AIMC Topic: Multiomics

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Multi-omics identification of circulating protein biomarkers for intervertebral disc degeneration using Mendelian randomization and scRNA-seq.

Clinical rheumatology
BACKGROUND: Intervertebral disc degeneration (IVDD) is a primary cause of chronic low back pain, significantly impacting quality of life and healthcare systems globally. Despite its prevalence, the molecular mechanisms underlying IVDD remain unclear,...

Identification of inflammation-related biomarkers and therapeutic targets for neurogenic bladder fibrosis via multi-omics analysis.

Computers in biology and medicine
Inflammatory responses play a crucial role in the progression of pediatric neurogenic bladder (NB)-associated fibrosis; however, their specific contributions remain poorly understood. This study aimed to identify inflammation-related biomarkers for d...

Identification of hub genes involved in the pathogenesis of diabetic nephropathy: A multi-omics study integrating machine learning, mendelian randomization and mediation analysis.

Diabetes, obesity & metabolism
BACKGROUND: Diabetic nephropathy (DN), affecting 30%-40% of diabetic patients, is the leading cause of end-stage renal disease worldwide. This study aims to identify diagnostic biomarkers and explore potential gene-metabolite interactions in DN patho...

Brassica microgreens shape gut microbiota and functional metabolite profiles in a species-related manner: A multi-omics approach following in vitro gastrointestinal digestion and large intestine fermentation.

Microbiological research
Brassicaceae microgreens constitute a novel and promising source of bioactive compounds, such as polyphenols and glucosinolates. In this work, an integrative computational approach was performed to decipher the interaction between bioaccessible micro...

Integration of multi-omics data and machine learning to identify antioxidant biomarkers in type 1 diabetes.

Free radical biology & medicine
The identification of biomarkers for early diagnosis and monitoring the progression of Type 1 Diabetes (T1DM) is essential for improving disease management. This study integrates multi-omics data with machine learning to identify antioxidant stress p...

Integrative multi-omics analysis reveals BEST1 as a potential tumor-associated gene in gliomas.

Neuroscience
BACKGROUND: The newest glioma classification in WHO 2021 emphasizes the importance of gene mutations in the glioma molecular pathogenesis. Our research aims to look for new glioma-related genes that have the potential to be therapeutic targets.

Integrated multi-omics reveals the impact of ruminal keystone bacteria and microbial metabolites on average daily gain in Xuzhou cattle.

Microbiology spectrum
UNLABELLED: The rumen microbiome plays a crucial role in determining the metabolic and digestive efficiency of livestock. Despite its crucial role, the impact of the rumen microbiome on average daily gain (ADG) in Xuzhou cattle remains underexplored....

The Future of a Myriad of Accelerated Biodiscoveries Lies in AI-Powered Mass Spectrometry and Multiomics Integration.

Journal of mass spectrometry : JMS
The intersection of modern artificial intelligence (AI) and mass spectrometry (MS) is set to transform the MS-based "omics" research fields, particularly proteomics, metabolomics, lipidomics, and glycomics, enabling advancements across a wide range o...

Multiomics and Machine Learning Identify Immunometabolic Biomarkers for Active Tuberculosis Diagnosis Against Nontuberculous Mycobacteria and Latent Tuberculosis Infection.

Journal of proteome research
This study utilized multiomics combined with a comprehensive machine learning-based predictive modeling approach to identify, validate, and prioritize circulating immunometabolic biomarkers in distinguishing tuberculosis (TB) from nontuberculous myco...