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The relationships between early ligand binding/receptor processing events and cellular responses for the N-formyl peptide receptor system on human neutrophilis as a model of a GPCR system in a physiologically relevant context is examined.

Pomacea maculata is a relatively new invasive species to the Gulf Coast region and potentially threatens local agriculture (rice) and ecosystems (aquatic vegetation). The population dynamics of P. maculata have largely been unquantified, and therefore, scientists and field‐workers are ill‐equipped to accurately project population sizes and the resulting impact of this species. We studied the growth of P. maculata ranging in weights from 6 to 105 g, identifying the sex of the animals when possible. Our studied population had a 4:9 male:female sex ratio. We present the findings from initial analysis of the individual growth data of males and females, from which it was apparent that females were generally larger than males and that small snails grew faster than larger snails. Since efforts to characterize the male and female growth rates from individual data do not yield statistically supported estimates, we present the estimation of several parameterized growth rate functions within a population‐level mathematical model. We provide a comparison of the results using these various growth functions and discuss which best characterizes the dynamics of our observed population. We conclude that both males and females exhibit biphasic growth rates, and thus, their growth is size‐dependent. Further, our results suggest that there are notable differences between males and females that are important to take into consideration in order to accurately model this species' population dynamics. Lastly, we include preliminary analyses of ongoing experiments to provide initial estimates of growth in the earliest life stages (hatchling to ≈6 g). [ABSTRACT FROM AUTHOR]

We present a second-order high-resolution finite difference scheme to approximate the solution of a mathematical model of the transmission dynamics ofMycobacterium marinum(Mm) in an aquatic environment. This work extends the numerical theory and continues the preliminary studies on the model first developed in Acklehet al.[Structured models for the spread of Mycobacterium marinum: foundations for a numerical approximation scheme, Math. Biosci. Eng. 11 (2014), pp. 679–721]. Numerical simulations demonstrating the accuracy of the method are presented, and we compare this scheme to the first-order scheme developed in Acklehet al.[Structured models for the spread of Mycobacterium marinum: foundations for a numerical approximation scheme, Math. Biosci. Eng. 11 (2014), pp. 679–721] to show that the first-order method requires significantly more computational time to provide solutions with a similar accuracy. We also demonstrated that the model can be a tool to understand surprising or nonintuitive phenomena regarding competitive advantage in the context of biologically realistic growth, birth and death rates. [ABSTRACT FROM AUTHOR]

Mycobacterium marinum (Mm), a genetically similar bacterium to Mycobacterium tuberculosis, affects a number of fish industries (fisheries, aquaculture, aquariums and research stocks) on a comparable scale to tuberculosis (TB) in humans. Because of this, and the practical advantages of working with animal models as opposed to humans, Mm infections in recently established fish models provide a unique opportunity for the study of mycobacterial infections. We derive a model of transmission dynamics of Mm in fish, which either involves consumption of an infected host or a source of bacteria to ensure "activation" into a highly infectious state. We derive a model of transmission within a food web, in which infected fish behavior is structured by infection severity. This is a key component as chronic (seemingly asymptomatic) infection is prominent in both fish and human TB. We illustrate, via a novel numerical scheme, that this model can be used to reproduce experimental settings. We further argue that the framework developed herein is a useful tool to address key questions such as design in experimental settings and potential control strategies in large-scale situations. [ABSTRACT FROM AUTHOR]

Public health professionals are charged with the task of designing prevention programs for the effective control of biologically intricate infectious diseases at a population level. The effective vaccination of a population for pneumococcal diseases (infections caused by Streptococcus pneumoniae) remains a relevant question in the scientific community. It is complicated by heterogeneity in individuals' responses to exposure to the bacterium and their responses to vaccination. Due to these complexities, most modelling efforts in this area have been on the cellular/bacteria level. Here, we introduce an age-structured SEIS-type model of pneumococcal diseases and their vaccination. We discuss the use of this framework in predicting the impact of vaccine strategies, with pneumococcal diseases as an example. Using parameter values reasonable for a developed country, we discuss the effects of targeting the colonization and/or infection stages on the age profiles of morbidity in a population.