Metabolomics FAQ

• • What Are the Effective Strategies for Removing Impurities from Crude Polysaccharide Extracts?

  Polysaccharides are macromolecular compounds composed of multiple monosaccharide units and exhibit a wide range of biological activities and potential applications. Crude extracts of polysaccharides often contain various impurities, including proteins, nucleic acids, pigments, and minerals, among others. The choice of impurity removal strategies typically depends on the source, structural characteristics, and physicochemical properties of the polysaccharide, as well as the nature of the impurities pre......

• • What Analytical Techniques Are Available for the Detection of Bile Acids in Fecal Samples?

  The detection of bile acids in fecal samples primarily relies on advanced biochemical analytical techniques characterized by high sensitivity and efficiency. Commonly employed methods include the following:   Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS) LC-MS/MS enables comprehensive structural and quantitative profiling of bile acids. Owing to its high sensitivity and specificity, it is particularly well-suited for analyzing multiple bile acid species in complex biological matrices such ......

• • How Are Lipids Extracted and Exosomes Isolated in Lipidomics Research?

  In lipidomics research, the extraction of lipids and the isolation of exosomes represent two essential procedures. The following summarizes widely adopted techniques for both processes:   Lipid Extraction Two classical protocols are commonly employed: the Folch and Bligh-Dyer methods.   1. Folch Method Samples are mixed with a chloroform–methanol solution at a 2:1 (v/v) ratio, followed by the addition of saline to induce phase separation. This results in a biphasic system: the upper aqueous/methanol p......

• • How Should Non-Normally Distributed Data Be Addressed in Univariate Statistical Analysis?

  In univariate statistical analysis, data normality is typically a key assumption underlying parametric testing. When data deviate from a normal distribution, several strategies can be employed to address this issue:   Applying Data Transformations Transformations such as logarithmic, square root, or Box-Cox can help approximate normality. Following transformation, the data's distribution should be reassessed for normality before proceeding with parametric analyses.   Employing Non-Parametric Tests If ......

• • How Can PLS Analysis Be Conducted in SIMCA-P?

  SIMCA-P is a professional statistical software that provides a user-friendly interface and robust analytical tools. Conducting Partial Least Squares (PLS) analysis using SIMCA-P involves the following steps:   1. Data Preparation (1) Data Format: Ensure that the dataset is imported in a format compatible with SIMCA-P, typically CSV or Excel. (2) Data Organization: Structure the dataset such that samples are arranged in rows and variables in columns. For instance, in metabolomics studies, each row corr......

• • How Can the Water Solubility of Bletilla Polysaccharides Be Improved After Vacuum Drying?

  The poor water solubility of Bletilla polysaccharides after vacuum drying may result from their molecular structure or physical alterations occurring during the drying process. Several strategies can be employed to enhance their solubility:   Physical Modification 1. Fine Grinding Reducing the particle size of polysaccharide powders increases their surface area, promoting faster dissolution.   2. Ultrasonic treatment Applying ultrasound can disrupt polysaccharide aggregates and enhance interactions wi......

• • What Are the Methods for Detecting Serum Metabolomics Indicators?

  Serum metabolomics is a field of study that investigates metabolic profiles by analyzing small-molecule metabolites in serum. This approach provides critical insights into biochemical processes and disease states. The primary detection indicators and analytical methods in serum metabolomics are outlined below.   Detection Indicators 1. Small-Molecule Metabolites Key metabolic components, including amino acids, fatty acids, carbohydrates, nucleotides, and vitamins.   2. Energy Metabolites Molecules inv......

• • How to Analyze and Present Non-Targeted Metabolomics Data Without a Control Group?

  If a study aims to investigate the composition of non-targeted metabolites without including a control group, the following analytical steps can be used to process and interpret the data:   Data Analysis Workflow 1. Data Preprocessing (1) Peak Detection and Integration: Utilize specialized software tools to detect and integrate peaks in mass spectrometry data, ensuring accurate metabolite signal extraction. (2) Signal Correction: Apply baseline correction, noise filtering, and normalization techniques......

• • What Are the Key Metabolomics Techniques and Their Distinctive Features?

  Metabolomics is the study of the comprehensive profile of metabolites in biological systems and their dynamic variations. Various analytical techniques are employed to detect and quantify metabolites in biological samples. Below are the major metabolomics techniques and their unique characteristics:   Characteristics of Nuclear Magnetic Resonance (NMR) Spectroscopy 1. Non-destructive method, suitable for analyzing live cells and tissues without compromising sample integrity. 2. Highly effective for st......

• • Is PLS-DA or OPLS-DA Generally Used to Evaluate Model Predictive Performance?

  When choosing between PLS-DA (Partial Least Squares Discriminant Analysis) and OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) for evaluating a model’s predictive performance, one must consider the data characteristics and the specific research objectives. Both methods are employed for multivariate statistical analysis and are widely used in metabolomics and chemometrics; however, they exhibit key differences:   PLS-DA PLS-DA is a supervised learning method designed to build models th......