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Related Concept Videos

Volatilization01:10

Volatilization

362
Volatilization gravimetry is an analytical technique that measures the mass lost due to the volatilization of the substance. This technique is used to estimate the amount of volatile material in a sample. To perform this method, heat a known amount of the sample to a high temperature in a crucible or other suitable vessel. The volatile substance in the sample evaporates, and the vapor is completely expelled from the crucible either by heating the sample or bubbling a stream of inert gas through...
362
Voltammetry: Stripping Methods01:13

Voltammetry: Stripping Methods

177
Anodic Stripping Voltammetry (ASV), Cathodic Stripping Voltammetry (CSV), and Adsorptive Stripping Voltammetry (AdSV) are electrochemical techniques used to determine trace amounts of analytes in solution. These methods involve applying a potential to an electrode and measuring the resulting current.
Anodic Stripping Voltammetry (ASV)
ASV is used to determine metals and metalloids at trace levels. It involves two steps: deposition and stripping. First, a negative potential is applied to the...
177
Sample Preparation for Analysis: Overview01:21

Sample Preparation for Analysis: Overview

191
Sample preparation is an essential step in the analytical process. It involves preparing a sample so that it can be analyzed accurately. The goal is to extract the analyte, the substance you want to measure, from the sample while removing any components that may interfere with the analysis. Sample preparation techniques vary depending on the physical state of the sample.
Bulk or large solid samples are typically reduced in size using grinding, crushing, or milling techniques to increase the...
191
Voltammograms: Overview01:16

Voltammograms: Overview

168
Voltammograms are current plots as a function of applied potential, offering insights into electrochemical systems. The shape of a voltammogram depends on how the current is measured and whether convection (heat transfer by fluid movement) is present or absent.
Shapes of Voltammograms
168
Voltammetry: Overview01:20

Voltammetry: Overview

1.2K
Voltammetry is an electroanalytical technique in which the current flowing through an electrochemical cell is measured as a function of applied potential, typically under conditions of concentration polarization. The technique provides valuable information about redox-active species, and the current response is plotted as a voltammogram.
A voltammetric cell uses three electrodes: a working electrode, a reference electrode, and an auxiliary electrode. The redox reactions occur in the working...
1.2K

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Updated: Jun 5, 2025

Untargeted Metabolomics from Biological Sources Using Ultraperformance Liquid Chromatography-High Resolution Mass Spectrometry UPLC-HRMS
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A comprehensive guide to volatolomics data analysis.

M Skawinski1, F J van Schooten1, A Smolinska1

  • 1Department of Pharmacology and Toxicology, Institute of Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University, Maastricht, The Netherlands.

Journal of Breath Research
|December 6, 2024
PubMed
Summary

Volatolomics, the study of volatile organic compounds, offers non-invasive disease diagnostics. This guide details data analysis methods for accurate metabolite identification and reliable disease monitoring using complex biological data.

Keywords:
data pretreatmentmachine learningmass spectrometrymultivariate data analysisvolatile organic compounds (VOCs)volatolomics

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Area of Science:

  • Metabolomics
  • Analytical Chemistry
  • Bioinformatics

Background:

  • Volatolomics, the study of volatile organic compounds (VOCs), is a growing field within metabolomics.
  • It holds significant promise for non-invasive diagnostics and disease monitoring.
  • Analyzing high-resolution data from instruments like mass spectrometry and gas sensor arrays presents challenges.

Purpose of the Study:

  • To provide a comprehensive guide to volatolomics data analysis.
  • To highlight essential steps for enhancing data quality and analytical outcomes.
  • To empower researchers with knowledge for navigating complex volatolomics datasets.

Main Methods:

  • Exploration of data cleaning and pretreatment strategies.
  • Application of statistical and machine learning techniques (dimensionality reduction, clustering, classification, variable selection).
  • Discussion of data handling practices: missing data imputation, outlier detection, model validation, and data integration.

Main Results:

  • Emphasizes the critical role of method selection and data handling in identifying meaningful metabolites.
  • Demonstrates how robust analysis leads to accurate diagnostic conclusions.
  • Underscores the importance of understanding method strengths and limitations for reliable findings.

Conclusions:

  • Informed decision-making in volatolomics data analysis enhances finding reliability.
  • This guide advances the field by improving the understanding of metabolic processes in health and disease.
  • Effective volatolomics data analysis is key to unlocking its diagnostic potential.