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We propose a statistical model of a large random network with highconnectivity in order to describe the behavior of {\it E.\,coli} cells afterexposure to acute stress. The building blocks of this network are feedbackcycles typical of the genetic and metabolic networks of a cell. Each node onthe cycles is a spin degree of freedom representing a component in the cell'snetwork that can be in one of two states - active or inactive. The cycles areinterconnected by regulation or by the exchange of metabolites. Stress isrealized by an external magnetic field that drives the nodes into an inactivestate, and the time the magnetization passes zero value for the first timerepresents the first division event of the cell after the stress period. Thenumerical and analytical solutions for this first passage problem reproduce theaging dynamics observed in the experimental data.

Slow relaxation and aging in the model of randomly connected cycles network