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Adaptations that Reduce Water Loss01:57

Adaptations that Reduce Water Loss

Though evaporation from plant leaves drives transpiration, it also results in loss of water. Because water is critical for photosynthetic reactions and other cellular processes, evolutionary pressures on plants in different environments have driven the acquisition of adaptations that reduce water loss.
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Adhesion

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Updated: May 17, 2026

Vascular Organoid Generation from Human-Induced Pluripotent Stem Cells
04:41

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Published on: December 13, 2024

Dynamic adaption of vascular morphology.

Fridolin Okkels1, Jens Christian Brings Jacobsen

  • 1Department of Micro- and Nanotechnology, Technical University of Denmark Lyngby, Denmark.

Frontiers in Physiology
|October 13, 2012
PubMed
Summary

Vascular networks adapt to tissue demand by optimizing flow channels. Optimal parameters cluster near critical transitions, suggesting systems evolve towards a critical state for stability and adaptability.

Area of Science:

  • Physiology
  • Biophysics
  • Computational Biology

Background:

  • Vascular network structure adapts to tissue metabolic needs.
  • Adaptation mechanisms often rely on local responses to stimuli like pressure and flow.
  • Existing models primarily focus on local feedback loops.

Purpose of the Study:

  • To present a novel two-dimensional model of vascular network adaptation.
  • To investigate an alternative approach where tissue is modeled as a porous medium with flow channels.
  • To explore how flow-channel structures adapt to ensure uniform tissue supply.

Main Methods:

  • Developed a simplified 2D model representing tissue as a porous medium with defined flow channels.
  • Incorporated physiologically realistic assumptions for flow-channel adaptation.
Keywords:
adaptationmorphologyremodelingvascular

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  • Analyzed model dynamics based on a set of parameters to identify optimal configurations.

    • Main Results:

    • The model demonstrates that flow-channel structures adapt to achieve complete tissue supply.
    • A specific region of optimal model parameters (global optimum) was identified.
    • Optimal parameters were found to localize near critical transition zones in the parameter space, characterized by steep fitness gradients.

    Conclusions:

    • Vascular network adaptation appears to be driven towards a critical state.
    • This critical state arises from continuous parameter optimization, analogous to evolutionary pressure.
    • Optimal solutions are stable under small perturbations but can shift profoundly with larger ones.