Objective: Crocin has been proposed as a promising candidate for cancer chemoprevention. The purpose of this investigation was to investigate the chemopreventive action and the possible mechanisms of crocin against human colon cancer cells in vitro. Methods: Cell proliferation was examined using MTT assay and the cell cycle distribution fractions were analyzed using fow cytometric analysis after propidium iodide staining. Apoptosis was detected using theTUNEL Apoptosis Detection Kit with laser scanning confocal microscope. DNA damage was assessed using the alkaline single-cell gel electrophoresis assay, while expression levels of p53, cdk2, cyclinA and P21 were examined by Western blot analysis.

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In this paper, we introduce control laws for multi‐agent formation maneuvering and target interception problems. In the target interception problem, we consider that the target velocity is unknown. Using a single‐integrator agent model, the proposed controls consist of a formation acquisition term, dependent on the graph rigidity matrix, and a formation maneuvering or target interception term. The control laws are only a function of the relative position of agents in an infinitesimally and minimally rigid graph, and either the desired maneuvering velocity of the formation or the target's relative position to the leader. The target interception control includes a continuous dynamic estimation term to identify the unknown target velocity. A Lyapunov‐like stability analysis is used to prove that the control objectives are met.

In this paper, we consider the problem of formation control of multi-agent systems in three-dimensional (3D) space, where the desired formation is dynamic. This is motivated by applications where the formation size and/or geometric shape needs to vary in time. Using a single-integrator model and rigid graph theory, we propose a new control law that exponentially stabilizes the origin of the nonlinear, interagent distance error dynamics and ensures tracking of the desired, 3D time-varying formation. Extensions to the formation maneuvering problem and double-integrator model are also discussed. The formation control is illustrated with a simulation of eight agents forming a dynamic cube.