Keratin Dynamics: Modeling the Interplay between Turnover and Transport

Keratin are among the most abundant proteins in epithelial cells. Functions of the keratin network in cells are shaped by their dynamical organization. Using a collection of experimentally-driven mathematical models, different hypotheses for the turnover and transport of the keratin material in epithelial cells are tested. The interplay between turnover and transport and their effects on the keratin organization in cells are hence investigated by combining mathematical modeling and experimental data. Amongst the collection of mathematical models considered, a best model strongly supported by experimental data is identified. Fundamental to this approach is the fact that optimal parameter values associated with the best fit for each model are established. The best candidate among the best fits is characterized by the disassembly of the assembled keratin material in the perinuclear region and an active transport of the assembled keratin. Our study shows that an active transport of the assembled keratin is required to explain the experimentally observed keratin organization.     

Modeling and Analyzing the Transmission Dynamics of HBV Epidemic in Xinjiang,China

Hepatitis B is an infectious disease caused by the hepatitis B virus (HBV) which affects livers. In this paper, we formulate a hepatitis B model to study the transmission dynamics of hepatitis B in Xinjiang, China. The epidemic model involves an exponential birth rate and vertical transmission. For a better understanding of HBV transmission dynamics, we analyze the dynamic behavior of the model. The modified reproductive number σ is obtained. When σ < 1, the disease-free equilibrium is locally asymptotically stable, when σ > 1, the disease-free equilibrium is unstable and the disease is uniformly persistent. In the simulation, parameters are chosen to fit public data in Xinjiang. The simulation indicates that the cumulated HBV infection number in Xinjiang will attain about 600,000 cases unless there are stronger or more effective control measures by the end of 2017. Sensitive analysis results show that enhancing the vaccination rate for newborns in Xinjiang is very effective to stop the transmission of HBV. Hence, we recommend that all infants in Xinjiang receive the hepatitis B vaccine as soon as possible after birth.     

Electricity Intensity of Internet Data Transmission: Untangling the Estimates

In order to understand the electricity use of Internet services, it is important to have accurate estimates for the average electricity intensity of transmitting data through the Internet (measured as kilowatt‐hours per gigabyte [kWh/GB]). This study identifies representative estimates for the average electricity intensity of fixed‐line Internet transmission networks over time and suggests criteria for making accurate estimates in the future. Differences in system boundary, assumptions used, and year to which the data apply significantly affect such estimates. Surprisingly, methodology used is not a major source of error, as has been suggested in the past. This article derives criteria to identify accurate estimates over time and provides a new estimate of 0.06 kWh/GB for 2015. By retroactively applying our criteria to existing studies, we were able to determine that the electricity intensity of data transmission (core and fixed‐line access networks) has decreased by half approximately every 2 years since 2000 (for developed countries), a rate of change comparable to that found in the efficiency of computing more generally.     

Aerial Dispersal and Multiple-Scale Spread of Epidemic Disease

Disease spread has traditionally been described as a traveling wave of constant velocity. However, aerially dispersed pathogens capable of long-distance dispersal often have dispersal gradients with extended tails that could result in acceleration of the epidemic front. We evaluated empirical data with a simple model of disease spread that incorporates logistic growth in time with an inverse power function for dispersal. The scale invariance of the power law dispersal function implies its applicability at any spatial scale; indeed, the model successfully described epidemics ranging over six orders of magnitude, from experimental field plots to continental-scale epidemics of both plant and animal diseases. The distance traveled by epidemic fronts approximately doubled per unit time, velocity increased linearly with distance (slope ~½), and the exponent of the inverse power law was approximately 2. We found that it also may be possible to scale epidemics to account for initial outbreak focus size and the frequency of susceptible hosts. These relationships improve understanding of the geographic spread of emerging diseases, and facilitate the development of methods for predicting and preventing epidemics of plants, animals, and humans caused by pathogens that are capable of long-distance dispersal.     

Interplay between Endophyte Prevalence,Effects and Transmission: Insights from a Natural Grass Population

Two main mechanisms are thought to affect the prevalence of endophyte-grass symbiosis in host populations: the mode of endophyte transmission, and the fitness differential between symbiotic and non-symbiotic plants. These mechanisms have mostly been studied in synthetic grass populations. If we are to improve our understanding of the ecological and evolutionary dynamics of such symbioses, we now need to determine the combinations of mechanisms actually operating in the wild, in populations shaped by evolutionary history. We used a demographic population modeling approach to identify the mechanisms operating in a natural stand of an intermediate population (i.e. 50% of plants symbiotic) of the native grass Festuca eskia. We recorded demographic data in the wild over a period of three years, with manipulation of the soil resources for half the population. We developed two stage-structured matrix population models. The first model concerned either symbiotic or non-symbiotic plants. The second model included both symbiotic and non-symbiotic plants and took endophyte transmission rates into account. According to our models, symbiotic had a significantly higher population growth rate than non-symbiotic plants, and endophyte prevalence was about 58%. Endophyte transmission rates were about 0.67 or 0.87, depending on the growth stage considered. In the presence of nutrient supplementation, population growth rates were still significantly higher for symbiotic than for non-symbiotic plants, but endophyte prevalence fell to 0%. At vertical transmission rates below 0.10–0.20, no symbiosis was observed. Our models showed that a positive benefit of the endophyte and vertical transmission rates of about 0.6 could lead to the coexistence of symbiotic and non-symbiotic F. eskia plants. The positive effect of the symbiont on host is not systematically associated with high transmission rates of the symbiont over short time scales, in particular following an environmental change.     

Interplay between inflammation and cancer

Tumor-promoting inflammation is one of the hallmarks of cancer. It has been shown that cancer development is strongly influenced by both chronic and acute inflammation process. Progress in research on inflammation revealed a connection between inflammatory processes and neoplastic transformation, the progression of tumour, and the development of metastases and recurrences. Moreover, the tumour invasive procedures (both surgery and biopsy) affect the remaining tumour cells by increasing their survival, proliferation and migration. One of the concepts explaining this phenomena is an induction of a wound healing response. While in normal tissue it is necessary for tissue repair, in tumour tissue, induction of adaptive and innate immune response related to wound healing, stimulates tumour cell survival, angiogenesis and extravasation of circulating tumour cells. It has become evident that certain types of immune response and immune cells can promote tumour progression more than others. In this review, we focus on current knowledge on carcinogenesis and promotion of cancer growth induced by inflammatory processes.     

Phylogeography Reveals Association between Swine Trade and the Spread of Porcine Epidemic Diarrhea Virus in China and across the World

The ongoing SARS (severe acute respiratory syndrome)-CoV (coronavirus)-2 pandemic has exposed major gaps in our knowledge on the origin, ecology, evolution, and spread of animal coronaviruses. Porcine epidemic diarrhea virus (PEDV) is a member of the genus Alphacoronavirus in the family Coronaviridae that may have originated from bats and leads to significant hazards and widespread epidemics in the swine population. The role of local and global trade of live swine and swine-related products in disseminating PEDV remains unclear, especially in developing countries with complex swine production systems. Here, we undertake an in-depth phylogeographic analysis of PEDV sequence data (including 247 newly sequenced samples) and employ an extension of this inference framework that enables formally testing the contribution of a range of predictor variables to the geographic spread of PEDV. Within China, the provinces of Guangdong and Henan were identified as primary hubs for the spread of PEDV, for which we estimate live swine trade to play a very important role. On a global scale, the United States and China maintain the highest number of PEDV lineages. We estimate that, after an initial introduction out of China, the United States acted as an important source of PEDV introductions into Japan, Korea, China, and Mexico. Live swine trade also explains the dispersal of PEDV on a global scale. Given the increasingly global trade of live swine, our findings have important implications for designing prevention and containment measures to combat a wide range of livestock coronaviruses.     

On Branching Processes and the Early Stages of the Spread of an Epidemic

Branchingprocess(BP)isusedtomodeltheearlystagesofthespreadofasexuallytransmitteddisease.TheearlystagesofAIDSspreadwhichistransmittedbothhomosexuallyandheterosexuallyarestudiedasaBP.     

Modeling the Underlying Dynamics of the Spread of Crime

The spread of crime is a complex, dynamic process that calls for a systems level approach. Here, we build and analyze a series of dynamical systems models of the spread of crime, imprisonment and recidivism, using only abstract transition parameters. To find the general patterns among these parameters—patterns that are independent of the underlying particulars—we compute analytic expressions for the equilibria and for the tipping points between high-crime and low-crime equilibria in these models. We use these expressions to examine, in particular, the effects of longer prison terms and of increased incarceration rates on the prevalence of crime, with a follow-up analysis on the effects of a Three-Strike Policy.     

On the Exact Measure of Disease Spread in Stochastic Epidemic Models

The basic reproduction number, R ₀, is probably the most important quantity in epidemiology. It is used to measure the transmission potential during the initial phase of an epidemic. In this paper, we are specifically concerned with the quantification of the spread of a disease modeled by a Markov chain. Due to the occurrence of repeated contacts taking place between a typical infective individual and other individuals already infected before, R ₀ overestimates the average number of secondary infections. We present two alternative measures, namely, the exact reproduction number, R _e0, and the population transmission number, R _p , that overcome this difficulty and provide valuable insight. The applicability of R _e0 and R _p to control of disease spread is also examined.     

Interplay between wrn and the checkpoint in s-phase

Stability of the genome is crucial for survival and faithful transmission of the genetic blueprint to progenitors. During DNA replication chromosome integrity can be challenged by a variety of exogenous and endogenous damaging agents and by the process of duplication itself. Thus, eukaryotic cells have evolved a sophisticated response called replication checkpoint supervising the accurate and complete genome replication. The replication checkpoint response bridges together replication, repair and cell cycle proteins in a coordinated network having the ATR kinase as culprit. ATR-mediated phosphorylation events control that stalled replication forks are properly sensed and stabilised, cell cycle progression halted and replication eventually recovered. In the recent years, the Werner syndrome protein (WRN) emerged as a central actor of the replication checkpoint being instrumental for correct recovery from arrested replication and a substrate of ATR. In this review, how WRN and the replication checkpoint could cross-talk and contribute to faithful recovery of stalled replication forks will be discussed.     

Untangling the crosstalk between BRCA1 and R-loops during DNA repair

R-loops are RNA:DNA hybrids assembled during biological processes but are also linked to genetic instability when formed out of their natural context. Emerging evidence suggests that the repair of DNA double-strand breaks requires the formation of a transient R-loop, which eventually must be removed to guarantee a correct repair process. The multifaceted BRCA1 protein has been shown to be recruited at this specific break-induced R-loop, and it facilitates mechanisms in order to regulate R-loop removal. In this review, we discuss the different potential roles of BRCA1 in R-loop homeostasis during DNA repair and how these processes ensure faithful DSB repair.     

Interplay between membrane curvature and the actin cytoskeleton

An intimate interplay of the plasma membrane with curvature-sensing and curvature-inducing proteins would allow for defining specific sites or nanodomains of action at the plasma membrane, for example, for protrusion, invagination, and polarization. In addition, such connections are predestined to ensure spatial and temporal order and sequences. The combined forces of membrane shapers and the cortical actin cytoskeleton might hereby in particular be required to overcome the strong resistance against membrane rearrangements in case of high plasma membrane tension or cellular turgor. Interestingly, also the opposite might be necessary, the inhibition of both membrane shapers and cytoskeletal reinforcement structures to relieve membrane tension to protect cells from membrane damage and rupturing during mechanical stress. In this review article, we discuss recent conceptual advances enlightening the interplay of plasma membrane curvature and the cortical actin cytoskeleton during endocytosis, modulations of membrane tensions, and the shaping of entire cells.     

Cross-Species Virus Transmission and the Emergence of New Epidemic Diseases

Summary: Host range is a viral property reflecting natural hosts that are infected either as part of a principal transmission cycle or, less commonly, as “spillover” infections into alternative hosts. Rarely, viruses gain the ability to spread efficiently within a new host that was not previously exposed or susceptible. These transfers involve either increased exposure or the acquisition of variations that allow them to overcome barriers to infection of the new hosts. In these cases, devastating outbreaks can result. Steps involved in transfers of viruses to new hosts include contact between the virus and the host, infection of an initial individual leading to amplification and an outbreak, and the generation within the original or new host of viral variants that have the ability to spread efficiently between individuals in populations of the new host. Here we review what is known about host switching leading to viral emergence from known examples, considering the evolutionary mechanisms, virus-host interactions, host range barriers to infection, and processes that allow efficient host-to-host transmission in the new host population.     

A Simulation Study Comparing Epidemic Dynamics on Exponential Random Graph and Edge-Triangle Configuration Type Contact Network Models

We compare two broad types of empirically grounded random network models in terms of their abilities to capture both network features and simulated Susceptible-Infected-Recovered (SIR) epidemic dynamics. The types of network models are exponential random graph models (ERGMs) and extensions of the configuration model. We use three kinds of empirical contact networks, chosen to provide both variety and realistic patterns of human contact: a highly clustered network, a bipartite network and a snowball sampled network of a “hidden population”. In the case of the snowball sampled network we present a novel method for fitting an edge-triangle model. In our results, ERGMs consistently capture clustering as well or better than configuration-type models, but the latter models better capture the node degree distribution. Despite the additional computational requirements to fit ERGMs to empirical networks, the use of ERGMs provides only a slight improvement in the ability of the models to recreate epidemic features of the empirical network in simulated SIR epidemics. Generally, SIR epidemic results from using configuration-type models fall between those from a random network model (i.e., an Erdős-Rényi model) and an ERGM. The addition of subgraphs of size four to edge-triangle type models does improve agreement with the empirical network for smaller densities in clustered networks. Additional subgraphs do not make a noticeable difference in our example, although we would expect the ability to model cliques to be helpful for contact networks exhibiting household structure.