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Related Concept Videos

Clearance Models: Physiological Models01:09

Clearance Models: Physiological Models

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Drug clearance is a critical pharmacokinetic process involving the irreversible removal of drugs from the body through various organs over a specified time period. Physiological models are indispensable in determining organ-specific clearance, defined by the proportion of the drug eliminated per unit of time from the organ's blood volume.
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Model Approaches for Pharmacokinetic Data: Physiological Models01:15

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Physiological models in pharmacokinetics are instrumental in understanding the distribution and elimination of drugs within the body. These models describe the drug concentration within target organs, influenced by factors such as drug uptake, tissue volume, and blood flow. Drug uptake is governed by the partition coefficient, which signifies the drug concentration ratio in tissue to that in the blood. The blood flow rate to a specific tissue is expressed as Qt, and the rate of change in tissue...
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In analyzing the behavior of diodes in circuits, the relationship between the current through a diode and the voltage across it is of particular interest, especially when considering the effect of a direct current (DC) bias voltage. When applied, this DC bias influences the diode's operating point, known as the Q point, around which the current-voltage (I-V) characteristic of the diode exhibits exponential behavior. Introducing a small, time-varying signal on top of this bias aids in examining...
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Physiological models with protein binding in pharmacokinetics offer a sophisticated approach to understanding drug disposition. These models consider drug-protein interactions, enabling them to effectively predict drug concentrations in different organs and tissues. This precision aids in accurate drug dosing, providing a significant advantage over conventional models. A key process within these models is equilibration, which ensures that drug concentrations achieve a steady state within the...
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Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
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Physiological barriers are semi-permeable cellular structures restricting drug diffusion into intracellular compartments and tissues. There are six types of physiological barriers: blood endothelial, cell membrane, blood-brain, blood-cerebrospinal fluid (CSF), blood-placenta, and blood-testis barriers.
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BOLD signal physiology: Models and applications.

C J Gauthier1, A P Fan2

  • 1Concordia University, Montreal, Canada.

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|March 17, 2018
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This summary is machine-generated.

Understanding the Blood-Oxygen-Level-Dependent (BOLD) signal is crucial for neuroscience. This review clarifies BOLD contrast mechanisms and their physiological underpinnings for accurate brain activity interpretation.

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Area of Science:

  • Neuroimaging
  • Physiology
  • Biophysics

Background:

  • The Blood-Oxygen-Level-Dependent (BOLD) contrast mechanism is fundamental to functional magnetic resonance imaging (fMRI).
  • Its complex relationship with brain activity, metabolism, and vascular factors requires detailed understanding for accurate interpretation.
  • Existing interpretations often overlook crucial physiological and disease-related confounding factors.

Purpose of the Study:

  • To elucidate the physiological components contributing to the BOLD signal.
  • To explain steady-state calibrated BOLD models for quantifying functional brain changes.
  • To apply these principles for interpreting BOLD signals in neurological disorders.

Main Methods:

  • Review of physiological factors influencing BOLD signal.
  • Description of steady-state calibrated BOLD models.
  • Application of biophysical principles to interpret BOLD in disease contexts.

Main Results:

  • Detailed description of the physiological basis of BOLD contrast.
  • Explanation of how calibrated BOLD models enable quantitative analysis of brain function.
  • Framework for interpreting BOLD signals considering vascular alterations in neurological diseases.

Conclusions:

  • A clear understanding of BOLD physiology is essential for accurate neuroscience and clinical applications.
  • Calibrated BOLD models provide a robust method for quantifying functional brain changes.
  • This framework aids in interpreting BOLD measurements in neurological disorders despite vascular complexities.