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Biomarkers

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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...

Identification of potential markers of elevated anticandidal activity of propolis extracts.

Journal of ethnopharmacology
ETHNOPHARMACOLOGICAL RELEVANCE: For centuries, propolis has been one of the most important and popular antimicrobial (antibacterial and antifungal) agents used in traditional medicine worldwide, including Central and Eastern Europe. Despite centuries...

c-Triadem: A constrained, explainable deep learning model to identify novel biomarkers in Alzheimer's disease.

PloS one
Alzheimer's disease (AD) is a neurodegenerative disorder that requires early diagnosis for effective management. However, issues with currently available diagnostic biomarkers preclude early diagnosis, necessitating the development of alternative bio...

Identification of Crohn's Disease-Related Biomarkers and Pan-Cancer Analysis Based on Machine Learning.

Mediators of inflammation
: In recent years, the incidence of Crohn's disease (CD) has shown a significant global increase, with numerous studies demonstrating its correlation with various cancers. This study aims to identify novel biomarkers for diagnosing CD and explore the...

Development and validation of multi-center serum creatinine-based models for noninvasive prediction of kidney fibrosis in chronic kidney disease.

Renal failure
OBJECTIVE: Kidney fibrosis is a key pathological feature in the progression of chronic kidney disease (CKD), traditionally diagnosed through invasive kidney biopsy. This study aimed to develop and validate a noninvasive, multi-center predictive model...

Exploring the potential of cell-free RNA and Pyramid Scene Parsing Network for early preeclampsia screening.

BMC pregnancy and childbirth
BACKGROUND: Circulating cell-free RNA (cfRNA) is gaining recognition as an effective biomarker for the early detection of preeclampsia (PE). However, the current methods for selecting disease-specific biomarkers are often inefficient and typically on...

Pseudotargeted metabolomics profiles potential damage-associated molecular patterns as machine learning predictors for acute pancreatitis.

Journal of pharmaceutical and biomedical analysis
Acute pancreatitis (AP) is a common gastrointestinal disease characterized by pancreatic cell damage and inflammation. Given the early clinical diagnosis and management challenges, exploring novel analytical frameworks from new orientations for inter...

Uncovering hepatic transcriptomic and circulating proteomic signatures in MASH: A meta-analysis and machine learning-based biomarker discovery.

Computers in biology and medicine
BACKGROUND: Metabolic-associated steatohepatitis (MASH), the progressive form of metabolic-associated steatotic liver disease (MASLD), poses significant risks for liver fibrosis and cardiovascular complications. Despite extensive research, reliable b...

Machine learning-based integration reveals reliable biomarkers and potential mechanisms of NASH progression to fibrosis.

Scientific reports
Non-alcoholic fatty liver disease (NAFLD) affects about 25% of adults worldwide. Its advanced form, non-alcoholic steatohepatitis (NASH), is a major cause of liver fibrosis, but there are no non-invasive tests for diagnosing or preventing it. In our ...

Leveraging machine learning in precision medicine to unveil organochlorine pesticides as predictive biomarkers for thyroid dysfunction.

Scientific reports
Exposure to organochlorine pesticides (OCPs) poses significant health risks, including cancer, endocrine dysregulation, neurological disorders, and reproductive disruption. This study investigates the association between OCP exposure and thyroid dist...