AIMC Topic: Mass Spectrometry

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Support Vector Machine Classification of Adulterated Illicit Opioids Using Paper-Spray Mass Spectrometry.

Analytical chemistry
The complexity and potency of the illicit opioid supply in North America has become increasingly concerning for people who use drugs. Drug checking efforts aim to keep up with the evolving psychoactive components present in the illicit drug supply. W...

Mass Spectrometry Proteomics: A Key to Faster Drug Discovery.

Journal of medicinal chemistry
Mass spectrometry (MS)-based proteomics is a disruptive platform in drug discovery that offers an exhaustive view of the proteome's complexity. Focusing on bottom-up MS proteomics, this technology enables high-throughput analysis of protein expressio...

Large Data Set Analysis Reveals Structural Origin of Peptide Collisional Cross Section Bimodal Behavior.

Journal of the American Society for Mass Spectrometry
Recent advances in ion mobility spectrometry have enabled the measurement of rotationally averaged collisional cross-sectional area (CCS) for millions of peptides as part of routine proteomic mass spectrometry workflows. One of the most striking find...

Combining Retip Retention Time Prediction with High-Resolution Mass Spectrometry: A Systematic Analysis of - Conducted for the First Time.

Analytical chemistry
- Herbal Pair (SEHP) is one of the classic Chinese herbal formulas for treating Alzheimer's disease (AD), but its complex chemical composition renders traditional analytical methods inefficient. Retention time (RT) provides complementary information ...

Machine Learning-Assisted False Positive Detection in Metabolite Identification Workflows.

Analytical chemistry
Metabolite identification is a pivotal step in drug discovery and development, enabling the comprehensive analysis of drug-derived compounds within biological systems. However, the complexity of liquid chromatography-mass spectrometry data often resu...

RSR-MSI: Reference-Based Super-Resolution for Mass Spectrometry Imaging of Tissues and Single Cells.

Analytical chemistry
High-spatial-resolution mass spectrometry imaging (MSI) visualizes molecular distributions in tissues and cells. However, achieving higher spatial resolution typically necessitates smaller pixel dimensions and an increased number of pixels, leading t...

Integrated Metabolomics and Lipidomics of Tissue and Serum Reveal Mechanistic Pathways and Lipid Signatures Distinguishing Meningioma Grades.

Journal of proteome research
Meningioma, the most prevalent primary intracranial tumor, presents significant clinical challenges due to unclear molecular mechanisms underlying its progression from low-grade (LG) to high-grade (HG) and lack of grade-specific biomarkers. Here, we ...

Resolution-Adaptive Binning Enhances Machine Learning Modeling by Interbatch and Multiplatform Orbitrap-Based Shotgun Mass Spectrometry Data Integration.

Analytical chemistry
Machine learning (ML) modeling on mass spectrometry (MS)-based shotgun data facilitates feature selection and disease modeling. However, batch-specific models often struggle with limited transferability and generalizability, necessitating data integr...

MSformer: A Meta-Structure Based Interpretable Framework for Representation Learning of Natural Products.

Analytical chemistry
Natural products (NPs) are a treasure trove of drug discovery, yet their structural complexity and extreme data scarcity critically hinder AI-driven exploration. To address this challenge, we present MSformer, a transformer-based architecture that br...

Integrating Model-Based Reconstruction and Deep Learning for Accelerating Mass Spectrometry Imaging.

Analytical chemistry
Mass spectrometry imaging (MSI) is a powerful multiplexed biochemical imaging modality. It relies on raster scanning for localized data acquisition, which can be time-consuming, limiting applications of high-resolution tissue mapping and 3D reconstru...