AIMC Topic: Metabolomics

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Single-Cell Raman Spectroscopy Combined with Metabolomics Reveals Distinct Metabolic Profiles in Medulloblastoma Subtypes.

Analytical chemistry
Tumor heterogeneity poses a major challenge to the precision treatment of medulloblastoma (MB). Rapid and accurate subtyping tools are urgently needed for informed clinical decision-making. Herein, we demonstrate the utility of Raman spectroscopy (RS...

Metabolic remodeling and its hidden heterogeneity in uterine fibroids: comprehensive metabolomic profiling and mass spectrometry imaging.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: As the most common benign gynecological tumor in women, uterine fibroids not only pose a serious threat to reproductive health but also directly impair fertility. The structural abnormalities of the uterus and metabolic disturbances the...

Integrative Omics and AI-Driven Systems Biology: Multilayer Networks Decoding Health and Resilience.

Journal of proteome research
Honey bees () are vital pollinators essential for maintaining ecosystem stability and global food production, but they face escalating threats from pathogens, agrochemicals, and climate change. Although proteomics has advanced our understanding of be...

Machine learning and data-driven inverse modeling of metabolomics unveil key processes of active aging.

NPJ systems biology and applications
Physical inactivity and low fitness have become global health concerns. Metabolomics, as an integrative approach, may link fitness to molecular changes. In this study, we analyzed blood metabolomes from elderly individuals under different treatments....

Unsupervised machine learning for mass spectrometry imaging data analysis with isotope labeling.

The Analyst
Mass spectrometry imaging (MSI) has emerged as a powerful tool for spatial metabolomics, but untargeted data analysis has proven to be challenging. When combined with isotope labeling (MSI), MSI provides insights into metabolic dynamics with high sp...

Exosomal biomarkers in cancer: Insights from Multi-OMIC approaches.

Clinica chimica acta; international journal of clinical chemistry
Extracellular vesicles, particularly exosomes, are emerging as powerful tools in cancer research due to their role in intercellular communication and their capacity to reflect the molecular composition of their originating cells. Multi-omic approache...

Metabolomic profiling and machine learning-based biomarker identification for oligoasthenozoospermia.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION AND OBJECTIVES: Oligoasthenozoospermia, characterized by a low sperm count and impaired progressive motility, significantly contributes to male infertility. This study examines the metabolic disparities between individuals with oligoasth...

A New Approach to Large Multiomics Data Integration.

Analytical chemistry
Data reduction and data mining are common practices for handling large-scale data from wide-ranging sources, but high-dimensional omics and imaging data sets present difficult challenges for feature extraction and data mining due to the large number ...

Genome-scale prediction of gene ontology from mass fingerprints reveals new metabolic gene functions.

Life science alliance
Mass-based fingerprinting can characterize microorganisms; however, expansion of these methods to predict specific gene functions is lacking. Therefore, mass fingerprinting was developed to functionally profile a yeast knockout library. Matrix-assist...

Molecular networking and deep learning synergy for bioactive metabolite discovery in L. plantarum-Fermented Sea buckthorn milk.

Food chemistry
This study investigated the metabolomic transformation of sea buckthorn milk fermented by Lactiplantibacillus plantarum to identify novel bioactive compounds and improve both nutritional and sensory attributes. An untargeted metabolomics workflow int...