scientific reports
Our study explores signatures for Crohn's disease (CD) and Ulcerative Colitis (UC) reflecting an interplay between the intestinal microbiota, systemic inflammation, and plasma bile acid homeostasis. For this, 1,257 individuals scheduled for colonosco...

Identification of early warning biomarkers for type 4 cardio-renal syndrome based on bioinformatics analysis and secreted proteins.

Scientific reports
Chronic kidney disease (CKD) can induce chronic heart failure (CHF), a condition referred to as type 4 cardiorenal syndrome (CRS4). The pathophysiological mechanisms remain unclear, and suitable early warning biomarkers for CHF in CKD patients are la...

Robust detection of femtogram-level Alzheimer's biomarkers using machine learning-enhanced graphene biosensors.

Biosensors & bioelectronics
Early diagnosis of Alzheimer's disease (AD) requires blood biomarker tests sensitive to femtogram/mL concentrations. Graphene field-effect transistors (GFETs) are promising for this application, but suffer from device-to-device variability and requir...

Discovering Biomarkers for Asymptomatic Tuberculosis via Olink Proteomics and Machine Learning.

Journal of proteome research
The diagnosis of asymptomatic tuberculosis (TB) remains challenging due to an early disease stage. This study aimed to identify and validate plasma biomarkers for asymptomatic TB by integrating the Olink proteomics with multiple machine learning algo...

Paired snRNA-seq and scRNA-seq analysis of MASLD patients to identify early-stage markers for disease progression.

Hepatology communications
BACKGROUND AND AIMS: Metabolic dysfunction-associated steatotic liver disease (MASLD) is a leading cause of chronic liver disease worldwide. Progression from simple metabolic dysfunction-associated steatotic liver (MASL) without necro-inflammation to...

Neutrophil extracellular trapping network-associated biomarkers in liver fibrosis: machine learning and experimental validation.

Journal of translational medicine
BACKGROUND: The diagnostic and therapeutic potential of neutrophil extracellular traps (NETs) in liver fibrosis (LF) has not been fully explored. We aim to screen and verify NETs-related liver fibrosis biomarkers through machine learning.

Natural lithium isotope variations in serum after lithium administration as a novel biomarker for differentiating schizophrenia and bipolar disorder.

Translational psychiatry
Accurate differentiation of schizophrenia (SZ) and bipolar disorder (BD) is crucial for effective clinical management. However, current diagnostic methods, which rely heavily on subjective assessments, are prone to high rates of misdiagnosis. This st...