AIMC Topic: Mass Spectrometry

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Insights into the transformation of natural organic matter during UV/peroxydisulfate treatment by FT-ICR MS and machine learning: Non-negligible formation of organosulfates.

Water research
Natural organic matter (NOM) is a major sink of radicals in advanced oxidation processes (AOPs) and understanding the transformation of NOM is important in water treatment. By using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR ...

Rapid and non-destructive microbial quality prediction of fresh pork stored under modified atmospheres by using selected-ion flow-tube mass spectrometry and machine learning.

Meat science
Volatile organic compounds (VOCs) indicative of pork microbial spoilage can be quantified rapidly at trace levels using selected-ion flow-tube mass spectrometry (SIFT-MS). Packaging atmosphere is one of the factors influencing VOC production patterns...

Ultra-sensitive analysis of exhaled biomarkers in ozone-exposed mice via PAI-TOFMS assisted with machine learning algorithms.

Journal of hazardous materials
Ground-level ozone ranks sixth among common air pollutants. It worsens lung diseases like asthma, emphysema, and chronic bronchitis. Despite recent attention from researchers, the link between exhaled breath and ozone-induced injury remains poorly un...

PSMS: A Deep Learning-Based Prediction System for Identifying New Psychoactive Substances Using Mass Spectrometry.

Analytical chemistry
The rapid proliferation of new psychoactive substances (NPS) poses significant challenges to conventional mass-spectrometry-based identification methods due to the absence of reference spectra for these emerging substances. This paper introduces PSMS...

Rapid classification of coffee origin by combining mass spectrometry analysis of coffee aroma with deep learning.

Food chemistry
Mislabeling the geographical origin of coffee is a prevalent form of fraud. In this study, a rapid, nondestructive, and high-throughput method combining mass spectrometry (MS) analysis and intelligence algorithms to classify coffee origin was develop...

DeepION: A Deep Learning-Based Low-Dimensional Representation Model of Ion Images for Mass Spectrometry Imaging.

Analytical chemistry
Mass spectrometry imaging (MSI) is a high-throughput imaging technique capable of the qualitative and quantitative in situ detection of thousands of ions in biological samples. Ion image representation is a technique that produces a low-dimensional v...

Multiscale biochemical mapping of the brain through deep-learning-enhanced high-throughput mass spectrometry.

Nature methods
Spatial omics technologies can reveal the molecular intricacy of the brain. While mass spectrometry imaging (MSI) provides spatial localization of compounds, comprehensive biochemical profiling at a brain-wide scale in three dimensions by MSI with si...

Personalized Drug Therapy: Innovative Concept Guided With Proteoformics.

Molecular & cellular proteomics : MCP
Personalized medicine can reduce adverse effects, enhance drug efficacy, and optimize treatment outcomes, which represents the essence of personalized medicine in the pharmacy field. Protein drugs are crucial in the field of personalized drug therapy...

Deep learning-assisted mass spectrometry imaging for preliminary screening and pre-classification of psychoactive substances.

Talanta
Currently, it is of great urgency to develop a rapid pre-classification and screening method for suspected drugs as the constantly springing up of new psychoactive substances. In most researches, psychoactive substances classification approaches depe...

Deep Learning Enables Automatic Correction of Experimental HDX-MS Data with Applications in Protein Modeling.

Journal of the American Society for Mass Spectrometry
Observed mass shifts associated with deuterium incorporation in hydrogen-deuterium exchange mass spectrometry (HDX-MS) frequently deviate from the initial signals due to back and forward exchange. In typical HDX-MS experiments, the impact of these di...