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Diffusion01:12

Diffusion

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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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Diffusion01:21

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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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The plasma membrane, a critical structure in cellular biology, houses an array of transporters, or carrier proteins, interspersed within its lipid bilayer. These proteins play a crucial role in solute transport through facilitated diffusion, a form of passive diffusion that uses transporters to move the molecules across the membrane.
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Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

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Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
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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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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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Estimating Future Health Technology Diffusion Using Expert Beliefs Calibrated to an Established Diffusion Model.

Sabine E Grimm1, John W Stevens2, Simon Dixon2

  • 1Maastricht University Medical Center, Department of Clinical Epidemiology and Medical Technology Assessment, School for Public Health and Primary Care, Maastricht, The Netherlands.

Value in Health : the Journal of the International Society for Pharmacoeconomics and Outcomes Research
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Summary

This study introduces a novel method for estimating health technology diffusion using expert beliefs calibrated to the Bass model. Results indicate lower adoption rates than anticipated, with research evidence slightly improving adoption numbers and increasing diffusion speed.

Keywords:
budget impact analysiscost effectivenessdiffusion of innovationselicitationvalue of information

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Area of Science:

  • Health technology assessment
  • Diffusion modeling
  • Preterm birth screening

Background:

  • Accurate health technology diffusion estimates are crucial for health technology assessments.
  • Current methods lack theoretical grounding in established diffusion models.
  • Expert opinion and extrapolation from initial data are common but limited approaches.

Purpose of the Study:

  • To propose and validate an approach for estimating health technology diffusion using expert beliefs calibrated to a diffusion model.
  • To address the methodological gap in current diffusion estimation techniques.
  • To improve the reliability of diffusion forecasts for health technologies.

Main Methods:

  • Elicitation of expert beliefs on the future diffusion of a new preterm birth screening technology.
  • Calibration of elicited expert beliefs to the parameters of the Bass diffusion model.
  • Utilizing three key quantities per diffusion curve to model adoption patterns.

Main Results:

  • Quantified uncertainty in diffusion estimates across different scenarios.
  • Pooled results predicted a lower attainable number of adoptions than initially expected.
  • Further research evidence minimally increased adoption numbers but significantly enhanced diffusion speed.

Conclusions:

  • The proposed approach effectively fills a methodological gap in diffusion estimation for health technology assessments.
  • Informing the Bass model with expert beliefs offers a robust method for forecasting technology uptake.
  • This approach has implications for value of implementation, research, budget impact, and cost-effectiveness analyses.