Molecular Communications Loss Budget for tsRNA Detection in the Brain

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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Publication Details

Journal
IEEE Transactions on Molecular Biological and Multi-Scale Communications
Published
2025-03-26
DOI
https://doi.org/10.1109/tmbmc.2025.3554674
Primary Topic
Advanced biosensing and bioanalysis techniques
Type
article
Field-Weighted Citation Impact
0.00

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article

Molecular Communications Loss Budget for tsRNA Detection in the Brain

Aiman Khalil, Daniel P. Martins, Anne Skogberg, Deirdre Kilbane et al.
IEEE Transactions on Molecular Biological and Multi-Scale Communications
Advanced biosensing and bioanalysis techniques
article

Molecular Communications Loss Budget for tsRNA Detection in the Brain

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

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.

IEEE Transactions on Molecular Biological and Multi-Scale CommunicationsVol. 11(3)
University of Essex (GB), Tampere University (FI), Technological University Dublin (IE), South East Technological University (IE)
Science Foundation Ireland, European Regional Development Fund
Openalex Percentile: Top 95%
Advanced biosensing and bioanalysis techniques
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