AIMC Topic: Metabolomics

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A holistic strategy for the in-depth discrimination and authentication of 16 citrus herbs and associated commercial products based on machine learning techniques and non-targeted metabolomics.

Journal of chromatography. A
Citrus-derived raw medicinal materials are frequently used for health care, flavoring, and therapeutic purposes. However, Due to similarities in origin or appearance, citrus herbs are often misused in the market, necessitating effective differentiati...

Untargeted metabolomics and machine learning unveil the exposome and metabolism linked with the risk of early pregnancy loss.

Journal of hazardous materials
Early pregnancy loss (EPL) may result from exposure to emerging contaminants (ECs), although the underlying mechanisms remain poorly understood. This case-control study measured over 2000 serum features, including 37 ECs, 6 biochemicals, and 2057 end...

QuanFormer: A Transformer-Based Precise Peak Detection and Quantification Tool in LC-MS-Based Metabolomics.

Analytical chemistry
In metabolomic analysis based on liquid chromatography coupled with mass spectrometry, detecting and quantifying intricate objects is a massive job. Current peak picking methods still cause high rates of incorrectly picked peaks to influence the reli...

Machine learning-based classification and prediction of typical Chinese green tea taste profiles.

Food research international (Ottawa, Ont.)
The taste of Chinese green tea is highly diverse. In this study, a combination of unsupervised and supervised learning methods was utilized to develop a model for classifying and predicting typical Chinese green tea taste. Three clustering methods we...

Perspective: Multiomics and Artificial Intelligence for Personalized Nutritional Management of Diabetes in Patients Undergoing Peritoneal Dialysis.

Advances in nutrition (Bethesda, Md.)
Managing diabetes in patients on peritoneal dialysis (PD) is challenging due to the combined effects of dietary glucose, glucose from dialysate, and other medical complications. Advances in technology that enable continuous biological data collection...

ABCoRT: Retention Time Prediction for Metabolite Identification via Atom-Bond Co-Learning.

Journal of chemical information and modeling
Liquid chromatography retention time (RT) prediction plays a crucial role in metabolite identification, a challenging and essential task in untargeted metabolomics. Accurate molecular representation is vital for reliable RT prediction. To address thi...

Precision fetal cardiology detects cyanotic congenital heart disease using maternal saliva metabolome and artificial intelligence.

Scientific reports
Prenatal sonographic diagnosis of congenital heart disease (CHD) can lead to improved morbidity and mortality. However, the diagnostic accuracy of ultrasound, the sole prenatal screening tool, remains limited. Failed prenatal or early newborn detecti...

Machine learning and multi-omics in precision medicine for ME/CFS.

Journal of translational medicine
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a complex and multifaceted disorder that defies simplistic characterisation. Traditional approaches to diagnosing and treating ME/CFS have often fallen short due to the condition's hetero...

Discrimination of Benign and Malignant Thyroid Nodules through Comparative Analyses of Human Saliva Samples via Metabolomics and Deep-Learning-Guided Label-free SERS.

ACS applied materials & interfaces
Thyroid nodules are a very common entity. The overall prevalence in the populace is estimated to be around 65-68%, among which a small portion (less than 5%) is malignant (cancerous). Therefore, it is important to discriminate benign thyroid nodules ...

Investigation of alpha-glucosidase inhibition activity of Artabotrys sumatranus leaf extract using metabolomics, machine learning and molecular docking analysis.

PloS one
One way to treat diabetes mellitus type II is by using α-glucosidase inhibitor, that will slow down the postprandial glucose intake. Metabolomics analysis of Artabotrys sumatranus leaf extract was used in this research to predict the active compounds...