NDLI: A stochastic control framework for regulating collective behaviors of an angiogenesis cell population

Content Provider	IEEE Xplore Digital Library
Author	Wood, L.B. Das, A. Kamm, R.D. Asada, H.H.
Copyright Year	2008
Description	Author affiliation: Dept. of Mech. Eng., Massachusetts Inst. of Technol., Cambridge, MA (Wood, L.B.; Das, A.; Kamm, R.D.; Asada, H.H.)
Abstract	This paper presents a framework for controlling the development of a vascular system in an in vitro angiogenesis process. Based on on-line measurement of cell growth and a stochastic model of cell population, a closed-loop control system is developed for regulating the process of cell migration and tissue formation. Angiogenesis develops in a wet environment and it is difficult to control each and every cell individually and specifically. Instead, chemical and mechanical stimuli can be applied pervasively to the whole process as global control inputs, which can allow for control of collective behaviors of the cell population. This paper formulates a systems level description of the angiogenesis process and proposes a control scheme that chooses global control inputs to drive collective cell patterns, such as branch density per unit length of sprout, toward a desired goal. In response to control inputs, the k-step ahead prediction of collective cell pattern is evaluated, and the input that is most likely to bring the predicted cell pattern to the desired one is selected for the current control. Simulation demonstrates that the global branch density of a simplified angiogenesis model can be controlled using this technique. To our knowledge, this paper is the first to formulate feedback control for regulating an in vitro angiogenesis process.
Starting Page	390
Ending Page	396
File Size	407319
Page Count	7
File Format	PDF
ISBN	9781424428823
DOI	10.1109/BIOROB.2008.4762822
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-10-19
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Stochastic processes Medical control systems Biomechatronics Control systems Chemical processes Feedback control Engineering in medicine and biology In vitro Robots Biomedical engineering
Content Type	Text
Resource Type	Article

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