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Related Concept Videos

Clot Retraction and Fibrinolysis01:16

Clot Retraction and Fibrinolysis

After a fibrin clot is formed, the next step is clot retraction, a vital process facilitated by platelet contractile proteins, such as actin and myosin. These proteins pull the fibrin strands closer together and condense the clot. This action reduces the size of the clot, creating a smaller, denser structure that effectively seals off the damaged vessel. Clot retraction consolidates the clot and helps with wound healing by bringing the edges of the damaged blood vessel closer together.

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Related Experiment Video

Updated: May 16, 2026

Tracking Fibrinolysis of Chandler Loop-Formed Whole Blood Clots Under Shear Flow in An In-Vitro Thrombolysis Model
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Tracking Fibrinolysis of Chandler Loop-Formed Whole Blood Clots Under Shear Flow in An In-Vitro Thrombolysis Model

Published on: April 19, 2024

Modelling fibrinolysis: a 3D stochastic multiscale model.

Brittany E Bannish1, James P Keener, Aaron L Fogelson

  • 1Department of Mathematics and Statistics, University of Central Oklahoma, 100 North University Dr., Box 129, Edmond, OK 73034, USA.

Mathematical Medicine and Biology : a Journal of the IMA
|December 11, 2012
PubMed
Summary

Fibrinolysis, the breakdown of blood clots, depends on clot structure. A new stochastic model explains why coarse clots may lyse faster or slower than fine clots, resolving conflicting experimental results.

Keywords:
enzymatic degradationfibrinlysis frontlysis speeds

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Last Updated: May 16, 2026

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Published on: October 28, 2013

Area of Science:

  • Biophysics
  • Biochemistry
  • Computational Biology

Background:

  • Fibrinolysis is crucial for blood clot breakdown, initiated by tissue-type plasminogen activator (tPA) converting plasminogen to plasmin.
  • Experimental observations on fibrin clot lysis rates (coarse vs. fine clots) show conflicting results, challenging existing explanations.
  • Deterministic models may be insufficient for low tPA concentrations, necessitating stochastic approaches.

Purpose of the Study:

  • To develop and utilize a 3D stochastic multiscale model to investigate fibrinolysis.
  • To reconcile divergent experimental findings regarding the lysis rates of coarse versus fine fibrin clots.
  • To explore the influence of clot structure and tPA availability on fibrinolysis speed.

Main Methods:

  • Developed a 3D stochastic multiscale model integrating microscale and macroscale components.
  • Microscale model simulated detailed biochemical reactions at the fiber cross-section level.
  • Macroscale model simulated the entire fibrin clot, analyzing lysis front velocities and tPA distribution.

Main Results:

  • The model identified that both fiber number and the ratio of tPA molecules to clot surface area significantly impact lysis speed.
  • The study found that coarse clots can lyse faster or slower than fine clots, depending on these factors.
  • This provides a potential explanation for previously contradictory experimental observations in fibrinolysis.

Conclusions:

  • The developed stochastic multiscale model offers a more comprehensive understanding of fibrinolysis dynamics.
  • Clot structure (fiber density) and tPA availability are critical determinants of lysis rate.
  • The model successfully explains the variability in experimental findings on fibrin clot lysis speed.