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Spectrometry, Mass, Electrospray Ionization

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Sodium adduct formation with graph-based machine learning can aid structural elucidation in non-targeted LC/ESI/HRMS.

Analytica chimica acta
Non-targeted screening with LC/ESI/HRMS aims to identify the structure of the detected compounds using their retention time, exact mass, and fragmentation pattern. Challenges remain in differentiating between isomeric compounds. One untapped possibil...

HPLC-MS/MS method for the determination and pharmacokinetic study of six compounds against rheumatoid arthritis in rat plasma after oral administration of the extract of Caulophyllum robustum Maxim.

Journal of pharmaceutical and biomedical analysis
Caulophyllum robustum Maxim (CRM) is a well-known traditional Chinese medicine (TCM) mainly present in the northeast, northwest and southwest regions of China, which is belong to the family Berberidaceae. The roots and rhizomes of CRM have been used ...

Predicting Breast Cancer by Paper Spray Ion Mobility Spectrometry Mass Spectrometry and Machine Learning.

Analytical chemistry
Paper spray ionization has been used as a fast sampling/ionization method for the direct mass spectrometric analysis of biological samples at ambient conditions. Here, we demonstrated that by utilizing paper spray ionization-mass spectrometry (PSI-MS...

Applications of Machine Learning to In Silico Quantification of Chemicals without Analytical Standards.

Journal of chemical information and modeling
Non-targeted analysis provides a comprehensive approach to analyze environmental and biological samples for nearly all chemicals present. One of the main shortcomings of current analytical methods and workflows is that they are unable to provide any ...

Towards compound identification of synthetic opioids in nontargeted screening using machine learning techniques.

Drug testing and analysis
The constant evolution of the illicit drug market makes the identification of unknown compounds problematic. Obtaining certified reference materials for a broad array of new analogues can be difficult and cost prohibitive. Machine learning provides a...

A new rapid diagnostic system with ambient mass spectrometry and machine learning for colorectal liver metastasis.

BMC cancer
BACKGROUND: Probe electrospray ionization-mass spectrometry (PESI-MS) can rapidly visualize mass spectra of small, surgically obtained tissue samples, and is a promising novel diagnostic tool when combined with machine learning which discriminates ma...

Changes of Mass Spectra Patterns on a Brain Tissue Section Revealed by Deep Learning with Imaging Mass Spectrometry Data.

Journal of the American Society for Mass Spectrometry
The characteristic patterns of mass spectra in imaging mass spectrometry (IMS) strongly reflect the tissue environment. However, the boundaries formed where different tissue environments collide have not been visually assessed. In this study, IMS and...

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...

Machine Learning-Based Integrated Multiomics Characterization of Colorectal Cancer Reveals Distinctive Metabolic Signatures.

Analytical chemistry
The metabolic signature identification of colorectal cancer is critical for its early diagnosis and therapeutic approaches that will significantly block cancer progression and improve patient survival. Here, we combined an untargeted metabolic analys...