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Tandem Mass Spectrometry

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UPLC-MS/MS Method for Detection of Etomidate and Its Metabolite Etomidate Acid Quantity in Blood.

Fa yi xue za zhi
OBJECTIVES: To establish a method for the simultaneous quantitative analysis of etomidate and its metabolite etomidate acid in blood, and to discuss its application value in actual cases.

Variability analysis of LC-MS experimental factors and their impact on machine learning.

GigaScience
BACKGROUND: Machine learning (ML) technologies, especially deep learning (DL), have gained increasing attention in predictive mass spectrometry (MS) for enhancing the data-processing pipeline from raw data analysis to end-user predictions and rescori...

Deep Learning Based Metabolite Annotation.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Metabolite annotation is a major bottleneck in untargeted metabolomics studies by liquid chromatography coupled with mass spectrometry (LC-MS). This is in part due to the limited publicly available spectral libraries, which consist of tandem mass spe...

Identification, synthesis, and characterization of an unprecedented N-(2-carboxyethyl) adduct impurity in an injectable ganirelix formulation.

Journal of peptide science : an official publication of the European Peptide Society
Ganirelix, a peptide-based drug used to treat female infertility, has been in high market demand, which attracted generic formulation. A hitherto unknown impurity of ganirelix was observed in our formulation process, which reached ~0.3% in 6 months a...

Deep Learning-Enabled MS/MS Spectrum Prediction Facilitates Automated Identification Of Novel Psychoactive Substances.

Analytical chemistry
The market for illicit drugs has been reshaped by the emergence of more than 1100 new psychoactive substances (NPS) over the past decade, posing a major challenge to the forensic and toxicological laboratories tasked with detecting and identifying th...

Deep Learning-Assisted Analysis of Immunopeptidomics Data.

Methods in molecular biology (Clifton, N.J.)
Liquid chromatography-coupled mass spectrometry (LC-MS/MS) is the primary method to obtain direct evidence for the presentation of disease- or patient-specific human leukocyte antigen (HLA). However, compared to the analysis of tryptic peptides in pr...

AttnPep: A Self-Attention-Based Deep Learning Method for Peptide Identification in Shotgun Proteomics.

Journal of proteome research
In shotgun proteomics, the proteome search engine analyzes mass spectra obtained by experiments, and then a peptide-spectra match (PSM) is reported for each spectrum. However, most of the PSMs identified are incorrect, and therefore various postproce...

Prediction of glycopeptide fragment mass spectra by deep learning.

Nature communications
Deep learning has achieved a notable success in mass spectrometry-based proteomics and is now emerging in glycoproteomics. While various deep learning models can predict fragment mass spectra of peptides with good accuracy, they cannot cope with the ...

The combination of deep learning and pseudo-MS image improves the applicability of metabolomics to congenital heart defect prenatal screening.

Talanta
To investigate the metabolic alterations in maternal individuals with fetal congenital heart disease (FCHD), establish the FCHD diagnostic models, and assess the performance of these models, we recruited two batches of pregnant women. By metabolomics...

Prediction of quality markers in Maren Runchang pill for constipation using machine learning and network pharmacology.

Molecular omics
Maren Runchang pill (MRRCP) is a Chinese patent medicine used to treat constipation in clinics. It has multi-component and multi-target characteristics, and there is an urgent need to screen markers to ensure its quality. The aim of this study was to...