In this paper we consider the influence of inter-cellular communication on the development and progression of Glioblastoma Multiforme (GBM), a grade IV malignant glioma which is defined by an interplay Grow i.e. self renewal and Go i.e. invasiveness potential of multiple malignant glioma stem cells. Firstly, we performed wet lab experiments with U87 malignant glioma cells to study the node-stem growth pattern of GBM. Next we develop a model accounting for the structural influence of multiple transmitter and receiver glioma stem cells resulting in the node-stem growth structure of GBM tumour. By using information theory we study different properties associated with this communication model to show that the growth of GBM in a particular direction (node to stem) is related to an increase in mutual information. We further show that information flow between glioblastoma cells for different levels of invasiveness vary at different points between node and stem. These findings are expected to contribute significantly in the design of future therapeutic mechanisms for GBM.

The phenomenon of retroactivity describes the impact that a downstream system has on an upstream one when they are connected. From a molecular communication point of view, the effect of the signal that is back propagated between the two systems leads to a reduction of the correct amount of information that can be exchanged between the input and the output of the upstream system. In this work we propose a solution to mitigate such a negative effect. Specifically, a retroactivity suppressor is introduced, which role is that of binding to the downstream system in place of the output of the primary upstream system.

This work builds on our earlier work on designing demodulators for diffusion-based molecular communications using a Markovian approach. The demodulation filters take the form of an ordinary differential equation (ODE) which computes the log-posteriori probability of observing a transmission symbol given the continuous history of receptor activities. A limitation of our earlier work is that the receiver is assumed to be a small cubic volume called a voxel. In this work, we extend the maximum a-posteriori demodulation to the case where the receiver may consist of multiple voxels and derive the ODE for log-posteriori probability calculation. This extension allows us to study receiver behaviour of different volumes and shapes. In particular, it also allows us to consider spatially partitioned receivers where the chemicals in the receiver are not allowed to mix. The key result of this paper is that spatial partitioning can be used to reduce bit-error rate in diffusion-based molecular communications.

This paper considers information-theoretic aspects of mechanosensitive based communication signals in living organisms such as plants and bacteria. Mechanosensitive ion channels function as mechanosensitive transducers, which generate an activation signal in response to a mechanical stimulus. This activation signal is necessary for performing different functions, such as the coordination of growth or determining a response to a stress. The activation signal works by releasing a number of protein molecules carrying information in the transmitter cell which is the input signal of the system. These protein molecules propagate to the receiver cells through a diffusion based medium and react with receptors to produce output protein molecules, forming a molecular communication system. In this paper we develop a communication system model for mechanosensitive systems, and study the mutual information and the information propagation speed associated with their signals.

This paper focuses on different properties of an electrochemical signal based model for inter-cellular communication in plants. The input signal in this communication system can be either composed of (a) a number of fast moving charged molecules or (b) randomly diffusing molecules, which are driven by an action potential (AP) signal. APs are usually generated by an external stimulus such as change in temperature or light. We use a model of AP generation in this paper from previous works. The three main contributions of this paper are: firstly we consider the impact of multiple AP signals on the mutual information of the system for multiple (varying) numbers of receiver cells in different configurations, second, we compare the impact of different propagation mechanisms (i.e. fast active movement and random diffusion of molecules) on the output molecules and mutual information of the system, and finally we study the impact of multiple APs on the information propagation speed of the system and compare it for the different receiver cell configurations.

This paper considers an electro-chemical signal based model for inter-cellular communication in plants. The input signal, composed of fast moving charged molecules is driven by an action potential (AP). APs, generated by an external stimulus, are part of the communication mechanism in plants. We extend the simple model for AP generation presented in previous work to incorporate the AP signal arriving from neighboring cells. Furthermore in this model we study the transfer of information between cells via fast moving ions. Unlike previous work, this paper does not consider diffusion but only reactions between molecules at each step. We then use an information-theoretic analysis to compute the mutual information between the input and output of this system. The key aim is to study the impact of an increase in population of cells on the mutual information. We calculate the mutual information for a large group of cells (up to 100) in three different topologies i.e., parallel, series and mixed. Finally we study the impact of a single AP on multiple cells in the system.

This paper considers an electro-chemical based communication model for intercellular communication in plants. Many plants, such as Mimosa pudica (the "sensitive plant"), employ electrochemical signals known as action potentials (APs) for communication purposes. In this paper we present a simple model for action potential generation. We make use of the concepts from molecular communication to explain the underlying process of information transfer in a plant. Using the information-theoretic analysis, we compute the mutual information between the input and output in this work. The key aim is to study the variations in the information propagation speed for varying number of plant cells for one simple case. Furthermore we study the impact of the AP signal on the mutual information and information propagation speed. We further aim to explore the impact of increasing number of cells on the information propagation speed.

This paper considers a diffusion-based molecular communication system, where the transmitter uses reaction shift keying (RSK) as the modulation scheme. We focus on the demodulation of RSK signal at the receiver. The receiver consists of a front-end molecular circuit and a back-end demodulator. The front-end molecular circuit is a set of chemical reactions consisting of multiple chemical species. The optimal demodulator computes the posteriori probability of the transmitted symbols given the history of the observation. The derivation of the optimal demodulator requires the solution to a specific Bayesian filtering problem. The solution to this Bayesian filtering problem had been derived for a few specific molecular circuits and specific choice(s) of observed chemical species. The derivation of such solution is also lengthy. The key contribution of this paper is to present a general solution to this Bayesian filtering problem, which can be applied to any molecular circuit and any choice of observed species.

This paper is concerned with the performance of diffusion-based molecular communication when both the transmitter and receiver are molecular circuit based or chemical reaction based. On the transmitter side, we use Reaction Shift Keying (RSK) which is a recently proposed modulation scheme. RSK uses different chemical reactions to generate different emission patterns for different transmission symbols. On the receiver side, we use a molecular circuit found in living organisms. This circuit uses multiple intermediate chemical species and negative feedback. The information on the transmitted symbol is contained in the time series of the counts of the intermediate species. If the receiver measures the counts of some of these intermediate species, it can use these counts to infer the symbol sent by the transmitter. We are interested to study how the choice of measurements and negative feedback affect the communication performance in terms of symbol error rate. We address these questions by first deriving the optimal demodulator using the maximum a posteriori framework and Bayesian filtering. We learnt two lessons from this study. First, there is a pattern in the form of the optimal demodulation filters where the rates of reactions leading to the production or consumption of the measured chemical species play a strong role. Second, negative feedback can impact on the communication performance in different ways depending on which chemical species are measured.