AIMC Topic: Mass Spectrometry

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Revisiting In-Gas Transformations of Quinate Conjugates Through the LC-qTOF-MS and Molecular Networking Topology.

Rapid communications in mass spectrometry : RCM
RATIONALE: The emergence of computational metabolomics tools such as molecular networking and machine learning-based platforms like SIRIUS has significantly advanced MS-based metabolomics studies. These tools enable rapid metabolite identification by...

AI-powered insights into the UniSpray ionization in supercritical fluid chromatography-mass spectrometry.

Journal of chromatography. A
Selection of the optimal makeup solvent composition is critical for achieving sensitive and reproducible ionization in supercritical fluid chromatography-mass spectrometry (SFC-MS). This study investigated the ionization processes in a spray-based io...

The Future of a Myriad of Accelerated Biodiscoveries Lies in AI-Powered Mass Spectrometry and Multiomics Integration.

Journal of mass spectrometry : JMS
The intersection of modern artificial intelligence (AI) and mass spectrometry (MS) is set to transform the MS-based "omics" research fields, particularly proteomics, metabolomics, lipidomics, and glycomics, enabling advancements across a wide range o...

Circulating Proteomic Panels for Noninvasive Diagnosis and Prognostication of Thromboangiitis Obliterans.

Journal of proteome research
Thromboangiitis obliterans (TAO) is often diagnosed late and characterized by high amputation rates. TAO-specific early diagnostic and disease-staging biomarkers are urgently needed. A staged mass spectrometry (MS)-based discovery-verification-valida...

Assessing the Impact of Measurement Precision on Metabolite Identification Probability in Multidimensional Mass Spectrometry-Based, Reference-Free Metabolomics.

Analytical chemistry
Identification of compounds with minimal ambiguity remains a central challenge in mass spectrometry-based metabolomics. Conventional compound identification relies on comparing analytical signatures (e.g., mass-to-charge ratio, collision cross sectio...

Next generation technologies for protein structure determination: challenges and breakthroughs in plant biology applications.

Journal of plant physiology
Advancements in structural biology have significantly deepened our understanding of plant proteins, which are central to critical biological functions such as photosynthesis, metabolism, signal transduction, and structural architechture. Gaining insi...

To Fly, or Not to Fly, That Is the Question: A Deep Learning Model for Peptide Detectability Prediction in Mass Spectrometry.

Journal of proteome research
Identifying detectable peptides, known as flyers, is key in mass spectrometry-based proteomics. Peptide detectability is strongly related to peptide sequences and their resulting physicochemical properties. Moreover, the high variability in MS data c...

Extracting Residue Solvent Exposure from Covalent Labeling Data with Machine Learning: A Hybrid Approach for Protein Structure Prediction.

Journal of the American Society for Mass Spectrometry
Hydroxyl radical protein footprinting (HRPF) coupled with mass spectrometry yields information about residue solvent exposure and protein topology. However, data from these experiments are sparse and require computational interpretation to generate u...

Early Prediction of Septic Shock in Emergency Department Using Serum Metabolites.

Journal of the American Society for Mass Spectrometry
Early recognition of septic shock is crucial for improving clinical management and patient outcomes, especially in the emergency department (ED). This study conducted serum metabolomic profiling on ED patients diagnosed with septic shock (n = 32) and...

An end-to-end mass spectrometry data classification model with a unified architecture.

Scientific reports
Mass spectrometry, known for its high sensitivity, selectivity, rich structural information, and rapid analysis capabilities, is widely used in disease diagnosis and bioanalysis. Despite progress in classification methods/tools for data collection in...