Nikolaos Ntetsikas;Styliana Kyriakoudi;Antonis Kirmizis;Bige Deniz Unluturk;Andreas Pitsillides;Ian F. Akyildiz;Marios Lestas
{"title":"Engineering Yeast Cells to Facilitate Information Exchange","authors":"Nikolaos Ntetsikas;Styliana Kyriakoudi;Antonis Kirmizis;Bige Deniz Unluturk;Andreas Pitsillides;Ian F. Akyildiz;Marios Lestas","doi":"10.1109/TMBMC.2024.3360051","DOIUrl":"https://doi.org/10.1109/TMBMC.2024.3360051","url":null,"abstract":"Although continuous advances in theoretical modelling of Molecular Communications (MC) are observed, there is still an insuperable gap between theory and experimental testbeds, especially at the microscale. In this paper, the development of the first testbed incorporating engineered yeast cells is reported. Different from the existing literature, eukaryotic yeast cells are considered for both the sender and the receiver, with \u0000<inline-formula> <tex-math>$alpha $ </tex-math></inline-formula>\u0000-factor molecules facilitating the information transfer. The use of such cells is motivated mainly by the well understood biological mechanism of yeast mating, together with their genetic amenability. In addition, recent advances in yeast biosensing establish yeast as a suitable detector and a neat interface to in-body sensor networks. The system under consideration is presented first, and the mathematical models of the underlying biological processes leading to an end-to-end (E2E) system are given. The experimental setup is then described and used to obtain experimental results which validate the developed mathematical models. Beyond that, the ability of the system to effectively generate output pulses in response to repeated stimuli is demonstrated, reporting one event per two hours. However, fast RNA fluctuations indicate cell responses in less than three minutes, demonstrating the potential for much higher rates in the future.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161169","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":"Individual Adaptive Regulation Strategy Inspired by Artificial Fish Swarm Algorithm for Tumor Targeting","authors":"Yue Sun;Shanchao Wen;Shaolong Shi;Yifan Chen","doi":"10.1109/TMBMC.2024.3361251","DOIUrl":"https://doi.org/10.1109/TMBMC.2024.3361251","url":null,"abstract":"The use of nanoparticles for tumor-targeted therapy has become an emergent topic in molecular communications due to the similarity in information propagation and drug delivery. This paper introduces a novel approach called individual adaptive regulation strategy (IARS) to enhance tumor targeting, drawing inspiration from the collective behavior of fish swarms. This approach does not require any prior knowledge of tumor location. The goal is to leverage the intelligence and adaptability of fish swarms to improve drug delivery efficiency and effectiveness and enhance the early-stage tumor detection rate. The approach integrates the perceptual information of nanoswimmers (NSs) with the biological gradient fields (BGFs) induced by tumors, which departs from the existing approaches that rely solely on the information perception of a single nanoparticle to the BGFs. IARS can dynamically adjust the motion direction of NSs in response to the characteristics of the tumor microenvironment. Extensive simulations and experiments demonstrate the efficacy and resilience of the proposed strategy, indicating promising outcomes in cancer treatment through targeted drug delivery.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161105","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":"Microfluidic Molecular Communication Transmitter Based on Hydrodynamic Gating","authors":"Iman Mokari Bolhassan;Ali Abdali;Murat Kuscu","doi":"10.1109/TMBMC.2024.3361443","DOIUrl":"https://doi.org/10.1109/TMBMC.2024.3361443","url":null,"abstract":"Molecular Communications (MC) is a bio-inspired paradigm for transmitting information using chemical signals, which can enable novel applications at the junction of biotechnology, nanotechnology, and information and communication technologies. However, designing efficient and reliable MC systems poses significant challenges due to the complex nature of the physical channel and the limitations of the micro/nanoscale transmitter and receiver devices. In this paper, we propose a practical microfluidic transmitter architecture for MC based on hydrodynamic gating, a widely utilized technique for generating chemical waveforms in microfluidic channels with high spatiotemporal resolution. We develop an approximate analytical model that can capture the fundamental characteristics of the generated molecular pulses, such as pulse width, pulse amplitude, and pulse delay, as functions of main system parameters, such as flow velocity and gating duration. We validate the accuracy of our model by comparing it with finite element simulations using COMSOL Multiphysics under various system settings. Our analytical model can enable the optimization of microfluidic transmitters for MC applications in terms of minimizing intersymbol interference and maximizing data transmission rate.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161218","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":"Signal Detection of Cooperative Multi-Hop Mobile Molecular Communication via Diffusion","authors":"Zhen Cheng;Zhichao Zhang;Jie Sun","doi":"10.1109/TMBMC.2024.3360341","DOIUrl":"https://doi.org/10.1109/TMBMC.2024.3360341","url":null,"abstract":"The data-driven detectors based on deep learning have promising applications in signal detection with unknown channel parameters of molecular communication via diffusion (MCvD) system. In this paper, a signal detector for cooperative multi-hop mobile MCvD system with amplify-forward relaying strategy by using Transformer-based model is proposed. The mathematical expressions of the numbers of received molecules when considering two transmission schemes including multi-molecule-type (MMT) and single-molecule-type (SMT) are derived in order to generate the training dataset. On this basis, the training dataset is used to train the Transformer-based model offline. Then the trained Transformer-based model is adopted to detect the received signal under unknown channel parameters under MMT and SMT. Numerical results show that the Transformer-based model performs the best detection ability in cooperative multi-hop mobile MCvD system with lowest bit error rate of signal detection compared with deep neural networks (DNN) detector and convolutional neural networks (CNN) detector.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161106","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}
Chengyi Zhang;Hao Yan;Qiang Liu;Kun Yang;Fuqiang Liu;Lin Lin
{"title":"Design and Analysis of a Through-Body Signal Transmission System Based on Human Oxygen Saturation Detection","authors":"Chengyi Zhang;Hao Yan;Qiang Liu;Kun Yang;Fuqiang Liu;Lin Lin","doi":"10.1109/TMBMC.2023.3349326","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3349326","url":null,"abstract":"For a long time, people have carried out various studies on molecular communication (MC) and the Internet of Bio-Nanothings (IoBNT) in order to realize biomedical applications inside the human body. However, how to realize the communication between these applications and the outside body has become a new problem. In general, different components in the blood have different light absorption rates. Based on this, we propose a new through-body communication method. The nanomachine in the blood vessel transmits signals by releasing certain substances that can influence blood oxygen saturation. The change in blood oxygen saturation can be detected by an outside body device measuring the attenuation of the light through the blood. The framework of the entire communication system is proposed and mathematically modeled. Its error performance is discussed and evaluated. The mutual information (MI) of the designed communication system is also derived and calculated. This research will contribute to the realization of the connection of the IoBNT inside the human body to the outside device.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2024-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161128","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":"2023 Index IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Vol.9","authors":"","doi":"10.1109/TMBMC.2023.3345590","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3345590","url":null,"abstract":"","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10372180","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139034111","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}
{"title":"Received Signal and Channel Parameter Estimation in Molecular Communications","authors":"O. Tansel Baydas;Ozgur B. Akan","doi":"10.1109/TMBMC.2023.3342731","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3342731","url":null,"abstract":"Molecular communication (MC) is a paradigm that employs molecules as information carriers, hence, requiring unconventional transceivers and detection techniques for the Internet of Bio-Nano Things (IoBNT). In this study, we provide a novel MC model that incorporates a spherical transmitter and receiver with partial absorption. This model offers a more realistic representation than receiver architectures in literature, e.g., passive or entirely absorbing configurations. An optimization-based technique utilizing particle swarm optimization (PSO) is employed to accurately estimate the cumulative number of molecules received. This technique yields nearly constant correction parameters and demonstrates a significant improvement of 5 times in terms of root mean square error (RMSE) compared to the literature. The estimated channel model provides an approximate analytical impulse response; hence, it is used for estimating channel parameters such as distance, diffusion coefficient, or a combination of both. The iterative maximum likelihood estimation (MLE) is applied for the parameter estimation, which gives consistent errors compared to the estimated Cramer-Rao Lower Bound (CLRB).","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161246","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":"Advances in Predicting Drug Functions: A Decade-Long Survey in Drug Discovery Research","authors":"Pranab Das;Dilwar Hussain Mazumder","doi":"10.1109/TMBMC.2023.3345145","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3345145","url":null,"abstract":"Drug function study is vital in current drug discovery, design, and development. Determining the drug functions of a novel drug is time-consuming, complicated, expensive, and requires many experts and clinical testing phases. The computational-based drug function prediction activity has recently become more attractive due to its capability to reduce drug development design complexity, time, human resources, cost, chemical waste, and the risk of failure. The evolution of the computational model has advanced as an effective tool for predicting and analyzing drug functions, which are derived from Medical Subject Headings (MeSH). However, predicting drug functions still faces several difficulties. Therefore, an exhaustive literature survey was conducted that discusses the application of computational methods to predict drug functions in the past decade. Additionally, this paper discusses the utilization of drug functions as an input feature to predict adverse drug reactions and disease classification. This work also provides an overview of the computational models with their performance, multi-label problem transformation methods, drug properties, and their sources needed for the task of drug function prediction. Finally, unsolved issues, research gaps, and difficulties with the drug function prediction task have been summarized.","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140161170","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":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Publication Information","authors":"","doi":"10.1109/TMBMC.2023.3326009","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3326009","url":null,"abstract":"","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10364886","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138739585","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}
{"title":"IEEE Communications Society Information","authors":"","doi":"10.1109/TMBMC.2023.3326011","DOIUrl":"https://doi.org/10.1109/TMBMC.2023.3326011","url":null,"abstract":"","PeriodicalId":36530,"journal":{"name":"IEEE Transactions on Molecular, Biological, and Multi-Scale Communications","volume":null,"pages":null},"PeriodicalIF":2.2,"publicationDate":"2023-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10364920","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138739584","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}