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Tandem Mass Spectrometry

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Target Cell Extraction and Spectrum-Effect Relationship Coupled with BP Neural Network Classification for Screening Potential Bioactive Components in Ginseng Extract with a Protective Effect against Myocardial Damage.

Molecules (Basel, Switzerland)
Cardiovascular disease has become a common ailment that endangers human health, having garnered widespread attention due to its high prevalence, recurrence rate, and sudden death risk. Ginseng possesses functions such as invigorating vital energy, en...

Determination of Patulin in Apple Juice and Apple-Derived Products Using a Robotic Sample Preparation System and LC-APCI-MS/MS.

Toxins
Patulin, a toxic mycotoxin, can contaminate apple-derived products. The FDA has established an action level of 50 ppb (ng/g) for patulin in apple juice and apple juice products. To effectively monitor this mycotoxin, there is a need for adequate anal...

Predicting the Predicted: A Comparison of Machine Learning-Based Collision Cross-Section Prediction Models for Small Molecules.

Analytical chemistry
The application of machine learning (ML) to -omics research is growing at an exponential rate owing to the increasing availability of large amounts of data for model training. Specifically, in metabolomics, ML has enabled the prediction of tandem mas...

Fragment ion intensity prediction improves the identification rate of non-tryptic peptides in timsTOF.

Nature communications
Immunopeptidomics is crucial for immunotherapy and vaccine development. Because the generation of immunopeptides from their parent proteins does not adhere to clear-cut rules, rather than being able to use known digestion patterns, every possible pro...

Systematic Assessment of Deep Learning-Based Predictors of Fragmentation Intensity Profiles.

Journal of proteome research
In recent years, several deep learning-based methods have been proposed for predicting peptide fragment intensities. This study aims to provide a comprehensive assessment of six such methods, namely Prosit, DeepMass:Prism, pDeep3, AlphaPeptDeep, Pros...

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...

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...

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...