AIMC Topic: Metabolomics

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Comparative metabolomics profiling reveals the aroma and nutritional diversity of eight wild edible plants.

Food chemistry
Wild edible plants are important yet undervalued vegetables, due to limited knowledge of their bioactive components and nutritional/functional potential. In this study, we used full-spectrum metabolomics and machine learning to analyze the aroma-rela...

Metabolomic profiling of plasma reveals differential disease severity markers in avian influenza A(H7N9) infection patients.

International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases
OBJECTIVES: Avian influenza such as H7N9 is currently a major global public health risk, and at present, there is a lack of relevant diagnostic and treatment markers.

Comprehensive statistical and machine learning framework for identification of metabolomic biomarkers in breast cancer.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: Breast cancer is the most common cancer among women, with its burden increasing over the past decades. Early diagnosis significantly improves survival rates and reduces lethality. Innovative technologies are being developed for early de...

Pan-omics insights into abiotic stress responses: bridging functional genomics and precision crop breeding.

Functional & integrative genomics
Crop production has been regarded as the major goal of agricultural activities, but the rapidly growing population and climate change have become more complex in the agricultural systems. Abiotic stress greatly affects crop productivity globally; dev...

On Selecting Robust Approaches for Learning Predictive Biomarkers in Metabolomics Data Sets.

Analytical chemistry
Metabolomics, the study of small molecules within biological systems, offers insights into metabolic processes and, consequently, holds great promise for advancing health outcomes. Biomarker discovery in metabolomics represents a significant challeng...

A plasma metabolome-derived model predicts severe liver outcomes of nonalcoholic fatty liver disease in the UK Biobank.

Diabetes, obesity & metabolism
AIMS: Severe liver disease (SLD) in nonalcoholic fatty liver disease (NAFLD) is often diagnosed late due to the long asymptomatic period of progressive fibrosis. We aimed to identify metabolomic profiles associated with SLD and develop a predictive m...

Visualizing fatigue mechanisms in non-communicable diseases: an integrative approach with multi-omics and machine learning.

BMC medical informatics and decision making
BACKGROUND: Fatigue is a prevalent and debilitating symptom of non-communicable diseases (NCDs); however, its biological basis are not well-defined. This exploratory study aimed to identify key biological drivers of fatigue by integrating metabolomic...

Multiomics in Renal Cell Carcinoma: Current Landscape and Future Directions for Precision Medicine.

Current urology reports
PURPOSE OF REVIEW: Renal cell carcinoma (RCC) is a prevalent and increasingly diagnosed malignancy associated with high mortality and recurrence rates. Traditional diagnostic and therapeutic approaches have limitations due to the disease's molecular ...

Metabolic signature of COVID-19 progression: potential prognostic markers for severity and outcome.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: There are significant challenges remain in accurately categorizing the risk of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) patients.