Umut Akalp

  • Citations Per Year
Learn More
Damage to cartilage caused by injury or disease can lead to pain and loss of mobility, diminishing one's quality of life. Because cartilage has a limited capacity for self-repair, tissue engineering strategies, such as cells encapsulated in synthetic hydrogels, are being investigated as a means to restore the damaged cartilage. However, strategies to date(More)
Enzyme-sensitive hydrogels are promising cell delivery vehicles for cartilage tissue engineering. However, a better understanding of their spatiotemporal degradation behavior and its impact on tissue growth is needed. The goal of this study was to combine experimental and computational approaches to provide new insights into spatiotemporal changes in(More)
Despite tremendous advances in the field of tissue engineering, a number of obstacles remain that hinder its successful translation to the clinic. One challenge that relates to the use of cells encapsulated in a hydrogel is identifying a hydrogel design that can provide an appropriate environment for cells to successfully synthesize and deposit new matrix(More)
We propose a mechanism of adherent cell mechanosensing, based on the idea that the contractile actomyosin machinery behaves as a catch bond. For this, we construct a simplified model of the actomyosin structure that constitutes the building block of stress fibers and express the stability of cross bridges in terms of the force-dependent bonding energy of(More)
Enzyme-sensitive hydrogels are promising for cell encapsulation and tissue engineering, but result in complex spatiotemporal degradation behavior that is characteristic of reaction-diffusion mechanisms. An experimental and theoretical approach is presented to identify dimensionless quantities that serve as a design tool for engineering enzyme-sensitive(More)
Concentrating on the case of poly(ethylene glycol) hydrogels, this paper introduces a methodology that enables a natural integration between the development of a so-called mechanistic model and experimental data relating material's processing to response. In a nutshell, we develop a data-driven modeling component that is able to learn and indirectly infer(More)
  • 1