Bead Depth Quantification
Bead Depth Quantification - Related Videos
08:01
LERLIC-MS/MS for In-depth Characterization and Quantification of Glutamine and Asparagine Deamidation in Shotgun Proteomics
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Cited by 6 •
2017
Here we present a step-by-step protocol of the long-length electrostatic repulsion-hydrophilic interaction chromatography-tandem mass spectrometry (LERLIC-MS/MS) method. This is a novel methodology that enables for the first time quantification and characterization of the glutamine and asparagine deamidation isoforms by shotgun proteomics.
14:11
Quantification of Hydrogen Concentrations in Surface and Interface Layers and Bulk Materials through Depth Profiling with Nuclear Reaction Analysis
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Cited by 21 •
2016
We illustrate the application of 1H(15N,αγ)12C resonant nuclear reaction analysis (NRA) to quantitatively evaluate the density of hydrogen atoms on the surface, in the volume, and at an interfacial layer of solid materials. The near-surface hydrogen depth profiling of a Pd(110) single crystal and of SiO2/Si(100) stacks is described.
01:27
Uniform Depth Channel Flow
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2025
Uniform depth channel flow keeps fluid depth consistent along channels such as irrigation canals. In natural channels, such as rivers, approximate uniform flow is often assumed. This condition occurs when the channel’s bottom slope matches the energy slope, balancing potential energy lost from gravity with head loss due to shear stress. This balance prevents depth changes along the channel length, resulting in a steady, uniform flow.Uniform flow in open channels with a constant cross-section...
01:15
Depth Perception and Spatial Vision
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2024
Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.
11:52
Microbubble Fabrication of Concave-porosity PDMS Beads
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Cited by 2 •
2015
Procedures used to generate microstructured concave-porosity polydimethylsiloxane beads are presented. Effects of electrolyte concentration and identity within the aqueous phase are particularly emphasized.
FAQs
Spatial calibration links a bead’s observed position in an optical section to a physical location along the z-axis. The analysis identifies detectable bead signals and then uses the calibration to express their positions relative to a defined surface or reference plane. This conversion makes measurements comparable across locations within scaffolds, hydrogels, tissues, or other engineered constructs.
A defined reference plane establishes the zero point for depth measurements. If that plane is inconsistent or poorly assigned, the same bead position can receive different depth values, making spatial comparisons unreliable. Referencing all bead locations to the relevant sample surface or internal plane allows the dataset to describe particle location consistently within a three-dimensional material.
Bead depth adds an axial dimension to bead localization, allowing signals at different positions within a three-dimensional sample to be distinguished. The resulting measurements can show whether beads are concentrated near a surface, distributed throughout a construct, or located at specific internal regions. This helps reveal structural organization, penetration, and localization rather than simple bead presence alone.
A workflow generally begins by imaging the sample in optical sections that capture detectable bead signals. The signals are then identified, their positions along the z-axis are determined, and those positions are converted into depth values through spatial calibration. Finally, the values are interpreted relative to a defined reference plane to evaluate bead distribution within the sample or construct.
In bioengineering, the approach can be applied to scaffolds, hydrogels, tissues, and microfluidic systems when beads serve as detectable spatial markers. Measuring their axial positions helps characterize how particles are distributed or localized within these environments. The resulting spatial information supports evaluation of material structure and how engineered systems interact with embedded or transported beads.
Changes in bead location through the depth of a construct can provide spatial evidence about penetration and distribution. Examining where detectable beads occur relative to a surface or internal reference plane helps indicate whether particles remain near an interface or reach deeper regions. In engineered materials and biological environments, these patterns can support interpretation of transport behavior.
Depth measurements provide spatial data that can be compared with the intended organization or performance of an engineered construct. Bead distribution and localization may reveal whether particles occupy expected regions within scaffolds, hydrogels, tissues, or microfluidic systems. This makes the method useful for validating structural organization and assessing particle interactions in complex bioengineered environments.