Bdellovibrio predation in the presence of decoys:Three-way bacterial interactions revealed by mathematical and experimental analyses

Bdellovibrio bacteriovorus is a small, gram-negative, motile bacterium that preys upon other gram-negative bacteria, including several known human pathogens. Its predation efficiency is usually studied in pure cultures containing solely B. bacteriovorus and a suitable prey. However, in natural environments, as well as in any possible biomedical uses as an antimicrobial, Bdellovibrio is predatory in the presence of diverse decoys, including live nonsusceptible bacteria, eukaryotic cells, and cell debris. Here we gathered and mathematically modeled data from three-member cultures containing predator, prey, and nonsusceptible bacterial decoys. Specifically, we studied the rate of predation of planktonic late-log-phase Escherichia coli S17-1 prey by B. bacteriovorus HD100, both in the presence and in the absence of Bacillus subtilis nonsporulating strain 671, which acted as a live bacterial decoy. Interestingly, we found that although addition of the live Bacillus decoy did decrease the rate of Bdellovibrio predation in liquid cultures, this addition also resulted in a partially compensatory enhancement of the availability of prey for predation. This effect resulted in a higher final yield of Bdellovibrio than would be predicted for a simple inert decoy. Our mathematical model accounts for both negative and positive effects of predator-prey-decoy interactions in the closed batch environment. In addition, it informs considerations for predator dosing in any future therapeutic applications and sheds some light on considerations for modeling the massively complex interactions of real mixed bacterial populations in nature.

Recognition of O6MeG lesions by MGMT and mismatch repair proficiency may be a prerequisite for low-dose radiation hypersensitivity

Low-dose hyper-radiosensitivity (HRS) is the phenomenon whereby cells exposed to radiation doses of less than approximately 0.5 Gy exhibit increased cell killing relative to that predicted from back-extrapolating high-dose survival data using a linear-quadratic model. While the exact mechanism remains to be elucidated, the involvement of several molecular repair pathways has been documented. These processes in turn are also associated with the response of cells to O6-methylguanine (O6MeG) lesions. We propose a model in which the level of low-dose cell killing is determined by the efficiency of both pre-replicative repair by the DNA repair enzyme O6-methylguanine methyltransferase (MGMT) and post-replicative repair by the DNA mismatch repair (MMR) system. We therefore hypothesized that the response of cells to low doses of radiation is dependent on the expression status of MGMT and MMR proteins. MMR (MSH2, MSH6, MLH1, PMS1, PMS2) and MGMT protein expression signatures were determined in a panel of normal (PWR1E, RWPE1) and malignant (22RV1, DU145, PC3) prostate cell lines and correlated with clonogenic survival and cell cycle analysis. PC3 and RWPE1 cells (HRS positive) were associated with MGMT and MMR proficiency, whereas HRS negative cell lines lacked expression of at least one (MGMT or MMR) protein. MGMT inactivation had no significant effect on cell survival. These results indicate a possible role for MMR-dependent processing of damage produced by low doses of radiation.

Methodological aspects of a mathematical programming model to evaluate soil tillage technologies in a risky environment

In this work we develop a methodology for the economic evaluation of soil tillage technologies, in a risky environment, and to capture the influence of farmer behaviour on his technology choice. The model has short-term activities, that change with the type of year, and long-term activities, in which sets of traction investment activities are included. Although these activities do not change with the type of year, they lead to different availability of resources for each type of year, since the same tractor has different available fieldwork days under different weather conditions. We prove that the model is sensitive to the greater income variability resulting from the use of alternative technologies and to the balance between income and risk, accounting for the probability of occurrence of each state of nature and giving an investment solution that considers the best production plan for each type of year. (c) 2005 Elsevier B.V. All rights reserved.

Mathematical modelling of supercritical CO2 extraction of volatile oils from aromatic plants

The modelling of the experimental data of the extraction of the volatile oil from six aromatic plants (coriander, fennel, savoury, winter savoury, cotton lavender and thyme) was performed using five mathematical models, based on differential mass balances. In all cases the extraction was internal diffusion controlled and the internal mass transfer coefficienty (k(s)) have been found to change with pressure, temperature and particle size. For fennel, savoury and cotton lavender, the external mass transfer and the equilibrium phase also influenced the second extraction period, since k(s) changed with the tested flow rates. In general, the axial dispersion coefficient could be neglected for the conditions studied, since Peclet numbers were high. On the other hand, the solute-matrix interaction had to be considered in order to ensure a satisfactory description of the experimental data.

Fuzzy Monte Carlo mathematical model for load curtailment minimization in transmission power systems

This paper presents a methodology which is based on statistical failure and repair data of the transmission power system components and uses fuzzyprobabilistic modeling for system component outage parameters. Using statistical records allows developing the fuzzy membership functions of system component outage parameters. The proposed hybrid method of fuzzy set and Monte Carlo simulation based on the fuzzy-probabilistic models allows catching both randomness and fuzziness of component outage parameters. A network contingency analysis to identify any overloading or voltage violation in the network is performed once obtained the system states by Monte Carlo simulation. This is followed by a remedial action algorithm, based on optimal power flow, to reschedule generations and alleviate constraint violations and, at the same time, to avoid any load curtailment, if possible, or, otherwise, to minimize the total load curtailment, for the states identified by the contingency analysis. In order to illustrate the application of the proposed methodology to a practical case, the paper will include a case study for the Reliability Test System (RTS) 1996 IEEE 24 BUS.

Inexact restoration approaches to solve mathematical program with complementarity constraints

Mathematical Program with Complementarity Constraints (MPCC) finds applica- tion in many fields. As the complementarity constraints fail the standard Linear In- dependence Constraint Qualification (LICQ) or the Mangasarian-Fromovitz constraint qualification (MFCQ), at any feasible point, the nonlinear programming theory may not be directly applied to MPCC. However, the MPCC can be reformulated as NLP problem and solved by nonlinear programming techniques. One of them, the Inexact Restoration (IR) approach, performs two independent phases in each iteration - the feasibility and the optimality phases. This work presents two versions of an IR algorithm to solve MPCC. In the feasibility phase two strategies were implemented, depending on the constraints features. One gives more importance to the complementarity constraints, while the other considers the priority of equality and inequality constraints neglecting the complementarity ones. The optimality phase uses the same approach for both algorithm versions. The algorithms were implemented in MATLAB and the test problems are from MACMPEC collection.

Numerical experiments with a modified regularization scheme for mathematical programs with complementarity constraints

On this paper we present a modified regularization scheme for Mathematical Programs with Complementarity Constraints. In the regularized formulations the complementarity condition is replaced by a constraint involving a positive parameter that can be decreased to zero. In our approach both the complementarity condition and the nonnegativity constraints are relaxed. An iterative algorithm is implemented in MATLAB language and a set of AMPL problems from MacMPEC database were tested.

Dermic diffusion and stratum corneum: a state of the art review of mathematical models

Transdermal biotechnologies are an ever increasing field of interest, due to the medical and pharmaceutical applications that they underlie. There are several mathematical models at use that permit a more inclusive vision of pure experimental data and even allow practical extrapolation for new dermal diffusion methodologies. However, they grasp a complex variety of theories and assumptions that allocate their use for specific situations. Models based on Fick's First Law found better use in contexts where scaled particle theory Models would be extensive in time-span but the reciprocal is also true, as context of transdermal diffusion of particular active compounds changes. This article reviews extensively the various theoretical methodologies for studying dermic diffusion in the rate limiting dermic barrier, the stratum corneum, and systematizes its characteristics, their proper context of application, advantages and limitations, as well as future perspectives.

Mathematical modeling and simulation of heat flow through pultrusion die assembly system for thermoset composites

Pultrusion is an industrial process used to produce glass fibers reinforced polymers profiles. These materials are worldwide used when performing characteristics, such as great electrical and magnetic insulation, high strength to weight ratio, corrosion and weather resistance, long service life and minimal maintenance are required. In this study, we present the results of the modelling and simulation of heat flow through a pultrusion die by means of Finite Element Analysis (FEA). The numerical simulation was calibrated based on temperature profiles computed from thermographic measurements carried out during pultrusion manufacturing process. Obtained results have shown a maximum deviation of 7%, which is considered to be acceptable for this type of analysis, and is below to the 10% value, previously specified as maximum deviation. © 2011, Advanced Engineering Solutions.

Mathematical model for HIV dynamics in HIV-specific helper cells

In this paper we study a delay mathematical model for the dynamics of HIV in HIV-specific CD4 + T helper cells. We modify the model presented by Roy and Wodarz in 2012, where the HIV dynamics is studied, considering a single CD4 + T cell population. Non-specific helper cells are included as alternative target cell population, to account for macrophages and dendritic cells. In this paper, we include two types of delay: (1) a latent period between the time target cells are contacted by the virus particles and the time the virions enter the cells and; (2) virus production period for new virions to be produced within and released from the infected cells. We compute the reproduction number of the model, R0, and the local stability of the disease free equilibrium and of the endemic equilibrium. We find that for values of R0<1, the model approaches asymptotically the disease free equilibrium. For values of R0>1, the model approximates asymptotically the endemic equilibrium. We observe numerically the phenomenon of backward bifurcation for values of R0⪅1. This statement will be proved in future work. We also vary the values of the latent period and the production period of infected cells and free virus. We conclude that increasing these values translates in a decrease of the reproduction number. Thus, a good strategy to control the HIV virus should focus on drugs to prolong the latent period and/or slow down the virus production. These results suggest that the model is mathematically and epidemiologically well-posed.