Detection in molecular communications with ligand receptors under molecular interference

In recent years, conveying information using molecules via diffusion has attracted significant interest in micro and nanoscale applications. Yet, very little research have been conducted on the performance analysis of large-scale molecular communication (MC) systems with swarm of interfering receivers. In this type of MC system, the collective signal strength at a desired receiver can be impaired by the interference caused by other MC transmitters. The paper presents the first tractable analytical framework for the collective signal strength at a partially absorbing receiver due to a desired transmitter under the impact of a swarm of interfering transmitters in a three-dimensional (3D) large-scale MC system using stochastic geometry. We propose Reed Solomon (RS) coding as an error correction technique to combat the effects of interference caused by the multiple transmitters and the delayed molecules from the previous bits. We derive analytical expressions for the bit error probability (BEP) to evaluate the level of reliability that can be achieved by the proposed scheme. The results obtained using Monte Carlo simulations, matched extactly with the anlytical results, justifying the accuracy of the derivations. Results reveal that the RS codes are capable of providing an acceptable level of improvement in terms of BEP. Furthermore, by carefully selecting the code length, n, and the message length, k, of the RS(n, k) code, we can fine tune the BEP improvement to match the system requirements.

It is generally accepted that abnormal autonomic responsiveness may contribute to the pathogenesis of hyperesthetic rhinitis. Histologically, in the nasal mucosa, cholinergic fibers are found close to blood vessels, but are particularly numerous around the glands. Adrenergic fibers are found mainly around the vascular structures. Physiological and pharmacological studies demonstrate that parasympathetic hypersensitivity causes hypersecretion, and sympathetic hyposensitivity causes vasodilatation. alpha 1-adrenergic receptor function is dominant for this vasodilatation. Using radioligand binding techniques, it has been found that there is an increased number of muscarinic cholinergic receptors and a decreased number of alpha 1- and beta-adrenergic receptors in patients with nasal allergy, while the binding affinities do not change. In this report, using radioligand binding techniques, we investigated the relationships between the number of receptors and the degree of the hyperreactive nasal symptoms in patients with hyperesthetic rhinitis. The results are as follows. 1. The number of muscarinic cholinergic receptors of human nasal mucosa in patients with hyperesthetic rhinitis was related significantly (P less than 0.01) to the degree of hypersecretion induced by methacholine and frequency of blowing nose estimated from allergy diary. 2. There was no relationship between frequency of sneezing and the number of muscarinic cholinergic receptors. 3. The number of alpha 1-adrenergic receptors was related significantly (P less than 0.05) to the degree of swelling of nasal mucosa induced by methoxyamine. Judging from these results, it was assumed that pathogenesis of hyperreactive nasal symptoms may be associated at least partially to the changes of number of autonomic nerve receptors in the nasal mucosa.

In the Molecular Communication (MC), molecules are utilized to encode, transmit, and receive information. Transmission of the information is achieved by means of diffusion of molecules and the information is recovered based on the molecule concentration variations at the receiver location. The MC is very prone to intersymbol interference (ISI) due to residual molecules emitted previously. Furthermore, the stochastic nature of the molecule movements adds noise to the MC. For the first time, we propose four methods for a receiver in the MC to recover the transmitted information distorted by both ISI and noise. We introduce sequence detection methods based on maximum a posteriori (MAP) and maximum likelihood (ML) criterions, a linear equalizer based on minimum mean-square error (MMSE) criterion, and a decision-feedback equalizer (DFE) which is a nonlinear equalizer. We present a channel estimator to estimate time varying MC channel at the receiver. The performances of the proposed methods based on bit error rates are evaluated. The sequence detection methods reveal the best performance at the expense of computational complexity. However, the MMSE equalizer has the lowest performance with the lowest computational complexity. The results show that using these methods significantly increases the information transmission rate in the MC.

In the field of wireless communication, there is growing interest in molecular communication (MC), which integrates nano-, bio-, and communication technologies. Inspired by nature, MC uses molecules to transmit data, especially in environments where EM waves struggle to penetrate. In MC, signals can be distinguished based on molecular concentration, known as concentrated-encoded molecular communication (CEMC). These molecules diffuse through an MC channel and are received via ligand–receptor binding mechanisms. Synchronization in CEMC is critical for minimizing errors and enhancing communication performance. This study introduces a novel preamble-based noncoherent synchronization method, specifically designed for resource-constrained environments like nanonetworks. The method’s simple, low-complexity structure makes it suitable for nanomachines, while machine learning (ML) techniques are used to improve synchronization accuracy by adapting to the nonlinear characteristics of the channel. The proposed approach leverages ML to achieve robust performance. Simulation results demonstrate a synchronization probability of 0.8 for a transmitter-receiver distance of 1 cm, given a molecular collection time duration four times the pulse duration. These results confirm the significant benefits of integrating ML, showcasing improved synchronization probability and reduced mean square error. The findings contribute to the advancement of efficient and practical MC systems, offering insights into synchronization and error reduction in complex environments.

In diffusion-based communication, as for molecular systems, the achievable data rate is low due to the stochastic nature of diffusion which exhibits a severe inter-symbol-interference (ISI). Multiple-Input Multiple-Output (MIMO) multiplexing improves the data rate at the expense of an inter-link interference (ILI). This paper investigates training-based channel estimation schemes for diffusive MIMO (D-MIMO) systems and corresponding equalization methods. Maximum likelihood and least-squares estimators of mean channel are derived, and the training sequence is designed to minimize the mean square error (MSE). Numerical validations in terms of MSE are compared with Cramer-Rao bound derived herein. Equalization is based on decision feedback equalizer (DFE) structure as this is effective in mitigating diffusive ISI/ILI. Zero-forcing, minimum MSE and least-squares criteria have been paired to DFE, and their performances are evaluated in terms of bit error probability. Since D-MIMO systems are severely affected by the ILI because of short transmitters inter-distance, D-MIMO time interleaving is exploited as countermeasure to mitigate the ILI with remarkable performance improvements. The feasibility of a block-type communication including training and data equalization is explored for D-MIMO, and system-level performances are numerically derived.

Molecular communication (MC) is the new nano-bio-communication paradigm that inspired by the nature to perform communication tasks at nanoscale networks. Although power utilization and large computation abilities are important factors that play a role in designing detection schemes for traditional communication systems, the MC is more sensitive to these factors due to its operating scale and power resources. Transmitters and receivers can be bio-cellular, bio-organisms, or nano-machines that can perform simple tasks due to their natural limitation with respect to size, power supply, and required simplicity. Accordingly, there is a need for efficient low-complexity detection schemes that can enable reliable communications despite impairments such as inter-symbol interference (ISI), noise and distortion. In this chapter, we propose a novel detection scheme for molecular communication via diffusion (MCvD) that achieves low computational complexity, yet deliver reliable information detection. Our proposed scheme encompasses a multi-layer structure where each layer performs a certain level of pin-pointing (or zoom-in) of the estimated received bits in a fashion that can be regarded as a form of sub-optimal minimum mean-square estimation (MMSE) that tradeoffs complexity for performance. Our detection method has been able to achieve un-coded bit error rate levels down to \(10^{-5}\) at signal-to-noise ratios where traditional threshold-based detection achieves worse than \(10^{-2}\).

The complexity of molecular communications system, involving a massive number of interacting entities, makes scalability a fundamental property of simulators and modeling tools. A typical scenario is that of targeted drug delivery systems, which makes use of biological nanomachines close to a biological target, able to release molecules in the diseased area. In this paper, we propose a simple but reliable receiver model for diffusion-based molecular communication systems tackling the time needed for analyzing such a system. The proposed model consists of using an equivalent markovian queuing model, which reproduces the aggregate behavior of thousands of receptors spread over the receiver surface. It takes into account not only the fact that the absorption of molecules can occur only through receptors, but also that absorption is not an instantaneous process and may require a significant time during which the receptor is not available to bind to other molecules. Our results, expressed in terms of number of absorbed molecules and average number of busy receptors, demonstrate that the proposed approach is in good agreement with results obtained through particle-based simulations of a large number of receptors, although the time taken for obtaining the results with the proposed model is an order of magnitudes lower than the simulation time. We believe that this model can be the precursor of novel class of models based on similar principles that allow realizing reliable simulations of much larger systems.

This work presents a performance analysis of a decode-and-forward (DF) relay-assisted diffusion-based molecular communication system consisting of one nanotransmitter, one nanoreceiver and one nanotransceiver acting as relay. We consider cases using one molecule in our two-hop relay network (1M2H), and using two molecules (2M2H). Inspired by the biological signal transduction systems, the ligand-receptor binding mechanism is introduced for the receptors on the surface of receiver. Inter-symbol interference (ISI) and self-interference (SI) can be identified as the performance-limiting effects in our relaying network. The number of received molecules can be approximated by the normal distribution, and using this approximation, a closed-form expression of bit error probability for the relay-assisted network is derived. Then, we put forward an optimization problem for minimizing the bit error probability, and solve it using an algorithm based on the gradient descent to find the optimal detection threshold. In addition, the expression of channel capacity is obtained for two-hop molecular communication with ligand receptors. Numerical results show that the 2M2H network has greater capacity than the 1M2H network.

The function of S100A4, a member of the calcium-binding S100 protein family, has been associated with tumor invasion and metastasis. Although an essential pro-metastatic role of extracellular S100A4 in tumor progression has been demonstrated, the identification of the precise underlying mechanisms and protein partners (receptors) has remained elusive. To identify putative targets for extracellular S100A4, we screened a phage display peptide library using S100A4 as bait. We identified three independent peptide motifs with varying affinities for the S100A4 protein. Sequence analyses indicated that the most abundant peptide mimicked the F/YCC motif present in the epidermal growth factor domain of ErbB receptor ligands. S100A4 selectively interacted with a number of epidermal growth factor receptor (EGFR) ligands, demonstrating highest affinity for amphiregulin. Importantly, we found that S100A4 stimulated EGFR/ErbB2 receptor signaling and enhanced the amphiregulin-mediated proliferation of mouse embryonic fibroblasts. S100A4-neutralizing antibodies, as well as EGFR- and ErbB2 receptor-specific tyrosine kinase inhibitors, blocked these effects. The present results suggest that extracellular S100A4 regulates tumor progression by interacting with EGFR ligands, thereby enhancing EGFR/ErbB2 receptor signaling and cell proliferation. Structured digital abstract: * MINT-7256556: EGF (uniprotkb:P01133) binds (MI:0407) to S100A4 (uniprotkb:P26447) by far western blotting (MI:0047) * MINT-7256512: BC (uniprotkb:P35070) binds (MI:0407) to S100A4 (uniprotkb:P26447) by far western blotting (MI:0047) * MINT-7256485, MINT-7256618, MINT-7256636: AR (uniprotkb:P15514) binds (MI:0407) to S100A4 (uniprotkb:P26447) by far western blotting (MI:0047) * MINT-7256494: HB-EGF (uniprotkb:Q99075) binds (MI:0407) to S100A4 (uniprotkb:P26447) by far western blotting (MI:0047) * MINT-7256502: P53 (uniprotkb:P04637) binds (MI:0407) to S100A4 (uniprotkb:P26447) by far western blotting (MI:0047) * MINT-7256654: S100A2 (uniprotkb:P29034) binds (MI:0407) to AR (uniprotkb:P15514) by far western blotting (MI:0047) * MINT-7256693: S100A5 (uniprotkb:P33763) binds (MI:0407) to AR (uniprotkb:P15514) by far western blotting (MI:0047) * MINT-7256593: S100A4 (uniprotkb:P26447) binds (MI:0407) to BC (uniprotkb:P35070) by pull down (MI:0096) * MINT-7256567: S100A4 (uniprotkb:P26447) binds (MI:0407) to AR (uniprotkb:P15514) by pull down (MI:0096).

This chapter focuses on nonviral nucleic acid vehicles and the barriers to their delivery to the central nervous system (CNS). Ligands for receptor- and carrier-mediated transport to the CNS are presented in the context of vehicles and strategies which have been successfully used to overcome delivery barriers in vivo. The increasing prevalence of CNS-related diseases urgently requires the development of biological drugs such as proteins, antibodies, peptides or nucleic acids which can cross the blood-brain barrier. Free nucleic acids cannot use any of the mentioned carrier-mediated transport, receptor-mediated transport or adsorptive-mediated transcytosis pathways, which is why they must be formulated with suitable carriers for brain delivery. A fundamental issue of brain delivery is the optimal size of nanoparticles, regardless of their decoration with targeting ligands. Endogenous transport systems of the cerebral vasculature include carrier-mediated transporters such as glucose and amino acid carriers.

Atomic force microscopy (AFM), developed in the late eighties to explore atomic details on hard material surfaces, has evolved to an imaging method capable of achieving fine structural details on biological samples. Its particular advantage in biology is that the measurements can be carried out in aqueous and physiological environment, which opens the possibility to study the dynamics of biological processes in vivo. The additional potential of the AFM to measure ultra-low forces at high lateral resolution has paved the way for measuring inter- and intra-molecular forces of bio-molecules on the single molecule level. Molecular recognition studies using AFM open the possibility to detect specific ligand–receptor interaction forces and to observe molecular recognition of a single ligand–receptor pair. Applications include biotin–avidin, antibody–antigen, NTA nitrilotriacetate–hexahistidine 6, and cellular proteins, either isolated or in cell membranes. The general strategy is to bind ligands to AFM tips and receptors to probe surfaces (or vice versa), respectively. In a force–distance cycle, the tip is first approached towards the surface whereupon a single receptor–ligand complex is formed, due to the specific ligand receptor recognition. During subsequent tip–surface retraction a temporarily increasing force is exerted to the ligand–receptor connection thus reducing its lifetime until the interaction bond breaks at a critical force (unbinding force). Such experiments allow for estimation of affinity, rate constants, and structural data of the binding pocket. Comparing them with values obtained from ensemble-average techniques and binding energies is of particular interest. The dependences of unbinding force on the rate of load increase exerted to the receptor–ligand bond reveal details of the molecular dynamics of the recognition process and energy landscapes. Similar experimental strategies were also used for studying intra-molecular force properties of polymers and unfolding–refolding kinetics of filamentous proteins. Recognition imaging, developed by combing dynamic force microscopy with force spectroscopy, allows for localization of receptor sites on surfaces with nanometer positional accuracy.

Diffusion-based molecular communication system (DBMC) is a system in which information-carrying molecules are sent from the transmitter and passively transported to the receiver in a fluid environment. Nanomachines, which are the main part of this system, have limited processing capacity. Besides, at the receiver, high inter-symbol interference (ISI) occurs due to free movement of molecules and the variance of the observation noise is signal dependent. Hence, it is important to design high-performance and low complexity receiver detection methods. In this paper, finite impulse response (FIR) Wiener filter is introduced for the first time, which has considerably less computational complexity compared to the minimum mean square error (MMSE) algorithm proposed in the literature. Moreover, extended Kalman filter is introduced for the first time to DBMC as a receiver detection method. Finally, Viterbi algorithm is modified and used as a benchmark for performance evaluation.

Molecular communication (MC) inspired drug delivery holds considerable promise as a new design for targeted therapy with high efficiency and minimal toxicity. The process of drug delivery can be modelled in a blood flow-based MC system, where nanoparticles (NPs) carry therapeutic agents through the blood vessel channels to the targeted diseased tissue. Most previous studies in the flow-based MC consider a Newtonian fluid with a laminar flow, which ignores the influence of red blood cells (RBCs). However, the nature of blood flow is a complex and non-Newtonian fluid composed of proteins, platelets, plasma and deformable cells, especially RBCs. The ability to change their shapes is essential to the proper functioning of RBCs in the microvasculature. Different shapes of RBCs have a great impact on the performance of blood flow. Changes in the properties and shapes of RBCs are often associated with different diseases, such as sickle cell anemia, diabetes, and malaria. Thus, it is highly important to establish a more realistic blood flow MC model considering the deformable cells. According to our previous study, the motion and adhesion of individual NPs are modelled through the Brownian adhesion dynamics. Subsequently, this paper establishes a particle-cell hybrid model in the flow-based MC, which focuses on the RBC deformation, aggregation, and dispersion in the blood suspension. Based on the state of the RBC deformation and aggregation in the vessels with different flow rates, this paper proposes a novel methodology for detecting the deformability of the cells. The blood state in terms of RBC deformability is determined by the difference in NPs' concentration at the receiving end., this paper sheds some light on the influence of RBCs on the motion of NPs, which provides new insights on the design of targeted drug delivery and the detection of vascular diseases.

Rats were twice daily (2 x 10 mg/kg, i.p.) treated for three weeks with the peripheral benzodiazepine (BZ) receptor ligands Ro 5-4864 (4'-chlorodiazepam) and PK 11,195 (1-(2-chlorophenyl)-N-methyl-N-(1-methylpropyl)-3-isoquinoline-carbox ami de). After the first injection there were no differences between the drug-treated and control animals in behavioral tests. After 10 days treatment, the number of sniffings was increased in Ro 5-4864-treated rats. After the last injection, sniffings and ambulations were decreased in PK 11,195-treated animals. The number of rearings and groomings remained unchanged throughout the treatment, and there were no changes in the results in the elevated plus-maze test. Apparently these compounds are devoid of anxiolytic and anxiogenic effects at moderate doses. The effect of 72 a h withdrawal from the above mentioned chronic treatment on peripheral and central BZ receptors as well as on GABAA receptors was studied with receptor binding techniques using 3H-Ro 5-4864, 3H-flumazenil and 3H-muscimol, respectively, as ligands. The number of GABAA and central BZ receptors was lower after Ro 5-4864 treatment, as was the effect of progesterone-induced stimulation of 3H-muscimol binding. The number of peripheral BZ receptors was decreased after Ro 5-4864 and PK 11,195 treatments in the olfactory bulb but not in the cerebral cortex. The chronic treatment with peripheral BZ receptor ligands Ro 5-4864 and PK 11,195 produced only little behavioral effects. Ro 5-4864, often presented as an agonist of peripheral BZ receptors, was behaviorally inactive.(ABSTRACT TRUNCATED AT 250 WORDS)

The goal of research with receptor ligands and PET is the characterization of an in vivo system that measures rates of association and dissociation of a ligand-receptor complex and the density of available binding sites. It has been suggested that multiple injection studies of radioactive ligand are more likely to identify model parameters than are single injection studies. Typically, at least one of the late injections is at a low specific activity (SA), so that part of the positron emission tomography (PET) curve reflects ligand dissociation. Low SA injections and the attendant reductions in receptor availability, however, may violate tracer kinetic assumptions, namely, tracer may no longer be in steady state with the total (labeled and unlabeled) ligand. Tissue response becomes critically dependent on the dose of total ligand, and an accurate description of the cold ligand in the tissue is needed to properly model the system. Two alternative models have been applied to the receptor modeling problem, which reduces to describing the time-varying number of available receptor sites. The first (Huang et al., 1989) contains only compartments for the hot ligand, 'hot only' (HO), but indirectly accounts for the action of cold ligand at receptor sites via SA. The second stipulates separate compartments for the hot and cold ligands, 'hot and cold' (HC), thus explicitly calculating available number of receptors. We examined these models and contrasted their abilities to predict PET activity, receptor availability, and SA in each tissue compartment. For multiple injection studies, the models consistently predicted different PET activities--especially following the third injection. Only for very high rate constants were the models identical for multiple injections. In one case, simulated PET curves were quite similar, but discrepancies appeared in predictions of receptor availability. The HO model predicted nonphysiological changes in the availability of receptor sites and introduced errors of 30-60% into estimates of B'max for test data. We, therefore, strongly recommend the use of the HC model for all analyses of multiple injection PET studies.