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Dissolution, the process by which drug particles dissolve in a solvent, is explained by the diffusion layer model, a theoretical framework that simulates the absorption of oral drugs and allows us to analyze experimental data.
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Diffusion is a type of passive transport. In passive transport, a substance tends to move from an area of high concentration to an area of low concentration until the concentration is equal across the space. For example, take the diffusion of substances through the air. When someone opens a perfume bottle in a room filled with people, the perfume is at its highest concentration in the bottle and is at its lowest at the edges of the room. The perfume vapor will diffuse, or spread away, from the...
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Diffusion is the passive movement of substances down their concentration gradients—requiring no expenditure of cellular energy. Substances, such as molecules or ions, diffuse from an area of high concentration to an area of low concentration in the cytosol or across membranes. Eventually, the concentration will even out, with the substance moving randomly but causing no net change in concentration. Such a state is called dynamic equilibrium, which is essential for maintaining overall...
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Proteins show rotational as well as lateral diffusion across the membrane. The lateral diffusion of proteins was confirmed through the cell fusion experiment where mouse and human cells were fused, resulting in hybrid cells. When the human and mouse cells fused, the specific membrane proteins on human and mouse cells were marked with the red and green-fluorescent markers, respectively. Initially, the red and green fluorescence was located on the respective hemisphere of the cell. As time...
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Passive diffusion is a critical process that allows small lipophilic drugs to cross the cell membrane along a concentration gradient. This mechanism's efficiency depends on four primary factors: the membrane's surface area, the drug's lipid-water partition coefficient, the concentration gradient, and the membrane's thickness.
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The Diffusion of Passive Tracers in Laminar Shear Flow
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Network reliability: the effect of local network structure on diffusive processes.

Mina Youssef1, Yasamin Khorramzadeh2, Stephen Eubank3

  • 1Network Dynamics and Simulation Science Laboratory, Virginia Bioinformatics Institute, Virginia Polytechnic Institute and State University, Blacksburg, Virginia 24061, USA.

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
|December 17, 2013
PubMed
Summary
This summary is machine-generated.

Network structure significantly impacts disease spread. Positively assortative graphs are more reliable, and increasing triangles doesn't enhance reliability in these networks.

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Area of Science:

  • Epidemiology
  • Network Science
  • Computational Biology

Background:

  • The network reliability polynomial, introduced by Moore and Shannon, is a valuable tool for analyzing network structure.
  • Understanding how network topology influences disease transmission is crucial for public health interventions.

Purpose of the Study:

  • To reintroduce and adapt the network reliability polynomial for disease spread analysis.
  • To investigate the impact of assortativity-by-degree and triangle count on network reliability.

Main Methods:

  • Utilized a representation of the network reliability polynomial suitable for distributed simulation.
  • Generated Erdős-Rényi and scale-free-like random graphs with manipulated assortativity and triangle counts.
  • Evaluated network reliability based on the expected size of connected components.

Main Results:

  • Network reliability did not increase with more triangles in positively or neutrally assortative graphs.
  • Positively assortative graphs demonstrated higher reliability than neutral or disassortative graphs with identical edge counts.
  • Assessed the combined influence of assortativity and triangles on critical points and subgraph reliability.

Conclusions:

  • Assortativity-by-degree is a more significant factor than triangle count in determining network reliability for disease spread.
  • Network structure, particularly assortativity, plays a critical role in disease propagation dynamics.