Molecular Communications Loss Budget for tsRNA Detection in the Brain

IF 2.3 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Pub Date : 2025-03-25 DOI:10.1109/TMBMC.2025.3554674

Aiman Khalil;Kurt J. A. Pumares;Anne Skogberg;Pasi Kallio;Deirdre Kilbane;Daniel P. Martins

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Abstract

Molecular communication (MC) is an emerging framework enabling communication among biological cells and bio-nanomachines at nano and micro scales through biochemical molecules. Recent studies have identified exosomal transfer RNA-derived small RNAs (tsRNAs) as potential biomarkers for epilepsy. Consequently, researchers are exploring innovative methods to predict epileptic seizures through tsRNA measurements, using implantable micro/nanoscale biosensors. This paper presents a propagation model for biomarkers in a heterogeneous fluidic environment, composed of the brain extracellular space (ECS), a polyethersulfone (PES) hollow fiber tube, and a hydrogel (e.g., collagen) containing bioengineered sensing cells for biomarker detection. Our proposed model aims to support the design of biosensing devices for epileptic seizure prediction by characterizing the propagation of biomarkers released from neuronal cells in the brain ECS to the implant. We analyse the communication performance of the proposed system by evaluating propagation loss under varying conditions-brain ECS tortuosity, fiber membrane thickness, permeability, and bioengineered sensing cell density. Furthermore, we develop an MC link budget to assess communication between exosomal tsRNA biomarkers and bioengineered sensing cells, based on received biomarkers. We observed an approximate 8-fold loss in received signal strength, highlighting the impact of MC communication media physicochemical characteristics for accurately designing devices to predict epileptic seizures.

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脑中tsRNA检测的分子通信损失预算

分子通信（Molecular communication， MC）是一种新兴的生物细胞和生物纳米机器之间通过生物化学分子在纳米和微尺度上进行通信的框架。最近的研究已经确定外显体转移rna衍生的小rna （tsRNAs）是癫痫的潜在生物标志物。因此，研究人员正在探索利用可植入的微/纳米级生物传感器，通过tsRNA测量来预测癫痫发作的创新方法。本文提出了生物标志物在异质流体环境中的传播模型，该模型由脑细胞外空间（ECS）、聚醚砜（PES）中空纤维管和含有生物工程传感细胞的水凝胶（如胶原蛋白）组成，用于生物标志物检测。我们提出的模型旨在通过表征大脑ECS中神经元细胞释放的生物标志物向植入物的传播来支持癫痫发作预测的生物传感装置的设计。我们通过评估不同条件下的传播损失（脑ECS扭曲度、纤维膜厚度、渗透率和生物工程传感细胞密度）来分析所提出系统的通信性能。此外，我们开发了一个MC链接预算来评估外泌体tsRNA生物标志物和生物工程传感细胞之间的通信，基于接收到的生物标志物。我们观察到接收到的信号强度大约损失了8倍，这突出了MC通信介质的物理化学特性对准确设计预测癫痫发作的设备的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Mathematics-Modeling and Simulation

CiteScore

3.90

自引率

13.60%

发文量

期刊介绍： As a result of recent advances in MEMS/NEMS and systems biology, as well as the emergence of synthetic bacteria and lab/process-on-a-chip techniques, it is now possible to design chemical “circuits”, custom organisms, micro/nanoscale swarms of devices, and a host of other new systems. This success opens up a new frontier for interdisciplinary communications techniques using chemistry, biology, and other principles that have not been considered in the communications literature. The IEEE Transactions on Molecular, Biological, and Multi-Scale Communications (T-MBMSC) is devoted to the principles, design, and analysis of communication systems that use physics beyond classical electromagnetism. This includes molecular, quantum, and other physical, chemical and biological techniques; as well as new communication techniques at small scales or across multiple scales (e.g., nano to micro to macro; note that strictly nanoscale systems, 1-100 nm, are outside the scope of this journal). Original research articles on one or more of the following topics are within scope: mathematical modeling, information/communication and network theoretic analysis, standardization and industrial applications, and analytical or experimental studies on communication processes or networks in biology. Contributions on related topics may also be considered for publication. Contributions from researchers outside the IEEE’s typical audience are encouraged.