Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Typical Model Studies01:30

Typical Model Studies

340
Fluid mechanics model studies often utilize scaled-down systems to predict fluid behavior in full-scale environments, such as river flows, dam spillways, and structures interacting with open surfaces. Maintaining Froude number similarity in river models is crucial, as it replicates surface flow features like wave patterns and velocities.
340
Autoregulation of Blood Flow01:17

Autoregulation of Blood Flow

2.2K
Autoregulation mechanisms are characterized by their inherent capacity for self-regulation without necessitating specific nervous stimulation or endocrine control. These mechanisms facilitate the adjustment of blood flow and, therefore, perfusion specific to each tissue region. This self-regulation encompasses chemical signals and myogenic controls.
Chemical Signaling in Autoregulation
Chemical signaling operates at the precapillary sphincter level, inciting either contraction or relaxation....
2.2K
Navier–Stokes Equations01:28

Navier–Stokes Equations

422
For incompressible Newtonian fluids, where density remains constant, stresses show a linear relationship with the deformation rate, defined by normal and shear stresses. Normal stresses depend on the pressure exerted on the fluid and the rate of deformation in specific directions, which determines how fluid flows under varying pressures. Shear stresses, on the other hand, act tangentially across fluid layers. They explain how adjacent fluid layers slide relative to one another, connecting...
422
Rapidly Varying Flow01:24

Rapidly Varying Flow

49
Rapidly varying flow (RVF) in open channels is characterized by abrupt changes in flow depth over a short distance, with the rate of depth change relative to distance often approaching unity. These flows are inherently complex due to their transient and multi-dimensional nature, making exact analysis difficult. However, approximate solutions using simplified models provide valuable insights into their behavior.Key Features of Rapidly Varying FlowRVF is commonly observed in scenarios involving...
49
Overview of the Vascular System01:20

Overview of the Vascular System

2.7K
The vascular system comprises an extensive network of arteries, capillaries, and veins. The vascular system can be broadly divided into the blood and lymphatic systems. Typically, blood vessels can be categorized into three histological regions: tunica intima, tunica media, and tunica adventitia. The tunica intima consists of a single layer of endothelial cells attached to the basal lamina. Underlying the basal lamina is a connective tissue layer and an elastic lamina that gives stability and...
2.7K
Design Example: Creating a Hydraulic Model of a Dam Spillway01:21

Design Example: Creating a Hydraulic Model of a Dam Spillway

122
Scaled hydraulic models of dam spillways provide a practical way to replicate and study the intricate flow dynamics of these structures. Often built to a 1:15 ratio, these models allow for observing critical water behavior, such as velocity distribution, flow patterns, and energy dissipation.
122

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Extracellular vesicle-integrated gelatin sponges enhance angiogenesis and cell migration in wound healing.

Journal of materials chemistry. B·2026
Same author

Artificial intelligence in retinal vein occlusion: Current applications, challenges, and future directions.

Survey of ophthalmology·2026
Same author

Wet-stable PLGA-PCL electrospun membranes as synthetic scaffolds for corneal applications.

Biomedical materials (Bristol, England)·2026
Same author

Development of 2-deoxy-d-ribose and zinc oxide loaded microneedle array patches of chitosan and PVA to stimulate angiogenesis and reduce infection and promote wound healing.

Biomaterials advances·2026
Same author

A critical comparison of polypropylene and polyurethane sling materials after implantation in a suburethral sheep model.

Biomaterials·2025
Same author

Predetermined Change Control Plans: Guiding Principles for Advancing Safe, Effective, and High-Quality AI-ML Technologies.

JMIR AI·2025

Related Experiment Video

Updated: Jun 3, 2025

In Vitro Model of Physiological and Pathological Blood Flow with Application to Investigations of Vascular Cell Remodeling
07:30

In Vitro Model of Physiological and Pathological Blood Flow with Application to Investigations of Vascular Cell Remodeling

Published on: November 3, 2015

9.6K

Angiogenesis Dynamics: A Computational Model of Intravascular Flow Within a Structural Adaptive Vascular Network.

Sahar Jafari Nivlouei1, Ana Guerra1, Jorge Belinha2

  • 1INEGI-Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Industrial, 4200-465 Porto, Portugal.

Biomedicines
|January 8, 2025
PubMed
Summary
This summary is machine-generated.

This study introduces a novel computational model for angiogenesis, simulating blood vessel growth and flow dynamics. The model accurately predicts capillary branching and provides quantitative insights into vascular development for improved wound healing strategies.

Keywords:
angiogenesis evaluationcapillary network remodellingchick chorioallantoic membrane assayflow dynamicshybrid meshless-based method

More Related Videos

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
06:18

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Published on: December 6, 2024

437
Microfluidic Model to Mimic Initial Event of Neovascularization
10:01

Microfluidic Model to Mimic Initial Event of Neovascularization

Published on: April 10, 2021

4.6K

Related Experiment Videos

Last Updated: Jun 3, 2025

In Vitro Model of Physiological and Pathological Blood Flow with Application to Investigations of Vascular Cell Remodeling
07:30

In Vitro Model of Physiological and Pathological Blood Flow with Application to Investigations of Vascular Cell Remodeling

Published on: November 3, 2015

9.6K
Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery
06:18

Intravascular Ultrasound Image-Based Finite Element Modeling Approach for Quantifying In Vivo Mechanical Properties of Human Coronary Artery

Published on: December 6, 2024

437
Microfluidic Model to Mimic Initial Event of Neovascularization
10:01

Microfluidic Model to Mimic Initial Event of Neovascularization

Published on: April 10, 2021

4.6K

Area of Science:

  • * Computational biology and mathematical modeling.
  • * Vascular biology and angiogenesis research.
  • * Biomedical engineering and tissue regeneration.

Background:

  • * Angiogenesis, the growth of new blood vessels, is vital for wound healing, but current models lack quantitative data on blood flow and vessel dynamics.
  • * Understanding vascular development is key to improving therapeutic strategies for chronic wound healing and tissue regeneration.
  • * Existing chorioallantoic membrane (CAM) models do not quantify essential parameters like blood flow rate, intravascular pressure, or vessel diameter changes.

Purpose of the Study:

  • * To develop a novel two-dimensional mathematical model for simulating angiogenesis.
  • * To integrate discrete and continuous modeling approaches for detailed capillary network analysis.
  • * To provide quantitative insights into vascular development and blood flow dynamics.

Main Methods:

  • * Developed a hybrid meshless-based mathematical model for simulating sprouting angiogenesis.
  • * Integrated discrete and continuous modeling to capture cellular interactions and capillary network structure.
  • * Utilized the in vivo chorioallantoic membrane (CAM) system for simulation.

Main Results:

  • * The model accurately predicted capillary branching with <15% deviation in capillary volume fraction.
  • * Simulated blood flow, calculating intravascular pressure and vessel wall shear stress distribution.
  • * An adaptive network demonstrated capillary responses to stimuli, showing significant diameter changes (p < 0.05) and metabolic stimuli (p < 0.01).

Conclusions:

  • * The novel model offers strong predictive capabilities for simulating intravascular flow and angiogenesis.
  • * Provides quantitative and qualitative assessments of vascular network development.
  • * Enhances understanding of angiogenesis by creating a biologically relevant network addressing tissue functional demands.