Molecular Communication Research Articles

Expanding the primary care workforce by integrating genetic counselors in multidisciplinary care teams.

Collectively, rare diseases are common, affecting approximately 8% of the population in Canada and the USA. Therefore, the majority of primary care (PC) clinicians will care for patients who are affected or at risk for a genetic disease. Considering the increasing ways in which genetics is being implemented into all areas of healthcare, one way to address these needs and expand the capacity of the PC workforce is through the integration of genetic counselors (GCs) into PC multidisciplinary teams. GCs are Masters-educated allied health professionals with specialized training in molecular genetics, communication, and short-term psychotherapeutic counseling. The current models of GCs in PC mimic other multidisciplinary models. Complex tasks related to genetics, such as pre- and post-test counseling, genetic test selection, and results interpretation, are conducted by GCs, which, in turn, allows physicians, nurse practitioners, and other PC providers to work at the top of their scope of practice. Quality genetics services provided by GCs improve clinical outcomes for patients and their families; the simultaneous provision of genetic education and psychological support by a GC is associated with an increase in patient knowledge, perceived personal control, decrease in distress, and can lead to positive health behavior changes, all of which are aligned with the goals of primary healthcare. With their extensive training in clinical care, medical communication, and psychotherapeutic counseling, integrating GCs into PC care teams will improve the care patients receive and allow PC clinicians to ensure their patients are at the forefront of the personalized medicine revolution.

Microbiome-derived metabolite effects on intestinal barrier integrity and immune cell response to infection.

The gut microbiota exerts a significant influence on human health and disease. While compositional changes in the gut microbiota in specific diseases can easily be determined, we lack a detailed mechanistic understanding of how these changes exert effects at the cellular level. However, the putative local and systemic effects on human physiology that are attributed to the gut microbiota are clearly being mediated through molecular communication. Here, we determined the effects of gut microbiome-derived metabolites l-tryptophan, butyrate, trimethylamine (TMA), 3-methyl-4-(trimethylammonio)butanoate (3,4-TMAB), 4-(trimethylammonio)pentanoate (4-TMAP), ursodeoxycholic acid (UDCA), glycocholic acid (GCA) and benzoate on the first line of defence in the gut. Using in vitro models of intestinal barrier integrity and studying the interaction of macrophages with pathogenic and non-pathogenic bacteria, we could ascertain the influence of these metabolites at the cellular level at physiologically relevant concentrations. Nearly all metabolites exerted positive effects on barrier function, but butyrate prevented a reduction in transepithelial resistance in the presence of the pathogen Escherichia coli, despite inducing increased apoptosis and exerting increased cytotoxicity. Induction of IL-8 was unaffected by all metabolites, but GCA stimulated increased intra-macrophage growth of E. coli and tumour necrosis-alpha (TNF-α) release. Butyrate, 3,4-TMAB and benzoate all increased TNF-α release independent of bacterial replication. These findings reiterate the complexity of understanding microbiome effects on host physiology and underline that microbiome metabolites are crucial mediators of barrier function and the innate response to infection. Understanding these metabolites at the cellular level will allow us to move towards a better mechanistic understanding of microbiome influence over host physiology, a crucial step in advancing microbiome research.

An insight into the solitonic features of the nonlinear generalized higher-order Schrödinger equation using the solver method

For many nonlinear applications described by the dynamics of nonlinear Schrödinger equation with higher-order terms (HONLSE) such as nonlinear optics, space plasma physics molecular biology, astrophysics, quantum mechanics, superfluid, fluid mechanics, and fiber optics communications, a unique closed-form solution have been obtained using energy equation. In addition, some new solitary solutions HONLSE have been obtained via the unified solver method. The resultant solutions behave as breathers, super solitons, envelope breathers, blow up, localized super waves, periodical super shock, train super solitons, and shock structures. The modulations of Kerr nonlinear, chromatic dispersive, and wave packet drift parameters on the wave characteristics of the obtained solutions have been investigated. It was reported that the model parameters affect the amplitude, steepness, and width of the resultant structures. The provided solution can be used as a box solver for a variety of natural science systems described by distinct nonlinear equations.

Structure elucidation of a human melanocortin-4 receptor specific orthosteric nanobody agonist

The melanocortin receptor 4 (MC4R) belongs to the melanocortin receptor family of G-protein coupled receptors and is a key switch in the leptin-melanocortin molecular axis that controls hunger and satiety. Brain-produced hormones such as α-melanocyte-stimulating hormone (agonist) and agouti-related peptide (inverse agonist) regulate the molecular communication of the MC4R axis but are promiscuous for melanocortin receptor subtypes and induce a wide array of biological effects. Here, we use a chimeric construct of conformation-selective, nanobody-based binding domain (a ConfoBody Cb80) and active state-stabilized MC4R-β2AR hybrid for efficient de novo discovery of a sequence diverse panel of MC4R-specific, potent and full agonistic nanobodies. We solve the active state MC4R structure in complex with the full agonistic nanobody pN162 at 3.4 Å resolution. The structure shows a distinct interaction with pN162 binding deeply in the orthosteric pocket. MC4R peptide agonists, such as the marketed setmelanotide, lack receptor selectivity and show off-target effects. In contrast, the agonistic nanobody is highly specific and hence can be a more suitable agent for anti-obesity therapeutic intervention via MC4R.

Transformer-Based Receiver Localization in Vessel-Like and Flow-Induced Molecular Communication via Diffusion

Transformer-Based Receiver Localization in Vessel-Like and Flow-Induced Molecular Communication via Diffusion

End-to-end synaptic molecular communication with astrocytic feedback and generic three-state receptors

This paper investigates the mutual information of synaptic molecular communications using a realistic end-to-end synaptic model. In particular, we have considered the influence of astrocytes on neural signaling within the synaptic molecular communication. We have evaluated the average mutual information of the resultant tripartite synapse while considering realistic synaptic geometry that accounts for neurotransmitter reflections from the pre-synaptic and post-synaptic boundaries. The clearance of neurotransmitters from the synapse through diffusion and re-absorption by pre-synaptic terminal is also considered in the simulated model. Moreover, we have used a generic three-state model for postsynaptic receptors to include desensitization state of the receptors. The presented simulation results depict the effects of different pre-synaptic and post-synaptic parameters on the information transfer for a tripartite synaptic channel with three-state receptor model, which is more realistic than the commonly-used bipartite synaptic channel with the two-state receptor model.

RNA:DNA triplexes: a mechanism for epigenetic communication between hosts and microbes?

Molecular communication between host and microbe is mediated by the transfer of many different classes of macromolecules. Recently, the trafficking of RNA molecules between organisms has gained prominence as an efficient way to manipulate gene expression via RNA interference (RNAi). Here, we posit a new epigenetic control mechanism based on triple helix (triplex) structures comprising nucleic acids from both host and microbe. Indeed, RNA:DNA triplexes are known to regulate gene expression in humans, but it is unknown whether interkingdom triplexes are formed either to manipulate host processes during pathogenesis or as a host defense response. We hypothesize that a fraction of the extracellular RNAs commonly released by microbes (e.g., bacteria, fungi, and protists) and their hosts form triplexes with the genome of the other species, thereby impacting chromatin conformation and gene expression. We invite the field to consider interkingdom triplexes as unexplored weaponry in the arms race between host and microbe.

Transcriptomic and Multi-scale Network Analyses Reveal Key Drivers of Cardiovascular Disease.

Cardiovascular diseases (CVDs) and pathologies are often driven by changes in molecular signaling and communication, as well as in cellular and tissue components, particularly those involving the extracellular matrix (ECM), cytoskeleton, and immune response. The fine-wire vascular injury model is commonly used to study neointimal hyperplasia and vessel stiffening, but it is not typically considered a model for CVDs. In this paper, we hypothesize that vascular injury induces changes in gene expression, molecular communication, and biological processes similar to those observed in CVDs at both the transcriptome and protein levels. To investigate this, we analyzed gene expression in microarray datasets from injured and uninjured femoral arteries in mice two weeks post-injury, identifying 1,467 significantly and differentially expressed genes involved in several CVDs such as including vaso-occlusion, arrhythmia, and atherosclerosis. We further constructed a protein-protein interaction network with seven functionally distinct clusters, with notable enrichment in ECM, metabolic processes, actin-based process, and immune response. Significant molecular communications were observed between the clusters, most prominently among those involved in ECM and cytoskeleton organizations, inflammation, and cell cycle. Machine Learning Disease pathway analysis revealed that vascular injury-induced crosstalk between ECM remodeling and immune response clusters contributed to aortic aneurysm, neovascularization of choroid, and kidney failure. Additionally, we found that interactions between ECM and actin cytoskeletal reorganization clusters were linked to cardiac damage, carotid artery occlusion, and cardiac lesions. Overall, through multi-scale bioinformatic analyses, we demonstrated the robustness of the vascular injury model in eliciting transcriptomic and molecular network changes associated with CVDs, highlighting its potential for use in cardiovascular research.

Molecular Communication-Based Intelligent Dopamine Rate Modulator for Parkinson's Disease Treatment.

Parkinson's disease (PD) is a progressive neurodegenerative disease, and it is caused by the loss of dopaminergic neurons in the basal ganglia (BG). Currently, there is no definite cure for PD, and available treatments mainly aim to alleviate its symptoms. Due to impaired neurotransmitter-based information transmission in PD, molecular communication-based approaches can be employed as potential solutions to address this issue. Molecular Communications (MC) is a bio-inspired communication method utilizing molecules to carry information. This mode of communication stands out for developing biocompatible nanomachines for diagnosing and treating, particularly in addressing neurodegenerative diseases like PD, due to its compatibility with biological systems. This study presents a novel treatment method that introduces an Intelligent Dopamine Rate Modulator (IDRM), which is located in the synaptic gap between the substantia nigra pars compacta (SNc) and striatum to compensate for insufficiency dopamine release in BG caused by PD. For storing dopamine in the IDRM, dopamine compound (DAC) is swallowed and crossed through the digestive system, blood circulatory system, blood-brain barrier (BBB), and brain extracellular matrix uptakes with IDRMs. Here, the DAC concentration is calculated in these regions, revealing that the required exogenous dopamine consistently reaches IDRM. Therefore, the perpetual dopamine insufficiency in BG associated with PD can be compensated. This method reduces drug side effects because dopamine is not released in other brain regions. Unlike other treatments, this approach targets the root cause of PD rather than just reducing symptoms.

Time-Hopping Concentration-Position Shift Keying for Multiple Access in Concentration-Encoded Molecular Communication

Molecular communication (MC) represents a paradigm shift in communication technologies, extending beyond traditional electromagnetic methods by incorporating advances in nanotechnology, biotechnology, and communication theory. This innovative approach holds promise for groundbreaking applications in diverse fields such as medicine, military operations, and environmental monitoring. MC employs molecules to carry and transmit data. In concentration-encoded molecular communication (CEMC), information is represented through the concentration levels of the transmitted molecules. In this study, we introduce a novel method named time-hopping concentration-position shift keying (TH-CPSK), designed to facilitate multiple access within MC networks. The TH-CPSK method encodes information based on the position of the transmitted molecular concentration, significantly enhancing the accuracy of data transmission by reducing interference in MC channels. Numerical simulations reveal that an increase in the number of users adversely affects communication performance. Furthermore, our findings indicate that augmenting the number of hops improves communication performance at transmitter-receiver distances of 1 cm and 2 cm. Conversely, at a distance of 3 cm, performance degradation is observed, attributed to the increased complexity. Therefore, it is important to carefully select the number of hops considering the molecular channel’s characteristics. Overall, TH-CPSK can enhance the efficiency and reliability of CEMC systems, offering a significant step forward in the realization of MC’s potential applications.

Guest Editorial Introduction to the Special Feature on the 8th Workshop on Molecular Communications

Guest Editorial Introduction to the Special Feature on the 8th Workshop on Molecular Communications

Synchronized Relaying in Molecular Communication: An AI-Based Approach Using a Mobile Testbed Setup

Synchronized Relaying in Molecular Communication: An AI-Based Approach Using a Mobile Testbed Setup

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Publication Information

IEEE Transactions on Molecular, Biological, and Multi-Scale Communications Publication Information

A Molecular Communication Perspective on Detecting Arterial Plaque Formation

A Molecular Communication Perspective on Detecting Arterial Plaque Formation

Resource Allocation Optimization in Mobile Multiuser Molecular Communication by Deep Neural Network

Resource Allocation Optimization in Mobile Multiuser Molecular Communication by Deep Neural Network

CCL2/CCR2 axis promotes perineural invasion of salivary adenoid cystic carcinoma via ITGβ5-mediated nerve-tumor interaction

Perineural invasion (PNI) is a notorious feature of salivary adenoid cystic carcinoma (SACC) and other neurotropic tumors. The pathogenesis of PNI that involves the molecular communication between the tumor and the suffered nerve is elusive. The in vitro co-culture assays of SACC cells with dorsal root ganglia (DRG) or neural cells showed that nerve-derived CCL2 activated CCR2 expression in SACC cells, promoting the proliferation, adhesion, migration, and invasion of SACC cells via the ERK1/2/ITGβ5 pathway. Meanwhile, SACC-derived exosomes delivered ITGβ5 to promote the neurite outgrowth of neural cells or DRG. Blocking of CCL2/CCR2 axis or ITGβ5 inhibited the PNI of SACC cells in models in vitro by 3D co-culture of DRG with SACC cells and in vivo by xenografting SACC cells onto the murine sciatic nerve. High levels of ITGβ5 in tissues or plasma exosomes were significantly correlated with CCL2 and CCR2 expression in the tissues and associated with PNI and poor prognosis of SACC cases. Our findings revealed a novel reciprocal loop between neural and tumor cells driven by the CCL2/CCR2 axis and exosomal ITGβ5 during PNI of SACC. The present study may provide a prospective diagnostic and anti-PNI treatment strategy for SACC patients via targeting the nerve-tumor interactions.

Optimization of distribution function and model parameters for molecular communication via diffusion with OtoO approximation

The analysis is generally conducted in stationary receiver and transmitter models in a diffusion environment for the fundamental Molecular communication (MOC) models. However, a mobile MOC model is employed in this study, deviating from the existing literature. This mobile MOC model considers the mobility of all variables in the diffusion environment, including the transmitter, receiver, and molecules. Firstly, a novel MOC model is proposed, departing from the conventional normal distribution for the mobility of variables. Instead, alternative distribution functions such as the Pareto distribution, extreme value distribution, t-distribution, and generalized extreme value distribution are employed. Furthermore, the system's performance is enhanced by optimizing the distribution function and model parameters, such as the diffusion coefficient, using the optimization of optimization (OtoO) approach. In this approach, the Multi-Verse Optimization (MVO) algorithm serves as the primary algorithm, while the Grey Wolf Optimization (GWO) algorithm functions as the auxiliary algorithm. Essentially, the MVO algorithm optimizes the parameters of the MOC model, while simultaneously, the GWO algorithm optimizes the impact of the optimization processes of MVO on the parameters ``p'' and ``N'' as well as the constant parameter of the distribution function. By optimizing both the parameters of the MOC model and the distribution function, the number of received molecules is significantly increased. Therefore, this study not only improves the results of the MOC model structure based on different distribution functions but also optimizes all parameters of the proposed model using the MVO-GWO OtoO approach.

Dissection of the cell communication interactions in lung adenocarcinoma identified a prognostic model with immunotherapy efficacy assessment and a potential therapeutic candidate gene ITGB1

BackgroundThe tumor microenvironment (TME) in lung adenocarcinoma (LUAD) influences tumor progression and immunosuppressive phenotypes through cell communication. We aimed to decipher cellular communication and molecular patterns in LUAD. MethodsWe analyzed scRNA-seq data from LUAD patients in multiple cohorts, revealing complex cell communication networks within the TME. Using cell chat analysis and COSmap technology, we inferred LUAD's spatial organization. Employing the NMF algorithm and survival screening, we identified a cell communication interactions (CCIs) model and validated it across various datasets. ResultsWe uncovered intricate cell communication interactions within the TME, identifying three LUAD patient subtypes with distinct prognosis, clinical characteristics, mutation status, expression patterns, and immune infiltration. Our CCI model exhibited robust performance in prognosis and immunotherapy response prediction. Several potential therapeutic targets and agents for high CCI score patients with immunosuppressive profiles were identified. Machine learning algorithms pinpointed the novel candidate gene ITGB1 and validated its role in LUAD tumor phenotype in vitro. ConclusionOur study elucidates molecular patterns and cell communication interactions in LUAD as effective biomarkers and predictors of immunotherapy response. Targeting cell communication interactions offers novel avenues for LUAD immunotherapy and prognostic evaluations, with ITGB1 emerging as a promising therapeutic target.

Molecular Communication Under Different Signaling Waveforms and Biological Deployments

Molecular Communication Under Different Signaling Waveforms and Biological Deployments

Molecular Communication Systems in Cylindrical Channels With Non-Newtonian Fluid Flows in IoBNT

Molecular Communication Systems in Cylindrical Channels With Non-Newtonian Fluid Flows in IoBNT