Particle Analysis
Particle Analysis - Related Videos
07:38
Open-source Single-particle Analysis for Super-resolution Microscopy with VirusMapper
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Cited by 9 •
2017
This manuscript uses the Fiji-based open-source software package VirusMapper to apply single-particle analysis to super-resolution microscopy images in order to generate precise models of nanoscale structure.
02:56
Fluorescence-Based Sorting of Individual Virus Particles for Genomic Analysis
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2026
Source: Zeigler Allen, L., et al. Isolation and Genome Analysis of Single Virions using 'Single Virus Genomics'. J. Vis. Exp. (2013).This video demonstrates how flow cytometry enables the isolation of individual, genome-containing viruses from mixed populations through fluorescence-based detection and precise particle sorting, followed by agarose embedding for subsequent genomic characterization.
13:28
High-resolution Single Particle Analysis from Electron Cryo-microscopy Images Using SPHIRE
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Cited by 218 •
2017
This paper presents a protocol for processing cryo-EM images using the software suite SPHIRE. The present protocol can be applied for nearly all single particle EM projects that target near-atomic resolution.
10:42
Flow Cytometric Analysis of Particle-bound Bet v 1 Allergen in PM10
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Cited by 8 •
2016
Here, we present a protocol to quantify allergen-loaded particles by flow cytometry. Ambient particulate matter particles may act as carriers of adsorbed allergens. We show here that flow cytometry, a method widely used to characterize suspended solids >0.5 µm in diameter, can be used to measure these allergen-loaded particles.
03:37
Subatomic Particles
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2020
Dalton was only partially correct about the particles that make up matter. All matter is composed of atoms, and atoms are composed of three smaller subatomic particles: protons, neutrons, and electrons. These three particles account for the mass and the charge of an atom. The Discovery of the Electron The first clue about the subatomic structure came at the end of the 19th century when J.J. Thomson discovered the electron using a cathode ray tube. This apparatus consisted of a sealed glass...
FAQs
Particle Analysis can produce different measurements because instruments interrogate particles through different physical signals. Some systems separate particles according to physical behavior, whereas others detect light scattering, movement through a fluid, imaging features, or spectroscopic responses. The selected signal determines whether the result emphasizes population size, concentration, shape, composition, or surface characteristics.
The measured outcome depends on the particle features that the selected method can resolve. Size and concentration describe population abundance, while shape and surface characteristics provide structural information. Composition adds a chemical perspective. Because these properties answer different questions, method selection should reflect whether the study focuses on particle populations, physical form, or molecular characteristics.
Separation-based approaches distinguish particles through differences in physical behavior, producing information about how populations partition under the measurement conditions. Light-scattering methods instead detect how particles interact with light, while imaging records visible structural features. These approaches are complementary: separation can emphasize population behavior, whereas imaging and scattering can characterize appearance or particle-associated signals.
Imaging can provide information about particle shape and visible structural features, while spectroscopy can contribute evidence about composition or surface characteristics. In neuroscience, these measurements can be applied to extracellular vesicles, protein aggregates, nanoparticles, and other particulate materials associated with neural cells or brain tissue. Together, they support more detailed characterization than a single population measurement alone.
Researchers should first identify the property most relevant to the biological question, such as size, concentration, shape, composition, or surface features. They can then select an approach based on whether the instrument separates particles, detects light scattering or fluid movement, or applies imaging and spectroscopy. This alignment helps ensure that the resulting measurements address the intended neural system or material.
In neuroscience, particle analysis helps characterize extracellular vesicles and protein aggregates associated with neural cells and brain tissue. Measurements can describe differences in particle populations and their physical or compositional features. Such characterization supports investigations of cellular communication and can help researchers examine how particulate materials relate to nervous-system development, disease, or treatment.
Comparing particle measurements across development, disease, or treatment can reveal changes in neural-associated particle populations. These results may support biomarker research by identifying measurable population differences, drug delivery studies by characterizing nanoparticles, and investigations of cellular communication through extracellular vesicles. The value lies in connecting quantitative particle properties with a defined biological or experimental context.