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Related Experiment Videos

Cell orientation induced by extracellular signals.

R Kemkemer1, C Neidlinger-Wilke, L Claes

  • 1BioPhysics Department, Complex Fluids Group, Ulm, Germany.

Cell Biochemistry and Biophysics
|June 5, 1999
PubMed
Summary
This summary is machine-generated.

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Cells align perpendicular to guiding signals via an automatic controller. This system uses deterministic and stochastic signals, with cells unable to sense signal direction but registering signal strength.

Area of Science:

  • Cell biology
  • Biophysics
  • Biomaterials

Background:

  • Cells like fibroblasts and osteoblasts respond to various extracellular cues for orientation.
  • These cues include electric fields, bent surfaces, and stretched surfaces.
  • Cell alignment is regulated by an automatic controller integrating deterministic and stochastic signals.

Purpose of the Study:

  • To characterize the properties of the automatic controller governing cell alignment.
  • To quantify the interplay between deterministic and stochastic signals in cell orientation.
  • To determine how cells perceive and respond to different extracellular guiding signals.

Main Methods:

  • Analysis of cellular signal transformer's angle dependence.
  • Quantification of the stochastic signal's characteristic time.

Related Experiment Videos

  • Measurement of extracellular signal registration thresholds for electric fields and bent surfaces.

    • Main Results:

    • Cellular signal transformer follows a cos 2(psi 0 - psi) dependence, with a set point of +/- 90 degrees.
    • Cells orient perpendicular to guiding signals and measure signals quadratically, ignoring sign.
    • Characteristic time for stochastic signal in fibroblasts is ~130 min; lag-time in signal transduction is ~4 min.

    Conclusions:

    • The automatic controller integrates deterministic and stochastic signals for cell alignment.
    • Cells exhibit specific thresholds for registering electric fields (~0.3 V/mm) and bent surfaces (~85 microns).
    • Understanding these mechanisms is crucial for biomaterial design and regenerative medicine.