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Related Concept Videos

Hypothalamic-Pituitary Axis01:37

Hypothalamic-Pituitary Axis

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The response to stress—be it physical or psychological, acute or chronic—involves activation of the Hypothalamic-Pituitary-Adrenal (HPA) axis. The HPA axis is part of the neuroendocrine system because it involves both neuronal and hormonal communication. Its function is to regulate homeostatic systems—metabolic, cardiovascular, and immune—providing the necessary means to respond to a stressor.
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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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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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Stress Response System01:21

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The stress response system, also known as the fight-or-flight response, is the body's automatic physiological reaction to perceived threats. Hans Selye introduced the concept of General Adaptation Syndrome (GAS) to describe the predictable pattern of changes that occur in response to stress. GAS consists of three sequential stages: alarm, resistance, and exhaustion. This model helps explain how chronic stress can contribute to health problems.
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Physiological Foundation of Stress01:24

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Stress triggers a coordinated physiological response involving the sympathetic nervous system (SNS) and the hypothalamic-pituitary-adrenal (HPA) axis. This dual activation ensures that the body is prepared for both immediate and prolonged stress management. The process begins with the perception of a stressor. This initial phase activates the SNS, leading to the rapid release of adrenaline (epinephrine) from the adrenal glands.
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Hormones of the Pituitary Gland01:27

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The small, pea-sized pituitary gland is located at the base of the brain. It is crucial in regulating various bodily functions, from growth to reproduction. The gland is divided into the anterior lobe and the posterior lobe. The secretory cell clusters in the pars distalis of the anterior pituitary lobe are controlled by hypothalamic regulators and synthesize six primary hormones.
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Related Experiment Video

Updated: Aug 16, 2025

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver
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VeVaPy, a Python Platform for Efficient Verification and Validation of Systems Biology Models with Demonstrations

Christopher Parker1, Erik Nelson2, Tongli Zhang1

  • 1Department of Pharmacology & Systems Physiology, College of Medicine, University of Cincinnati, Cincinnati, OH 45221, USA.

Entropy (Basel, Switzerland)
|December 23, 2022
PubMed
Summary

Mathematical model verification and validation (V&V) is crucial but time-consuming. We developed VeVaPy, a Python framework to efficiently perform V&V for systems biology and pharmacology models, including hypothalamic-pituitary-adrenal axis models.

Keywords:
HPA axisMajor Depressive DisorderPythonVerification &amp; Validationdifferential equations modelstress test

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Area of Science:

  • Computational biology
  • Mathematical modeling
  • Pharmacology

Background:

  • Mathematical models are essential for systems biology and pharmacology.
  • Current verification and validation (V&V) processes for these models are inefficient and time-consuming.
  • This inefficiency hinders the credibility and adoption of existing models.

Purpose of the Study:

  • To develop a computational framework, VeVaPy, to streamline the V&V of mathematical models.
  • To facilitate the systemic V&V of hypothalamic-pituitary-adrenal (HPA) axis models.
  • To provide objective V&V benchmarks using new and independent data.

Main Methods:

  • Developed VeVaPy, a Python-based computational framework with four functional modules.
  • Followed best practices for mathematical model development.
  • Applied VeVaPy to five selected HPA axis models.
  • Utilized new and independent datasets for model evaluation.

Main Results:

  • VeVaPy enables efficient and objective V&V of mathematical models.
  • Demonstrated the framework's effectiveness on five HPA axis models.
  • Generated objective V&V benchmarks for each model based on independent data.

Conclusions:

  • VeVaPy significantly improves the efficiency of model V&V.
  • The framework supports researchers in systems biology and pharmacology.
  • VeVaPy promotes the development of credible and reliable mathematical models.