Molecular communication (MC) is envisioned to realize nanotheranostics as an emerging diagnostic tool to improve existing treatment modalities. Phase separation (PS) is a complex time-dependent process responsible for discrimination of two independent phases from a single homogeneous mixture. Recently, PS was revealed to be the fundamental mechanism behind formation and organization of the living cells. Inspired by PS mechanisms in nature, we establish a novel modulation scheme for MC which encodes the information in the dispersion of molecules diffusing in the environment. Hence, the diffusion distribution can be considered as carriers of molecules. To evaluate the performance of this communication scheme, a dual-carrier diffusion-division modulation (DDM) is adopted where each carrier can be effectively modeled by superposition of multiple independent phases. We derive the theoretical bit error rate (BER) of the proposed DDM scheme which is validated by particle-based simulation (PBS). Furthermore, performance of the multi-carrier DDM scheme is compared to the well-known on-off keying (OOK) modulation scheme (as the most relevant benchmark) and pulse-position modulation (PPM) scheme. It is shown that performance of the DDM-based MC system can be boosted by increasing the transmission power and/or using multiple carriers. Interestingly, the proposed DDM is a covert modulation scheme since any other receiver cannot decode the transmitted signal by just counting the number of received molecules unless having the shared key. Moreover, the DDM scheme requires a receiver that exploits the displacement distribution of the molecules inside the receiver to infer about the tranmitted bit. We strongly believe that this concept will introduce novel types of communication schemes more compatible with biological microenvironments. Also, this work establishes the foundation for more complex orthogonal multi-carrier DDM schemes which can potentially unlock novel cellular sensing mechanisms in biology.

Intercellular communication is crucial for organ function, with extracellular vesicles (EVs) acting as common messengers for almost all cells. This study proposes a novel EV-mediated intercellular communication system that uses a modulation technique regulated via altered intracellular-cytosolic calcium dynamics regulation. As a case study, intercellular communication within a cardiac muscle is considered with cardiomyocyte cells serving as transceivers. Through molecular communication theory, we propose a comprehensive model addressing EV release kinetics, propagation, degradation, and uptake. A linear time-invariant Poisson channel model is developed and closed-form expressions, verified through particle-based simulations, are derived for EV detection probabilities at the receiver. A closed-form bit error probability is derived and validated through Monte Carlo simulations. By selecting an optimal receiver threshold: 1) bit error rate (BER) in EV-mediated intercellular communication is robust against adverse effects from cardiac disorders, such as myocardial infarction; 2) transmitter design can be optimized by minimizing actuation signal amplitude and pulse width; 3) BER stays stable across heart rates for different distances, demonstrating the robustness of EV-mediated communication. This study enhances our ability to engineer precise and reliable intra-body cardiac communications, which may offer valuable applications for cardiovascular disease treatment, for example, the realization of biological lead-less multi-nodal pacemakers.

Treating brain diseases with therapeutic particles imposes significant challenges as particles are usually too large to traverse the gaps between endothelial cells in the blood-brain barrier (BBB). Focused ultrasound (FUS) for disruption of the BBB has been proposed as a remedy. However, the extent of disruption and the efficiency of the particle delivery to the regions of interest are highly dependent on FUS sonication parameters. This study investigates the effects of not only FUS sonication parameters but also the therapeutic particle admin-istration scheme by exploiting communication-theoretic channel modeling. Specifically, the particle pathways from blood vessels to hallmarked spots in the brain interstitial space are abstracted as a single-input-multiple-output (SIMO) channel. The channel outputs are then examined through the lenses of communication-theoretic measures such as channel gain, transmission efficiency, signal-to-noise ratio, and bit error ratio. The numerical results are displayed utilizing the available clinical data on six patients with brain cancer. The results show that the proposed approach could be exploited in future studies to maximize the efficacy of the treatment and minimize adverse effects.

Novel non-invasive procedures, such as targeted drug delivery may enhance the efficacy of treatments of cardiac disorders. A possible solution is to utilize a molecular communication paradigm based on cell-derived nano-sized vesicles --- extracellular vesicles (EVs) --- that can be used as vehicles for therapeutic biological cargo. EVs can be engineered with specific cell-targeting transmembrane proteins to improve their pharmacokinetic properties. Here, we study the transport of EVs in a non-cellular component of cardiac tissue referred to as the cardiac extracellular matrix (ECM). We inspect EV diffusion and advection in cardiac ECM by considering 1) tortuosity, which describes the convoluted pathway of EV transportation, 2) volume fraction, which characterizes the porosity of the cardiac ECM; and 3) EV degradation according to their half-life in the body. We analytically describe the EV transportation dynamics via a partial differential equation and solve it numerically using finite element methods. The presented findings indicate that EV propagation is dependent on the cardiac ECM hindrance sources. Bulk flow in the cardiac ECM, however, can mediate the EVs to reach their distant target cells.

Information theory provides maximum possible information transfer over communication channels, including neural channels recently emerged as remarkable for disruptive nano-networking applications. Information theory was successfully applied to quantify the ability of biological sensory neurons to transfer the information from dynamic stimuli. However, a little of information theory has been subjected to quantify the reliability of neuro-transmission between synaptically coupled neurons. Neuro-transmission, regarded as molecular synaptic communication, relays information between neurons and significantly affects the overall brain processing performance. In this study, we use concepts from information theory to provide the framework based on closed-form expressions that quantify the information rate allowing assessment of neuro-transmission when the parameters are provided for any type of neurons. Considering Poissonian statistics and the rate coding model of neural communication, we show how the information transferred between cortical neurons depend on the molecular, physiological and morphological diversity of cells, the firing rate, and the synaptic wiring. With synaptic redundancy, we infer the ability of an isolated post-synaptic neuron to reliably convey information encoded in the spike train from a pre-synaptic neuron. Estimating information rate between neurons primarily serves in the evaluation of the overall performance of biological neural nano-networks and the development of artificial nano-networks.

Disease-affected nervous systems exhibit anatomical or physiological impairments that degrade processing, transfer, storage, and retrieval of neural information, leading to physical or intellectual disabilities. Brain implants may potentially promote clinical means for detecting and treating neurological symptoms by establishing direct communication between the nervous and artificial systems. Current technology can modify the neural function at the supracellular level as in Parkinson's disease, epilepsy, and depression. However, recent advances in nanotechnology, nanomaterials, and molecular communications have the potential to enable brain implants to preserve the neural function at the subcellular level, which could increase effectiveness, decrease energy consumption, and make the leadless devices chargeable from outside the body or by utilizing the body's own energy sources. In this paper, we focus on understanding the principles of elemental processes in synapses to enable diagnosis and treatment of brain diseases with pathological conditions using biomimetic synaptically interactive brain-machine interfaces (BMIs). First, we provide an overview of the synaptic communication system, followed by an outline of brain diseases that promote dysfunction in the synaptic communication system. Then, we discuss the technologies for brain implants and propose future directions for the design and fabrication of cognitive BMIs. The overarching goal of this paper is to summarize the status of engineering research at the interface between the technology and the nervous system and direct the ongoing research toward the point where synaptically interactive BMIs can be embedded in the nervous system.

Serving as peers in the central nervous system, neurons make use of two communication paradigms, electrochemical, and molecular. Owing to their effective coordination of all the voluntary and involuntary actions of the body, an intriguing neuronal communication nominates as a potential paradigm for nano-networking. In this paper, we propose an alternative representation of the neuron-to-neuron communication process, which should offer a complementary insight into the electrochemical signals propagation. To this end, we apply communication-engineering tools and abstractions, represent information about chemical and ionic behavior with signals, and observe biological systems as input-output systems characterized by a frequency response. In particular, we inspect the neuron-to-neuron communication through the concepts of electrochemical communication, which we refer to as the intra-neuronal communication due to the pulse transmission within the cell, and molecular synaptic transmission, which we refer to as the inter-neuronal communication due to particle transmission between the cells. The inter-neuronal communication is explored by means of the transmitter, the channel, and the receiver, aiming to characterize the spiking propagation between neurons. Reported numerical results illustrate the contribution of each stage along the neuronal communication pathway, and should be useful for the design of a new communication technique for nano-networks and intrabody communications.

Neuronal communication is a biological phenomenon of the central nervous system that influences the activity of all intra-body nano-networks. The implicit biocompatibility and dimensional similarity of neurons with miniature devices make their interaction a promising communication paradigm for nano-networks. To understand the information transfer in neuronal networks, there is a need to characterize the noise sources and unreliability associated with different components of the functional apposition between two cells-the synapse. In this paper, we introduce analogies between the optical communication system and the neuronal communication system to apply results from optical Poisson channels in deriving theoretical upper bounds on the information capacity of both the bipartite and tripartite synapses. The latter refer to the anatomical and functional integration of two communicating neurons and surrounding glia cells. The efficacy of information transfer is analyzed under different synaptic setups with progressive complexity, and is shown to depend on the peak rate of the communicated spiking sequence and neurotransmitter (spontaneous) release, neurotransmitter propagation, and neurotransmitter binding. The results provided serve as a progressive step in the evaluation of the performance of neuronal nano-networks and the development of new artificial nano-networks.

Biological structures are typically based on molecular communication systems which use a myriad of molecule types to encode messages. Among the cells found in living organisms, interconnected neurons communicate by means of neurotransmitters, particles that serve as physical carriers of information. Owing to information propagation among the nano-scale components, neuronal communication is recently identified as a potential candidate for nano-networking. This paper elaborates on the concept of molecular synaptic transmission between neurons, aiming to give an insight into the performance of physical end-to-end model according to the cell physiology. The synaptic transmission is investigated from several aspects: the transmitter (pre-synaptic terminal), the channel (synaptic cleft), and the receiver (post-synaptic terminal), with a goal to characterize the propagation of the spiking rate function between neurons. Moreover, some ideas on how to incorporate the impact of astrocytic processes to the neuronal communication are presented.