AIMC Topic: Biomarkers

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Exploring the mechanism of metabolic cell death-related genes AKR1C2 and MAP1LC3A as biomarkers in Parkinson's disease.

Scientific reports
There is a strong relationship between metabolic cell death (MCD) and neurodegenerative diseases. However, the involvement of metabolic cell death (MCD)-related genes (MCDRGs) in Parkinson's disease (PD) pathogenesis remains poorly analyzed. Integrat...

Exploring novel molecular mechanisms underlying recurrent pregnancy loss in decidual tissues.

Scientific reports
Recurrent pregnancy loss (RPL), which affects approximately 2.5% of reproductive-aged women, remains idiopathic in more than 50% of cases, necessitating mechanistic insights and biomarkers. Three RPL decidual tissue transcriptomic datasets (GSE113790...

Identification of necroptotic biomarkers associated with immune microenvironment in sepsis based on the protein-protein interaction network and machine learning.

Clinica chimica acta; international journal of clinical chemistry
BACKGROUND: Necroptosis is inflammatorily sparked and closely associated with sepsis, but the crosstalk between necroptosis and inflammation in sepsis has rarely been studied in depth. This study is designed to reveal the role of necroptosis in the p...

Identification of diagnostic biomarkers and dissecting immune microenvironment with crosstalk genes in the POAG and COVID-19 nexus.

Scientific reports
An underlying association between primary open-angle glaucoma (POAG) and COVID-19 has been hypothesized, but the causal link and shared mechanisms remain unclear. This study integrates epidemiological and bioinformatics approaches to investigate thei...

Fusion of bio-inspired optimization and machine learning for Alzheimer's biomarker analysis.

Computers in biology and medicine
Identification of Alzheimer's Disease (AD), especially in its early phases, presents significant challenges due to the nonexistence of reliable biomarkers and effective treatments. Clinical trials for AD medications also suffer from high failure rate...

Diagnostic immune-related markers for diabetic kidney disease: a bioinformatics and machine learning approach.

Renal failure
OBJECTIVE: Diabetic kidney disease (DKD) is a leading cause of chronic kidney disease, with chronic inflammation driving its progression. This study aimed to identify immune-related diagnostic biomarkers for DKD and explore their association with imm...

MAMSI: Integration of Multiassay Liquid Chromatography-Mass Spectrometry Metabolomics Data Using Multiview Machine Learning.

Analytical chemistry
Liquid chromatography-mass spectrometry (LC-MS) is a commonly used analytical technique in untargeted metabolomics. However, the diverse chemical and physical properties of metabolites often require the use of several different analytical assays for ...

Biomarkers and therapeutic strategies targeting microglia in neurodegenerative diseases: current status and future directions.

Molecular neurodegeneration
Recent advances in our understanding of non-cell-autonomous mechanisms in neurodegenerative diseases (NDDs) have highlighted microglial dysfunction as a core driver of disease progression. Conditions such as Alzheimer's disease (AD), amyotrophic late...

Interpretive prediction of hyperuricemia and gout patients via machine learning analysis of human gut microbiome.

BMC microbiology
Hyperuricemia (HUA) and gout result from imbalances in uric acid metabolism and are closely associated with the gut microbiota. Advanced analytical methods facilitate the exploration of microbiota complexity. In this study, 16S rRNA sequencing data f...

Inflammatory, fibrotic and endothelial biomarker profiles in COVID-19 patients during and following hospitalization.

Scientific reports
Survivors of severe COVID-19 often suffer from long-term respiratory issues, but the molecular drivers of this damage remain unclear. This study explored the dynamics of inflammatory, fibrotic, and endothelial biomarkers in hospitalized COVID-19 pati...