IEEE Transactions on Molecular, Biological, and Multi-Scale Communications最新文献

{"title":"Diffusion Dynamics in Biofilms With Time-Varying Channels","authors":"Yanahan Paramalingam;Adam Noel","doi":"10.1109/TMBMC.2026.3712314","DOIUrl":"https://doi.org/10.1109/TMBMC.2026.3712314","url":null,"abstract":"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.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"12 ","pages":"730-739"},"PeriodicalIF":2.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148627495","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}

{"title":"Vessel Network Topology in Molecular Communication: Insights From Experiments and Theory","authors":"Timo Jakumeit;Lukas Brand;Jens Kirchner;Robert Schober;Sebastian Lotter","doi":"10.1109/TMBMC.2026.3719315","DOIUrl":"https://doi.org/10.1109/TMBMC.2026.3719315","url":null,"abstract":"The notion of synthetic molecular communication (MC) refers to the transmission of information via signaling molecules and is foreseen to enable innovative medical applications in the human cardiovascular system (CVS). Crucially, the design of such applications requires accurate and experimentally validated channel models that characterize the propagation of signaling molecules, not just in individual blood vessels, but in complex vessel networks (VNs), as prevalent in the CVS. However, experimentally validated models for MC in VNs remain scarce. To address this gap, we propose a novel channel model for MC in complex VN topologies, which captures molecular transport via advection, molecular and turbulent diffusion, as well as adsorption and desorption at the vessel walls. We specialize this model for superparamagnetic iron-oxide nanoparticles (SPIONs) as signaling molecules by introducing a new receiver (RX) model for planar coil inductive sensors, enabling end-to-end experimental validation with a dedicated SPION testbed. Validation covers a range of channel topologies, from single-vessel topologies to branched VNs with multiple paths between transmitter (TX) and RX. Additionally, to quantify how the VN topology impacts signal quality, and inspired by multi-path propagation models in conventional wireless communications, we introduce two metrics, namely <italic>molecule delay</i> and <italic>multi-path spread</i>. We show that these metrics link the VN structure to molecule dispersion induced by the VN and mediately to the resulting signal-to-noise ratio (SNR) at the RX. The proposed VN structure-SNR link is validated experimentally, indicating that the proposed framework may be able to guide prospective tasks such as optimal sensor placement in the CVS or the identification of suitable testbed topologies for specific SNR requirements. All experimental data are openly available on Zenodo.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"12 ","pages":"882-899"},"PeriodicalIF":2.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148780947","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}

{"title":"Achievable Information Rate of Diffusive Molecular Communication Channels With Binary Concentration Shift Keying","authors":"Fardad Vakilipoor;Luca Barletta;Stefano Bregni;Maurizio Magarini","doi":"10.1109/TMBMC.2026.3735194","DOIUrl":"https://doi.org/10.1109/TMBMC.2026.3735194","url":null,"abstract":"This paper explores the achievable information rate (AIR) of a diffusive molecular communication (MC) channel featuring a fully absorbing (FA) receiver that counts the absorbed particles during symbol time intervals (STIs). The MC channel, influenced by memory effect, experiences inter-symbol interference (ISI) arising from the molecules’ delayed arrival. The channel’s memory is quantified as an integer multiple of the STI and a single-sample memoryless detector is employed to mitigate complexity in computing the mutual information (MI). To maximize MI, the detector threshold is optimized under Gaussian approximation of its input. The channel’s MI is calculated, considering the influence of ISI, in the context of binary concentration shift keying modulation. Two distinct scenarios were considered; memoryless and correlated source-generated symbols, the latter modeled as a first-order Markov process. For each communication scenario, two degrees of knowledge: ISI-Aware and ISI-Unaware were considered. Remarkably, it is demonstrated that employing a correlated source enables attaining higher constrained capacity (CC). The results indicate that the CC-achieving input distribution is not necessarily uniform. Notably, when the STI is small, corresponding to the case of strong ISI, the maximum AIR is not achieved through equiprobable symbol transmission.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"12 ","pages":"1019-1028"},"PeriodicalIF":2.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149033613","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}

{"title":"Deterministic Identification in Molecular Communication Over Diffusion-Based Discrete-Time Poisson Channels","authors":"Yaning Zhao;Luca Miszewski;Christian Deppe;Massimiliano Pierobon","doi":"10.1109/TMBMC.2026.3738681","DOIUrl":"https://doi.org/10.1109/TMBMC.2026.3738681","url":null,"abstract":"Molecular communication (MC) enables information exchange at the nano- and microscale and has promising applications in targeted drug delivery, health monitoring, quorum sensing and other biomedical systems. Such event-driven scenarios often require alternatives to conventional data transmission. Message identification, introduced by Ahlswede and Dueck, provides a suitable paradigm in which the receiver determines only whether a particular message was sent, making it well suited for resource-constrained and event-triggered systems. In this paper, we integrate identification theory with MC and propose a one-dimensional (1D) diffusion-based discrete-time Poisson channel (DTPC) model. We derive both lower and upper bounds on the identification capacity of the proposed channel. Furthermore, simulations using short-length deterministic codes are conducted to validate the theoretical analysis, including the channel impulse response and error performance. The results provide insights into the fundamental limits of identification over MC channels and support the design of practical MC systems and testbeds.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"12 ","pages":"1139-1149"},"PeriodicalIF":2.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149249768","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}

{"title":"Understanding Entanglement Through the Lens of Quantifiable Algebraic Structures: Application to Bird Navigation","authors":"Sahil Imtiyaz;Serafim Rodrigues","doi":"10.1109/TMBMC.2025.3650156","DOIUrl":"https://doi.org/10.1109/TMBMC.2025.3650156","url":null,"abstract":"We propose a unified mathematical meta-framework for long-distance navigation in birds, based on a bundle-theoretic representation of multisensory integration within evolving combinatorial structures. Various information streams—such as magnetic, celestial, olfactory, and landmark cues—are modeled as typed fibers over a time-varying simplicial base, which is reconstructed from behavioral trajectories and neural co-activity. In this framework, integration is framed as a global consistency problem: coherent system-level representations occur when there are globally compatible assignments across overlapping local contexts. This is equivalent to finding global sections of an evolving bundle. The tension between local and global perspectives is formalized in quantum theory through the concept of contextuality, which expresses the impossibility of a single, non-contextual global assignment that is consistent with all local marginals. In Bell-type scenarios, this aligns with operational non-locality and device-independent signatures of entanglement. We demonstrate that the same constraint semantics provide a precise mathematical connection between canonical contextuality models and biological cue integration, treating contextuality as a calculus for diagnosing and localizing incompatibilities in distributed representations. Our theory introduces two computable topological observables: critical simplices and interface loops. Critical simplices identify discrete remapping pivots where the structural scaffold must be reconfigured to restore consistency, while interface loops detect transient conflict cycles at the boundaries between different information streams. Together, these observables form a diagnostic “compass” that integrates cues onto a common scaffold, localizes incompatible overlaps, and predicts when spatial representations need to be remapped. We validate our framework using standard quantum contextuality scenarios, including Bell’s theorem and Klyachko–Can–Binicioǧlu–Shumovsky scenario (KCBS), successfully recovering established contextuality classifications through bundle obstructions and loop signatures. We then apply this framework to an anatomy-aware model of avian navigation, in which entanglement-capable cryptochrome/radical-pair dynamics serve as a microscopic source of non-classical correlations, without assuming that macroscopic entanglement occurs across neural circuits. In this model, microscopic non-classicality influences adaptive functions by leaving persistent, computable contextual footprints within the evolving biological scaffold, providing testable signatures at the level of remapping events and context-dependent cue integration.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"12 ","pages":"279-297"},"PeriodicalIF":2.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146082133","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}

{"title":"An Iterative Framework for Assessing the Firing Probability of Leaky Integrate and Fire Neurons With a Novel Threshold Adaptation Mechanism","authors":"Chittotosh Ganguly;Byomakesh Mahapatra","doi":"10.1109/TMBMC.2026.3686294","DOIUrl":"https://doi.org/10.1109/TMBMC.2026.3686294","url":null,"abstract":"Artificial intelligence and deep learning have opened a new frontier for solving complex real-life problems that are not analytically solvable. The core neuron model in the deep neural network (DNN) is based on activation functions. Recently, a shift has been observed towards biologically plausible, energy-efficient spiking neural networks (SNNs) that use spiking neurons as their core computational units. Leaky integrate-and-fire (LIF) models are widely used in spiking neural networks. However, a simple LIF model lacks spike-frequency adaptation (SFA), an intrinsic property of biological neurons. SFA provides spiking stability and prevents excessive spike generation under sustained stimulation. One way to implement SFA in spiking neuron models is through a history-dependent adaptive threshold. A novel neuron model based on the LIF framework with a prior spiking history-based threshold adaptation technique is proposed in this paper. Unlike conventional adaptive LIF models that use a fixed threshold increment after each spiking event, the proposed model employs inter-spike-interval-based threshold adaptation. The model is compared with three closely related existing models through extensive simulations, which show that the proposed model attains a better SFA. The proposed Spiking neuron model with the novel threshold adaptation technique has been used to perform an iterative statistical analysis of the probability of spike generation over time. A non-stationary random process has been treated as a sequence of random variables through this iterative statistical framework.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"12 ","pages":"517-526"},"PeriodicalIF":2.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828795","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}

{"title":"Flexure-FET-Based Receiver With Competitive Binding for Interference Mitigation in Molecular Communication","authors":"Dilara Aktas;Ozgur B. Akan","doi":"10.1109/TMBMC.2026.3690065","DOIUrl":"https://doi.org/10.1109/TMBMC.2026.3690065","url":null,"abstract":"Molecular communication (MC), a biologically-inspired technology, enables applications in nanonetworks and the Internet of Everything (IoE), offering unprecedented potential in intra-body systems for applications such as drug delivery, health monitoring, and disease detection. In this paper, we extend our previous research on the Flexure-FET MC receiver by integrating a competitive binding model to enhance its performance in high-interference environments, where multiple species coexist in the reception space. While previous studies have primarily focused on ligand concentration estimation and detection methods, they have not fully addressed the competition between molecular species for receptor binding sites. The competitive binding framework introduced here plays a pivotal role in multitarget environments, closely reflecting real-world biological scenarios. By accounting for the competition between species for receptor binding sites, this framework enhances the understanding of MC dynamics in complex environments. Leveraging this framework enables the fine-tuning of receptor responses, optimizing Flexure-FET MC receiver performance through adjustments in ligand concentrations and receptor affinities. Through comprehensive performance analysis, we demonstrate that integrating competitive binding underscores the importance of accounting for interference in MC systems to improve reliability and accuracy. While the signal-to-noise ratio (SNR) and symbol error probability (SEP) are impacted by factors such as interferer concentration and receptor dynamics, the framework emphasizes the need to manage these interference factors to optimize the system’s overall performance. The results show that accounting for interference—through competitive binding—provides a more realistic understanding of system behavior and enables the fine-tuning of the receiver’s response, ultimately ensuring more reliable and accurate detection in environments where multiple species are present.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"12 ","pages":"542-551"},"PeriodicalIF":2.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147828809","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}

{"title":"On the Reliability of Information Retrieval From MDS Coded Data in DNA Storage","authors":"Serge Kas Hanna","doi":"10.1109/TMBMC.2026.3690724","DOIUrl":"https://doi.org/10.1109/TMBMC.2026.3690724","url":null,"abstract":"This work presents a theoretical analysis of the probability of successfully retrieving data encoded with MDS codes (e.g., Reed-Solomon codes) in DNA storage systems. We study this probability under independent and identically distributed (i.i.d.) substitution errors, focusing on a common code design strategy that combines inner and outer MDS codes. Our analysis demonstrates how this probability depends on factors such as the total number of sequencing reads, their distribution across encoded sequences, the rates of the inner and outer codes, and the substitution error probabilities. These results provide actionable insights into optimizing DNA storage systems under reliability constraints, including determining the minimum number of sequencing reads needed for reliable data retrieval and identifying the optimal balance between the rates of inner and outer MDS codes.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"12 ","pages":"585-598"},"PeriodicalIF":2.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148003607","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}

{"title":"A Software-Defined Perspective on Molecular Networking in the Internet of BioNanoThings","authors":"Annalisa Ciuchi;Francesco Chiti;Stefano Caputo;Giacomo Borghini;Maurizio Magarini;Lorenzo Mucchi","doi":"10.1109/TMBMC.2026.3678212","DOIUrl":"https://doi.org/10.1109/TMBMC.2026.3678212","url":null,"abstract":"The Internet of BioNanoThings (IoBNT) envisions networks of nanoscale biological entities, called bionanomachines, capable of sensing, processing, and communicating within living systems. These entities rely on molecular communication (MC), a biologically compatible method that uses biochemical signals instead of electromagnetic waves. While promising for intra-body applications such as diagnostics and targeted therapy, MC faces inherent limitations, including noise, limited range, and lack of programmability. This work proposes a novel integration of Software-Defined Networking (SDN) principles into MC systems to address these challenges. By mapping SDN components, such as flow tables, match fields, and control logic, to biological counterparts, we introduce the concept of Bio-SDN: a programmable, layered architecture for orchestrating bionanomachines. DNA-based messaging and bacterial carriers enable addressable control channels, while synthetic biology tools such as logic gates and promoter tuning support decision-making and prioritization. Applications include real-time health monitoring, adaptive drug delivery, and environmental biosensing. The paper also discusses fault management strategies and outlines key challenges in reliability, mutation control, bio-cyber interfacing, and security. Bio-SDN offers a scalable framework for managing biological networks, paving the way for intelligent, responsive systems embedded within living organisms.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"12 ","pages":"451-466"},"PeriodicalIF":2.3,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147665341","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}

{"title":"Guest Editorial ISBRA 2025–Advanced Graph Models for Biological Systems","authors":"Jing Tang;Xin Lai","doi":"10.1109/TMBMC.2026.3683174","DOIUrl":"https://doi.org/10.1109/TMBMC.2026.3683174","url":null,"abstract":"","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":"12 ","pages":"viii-ix"},"PeriodicalIF":2.5,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11494405","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148505413","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}