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Topographical changes in extracellular matrix during skin fibrosis and recovery can be evaluated using automated image analysis algorithms.

Rachel H WyetznerElla X SegalAnna R JussilaRadhika P Atit
Published in: FEBS letters (2024)
Skin fibrosis is characterized by fibroblast activation and intradermal fat loss, resulting in excess deposition and remodeling of dermal extracellular matrix (ECM). The topography of the dominant ECM proteins, such as collagens, can indicate skin stiffness and remains understudied in evaluating fibrotic skin. Here, we adapted two different unbiased image analysis algorithms to define collagen topography and alignment in a genetically inducible and reversible Wnt activation fibrosis model. We demonstrated that Wnt-activated fibrotic skin has altered collagen fiber characteristics and a loss of collagen alignment, which were restored in the reversible model. This study highlights how unbiased algorithms can be used to analyze ECM topography, providing novel avenues to evaluate fibrotic skin onset, recovery, and treatment.
Keyphrases
  • extracellular matrix
  • wound healing
  • soft tissue
  • machine learning
  • idiopathic pulmonary fibrosis
  • systemic sclerosis
  • cell proliferation
  • adipose tissue
  • fatty acid