Pressure Gradient Modeling
Pressure Gradient Modeling - Related Videos
07:26
Synthesis and Microdiffraction at Extreme Pressures and Temperatures
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Cited by 5 •
2013
The laser heated diamond anvil cell combined with synchrotron micro-diffraction techniques allows researchers to explore the nature and properties of new phases of matter at extreme pressure and temperature (PT) conditions. Heterogeneous samples can be characterized in situ under high pressure by 2D mapping and combined powder, single-crystal and multigrain diffraction approaches.
07:10
Measurement of the Hepatic Venous Pressure Gradient and Transjugular Liver Biopsy
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Cited by 110 •
2020
Here, we present a protocol for measurement of hepatic venous pressure gradient (HVPG),the gold standard to diagnose clinically significant portal hypertension. Moreover, we describe how to perform a transjugular liver biopsy within the same session.
08:42
Density Gradient Ultracentrifugation
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2023
Density gradient ultracentrifugation is a common technique used to isolate and purify biomolecules and cell structures. This technique exploits the fact that, in suspension, particles that are more dense than the solvent will sediment, while those that are less dense will float. A high-speed ultracentrifuge is used to accelerate this process in order to separate biomolecules within a density gradient, which can be established by layering liquids of decreasing density in a centrifuge tube. The...
10:18
Ascending Aortic Constriction in Rats for Creation of Pressure Overload Cardiac Hypertrophy Model
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Cited by 17 •
2014
We describe a stepwise procedure for creating pressure overload and left ventricular hypertrophy in Wistar rats by constriction of the ascending aorta using a small metallic clip. This model is extensively used for studying remodeling changes during cardiac hypertrophy and for identifying and evaluating strategies for regression of such changes.
03:18
Developing a Translaminar Pressure Model Using a Translaminar Autonomous System
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2025
Source: Sharma, T. P., et al., Translaminar Autonomous System Model for the Modulation of Intraocular and Intracranial Pressure in Human Donor Posterior Segments. J. Vis. Exp. (2020).This video demonstrates the procedure of preparing a human eye to study the effects of translaminar pressure on retinal ganglion cell signaling by simulating intraocular and intracranial pressures in a translaminar autonomous system.
FAQs
Geometry, material properties, and boundary conditions determine how pressure differences are represented and how the modeled system responds. Geometry describes the spatial arrangement of vessels, cerebrospinal fluid spaces, or tissue, while material properties characterize relevant deformation behavior. Boundary conditions specify constraints at system limits. Changing any of these inputs can alter predicted flow, stress, or pressure distribution.
The model uses fluid-flow equations to relate spatial pressure differences to flow velocity and resistance. When tissue or other structures can deform, the same pressure information can also be connected with material behavior and tissue stress. This combined perspective helps explain how altered pressure conditions may influence transport, deformation, and intracranial dynamics rather than treating pressure as an isolated measurement.
Pressure may be evaluated within blood vessels, cerebrospinal fluid spaces, or brain tissue, and each location represents a different part of intracranial dynamics. Modeling these spaces allows pressure differences to be related to cerebral perfusion, cerebrospinal fluid circulation, or tissue stress. This compartment-specific view supports more meaningful interpretation of how pressure changes affect neural-system transport and deformation.
A study begins by representing the relevant geometry and identifying the fluid or tissue region being examined. Researchers then select fluid-flow equations, assign material properties, and specify boundary conditions before calculating pressure-related variables. The resulting simulation can be compared with experimental data or used to examine how changes in pressure conditions influence velocity, resistance, stress, or intracranial behavior.
It is useful when researchers need to examine how pressure differences affect cerebral perfusion, cerebrospinal fluid circulation, brain swelling, or other changes in intracranial dynamics. The approach can connect calculated pressure patterns with flow and tissue responses, helping organize observations from biological systems and supporting analysis of disorders involving altered pressure.
Simulation results provide calculated relationships among pressure gradients, flow velocity, resistance, tissue stress, and intracranial dynamics. Researchers can use those relationships to interpret experimental data and examine how modeled pressure changes might affect cerebral or cerebrospinal fluid behavior. This makes the approach useful for evaluating potential interventions in conditions characterized by altered pressure, while keeping conclusions tied to the modeled assumptions.