AIMC Topic: Tandem Mass Spectrometry
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A large-scale multicenter study of reference intervals and clinical potential for homocysteine-folate cycle metabolites in Northern Chinese population.
Clinica chimica acta; international journal of clinical chemistry
Mar 27, 2025
OBJECTIVES: The study was conducted to establish the reference intervals of homocysteine-folate cycle metabolites based on the healthy population from multiple centers in northern China, and determine their clinical significance in the diagnosis of r...
Bioactivity of Juglans regia kernel extracts optimized using response surface method and artificial neural Network-Genetic algorithm integration.
Scientific reports
Mar 15, 2025
In this study, the biological activities of the extracts obtained under optimum extraction conditions of the kernel part of Juglans regia L. were determined. Two different methods, Response Surface Method (RSM) and Artificial Neural Network-Genetic A...
SWAPS: A Modular Deep-Learning Empowered Peptide Identity Propagation Framework Beyond Match-Between-Run.
Journal of proteome research
Mar 7, 2025
Mass spectrometry (MS)-based proteomics relies heavily on MS/MS (MS2) data, which do not fully exploit the available MS1 information. Traditional peptide identity propagation (PIP) methods, such as match-between-runs (MBR), are limited to similar run...
FIORA: Local neighborhood-based prediction of compound mass spectra from single fragmentation events.
Nature communications
Mar 7, 2025
Non-targeted metabolomics holds great promise for advancing precision medicine and biomarker discovery. However, identifying compounds from tandem mass spectra remains a challenging task due to the incomplete nature of spectral reference libraries. A...
Machine Learning-Based Identification of Novel Exosome-Derived Metabolic Biomarkers for the Diagnosis of Systemic Lupus Erythematosus and Differentiation of Renal Involvement.
Current medical science
Feb 28, 2025
OBJECTIVE: This study aims to investigate the exosome-derived metabolomics profiles in systemic lupus erythematosus (SLE), identify differential metabolites, and analyze their potential as diagnostic markers for SLE and lupus nephritis (LN).
Machine Learning in Small-Molecule Mass Spectrometry.
Annual review of analytical chemistry (Palo Alto, Calif.)
Feb 27, 2025
Tandem mass spectrometry (MS/MS) is crucial for small-molecule analysis; however, traditional computational methods are limited by incomplete reference libraries and complex data processing. Machine learning (ML) is transforming small-molecule mass s...
IodoFinder: Machine Learning-Guided Recognition of Iodinated Chemicals in Nontargeted LC-MS/MS Analysis.
Environmental science & technology
Feb 27, 2025
Iodinated disinfection byproducts (I-DBPs) pose significant health concerns due to their high toxicity. Current approaches to recognize unknown I-DBPs in mass spectrometry (MS) analysis rely on negative ionization mode, in which the characteristic I ...
Serum Metabolomics Profiling Coupled with Machine Learning Identifies Potential Diagnostic and Prognostic Candidate Markers in Meningioma Using Raman Spectroscopy, ATR-FTIR, and LC-MS/MS.
Journal of proteome research
Feb 25, 2025
Meningioma, the most prevalent brain tumor, poses significant challenges due to its unclear transition from low-grade to aggressive forms, with limited knowledge about grade-specific markers. We have utilized vibrational spectroscopic techniques such...
Spectroscopy, Fourier Transform Infrared
Metabolomics
Chromatography, Liquid
Meningioma
Meningeal Neoplasms
Liquid Chromatography-Mass Spectrometry
Machine Learning
Tandem Mass Spectrometry
Prognosis
Middle Aged
Female
Humans
Adult
Case-Control Studies
Aged
Biomarkers, Tumor
Spectrum Analysis, Raman
Male
Machine Learning-Based Bioactivity Classification of Natural Products Using LC-MS/MS Metabolomics.
Journal of natural products
Feb 7, 2025
The rediscovery of known drug classes represents a major challenge in natural products drug discovery. Compound rediscovery inhibits the ability of researchers to explore novel natural products and wastes significant amounts of time and resources. Th...
An AI-assisted morphoproteomic approach is a supportive tool in esophagitis-related precision medicine.
EMBO molecular medicine
Feb 3, 2025
Esophagitis is a frequent, but at the molecular level poorly characterized condition with diverse underlying etiologies and treatments. Correct diagnosis can be challenging due to partially overlapping histological features. By proteomic profiling of...
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