Molecular Communications in Viral Infections Research: Modeling, Experimental Data, and Future Directions

In silico modelling of neuron signal impact of cytokine storm-induced demyelination

In this study, we develop an in silico model of a neuron's behaviour under demyelination caused by a cytokine storm to investigate the effects of viral infections in the brain. We use a comprehensive model to measure how cytokine-induced demyelination affects the propagation of action potential (AP) signals within a neuron. We analysed the effects of neuron-neuron communications by applying information and communication theory at different levels of demyelination. Our simulations demonstrate that virus-induced degeneration can play a role in the signal power and spiking rate, which compromise the propagation and processing of information between neurons. We propose a transfer function to model the weakening effects on the AP. Our results show that demyelination induced by a cytokine storm not only degrades the signal but also impairs its propagation within the axon. Our proposed in silico model can analyse virus-induced neurodegeneration and enhance our understanding of virus-induced demyelination.

Merkel Cell Polyomavirus and their Association with the Pathogenesis of Cervical Squamous Cell Carcinomas and Adenocarcinomas: A Review Article

Background

This review aims to determine the potential role of Merkel Cell Polyomavirus (MCPyV) in the pathogenesis of cervical squamous cell carcinomas and adenocarcinomas.

Methods

A PRISMA systematic search appraisal was conducted. The Scopus, Web of Science, PubMed, EMBASE, Google Scholar, and MEDLINE databases for publications in English were searched up to September 2022 for all relevant articles. All articles that have outlined the contributions of the MCPyV to cervical squamous cell carcinomas and adenocarcinomas were included.

Results

The six databases produced 6806 articles. Only six articles met the inclusion criteria and were included. The protocol of this review was submitted and registered with the PROSPERO (Code no. CRD42022369197). The total sample size across the articles was 1135; the age of the participants ranged between 18 and 75 years. In addition, the included articles were conducted between 2012 to 2016. All included articles have a cross-sectional design.Furthermore, different kinds of samples were collected in the reviewed articles, namely cervical tissue biopsies, cervical smears, formalin-fixed paraffin-embedded resection specimens, and cervical adenocarcinomas. Moreover, five articles showed no statistically significant association between the MCPyV and cervical squamous cell carcinomas and adenocarcinomas. In contrast, one article revealed a positive association between MCPyV and cervical squamous cell carcinomas and adenocarcinomas.

Conclusions

MCPyV could not be associated with the pathogenesis of cervical squamous cell carcinomas and adenocarcinomas. Further attention should be given to examining this association, and further studies with a large sample size are recommended to confirm these findings.

Mobile human ad hoc networks: A communication engineering viewpoint on interhuman airborne pathogen transmission

A number of transmission models for airborne pathogens transmission, as required to understand airborne infectious diseases such as COVID-19, have been proposed independently from each other, at different scales, and by researchers from various disciplines. We propose a communication engineering approach that blends different disciplines such as epidemiology, biology, medicine, and fluid dynamics. The aim is to present a unified framework using communication engineering, and to highlight future research directions for modeling the spread of infectious diseases through airborne transmission. We introduce the concept of mobile human ad hoc networks (MoHANETs), which exploits the similarity of airborne transmission-driven human groups with mobile ad hoc networks and uses molecular communication as the enabling paradigm. In the MoHANET architecture, a layered structure is employed where the infectious human emitting pathogen-laden droplets and the exposed human to these droplets are considered as the transmitter and receiver, respectively. Our proof-of-concept results, which we validated using empirical COVID-19 data, clearly demonstrate the ability of our MoHANET architecture to predict the dynamics of infectious diseases by considering the propagation of pathogen-laden droplets, their reception and mobility of humans.

Partnership for International Development: Finland-Nigeria Conference on Climate, Food, Health and Entrepreneurship

A joint collaboration between the Arctic Centre of the University of Lapland, Finland and the Federal Institute of Industrial Research, Oshodi, Lagos, Nigeria was organised as a hybrid conference on several topics that are related to climate, food, health and entrepreneurship. The utilisation of natural resources in both regions is an important theme in meeting the sustainable development goals agenda. The topics discussed were multidisciplinary, they include Nigerian indigenous foods, bioeconomy, circular economy, nutrition, health, innovation and entrepreneurship under four themes (Climate, Food, Health and Entrepreneurship). There were dignitaries from Finland and Nigeria. The presenters are researchers from Nigerian universities (University of Ibadan, University of Abuja and Eko university, Lagos), Nigerian Federal Institute of Industrial research centre and from the Finnish side we have the university of Lapland, Rovaniemi, University of Oulu, Oulu and the Centria University of Applied Sciences, Kokkola. The topics discussed will serve as training materials for students and learners, the discussion focussed on research opportunities for institutions in both countries. The experts from both countries will continue to dialogue on the possibility of promoting common topics as research agenda in these important areas with the possibilities of creating more jobs.

Epidemic-like Calcium Signaling in Mobile Molecular Communication Networks

Molecular Communication is an emerging technology enabling communications in nano-networks. Ca2+ signal is one promising option of MC due to the important role in biometabolisms and the available characteristics in communication engineering. So far, scientists analyze Ca2+ signaling via bioexperiments and simulations. Current researches lack a mathematical model for quantitative analysis of Ca2+ signal propagation on the network scale. In this work, we investigate the propagation patterns of Ca2+ signals in bio-cellular network. Firstly, we propose an improved Ca2+ dynamics model to describe Ca2+ signals considering movements of cells and attenuation of Ca2+ concentration. Then, we perform multi-modal analysis through the waveform characteristics, and classify cells according to their states. Moreover, a mathematical model is put forward to analyze the propagation of calcium signals based on typical epidemic model. The proposed model fully considers the similarity between: 1) epidemic disease propagates among mobile individuals; 2) Ca2+ signal propagates among mobile cells. The proposed model is amended to fit the case considering unique characters of Ca2+ signal. Finally, simulation results show that the proposed Ca2+ propagation model is coincident with Monte Carlo simulation results, indicating that the model is helpful for understanding how far and how fast Ca2+ signal can propagate.