Pub Date : 2025-04-18DOI: 10.1109/TMBMC.2025.3562353
Caglar Koca;Mustafa Ozger;Oktay Cetinkaya;Ozgur B. Akan
Internet of Things (IoT) translates the physical world into a cyber form using wireless sensors. However, these sensors often lack longevity due to their energy-constrained batteries. This limitation is particularly critical for the Internet of Bio-Nano Things (IoBNT), in which sensors usually operate within an organism with minimum opportunities for replenishment. Thus, adopting energy-efficient strategies is vital to maximize the lifetime of such sensors and ensure the reliable execution of associated applications. To address this, this letter proposes an event-driven, time-adaptive transmission scheme based on the Kullback-Leibler (KL) distance. Specifically, the KL distance is used to measure the worth of transmitting the current sensor reading, enabling the sensor to decide whether to transmit in that sampling period, thereby saving energy and extending its lifetime. Furthermore, we identify the operational regions for sensors, namely safe, unsafe, and action, depending on application-specific parameters. The design and implementation of the required circuitry are also discussed, considering the unique constraints of the IoBNT. Performance evaluation validates that the KL distance improves sensor lifetime with an acceptable information loss.
{"title":"Information-Theoretic Lifetime Maximization for IoBNT-Enabled Sensing","authors":"Caglar Koca;Mustafa Ozger;Oktay Cetinkaya;Ozgur B. Akan","doi":"10.1109/TMBMC.2025.3562353","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3562353","url":null,"abstract":"Internet of Things (IoT) translates the physical world into a cyber form using wireless sensors. However, these sensors often lack longevity due to their energy-constrained batteries. This limitation is particularly critical for the Internet of Bio-Nano Things (IoBNT), in which sensors usually operate within an organism with minimum opportunities for replenishment. Thus, adopting energy-efficient strategies is vital to maximize the lifetime of such sensors and ensure the reliable execution of associated applications. To address this, this letter proposes an event-driven, time-adaptive transmission scheme based on the Kullback-Leibler (KL) distance. Specifically, the KL distance is used to measure the worth of transmitting the current sensor reading, enabling the sensor to decide whether to transmit in that sampling period, thereby saving energy and extending its lifetime. Furthermore, we identify the operational regions for sensors, namely safe, unsafe, and action, depending on application-specific parameters. The design and implementation of the required circuitry are also discussed, considering the unique constraints of the IoBNT. Performance evaluation validates that the KL distance improves sensor lifetime with an acceptable information loss.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"11 3","pages":"462-466"},"PeriodicalIF":2.3,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036856","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Evolutionary developmental biology, biomedicine, neuroscience, and many aspects of the social sciences are impacted by insight into forces that facilitate the merging of active subunits into an emergent collective. The dynamics of interaction between agents are often studied in game theory, such as the popular Prisoner’s Dilemma (PD) paradigm, but the impact of these models on higher scales of organization, and their contributions to questions of how agents distinguish borders between themselves and the outside world, are not clear. Here we applied a spatialized, iterated PD model to understand the dynamics of the formation of large-scale tissues (colonies that act as one) out of single cell agents. In particular, we broke a standard assumption of PD: instead of a fixed number of players which can Cooperate or Defect on each round, we let the borders of individuality remain fluid, enabling agents to also Merge or Split. The consequences of enabling agents’ actions to change the number of agents in the world result in non-linear dynamics that are not known in advance: would higher-level (composite) individuals emerge? We characterized changes in collective formation as a function of memory size of the subunits. Our results show that when the number of agents is determined by the agents’ behavior, PD dynamics favor multicellularity, including the emergence of structured cell-groups, eventually leading to one single fully-merged tissue. These larger agents were found to have higher causal emergence than smaller ones. Moreover, we observed different spatial distributions of merged connectivity vs. of similar behavioral propensities, revealing that rich but distinct structures can coexist at the level of physical structure and the space of behavioral propensities. These dynamics raise a number of interesting and deep questions about decision-making in a self-modifying system that transitions from a metabolic to a morphological problem space, and how collective intelligences emerge, scale, and pattern.
{"title":"Extending Iterated, Spatialized Prisoner’s Dilemma to Understand Multicellularity: Game Theory With Self-Scaling Players","authors":"Lakshwin Shreesha;Federico Pigozzi;Adam Goldstein;Michael Levin","doi":"10.1109/TMBMC.2025.3562358","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3562358","url":null,"abstract":"Evolutionary developmental biology, biomedicine, neuroscience, and many aspects of the social sciences are impacted by insight into forces that facilitate the merging of active subunits into an emergent collective. The dynamics of interaction between agents are often studied in game theory, such as the popular Prisoner’s Dilemma (PD) paradigm, but the impact of these models on higher scales of organization, and their contributions to questions of how agents distinguish borders between themselves and the outside world, are not clear. Here we applied a spatialized, iterated PD model to understand the dynamics of the formation of large-scale tissues (colonies that act as one) out of single cell agents. In particular, we broke a standard assumption of PD: instead of a fixed number of players which can Cooperate or Defect on each round, we let the borders of individuality remain fluid, enabling agents to also Merge or Split. The consequences of enabling agents’ actions to change the number of agents in the world result in non-linear dynamics that are not known in advance: would higher-level (composite) individuals emerge? We characterized changes in collective formation as a function of memory size of the subunits. Our results show that when the number of agents is determined by the agents’ behavior, PD dynamics favor multicellularity, including the emergence of structured cell-groups, eventually leading to one single fully-merged tissue. These larger agents were found to have higher causal emergence than smaller ones. Moreover, we observed different spatial distributions of merged connectivity vs. of similar behavioral propensities, revealing that rich but distinct structures can coexist at the level of physical structure and the space of behavioral propensities. These dynamics raise a number of interesting and deep questions about decision-making in a self-modifying system that transitions from a metabolic to a morphological problem space, and how collective intelligences emerge, scale, and pattern.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"11 2","pages":"135-151"},"PeriodicalIF":2.4,"publicationDate":"2025-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10970107","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144272882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-09DOI: 10.1109/TMBMC.2025.3559470
Rinrada Jadsadaphongphaibool;Dadi Bi;Christian D. Lorenz;Yansha Deng;Robert Schober
Diabetes mellitus is a global health crisis characterized by poor blood sugar regulation, impacting millions of people worldwide and leading to severe complications and mortality. Although Type 1 Diabetes Mellitus (T1DM) has a lower number of cases compared to other forms of diabetes, it is often diagnosed at a young age and requires lifelong exogenous insulin administration. In this paper, we focus on understanding the interaction of insulin and glucose molecules within the subcutaneous layer, which is crucial for blood sugar control in T1DM patients. Specifically, we propose a comprehensive model to characterize the insulin-glucose system within the subcutaneous layer, incorporating a multicellular molecular communication system. We then divide the T1DM system into insulin and glucose subsystems and derive the end-to-end expression for insulin-glucose interaction in the subcutaneous layer. We further validate the insulin-glucose interaction analysis with an agent-based simulator. As effectively managing postprandial glucose levels is crucial for individuals with T1DM to safeguard their overall health and avert short-term and long-term complications, we also derive the optimal insulin administration time based on the derived glucose response via the Lagrange multiplier and gradient descent ascent method. This allows us to explore the impact of different types of insulin and dietary management on blood sugar levels. Simulation results confirm the correctness of our proposed model and the effectiveness of our optimized effective time window for injecting insulin in individuals with T1DM.
{"title":"Modeling and Optimization of Insulin Injection for Type-1 Diabetes Mellitus Management","authors":"Rinrada Jadsadaphongphaibool;Dadi Bi;Christian D. Lorenz;Yansha Deng;Robert Schober","doi":"10.1109/TMBMC.2025.3559470","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3559470","url":null,"abstract":"Diabetes mellitus is a global health crisis characterized by poor blood sugar regulation, impacting millions of people worldwide and leading to severe complications and mortality. Although Type 1 Diabetes Mellitus (T1DM) has a lower number of cases compared to other forms of diabetes, it is often diagnosed at a young age and requires lifelong exogenous insulin administration. In this paper, we focus on understanding the interaction of insulin and glucose molecules within the subcutaneous layer, which is crucial for blood sugar control in T1DM patients. Specifically, we propose a comprehensive model to characterize the insulin-glucose system within the subcutaneous layer, incorporating a multicellular molecular communication system. We then divide the T1DM system into insulin and glucose subsystems and derive the end-to-end expression for insulin-glucose interaction in the subcutaneous layer. We further validate the insulin-glucose interaction analysis with an agent-based simulator. As effectively managing postprandial glucose levels is crucial for individuals with T1DM to safeguard their overall health and avert short-term and long-term complications, we also derive the optimal insulin administration time based on the derived glucose response via the Lagrange multiplier and gradient descent ascent method. This allows us to explore the impact of different types of insulin and dietary management on blood sugar levels. Simulation results confirm the correctness of our proposed model and the effectiveness of our optimized effective time window for injecting insulin in individuals with T1DM.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"11 3","pages":"344-358"},"PeriodicalIF":2.3,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-04DOI: 10.1109/TMBMC.2025.3558109
Nihit Bhatnagar;Sandeep Joshi
This work considers a three-dimensional mobile molecular communication (MC) with intra-body disease spread applications. The communicating devices in the considered mobile MC system are point transmitters and passive spherical receiver nano-machines (NMs) with emitted information-carrying molecules following the Gaussian Brownian motion. These NMs can be used to detect the presence of disease spread and for targeted drug delivery. We propose stochastic diffusivity models for both communicating devices and information-carrying molecules. Using the stochastic diffusivity model and considering initial distance as a reference, we derive the probability density function of the relative distance between the communicating devices. We allocate the time-varying trajectory to the information-carrying molecules moving towards receiver NM and obtain its diffusivity distribution. Through the proposed stochastic diffusivity model, we characterize the mobile MC channel by channel impulse response and derive its statistical mean. We consider the discrete-time statistical channel model at a high inter-symbol interference regime and analyze the channel performance in terms of error analysis and receiver operating characteristics. We also derive the channel capacity for the considered system model. We show the degree of accuracy through root mean square error for the Poisson and Gaussian distribution models. Furthermore, the numerical results are verified through particle-based simulations.
{"title":"Stochastic Diffusivity With Time-Varying Trajectory in Mobile Molecular Communication: Performance Analysis and Channel Modeling","authors":"Nihit Bhatnagar;Sandeep Joshi","doi":"10.1109/TMBMC.2025.3558109","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3558109","url":null,"abstract":"This work considers a three-dimensional mobile molecular communication (MC) with intra-body disease spread applications. The communicating devices in the considered mobile MC system are point transmitters and passive spherical receiver nano-machines (NMs) with emitted information-carrying molecules following the Gaussian Brownian motion. These NMs can be used to detect the presence of disease spread and for targeted drug delivery. We propose stochastic diffusivity models for both communicating devices and information-carrying molecules. Using the stochastic diffusivity model and considering initial distance as a reference, we derive the probability density function of the relative distance between the communicating devices. We allocate the time-varying trajectory to the information-carrying molecules moving towards receiver NM and obtain its diffusivity distribution. Through the proposed stochastic diffusivity model, we characterize the mobile MC channel by channel impulse response and derive its statistical mean. We consider the discrete-time statistical channel model at a high inter-symbol interference regime and analyze the channel performance in terms of error analysis and receiver operating characteristics. We also derive the channel capacity for the considered system model. We show the degree of accuracy through root mean square error for the Poisson and Gaussian distribution models. Furthermore, the numerical results are verified through particle-based simulations.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"11 3","pages":"359-370"},"PeriodicalIF":2.3,"publicationDate":"2025-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-03DOI: 10.1109/TMBMC.2025.3556858
Zhongyang Cheng;Qiang Liu;Kun Yang
Molecular communication (MC) represents a novel approach to communication that employs nanoengineering and bioengineering technology to establish transient communication links in challenging environments. Deoxyribonucleic acid (DNA) molecular communication can transmit more and faster data than traditional molecular communication. Deoxyribonucleic acid (DNA) has been demonstrated to offer significant advantages over traditional information carriers, including its excellent storage density and structural stability, which renders it an ideal medium for information transmission. It is therefore imperative to investigate methods of increasing the data information density of DNA in order to reduce costs and enhance overall performance. LZW encoding is Lempel-Ziv–Welch encoding which creates a string table with shorter codes representing longer strings. Arithmetic coding is a compression process that involves the continuous refinement of probabilities of the input stream within an interval. A notable drawback of LZW coding is its suboptimal compression efficiency and the presence of data redundancy after dictionary mapping. Conversely, arithmetic coding attains compression efficiency that approaches the Shannon limit. In this study, we propose a novel DNA encoding method which is capable of adaptively generating coding streams in accordance with the characteristics of the stored content. The contribution of this paper is as follows: 1) A bespoke coding dictionary is constructed, which is capable of intelligently generating the corresponding coding stream in accordance with the specific characteristics of the file to be stored. 2) Utilising arithmetic coding techniques, these coding streams are converted into the final DNA sequence by means of compression techniques. Following comprehensive verification, it has been established that the information density of this encoding method is markedly superior to that of the prevailing mainstream encoding schemes.
{"title":"A Joint DNA Encoding Approach Based on LZW and Arithmetic Encoding","authors":"Zhongyang Cheng;Qiang Liu;Kun Yang","doi":"10.1109/TMBMC.2025.3556858","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3556858","url":null,"abstract":"Molecular communication (MC) represents a novel approach to communication that employs nanoengineering and bioengineering technology to establish transient communication links in challenging environments. Deoxyribonucleic acid (DNA) molecular communication can transmit more and faster data than traditional molecular communication. Deoxyribonucleic acid (DNA) has been demonstrated to offer significant advantages over traditional information carriers, including its excellent storage density and structural stability, which renders it an ideal medium for information transmission. It is therefore imperative to investigate methods of increasing the data information density of DNA in order to reduce costs and enhance overall performance. LZW encoding is Lempel-Ziv–Welch encoding which creates a string table with shorter codes representing longer strings. Arithmetic coding is a compression process that involves the continuous refinement of probabilities of the input stream within an interval. A notable drawback of LZW coding is its suboptimal compression efficiency and the presence of data redundancy after dictionary mapping. Conversely, arithmetic coding attains compression efficiency that approaches the Shannon limit. In this study, we propose a novel DNA encoding method which is capable of adaptively generating coding streams in accordance with the characteristics of the stored content. The contribution of this paper is as follows: 1) A bespoke coding dictionary is constructed, which is capable of intelligently generating the corresponding coding stream in accordance with the specific characteristics of the file to be stored. 2) Utilising arithmetic coding techniques, these coding streams are converted into the final DNA sequence by means of compression techniques. Following comprehensive verification, it has been established that the information density of this encoding method is markedly superior to that of the prevailing mainstream encoding schemes.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"11 2","pages":"237-245"},"PeriodicalIF":2.4,"publicationDate":"2025-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144272939","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-01DOI: 10.1109/TMBMC.2025.3556883
Michael Gattringer;Stefan Angerbauer;Andreas Springer;Werner Haselmayr
In this work, we present a novel thermomolecular communications gateway allowing communication through the human skin into the human body connecting the Internet of things (IoT) with the Internet of bio-nano things (IoBNT). We develop an experimental setup as a proof of concept and provide a detailed description of the testbed, its assembly and fabrication. Mathematical models for all components are derived and verified experimentally. Finally, we analyze the communications performance of the system and elaborate on future works.
{"title":"A Novel Experimental Platform for Thermomolecular Communications","authors":"Michael Gattringer;Stefan Angerbauer;Andreas Springer;Werner Haselmayr","doi":"10.1109/TMBMC.2025.3556883","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3556883","url":null,"abstract":"In this work, we present a novel thermomolecular communications gateway allowing communication through the human skin into the human body connecting the Internet of things (IoT) with the Internet of bio-nano things (IoBNT). We develop an experimental setup as a proof of concept and provide a detailed description of the testbed, its assembly and fabrication. Mathematical models for all components are derived and verified experimentally. Finally, we analyze the communications performance of the system and elaborate on future works.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"11 3","pages":"384-394"},"PeriodicalIF":2.3,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10947217","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-04-01DOI: 10.1109/TMBMC.2025.3556841
Huiyu Luo;Yi Huang;Lin Lin
With the advancement of the Internet of Nanothings (IoNT), information networks within organisms are becoming increasingly sophisticated, making the transmission of data from IoNT to the external environment a key research focus. Neural communication, as a promising solution, utilizes action potentials (APs) to carry information. However, enhancing the efficiency of data transmission for multiple IoNT nodes in a complex biological environment presents significant challenges. To address these challenges, this paper proposes an adaptive code division multiplexing (CDM) schemes in neural communication based on the oscillatory characteristics of membrane potential, enabling parallel information transmission for multiple IoNT nodes. This scheme assigns each signal an orthogonal code sequence and superimposes them onto a shared channel. To accommodate the oscillatory properties described by the resonate-and-fire (RF) neuron model, our approach further encodes the superimposed signals in CDM schemes, converting both symbolic and numerical bits into binary data for transmission. Simulation results demonstrate that the proposed scheme significantly enhances interference resistance while enabling multiple signals to share a single neuron channel. This paper paves the way for the implementation of IoNT applications.
随着纳米物联网（Internet of Nanothings, IoNT）的发展，生物体内的信息网络变得越来越复杂，使得从纳米物联网到外部环境的数据传输成为一个重要的研究热点。神经通信利用动作电位（ap）传递信息，是一种很有前途的解决方案。然而，在复杂的生物环境中，提高多个IoNT节点的数据传输效率是一个重大挑战。为了解决这些问题，本文提出了一种基于膜电位振荡特性的神经通信自适应码分复用（CDM）方案，实现多个IoNT节点的并行信息传输。该方案为每个信号分配一个正交码序列，并将它们叠加到一个共享信道上。为了适应谐振-放电（RF）神经元模型所描述的振荡特性，我们的方法进一步编码CDM方案中的叠加信号，将符号和数字位转换为二进制数据进行传输。仿真结果表明，该方案在使多个信号共享一个神经元通道的同时，显著提高了抗干扰能力。本文为物联网应用的实现铺平了道路。
{"title":"CDM in Neural Communication Based on Oscillatory Characteristics of Membrane Potential","authors":"Huiyu Luo;Yi Huang;Lin Lin","doi":"10.1109/TMBMC.2025.3556841","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3556841","url":null,"abstract":"With the advancement of the Internet of Nanothings (IoNT), information networks within organisms are becoming increasingly sophisticated, making the transmission of data from IoNT to the external environment a key research focus. Neural communication, as a promising solution, utilizes action potentials (APs) to carry information. However, enhancing the efficiency of data transmission for multiple IoNT nodes in a complex biological environment presents significant challenges. To address these challenges, this paper proposes an adaptive code division multiplexing (CDM) schemes in neural communication based on the oscillatory characteristics of membrane potential, enabling parallel information transmission for multiple IoNT nodes. This scheme assigns each signal an orthogonal code sequence and superimposes them onto a shared channel. To accommodate the oscillatory properties described by the resonate-and-fire (RF) neuron model, our approach further encodes the superimposed signals in CDM schemes, converting both symbolic and numerical bits into binary data for transmission. Simulation results demonstrate that the proposed scheme significantly enhances interference resistance while enabling multiple signals to share a single neuron channel. This paper paves the way for the implementation of IoNT applications.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"11 2","pages":"246-256"},"PeriodicalIF":2.4,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144272913","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-30DOI: 10.1109/TMBMC.2025.3575233
Sammy Hansali;Léo Pio-Lopez;Jennifer V. Lapalme;Michael Levin
Endogenous bioelectrical patterns are an important regulator of anatomical pattern during embryogenesis, regeneration, and cancer. While there are three known classes of instructive bioelectric patterns: directly encoding, indirectly encoding, and binary trigger, it is not known how these design principles could be exploited by evolution and what their relative advantages might be. To better understand the evolutionary role of bioelectricity in anatomical homeostasis, we developed a neural cellular automaton (NCA). We used evolutionary algorithms to optimize these models to achieve reliable morphogenetic patterns driven by the different ways in which tissues can interpret their bioelectrical pattern for downstream anatomical outcomes. We found that: (1) All three types of bioelectrical codes allow the reaching of target morphologies; (2) Resetting of the bioelectrical pattern and the change in duration of the binary trigger alter morphogenesis; (3) Direct pattern organisms show an emergent robustness to changes in initial anatomical configurations; (4) Indirect pattern organisms show an emergent robustness to bioelectrical perturbation; (5) Direct and indirect pattern organisms show a emergent generalizability competency to new (rotated) bioelectrical patterns; (6) Direct pattern organisms show an emergent repatterning competency in post-developmental-phase. Because our simulation was fundamentally a homeostatic system seeking to achieve specific goals in anatomical state space (the space of possible morphologies), we sought to determine how the system would react when we abrogated the incentive loop driving anatomical homeostasis. To abrogate the stress/reward system that drives error minimization, we used anxiolytic neuromodulators. Simulating the effects of selective serotonin reuptake inhibitors diminished the ability of artificial embryos to reduce error between anatomical state and bioelectric prepattern, leading to higher variance of developmental outcomes, global morphological degradation, and induced in some organisms a bistability with respect to possible anatomical outcomes. These computational findings were validated by data collected from in vivo experiments in SSRI exposure in planarian flatworm regeneration.
{"title":"The Role of Bioelectrical Patterns in Regulative Morphogenesis: An Evolutionary Simulation and Validation in Planarian Regeneration","authors":"Sammy Hansali;Léo Pio-Lopez;Jennifer V. Lapalme;Michael Levin","doi":"10.1109/TMBMC.2025.3575233","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3575233","url":null,"abstract":"Endogenous bioelectrical patterns are an important regulator of anatomical pattern during embryogenesis, regeneration, and cancer. While there are three known classes of instructive bioelectric patterns: directly encoding, indirectly encoding, and binary trigger, it is not known how these design principles could be exploited by evolution and what their relative advantages might be. To better understand the evolutionary role of bioelectricity in anatomical homeostasis, we developed a neural cellular automaton (NCA). We used evolutionary algorithms to optimize these models to achieve reliable morphogenetic patterns driven by the different ways in which tissues can interpret their bioelectrical pattern for downstream anatomical outcomes. We found that: (1) All three types of bioelectrical codes allow the reaching of target morphologies; (2) Resetting of the bioelectrical pattern and the change in duration of the binary trigger alter morphogenesis; (3) Direct pattern organisms show an emergent robustness to changes in initial anatomical configurations; (4) Indirect pattern organisms show an emergent robustness to bioelectrical perturbation; (5) Direct and indirect pattern organisms show a emergent generalizability competency to new (rotated) bioelectrical patterns; (6) Direct pattern organisms show an emergent repatterning competency in post-developmental-phase. Because our simulation was fundamentally a homeostatic system seeking to achieve specific goals in anatomical state space (the space of possible morphologies), we sought to determine how the system would react when we abrogated the incentive loop driving anatomical homeostasis. To abrogate the stress/reward system that drives error minimization, we used anxiolytic neuromodulators. Simulating the effects of selective serotonin reuptake inhibitors diminished the ability of artificial embryos to reduce error between anatomical state and bioelectric prepattern, leading to higher variance of developmental outcomes, global morphological degradation, and induced in some organisms a bistability with respect to possible anatomical outcomes. These computational findings were validated by data collected from in vivo experiments in SSRI exposure in planarian flatworm regeneration.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"11 3","pages":"305-331"},"PeriodicalIF":2.3,"publicationDate":"2025-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11018651","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145036857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-03-26DOI: 10.1109/TMBMC.2025.3554640
Nikolaos Ntetsikas;Styliana Kyriakoudi;Antonis Kirmizis Kirmizis;Ioannis Krikidis;Ian F. Akyildiz;Marios Lestas
A critical aspect of Molecular Communications (MC) is the implementation of signal detection policies amidst noise. To date, noise characterizations within the MC field have predominantly drawn from methodologies found in wireless communications literature. In this study, we diverge from existing MC research by utilizing a newly developed experimental platform that employs yeast, allowing us to consider more realistic noise characterizations based on the relevant signaling pathways. We propose suitable signal detection mechanisms tailored to this experimental setup, which focuses on yeast cell-to-cell communications. Our analysis identifies gene transcription as the primary source of noise, and we utilize a Markov birth-death process model with Poisson arrivals and departures to characterize it. The noisy expression of the FUS1 gene is best represented using a mixed Gaussian distribution model. This model serves as a foundation for evaluating the performance of Maximum Likelihood Detection mechanisms in terms of Bit Error Rate (BER) for both symbol-by-symbol and sequence transmission schemes. Error analysis indicates that appropriate adjustments to the signal threshold can reduce errors to as low as 10%, which is not negligible. In contrast, the detection of symbol sequences demonstrates enhanced error performance, achieving error rates as low as 0.4%, albeit at the cost of increased computational complexity.
{"title":"Noise Characterization and Robust Signal Detection in Yeast Pheromone Molecular Communication","authors":"Nikolaos Ntetsikas;Styliana Kyriakoudi;Antonis Kirmizis Kirmizis;Ioannis Krikidis;Ian F. Akyildiz;Marios Lestas","doi":"10.1109/TMBMC.2025.3554640","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3554640","url":null,"abstract":"A critical aspect of Molecular Communications (MC) is the implementation of signal detection policies amidst noise. To date, noise characterizations within the MC field have predominantly drawn from methodologies found in wireless communications literature. In this study, we diverge from existing MC research by utilizing a newly developed experimental platform that employs yeast, allowing us to consider more realistic noise characterizations based on the relevant signaling pathways. We propose suitable signal detection mechanisms tailored to this experimental setup, which focuses on yeast cell-to-cell communications. Our analysis identifies gene transcription as the primary source of noise, and we utilize a Markov birth-death process model with Poisson arrivals and departures to characterize it. The noisy expression of the FUS1 gene is best represented using a mixed Gaussian distribution model. This model serves as a foundation for evaluating the performance of Maximum Likelihood Detection mechanisms in terms of Bit Error Rate (BER) for both symbol-by-symbol and sequence transmission schemes. Error analysis indicates that appropriate adjustments to the signal threshold can reduce errors to as low as 10%, which is not negligible. In contrast, the detection of symbol sequences demonstrates enhanced error performance, achieving error rates as low as 0.4%, albeit at the cost of increased computational complexity.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"11 2","pages":"218-227"},"PeriodicalIF":2.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144272884","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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 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.
{"title":"Anisotropic Diffusion Model of Communication in 2D Biofilm","authors":"Yanahan Paramalingam;Hamidreza Arjmandi;Freya Harrison;Tara Schiller;Adam Noel","doi":"10.1109/TMBMC.2025.3552991","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3552991","url":null,"abstract":"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 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.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"11 2","pages":"176-185"},"PeriodicalIF":2.4,"publicationDate":"2025-03-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144272880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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