AIMC Topic: Tandem Mass Spectrometry

Clear Filters Showing 41 to 50 of 289 articles

Optimization of the extraction process of total steroids from (Schwein.) Pat. by artificial neural network (ANN)-response surface methodology and identification of extract constituents.

Preparative biochemistry & biotechnology
(Schwein.) Pat has pharmacological effects such as tonifying the spleen, dispelling dampness, and strengthening the stomach, in which sterol is one of the main compounds of , but there has not been thought you to its extraction and detailed identifi...

Deep Learning Powers Protein Identification from Precursor MS Information.

Journal of proteome research
Proteome analysis currently heavily relies on tandem mass spectrometry (MS/MS), which does not fully utilize MS1 features, as many precursors remain unselected for MS/MS fragmentation, especially in the cases of low abundance samples and wide abundan...

Lipidomics combined with random forest machine learning algorithms to reveal freshness markers for duck eggs during storage in different rearing systems.

Poultry science
The differences in lipids in duck eggs between the 2 rearing systems during storage have not been fully studied. Herein, we propose untargeted lipidomics combined with a random forest (RF) algorithm to identify potential marker lipids based on ultra-...

Discrimination of Common Strains in Urine by Liquid Chromatography-Ion Mobility-Tandem Mass Spectrometry and Machine Learning.

Journal of the American Society for Mass Spectrometry
Accurate identification of bacterial strains in clinical samples is essential to provide an appropriate antibiotherapy to the patient and reduce the prescription of broad-spectrum antimicrobials, leading to antibiotic resistance. In this study, we ut...

Amino acid metabolomics and machine learning-driven assessment of future liver remnant growth after hepatectomy in livers of various backgrounds.

Journal of pharmaceutical and biomedical analysis
Accurate assessment of future liver remnant growth after partial hepatectomy (PH) in patients with different liver backgrounds is a pressing clinical issue. Amino acid (AA) metabolism plays a crucial role in liver regeneration. In this study, we comb...

Prediction of inherited metabolic disorders using tandem mass spectrometry data with the help of artificial neural networks.

Turkish journal of medical sciences
BACKGROUND/AIM: Tandem mass spectrometry is helpful in diagnosing amino acid metabolism disorders, organic acidemias, and fatty acid oxidation disorders and can provide rapid and accurate diagnosis for inborn errors of metabolism. The aim of this stu...

In vitro metabolic studies and machine learning analysis of mass spectrometry data: A dual strategy for differentiating alpha-pyrrolidinohexiophenone (α-PHP) and alpha-pyrrolidinoisohexanophenone (α-PiHP) in urine analysis.

Forensic science international
Synthetic cathinones are some of the most prevalent new psychoactive substances (NPSs) globally, with alpha-pyrrolidinoisohexanophenone (α-PiHP) being particularly noted for its widespread use in the United States, Europe, and Taiwan. However, the an...

Predicting glycan structure from tandem mass spectrometry via deep learning.

Nature methods
Glycans constitute the most complicated post-translational modification, modulating protein activity in health and disease. However, structural annotation from tandem mass spectrometry (MS/MS) data is a bottleneck in glycomics, preventing high-throug...

A Support Vector Machine-Assisted Metabolomics Approach for Non-Targeted Screening of Multi-Class Pesticides and Veterinary Drugs in Maize.

Molecules (Basel, Switzerland)
The contamination risks of plant-derived foods due to the co-existence of pesticides and veterinary drugs (P&VDs) have not been fully understood. With an increasing number of unexpected P&VDs illegally added to foods, it is essential to develop a non...

UPLC-Q-TOF-MS/MS combined with machine learning methods for screening quality indicators of Hypericum perforatum L.

Journal of pharmaceutical and biomedical analysis
Hypericum perforatum L. (HPL), also known as St. John's wort, is one of the extensively researched domestically and internationally as a medicinal plant. In this study, non-targeted metabolomics combined with machine learning methods were used to ide...