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MetabolomicsOsmolality-based normalization enhances statistical discrimination of untargeted metabolomic urine analysis: results from a comparative study

INTRODUCTION: Because of its ease of collection, urine is one of the most commonly used matrices for metabolomics studies. However, unlike other biofluids, urine exhibits tremendous variability that can introduce confounding inconsistency during result interpretation. Despite man...

2023-09-04 | MTBLS1765 | MetaboLights
Metabolomics1H NMR chemometric models for classification of Czech wine type and variety

A set of 917 wines of Czech origin registered in a national competition were analysed using nuclear magnetic resonance spectroscopy (NMR) with the aim to build and evaluate multivariate statistical models and machine learning methods for the classification of type (5 types), variety (13 varieties...

2020-08-28 | MTBLS1677 | MetaboLights
MetabolomicsCharacterizing ex vivo models for studying lipid metabolism in triple negative breast cancer

Lipid metabolism drives cancer progression but is difficult to model using conventional methods. In vivo models provide circulating lipids, but are costly and low throughput, while in vitro models lack sufficient lipid availability in culture media. Here, we evaluate the chick chorioallantoic mem...

2026-07-16 | MTBLS13377 | MetaboLights
MetabolomicsComparative Analysis of Host Metabolic Alterations in Murine Malaria Models with Uncomplicated or Severe Malaria

Malaria varies in severity, with complications ranging from uncomplicated to severe malaria. Severe malaria could be attributed to peripheral hyperparasitemia or cerebral malaria. The metabolic interactions between the host and Plasmodium species are yet to be understood during these inf...

2022-09-14 | MTBLS4387 | MetaboLights
MetabolomicsProMetIS, deep phenotyping of mouse models by combined proteomics and metabolomics analysis

Genes are pleiotropic and getting a better knowledge of their function requires a comprehensive characterization of their mutants. Here, we generated multi-level data combining phenomic, proteomic and metabolomic acquisitions from plasma and liver tissues of two C57BL/6 N mouse models lacking the...

2021-09-01 | MTBLS1903 | MetaboLights
MetabolomicsAnalysis of the human adult urinary metabolome variations with age, body mass index and gender by implementing a comprehensive workflow for univariate and OPLS statistical analyses. ('Sacurine' data set)

Urine metabolomics is widely used for biomarker research in the fields of medicine and toxicology. As a consequence, characterization of the variations of the urine metabolome under basal conditions becomes critical in order to avoid confounding effects in cohort studies. Such physiological infor...

2017-01-20 | MTBLS404 | MetaboLights
MetabolomicsUntargeted Metabolomics Reveals Molecular Effects of Ketogenic Diet on Healthy and Tumor Xenograft Mouse Models
The application of ketogenic diet (KD) (high fat/low carbohydrate/adequate protein) as an auxiliary cancer therapy is a field of growing attention. KD provides sufficient energy supply for healthy cells, while possibly impairing energy production in highly glycolytic tumor cells. Moreover, KD regula...
2019-10-08 | MTBLS1066 | MetaboLights
MetabolomicsDifferential Metabolomic Biomarkers Analysis of Apheresis Platelet Storage Based on Machine Learning Models

Platelet storage lesion (PSL) is a critical factor limiting the efficacy of platelet transfusion. Although hypothermic (4°C) storage is considered beneficial for maintaining platelet function, the underlying mechanisms of systemic metabolic reprogramming remain incompletely understood. This study...

2026-07-27 | MTBLS15165 | MetaboLights
ProteomicsStatistical models for the analysis of isobaric Tags multiplexed quantitative proteomics
ABSTRACT: Mass spectrometry is being used to identify protein biomarkers that can facilitate development of drug treatment. Mass spectrometry based proteomics results in complex proteomic data that is hierarchical in nature often with small sample size studies. Generalized linear models (GLM) is th...
ORGANISM(S): Homo sapiens (Human) Escherichia coli 
2017-07-28 | PXD005486 | Pride
Statistical models : proteomics Tmt Mixed models Biomarkers 
MetabolomicsTargeted metabolomic profiling and machine learning-based prediction models for persistent atrial fibrillation: a multi-center observational study

Background. Atrial fibrillation (AF), the most common cardiac arrhythmia worldwide, carries a high risk of severe complications. Patients diagnosed with paroxysmal atrial fibrillation (PAF) may progress to persistent atrial fibrillation (PerAF) following a period. We aimed to identify metabo...

2026-07-03 | MTBLS13136 | MetaboLights
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