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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
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The Fluid Mosaic Model01:34

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The fluid mosaic model was first proposed as a visual representation of research observations. The model comprises the composition and dynamics of membranes and serves as a foundation for future membrane-related studies. The model depicts the structure of the plasma membrane with a variety of components, which include phospholipids, proteins, and carbohydrates. These integral molecules are loosely bound, defining the cell’s border and providing fluidity for optimal function.
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Fluid Mosaic Model01:19

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Scientists identified the plasma membrane in the 1890s and its principal chemical components (lipids and proteins) by 1915. The model for plasma membrane structure, proposed in 1935 by Hugh Davson and James Danielli, was the first model to be widely accepted in the scientific community. The model was based on the plasma membrane's "railroad track" appearance in early electron micrographs. Davson and Danielli theorized that the plasma membrane's structure resembled a sandwich...
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pH Scale02:41

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Hydronium and hydroxide ions are present both in pure water and in all aqueous solutions, and their concentrations are inversely proportional as determined by the ion product of water (Kw). The concentrations of these ions in a solution are often critical determinants of the solution’s properties and the chemical behaviors of its other solutes. Two different solutions can differ in their hydronium or hydroxide ion concentrations by a million, billion, or even trillion times. A common means of...
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Heart Valves01:16

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Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)01:20

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Related Experiment Video

Updated: Jan 24, 2026

Isolation and Characterization of Primary Rat Valve Interstitial Cells: A New Model to Study Aortic Valve Calcification
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Isolation and Characterization of Primary Rat Valve Interstitial Cells: A New Model to Study Aortic Valve Calcification

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Capturing Multi-Scale Dynamics of Aortic Valve Calcification With a Coupled Fluid-Structure and Systems Biology

Michael Quan, Tianyou Xie, Leonard A Harris

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    A new computational model integrates fluid dynamics and cellular signaling to simulate calcific aortic valve disease (CAVD). This approach reveals how mechanical changes accelerate calcification, offering insights into cardiovascular disease progression.

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    Area of Science:

    • Cardiovascular Research
    • Computational Biology
    • Biomedical Engineering

    Background:

    • Calcific aortic valve disease (CAVD) involves complex interactions between blood flow, tissue mechanics, and cellular signaling.
    • Existing computational models often address fluid-structure interaction (FSI) or systems biology (SB) separately, limiting understanding of disease feedback loops.

    Purpose of the Study:

    • To develop and present a multi-physics computational framework coupling 3D FSI simulations with a mechanistic SB model for CAVD.
    • To investigate the interplay between mechanical forces and biochemical pathways in driving aortic valve calcification.

    Main Methods:

    • Coupled 3D FSI simulations of aortic valve dynamics with a mechanistic SB model of calcification signaling.
    • Utilized FSI outputs (wall shear stress, tissue strain) as inputs for the SB module (inflammation, TGF-β/SMAD, NO pathways).

    Main Results:

    • Simulations predicted that fibrosis-induced stiffening reduces nitric oxide (NO) synthesis and enhances TGF-β activation.
    • These biochemical changes were shown to accelerate calcification progression in the aortic valve.

    Conclusions:

    • The developed multi-scale framework successfully integrates hemodynamics and biochemical signaling for studying cardiovascular disease.
    • This platform provides a foundation for next-generation modeling of CAVD, enabling exploration of disease mechanisms and potential interventions.