Tissue as a self-organizing system with fractal dynamics.

Area of Science:

• Systems biology
• Biophysics
• Complexity science

Background:

• Cells function as dynamic supramolecular networks.
• Genotype-phenotype relationships are non-bijective, with Mendelian inheritance as a specific case.
• This implies non-linearity and quasi-determinism in cellular networks.

Purpose of the Study:

• To investigate the fractal nature of cellular structures and dynamics.
• To characterize cell aggregation and differentiation using fractal geometry.
• To explore the implications of fractal dynamics in biological systems and potential extraterrestrial life.

Main Methods:

• Screening of tissue-specific cDNA libraries.
• Relative Reverse Transcription Polymerase Chain Reaction (RT-PCR).
• Box counting method to determine fractal dimensions.

Main Results:

• Higher-order morphological patterns, like gland-like structures and differentiating cancer cells, exhibit fractal dimensions and self-similarity.
• Cell aggregation shows a positive expansion coefficient, indicating a supracollective phenomenon.
• Cell differentiation displays a negative expansion coefficient, representing a collective phenomenon.
• Fractal properties are lost during tumor progression.

Conclusions:

• Cellular phenomena occur within a fractal space, characterized by specific dynamics.
• Fractal structure in tissues suggests an attractor organizing space-time, limiting cellular interactions.
• Fractal geometry may be a universal feature of interactive biosystems, applicable from terrestrial life to potential extraterrestrial forms.