Modeling CD40-Based Molecular Communications in Blood Vessels

Felicetti, Luca; Femminella, Mauro; Reali, Gianluca; Gresele, Paolo; Malvestiti, Marco; Daigle, John N.

doi:10.1109/tnb.2014.2340134

Cited by 53 publications

(28 citation statements)

References 41 publications

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“…In particular, in [9], bacterial populations were used as transceivers connected through a microfluidic channel. In [10], soluble CD40L molecules were released from platelets (as transmitter) into a fluid medium that upon contact triggered the activation of endothelial cells (as receiver).…”

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confidence: 99%

Biological Optical-to-Chemical Signal Conversion Interface: A Small-Scale Modulator for Molecular Communications

Grebenstein

Kirchner

Peixoto

et al. 2019

IEEE Trans.on Nanobioscience

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Although many exciting applications of molecular communication (MC) systems are envisioned to be at microscale, the MC testbeds reported in the literature so far are mostly at macroscale. This may partially be due to the fact that controlling an MC system at microscale is challenging. To link the macroworld to the microworld, we propose and demonstrate a biological signal conversion interface that can also be seen as a microscale modulator. In particular, the proposed interface transduces an optical signal, which is controlled using a lightemitting diode (LED), into a chemical signal by changing the pH of the environment. The modulator is realized using Escherichia coli bacteria as microscale entity expressing the light-driven proton pump gloeorhodopsin from Gloeobacter violaceus. Upon inducing external light stimuli, these bacteria locally change their surrounding pH level by exporting protons into the environment. To verify the effectiveness of the proposed optical-to-chemical signal converter, we analyze the pH signal measured by a pH sensor, which serves as receiver. We develop an analytical parametric model for the induced chemical signal as a function of the applied optical signal. Using this model, we derive a trainingbased channel estimator which estimates the parameters of the proposed model to fit the measurement data based on a least square error approach. We further derive the optimal maximum likelihood detector and a suboptimal low-complexity detector to recover the transmitted data from the measured received signal. It is shown that the proposed parametric model is in good agreement with the measurement data. Moreover, for an example scenario, we show that the proposed setup is able to successfully convert an optical signal representing a sequence of binary symbols into a chemical signal with a bit rate of 1 bit/min and recover the transmitted data from the chemical signal using the proposed estimation and detection schemes. The proposed modulator may form the basis for future MC testbeds and applications at microscale.

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mentioning

confidence: 99%

Biological Optical-to-Chemical Signal Conversion Interface: A Small-Scale Modulator for Molecular Communications

Grebenstein

Kirchner

Peixoto

et al. 2019

IEEE Trans.on Nanobioscience

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“…We note that similar inherent randomness and nonlinearities as discussed for the two examples above also exist for other experimental testbeds [59], [137], [138], [139], [140], [141], [72], [142], [143], [144], [145] and are challenging to model analytically or even simulate since their exact cause is unknown.…”

Section: B Experimentally-driven Modelsmentioning

confidence: 87%

“…Nevertheless, for system design, it is desirable to have simple yet sufficiently accurate analytical models for complex multi-node networks. Developing such analytical models constitutes an important future research topic, see [153], [42], [143], [75] for some related works.…”

Section: Challenges and Directions For Future Workmentioning

confidence: 99%

Channel Modeling for Diffusive Molecular Communication—A Tutorial Review

et al. 2019

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Molecular communication (MC) is a new communication engineering paradigm where molecules are employed as information carriers. MC systems are expected to enable new revolutionary applications such as sensing of target substances in biotechnology, smart drug delivery in medicine, and monitoring of oil pipelines or chemical reactors in industrial settings. As for any other kind of communication, simple yet sufficiently accurate channel models are needed for the design, analysis, and efficient operation of MC systems. In this paper, we provide a tutorial review on mathematical channel modeling for diffusive MC systems. The considered end-to-end MC channel models incorporate the effects of the release mechanism, the MC environment, and the reception mechanism on the observed information molecules. Thereby, the various existing models for the different components of an MC system are presented under a common framework and the underlying biological, chemical, and physical phenomena are discussed. Deterministic models characterizing the expected number of molecules observed at the receiver and statistical models characterizing the actual number of observed molecules are developed. In addition, we provide channel models for timevarying MC systems with moving transmitters and receivers, which are relevant for advanced applications such as smart drug delivery with mobile nanomachines. For complex scenarios, where simple MC channel models cannot be obtained from first principles, we investigate simulation-driven and experimentallydriven channel models. Finally, we provide a detailed discussion of potential challenges, open research problems, and future directions in channel modeling for diffusive MC systems.

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“…The response to a pulse of carriers released by a mobile transmitter, measured on a number of receivers located along the vessel wall based on simulation results is studied in [22]. In [23], the authors propose a mathematical model for MC between platelets and endothelial cells via CD40 signaling based on a two-dimensional Markov chain. This model along with typical propagation models of blood vessels, has been incorporated into a simulation platform.…”

Section: Introductionmentioning

confidence: 99%

Diffusive Molecular Communication in Biological Cylindrical Environment

Zoofaghari

Arjmandi

2019

IEEE Trans.on Nanobioscience

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Diffusive molecular communication (DMC) is one of the most promising approaches for realizing nano-scale communications in biological environments for healthcare applications. In this paper, a DMC system in biological cylindrical environment is considered, inspired by blood vessel structures in the body. The internal surface of the cylinder boundary is assumed to be covered by the biological receptors which may irreversibly react with hitting molecules. Also, information molecules diffusing in the fluid medium are subject to a degradation reaction and flow. The concentration Green's function of diffusion in this environment is analytically derived which takes into account asymmetry in all radial, axial and azimuthal coordinates. Employing obtained Green's function, information channel between transmitter and transparent receiver of DMC is characterized. To evaluate the DMC system in the biological cylinder, a simple on-off keying modulation scheme is adopted and corresponding error probability is derived.Particle based simulation results confirm the proposed analysis. Also, the effect of different system parameters on the concentration Green's function are examined. Our results reveal that the degradation reaction and the boundary covered by biological receptors may be utilized to mitigate intersymbol interference and outperform corresponding error probability. Index TermsDiffusive molecular communication (DMC), biological environment, partial differential equation, Green's function.

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Modeling CD40-Based Molecular Communications in Blood Vessels

Cited by 53 publications

References 41 publications

Biological Optical-to-Chemical Signal Conversion Interface: A Small-Scale Modulator for Molecular Communications

Biological Optical-to-Chemical Signal Conversion Interface: A Small-Scale Modulator for Molecular Communications

Channel Modeling for Diffusive Molecular Communication—A Tutorial Review

Diffusive Molecular Communication in Biological Cylindrical Environment

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