arXiv subjects

Adam Noel

Publications and source records attributed to Adam Noel.

At least 19 recordsLinked to original sources

arXiv2025

Diffusion Dynamics in Biofilms with Time-Varying Channels

A biofilm is a self-contained community of bacteria that uses signaling molecules called autoinducers (AIs) to coordinate responses through the process of quorum sensing. Biofilms exhibit a dual role that drives interest in both combating antimicrobial resistance (AMR) and leveraging their potential in bioprocessing, since their products can have commercial potential. Previous work has demonstrated how the distinct anisotropic channel geometry in some biofilms affects AIs propagation therein. In this paper, a 2D anisotropic biofilm channel model is extended to be a time-varying channel (TVC), in order to represent the diffusion dynamics during the maturation phase when water channels develop. Since maturation is associated with the development of anisotropy, the time-varying model captures the shift from isotropic to anisotropic diffusion. Particle-based simulation results illustrate how the TVC is a hybrid scenario incorporating propagation features of both isotropic and anisotropic diffusion. This hybrid behavior aligns with biofilm maturation. Further study of the TVC includes characterization of the mutual information (MI), which reveals that an increased AI count, reduced transmitter -- receiver distance, greater degree of anisotropy, and shorter inter-symbol interference lengths increase the MI. Finally, a brief dimensional analysis demonstrates the scalability of the anisotropic channel results for larger biofilms and timescales.

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arXiv2025

General Molecular Communication Model in Multi-Layered Spherical Channels

Spherical multi-layered structures are prevalent in numerous biological systems and engineered applications, including tumor spheroids, layered tissues, and multi-shell nanoparticles for targeted drug delivery. Despite their widespread occurrence, there remains a gap in modeling particle propagation through these complex structures from a molecular communication (MC) perspective. This paper introduces a generalized analytical framework for modeling diffusion-based molecular communication in multi-layered spherical environments. The framework is capable of supporting an arbitrary number of layers and flexible transmitter-receiver positioning. As an example, the detailed formulation is presented for the three-layer sphere, which is particularly relevant for different biological models such as tumor spheroids. The analytical results are validated using particle-based simulation (PBS) in scenarios that have short inter-layer distances. The findings reveal that the characteristics of each layer significantly impact molecule propagation throughout the entire structure, making their consideration crucial for designing targeted therapies and optimizing drug delivery systems.

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arXiv2024

Anisotropic Diffusion Model of Communication in 2D Biofilm

A biofilm is a microbial city. It consists of bacteria embedded in an extracellular polymeric substance (EPS) that functions as a protective barrier. Quorum sensing (QS) is a method of bacterial communication, where autoinducers (AIs) propagate via diffusion through the EPS and water channels within the biofilm. This diffusion process is anisotropic due to varying densities between the EPS and water channels. This study introduces a 2D anisotropic diffusion model for molecular communication (MC) within biofilms, analyzing information propagation between a point-to-point transmitter (TX) and receiver (RX) in bounded space. The channel impulse response is derived using Green's function for concentration (GFC) and is validated with particle-based simulation (PBS). The outcomes reveal similar results for both isotropic and anisotropic diffusion when the TX is centrally located due to symmetry. However, anisotropic conditions lead to greater diffusion peaks when the TX is positioned off-center. Additionally, the propagation of AIs is inversely proportional to both overall biofilm size and and diffusion coefficient values. It is hypothesized that anisotropic diffusion supports faster responses to hostile environmental changes because signals can propagate faster from the edge of the biofilm to the center.

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arXiv2024

Single Input Multi Output Model of Molecular Communication via Diffusion with Spheroidal Receivers

Spheroids are aggregates of cells that can mimic the cellular organization often found in tissues. They are typically formed through the self-assembly of cells in a culture where there is a promotion of interactions and cell-to-cell communication. Spheroids can be created from various cell types, including cancer cells, stem cells, and primary cells, and they serve as valuable tools in biological research. In this letter, molecule propagation from a point source is simulated in the presence of multiple spheroids to observe the impact of the spheroids on the spatial molecule distribution. The spheroids are modeled as porous media with a corresponding effective diffusion coefficient. System variations are considered with a higher spheroid porosity (i.e., with a higher effective diffusion coefficient) and with molecule uptake by the spheroid cells (approximated as a first-order degradation reaction while molecules diffuse within the spheroid). Results provide initial insights about the molecule propagation dynamics and their potential to model transport and drug delivery within crowded spheroid systems.

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arXiv2023

Spheroidal Molecular Communication via Diffusion: Signaling Between Homogeneous Cell Aggregates

Recent molecular communication (MC) research has integrated more detailed computational models to capture the dynamics of practical biophysical systems. This research focuses on developing realistic models for MC transceivers inspired by spheroids - three-dimensional cell aggregates commonly used in organ-on-chip experimental systems. Potential applications that can be used or modeled with spheroids include nutrient transport in an organ-on-chip system, the release of biomarkers or reception of drug molecules by a cancerous tumor site, or transceiver nanomachines participating in information exchange. In this paper, a simple diffusive MC system is considered where a spheroidal transmitter and receiver are in an unbounded fluid environment. These spheroidal antennas are modeled as porous media for diffusive signaling molecules, then their boundary conditions and effective diffusion coefficients are characterized. Further, for either a point source or spheroidal transmitter, Green's function for concentration (GFC) outside and inside the receiving spheroid is analytically derived and formulated in terms of an infinite series and confirmed by a particle-based simulator (PBS). The provided GFCs enable computation of the transmitted and received signals in the spheroidal communication system. This study shows that the porous structure of the receiving spheroid amplifies diffusion signals but also disperses them, thus there is a trade-off between porosity and information transmission rate. Also, the results reveal that the porous arrangement of the transmitting spheroid not only disperses the received signal but also attenuates it. System performance is also evaluated in terms of bit error rate (BER). Decreasing the porosity of the receiving spheroid is shown to enhance system performance. Conversely, reducing the porosity of the transmitting spheroid can adversely affect system performance.

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arXiv2023

Biophysical Model for Signal-Embedded Droplet Soaking into 2D Cell Culture

Using agar plates hosting a 2D cell population stimulated with signaling molecules is crucial for experiments such as gene regulation and drug discovery in a wide range of biological studies. In this paper, a biophysical model is proposed that incorporates droplet soaking, diffusion of molecules within agar, cell growth over an agar surface, and absorption of signaling molecules by cells. The proposed model describes the channel response and provides valuable insights for designing experiments more efficiently and accurately. The molecule release rate due to droplet soaking into agar, which is characterized and modeled as the source term for the diffusion model, is derived. Furthermore, cell growth is considered over the surface, which dictates the dynamics of signaling molecule reactions and leads to a variable boundary condition. As a case study, genetically-modified $E.\,coli$ bacteria are spread over the surface of agar and Isopropyl-beta-D thiogalactopyranoside (IPTG) is considered as a signaling molecule. IPTG droplets are dropped onto the bacteria-covered agar surface. The parameters for the IPTG molecule release rate as a diffusion source into the agar are estimated from this experiment. Then, a particle-based simulator is used to obtain the spatio-temporal profile of the signaling molecules received by the surface bacteria. The results indicate that the number of molecules reacting with or absorbed by bacteria at different locations on the surface could be widely different, which highlights the importance of taking this variation into account for biological inferences.

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arXiv2023

Diffusive Molecular Communication with a Spheroidal Receiver for Organ-on-Chip Systems

Realistic models of the components and processes are required for molecular communication (MC) systems. In this paper, a spheroidal receiver structure is proposed for MC that is inspired by the 3D cell cultures known as spheroids being widely used in organ-on-chip systems. A simple diffusive MC system is considered where the spheroidal receiver and a point source transmitter are in an unbounded fluid environment. The spheroidal receiver is modeled as a porous medium for diffusive signaling molecules, then its boundary conditions and effective diffusion coefficient are characterized. It is revealed that the spheroid amplifies the diffusion signal, but also disperses the signal which reduces the information communication rate. Furthermore, we analytically formulate and derive the concentration Green's function inside and outside the spheroid in terms of infinite series-forms that are confirmed by a particle-based simulator (PBS).

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arXiv2021

Membrane Fusion-Based Transmitter Design for Static and Diffusive Mobile Molecular Communication Systems

This paper proposes a novel imperfect transmitter (TX) model, namely the membrane fusion (MF)-based TX, that adopts MF between a vesicle and the TX membrane to release molecules encapsulated within the vesicle. For the MF-based TX, the molecule release probability and the fraction of molecules released from the TX membrane are derived. Incorporating molecular degradation and a fully-absorbing receiver (RX), the channel impulse response (CIR) is derived for two scenarios: 1) Both TX and RX are static, and 2) both TX and RX are diffusion-based mobile. Moreover, a sequence of bits transmitted from the TX to the RX is considered. The average bit error rate (BER) is obtained for both scenarios, wherein the probability mass function (PMF) of the number of molecules absorbed in the mobile scenario is derived. Furthermore, a simulation framework is proposed for the MF-based TX, based on which the derived analytical expressions are validated. Simulation results show that a low MF probability or low vesicle mobility slows the release of molecules and reduces the molecule hitting probability at the RX. Simulation results also indicate the difference between the MF-based TX and an ideal point TX in terms of the inter-symbol interference (ISI).

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arXiv2020

Membrane Fusion-Based Transmitter Design for Molecular Communication Systems

This paper proposes a novel imperfect spherical transmitter (TX) model, namely the membrane fusion (MF)-based TX, that adopts MF between a vesicle and the TX membrane to release molecules encapsulated within the vesicle. For the MF-based TX, the molecule release probability and the fraction of molecules released from the TX membrane are derived. Incorporating molecular degradation and a fully-absorbing receiver (RX), the end-to-end molecule hitting probability at the RX is also derived. A simulation framework for the MF-based TX is proposed, where the released point on the TX membrane and the released time of each molecule are determined. Aided by the simulation framework, the derived analytical expressions are validated. Simulation results verify that a low MF probability or low vesicle mobility slows the release of molecules from the TX, extends time required to reach the peak release probability, and reduces the end-to-end molecule hitting probability at the RX.

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arXiv2020

A Survey of Molecular Communication in Cell Biology: Establishing a New Hierarchy for Interdisciplinary Applications

Molecular communication (MC) engineering is inspired by the use of chemical signals as information carriers in cell biology. The biological nature of chemical signaling makes MC a promising methodology for interdisciplinary applications requiring communication between cells and other microscale devices. However, since the life sciences and communications engineering fields have distinct approaches to formulating and solving research problems, the mismatch between them can hinder the translation of research results and impede the development and implementation of interdisciplinary solutions. To bridge this gap, this survey proposes a novel communication hierarchy for MC signaling in cell biology and maps phenomena, contributions, and problems to the hierarchy. The hierarchy includes: 1) the Physical Signal Propagation level; 2) the Physical and Chemical Signal Interaction level; 3) the Signal-Data Interface level; 4) the Local Data Abstraction level; and 5) the Application level. To further demonstrate the proposed hierarchy, it is applied to case studies on quorum sensing, neuronal signaling, and communication via DNA. Finally, several open problems are identified for each level and the integration of multiple levels. The proposed hierarchy provides language for communication engineers to study and interface with biological systems, and also helps biologists to understand how communications engineering concepts can be exploited to interpret, control, and manipulate signaling in cell biology.

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arXiv2020

Characterization of Cooperators in Quorum Sensing with 2D Molecular Signal Analysis

In quorum sensing (QS), bacteria exchange molecular signals to work together. An analytically-tractable model is presented for characterizing QS signal propagation within a population of bacteria and the number of responsive cooperative bacteria (i.e., cooperators) in a two-dimensional (2D) environment. Unlike prior works with a deterministic topology and a simplified molecular propagation channel, this work considers continuous emission, diffusion, degradation, and reception among randomly-distributed bacteria. Using stochastic geometry, the 2D channel response and the corresponding probability of cooperation at a bacterium are derived. Based on this probability, new expressions are derived for the moment generating function and different orders of moments of the number of cooperators. The analytical results agree with the simulation results obtained by a particle-based method. In addition, the Poisson and Gaussian distributions are compared to approximate the distribution of the number of cooperators and the Poisson distribution provides the best overall approximation. The derived channel response can be generally applied to any molecular communication model where single or multiple transmitters continuously release molecules into a 2D environment. The derived statistics of the number of cooperators can be used to predict and control the QS process, e.g., predicting and decreasing the likelihood of biofilm formation.

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arXiv2020

Parameter Estimation in a Noisy 1D Environment via Two Absorbing Receivers

This paper investigates the estimation of different parameters, e.g., propagation distance and flow velocity, by utilizing two fully-absorbing receivers (RXs) in a one-dimensional (1D) environment. The time-varying number of absorbed molecules at each RX and the number of absorbed molecules in a time interval as time approaches infinity are derived. Noisy molecules in this environment, that are released by sources in addition to the transmitter, are also considered. A novel estimation method, namely difference estimation (DE), is proposed to eliminate the effect of noise by using the difference of received signals at the two RXs. For DE, the Cramer-Rao lower bound (CRLB) on the variance of estimation is derived. Independent maximum likelihood estimation is also considered at each RX as a benchmark to show the performance advantage of DE. Aided by particle-based simulation, the derived analytical results are verified. Furthermore, numerical results show that DE attains the CRLB and is less sensitive to the change of noise than independent estimation at each RX.

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arXiv2019

Channel Characterization for 1D Molecular Communication with Two Absorbing Receivers

This letter develops a one-dimensional (1D) diffusion-based molecular communication system to analyze channel responses between a single transmitter (TX) and two fully-absorbing receivers (RXs). Incorporating molecular degradation in the environment, rigorous analytical formulas for i) the fraction of molecules absorbed, ii) the corresponding hitting rate, and iii) the asymptotic fraction of absorbed molecules as time approaches infinity at each RX are derived when an impulse of molecules are released at the TX. By using particle-based simulations, the derived analytical expressions are validated. Simulations also present the distance ranges of two RXs that do not impact molecular absorption of each other, and demonstrate that the mutual imfluence of two active RXs reduces with the increase in the degradation rate.

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arXiv2019

Modeling Interference-Free Neuron Spikes with Optogenetic Stimulation

This paper predicts the ability to externally control the firing times of a cortical neuron whose behavior follows the Izhikevich neuron model. The Izhikevich neuron model provides an efficient and biologically plausible method to track a cortical neuron's membrane potential and its firing times. The external control is a simple optogenetic model represented by an illumination source that stimulates a saturating or decaying membrane current. This paper considers firing frequencies that are sufficiently low for the membrane potential to return to its resting potential after it fires. The time required for the neuron to charge and for the neuron to recover to the resting potential are numerically fitted to functions of the Izhikevich neuron model parameters and the peak input current. Results show that simple functions of the model parameters and maximum input current can be used to predict the charging and recovery times, even when there are deviations in the actual parameter values. Furthermore, the predictions lead to lower bounds on the firing frequency that can be achieved without significant distortion.

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arXiv2019

Molecular Information Delivery in Porous Media

Information delivery via molecular signals is abundant in nature and potentially useful for industry sensing. Many propagation channels (e.g., tissue membranes and catalyst beds) contain porous medium materials and the impact this has on communication performance is not well understood. Here, communication through realistic porous channels is investigated for the first time via statistical breakthrough curves. Assuming that the number of arrived molecules can be approximated as a Gaussian random variable and using fully resolved computational fluid dynamics results for the breakthrough curves, the numerical results for the throughput, mutual information, error probability, and information diversity gain are presented. Using these numerical results, the unique characteristics of the porous medium channel are revealed.

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arXiv2018

Channel Modeling for Diffusive Molecular Communication - A Tutorial Review

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 time-varying 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 experimentally-driven 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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arXiv2018

Expected Density of Cooperative Bacteria in a 2D Quorum Sensing Based Molecular Communication System

The exchange of small molecular signals within microbial populations is generally referred to as quorum sensing (QS). QS is ubiquitous in nature and enables microorganisms to respond to fluctuations in living environments by working together. In this study, a QS-based molecular communication system within a microbial population in a two-dimensional (2D) environment is analytically modeled. Microorganisms are randomly distributed on a 2D circle where each one releases molecules at random times. The number of molecules observed at each randomly-distributed bacterium is first derived by characterizing the diffusion and degradation of signaling molecules within the population. Using the derived result and some approximation, the expected density of cooperative bacteria is derived. Our model captures the basic features of QS. The analytical results for noisy signal propagation agree with simulation results where the Brownian motion of molecules is simulated by a particle-based method. Therefore, we anticipate that our model can be used to predict the density of cooperative bacteria in a variety of QS-coordinated activities, e.g., biofilm formation and antibiotic resistance.

q-bio.CB↗

arXiv2018

Diffusive Molecular Communication in a Biological Spherical Environment with Partially Absorbing Boundary

Diffusive molecular communication (DMC) is envisioned as a promising approach to help realize healthcare applications within bounded biological environments. In this paper, a DMC system within a biological spherical environment is considered, inspired by bounded biological sphere-like structures throughout the body. As a biological environment, it is assumed that the inner surface of the sphere's boundary is fully covered by biological receptors that may irreversibly react with hitting molecules. Moreover, information molecules diffusing in the sphere may undergo a degradation reaction and be transformed to another molecule type. Concentration Green's function (CGF) of diffusion inside this environment is analytically obtained in terms of a convergent infinite series. By employing the obtained CGF, the information channel between transmitter and transparent receiver of DMC in this environment is characterized. Interestingly, it is revealed that the information channel is reciprocal, i.e., interchanging the position of receiver and transmitter does not change the information channel. Our results indicate that the conventional simplifying assumption that the environment is unbounded may lead to an inaccurate characterization in such biological environments.

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