Extended master equation models for molecular communication networks

We consider molecular communication networks consisting of transmitters and receivers distributed in a fluidic medium. In such networks, a transmitter sends one or more signalling molecules, which are diffused over the medium, to the receiver to realise the communication. In order to be able to engineer synthetic molecular communication networks, mathematical models for these networks are required. This paper proposes a new stochastic model for molecular communication networks called reaction-diffusion master equation with exogenous input (RDMEX). The key idea behind RDMEX is to model the transmitters as time series of signalling molecule counts, while diffusion in the medium and chemical reactions at the receivers are modelled as Markov processes using master equation. An advantage of RDMEX is that it can readily be used to model molecular communication networks with multiple transmitters and receivers. For the case where the reaction kinetics at the receivers is linear, we show how RDMEX can be used to determine the mean and covariance of the receiver output signals, and derive closed-form expressions for the mean receiver output signal of the RDMEX model. These closed-form expressions reveal that the output signal of a receiver can be affected by the presence of other receivers. Numerical examples are provided to demonstrate the properties of the model.Comment: IEEE Transactions on Nanobioscience, 201

Impact of receiver reaction mechanisms on the performance of molecular communication networks

In a molecular communication network, transmitters and receivers communicate by using signalling molecules. At the receivers, the signalling molecules react, via a chain of chemical reactions, to produce output molecules. The counts of output molecules over time is considered to be the output signal of the receiver. This output signal is used to detect the presence of signalling molecules at the receiver. The output signal is noisy due to the stochastic nature of diffusion and chemical reactions. The aim of this paper is to characterise the properties of the output signals for two types of receivers, which are based on two different types of reaction mechanisms. We derive analytical expressions for the mean, variance and frequency properties of these two types of receivers. These expressions allow us to study the properties of these two types of receivers. In addition, our model allows us to study the effect of the diffusibility of the receiver membrane on the performance of the receivers

Molecular communication networks with general molecular circuit receivers

In a molecular communication network, transmitters may encode information in concentration or frequency of signalling molecules. When the signalling molecules reach the receivers, they react, via a set of chemical reactions or a molecular circuit, to produce output molecules. The counts of output molecules over time is the output signal of the receiver. The aim of this paper is to investigate the impact of different reaction types on the information transmission capacity of molecular communication networks. We realise this aim by using a general molecular circuit model. We derive general expressions of mean receiver output, and signal and noise spectra. We use these expressions to investigate the information transmission capacities of a number of molecular circuits

Regulation of durable adaptive immune response by the c-MYC-AP4 transcriptional cascade

The process of amplifying immune responses by expanding a small number of antigen-specific cells, termed clonal expansion, is an important feature of the adaptive immunity. Whereas clonal expansion of cytotoxic T lymphocytes is required for complete eradication of intracellular pathogens, proliferation of B lymphocytes in the germinal centers (GC) is critical for generating a diverse immunoglobulin gene repertoire from which protective antibody carrying multiple mutations can arise. While the proto-oncogene c-MYC is absolutely required for the activation and cell cycle initiation in lymphocytes, its expression is temporally restricted. Activated lymphocytes, however, continue to proliferate after c-MYC levels decay to maximize clonal expansion. It remains unknown how lymphocytes sustain their proliferative program in the absence c-MYC. We demonstrated that the c-MYC-inducible transcription factor, AP4 is required for sustained expansion of antigen-specific lymphocytes. Mice lacking AP4 in CD8 T cells exhibit diminished T cell clonal expansion and succumb to West Nile virus infection due to uncontrolled viral replication in the central nervous system. Genetic ablation of AP4 in B lymphocytes impaired GC growth. These mice failed to control persistent viral infection due to blunted neutralizing antibody development. The accumulation of AP4 requires IL-2 and IL-21 signals in CD8 T cells and GC B cells, respectively, suggesting that AP4 functions as a gauge for extracellular microenvironment and scales the magnitude of lymphocyte expansion accordingly. Mechanistically, ChIP-seq and gene expression analyses suggest that AP4 compensates for early termination of c-MYC by maintaining the transcription of activation signature genes initiated by c-MYC. Thus, both CD8 T and GC B cells have evolved to utilize the c-MYC-AP4 transcription factor cascade to maximize immune responses

Indication for Large Rescatterings in Charmless Rare B Decays

The current wealth of charmless B decay data may suggest the presence of final state rescattering. In a factorized amplitude approach, better fits are found by incorporating two SU(3) rescattering phase differences, giving delta ~ 65 degree and sigma ~ 90 - 100 degree. Fitting with unitarity phase phi_3 as a fit parameter gives phi_3 ~ 96 degree, the CP asymmetries A_{pi pi}, S_{pi pi} agree better with BaBar, and the sigma phase is slightly lower. Keeping phi_3 = 60 degree fixed in fit gives S_{pi pi} ~-0.9, which agrees better with Belle. With the sizable delta, sigma rescattering phases as fitted, many direct CP asymmetries flip sign, and B0 --> pi0 pi0, K- K+ rates are of order 10^{-6}, which can be tested soon.Comment: 6 pages, 4 figures, updated, references adde