Biofilm model calibration and microbial diversity study using Monte Carlo simulations

Mathematical models are useful tools for studying and exploring biological conversion processes as well as microbial competition in biological treatment processes. A single‐species biofilm model was used to describe biofilm reactor operation at three different hydraulic retention times (HRT). The single‐species biofilm model was calibrated with sparse experimental data using the Monte Carlo filtering method. This calibrated single‐species biofilm model was then extended to a multi‐species model considering 10 different heterotrophic bacteria. The aim was to study microbial diversity in bulk phase biomass and biofilm, as well as the competition between suspended and attached biomass. At steady state and independently of the HRT, Monte Carlo simulations resulted only in one unique dominating bacterial species for suspended and attached biomass. The dominating bacterial species was determined by the highest specific substrate affinity (ratio of µ/K_S). At a short HRT of 20 min, the structure of the microbial community in the bulk liquid was determined by biomass detached from the biofilm. At a long HRT of 8 h, both biofilm detachment and microbial growth in the bulk liquid influenced the microbial community distribution. Biotechnol. Bioeng. 2013; 110: 1323–1332. © 2012 Wiley Periodicals, Inc.     

Geant4 implementation of inter-atomic interference effect in small-angle coherent X-ray scattering for materials of medical interest

An extension to Geant4 Monte Carlo code was developed to take into account inter-atomic (molecular) interference effects in X-ray coherent scattering. Based on our previous works, the developed code introduces a set of form factors including interference effects for a selected variety of amorphous materials useful for medical applications, namely various tissues and plastics used to build phantoms. The code is easily upgradable in order to include new materials and offers the possibility to model a generic tissue as a combination of a set of four basic components. A dedicated Geant4 application for the simulation of X-ray diffraction experiments was created to validate the proposed upgrade of Rayleigh scattering model. A preliminary validation of the code obtained through a comparison with EGS4 and an experiment is presented, showing a satisfactory agreement.     

Analyzing indirect secondary electron contrast of unstained bacteriophage T4 based on SEM images and Monte Carlo simulations

The indirect secondary electron contrast (ISEC) condition of the scanning electron microscopy (SEM) produces high contrast detection with minimal damage of unstained biological samples mounted under a thin carbon film. The high contrast image is created by a secondary electron signal produced under the carbon film by a low acceleration voltage. Here, we show that ISEC condition is clearly able to detect unstained bacteriophage T4 under a thin carbon film (10-15 nm) by using high-resolution field emission (FE) SEM. The results show that FE-SEM provides higher resolution than thermionic emission SEM. Furthermore, we investigated the scattered electron area within the carbon film under ISEC conditions using Monte Carlo simulation. The simulations indicated that the image resolution difference is related to the scattering width in the carbon film and the electron beam spot size. Using ISEC conditions on unstained virus samples would produce low electronic damage, because the electron beam does not directly irradiate the sample. In addition to the routine analysis, this method can be utilized for structural analysis of various biological samples like viruses, bacteria, and protein complexes.     

Bayesian Nonparametric Nonproportional Hazards Survival Modeling

Summary .  We develop a dependent Dirichlet process model for survival analysis data. A major feature of the proposed approach is that there is no necessity for resulting survival curve estimates to satisfy the ubiquitous proportional hazards assumption. An illustration based on a cancer clinical trial is given, where survival probabilities for times early in the study are estimated to be lower for those on a high-dose treatment regimen than for those on the low dose treatment, while the reverse is true for later times, possibly due to the toxic effect of the high dose for those who are not as healthy at the beginning of the study.     

Aedes aegypti: model for blood finding strategy and prediction of parasite manipulation

Aedes aegypti mosquitoes salivate during intradermal probing of vertebrate prey before ingesting blood (Griffiths and Gordon 1952). Nonsalivating mosquitoes locate blood more slowly; this difference was ascribed to an anti-platelet activity found in the mosquito's saliva (Ribeiro et al. 1984). Mosquitoes infected with Plasmodium gallinaceum suffer pathology that specifically impairs saliva anti-hemostatic activity but without reducing volume of output (Rossignol et al. 1984). The complexity of the feeding apparatus of mosquitoes provides opportunity for a variety of strategies in which pathogens may produce specific lesions that enhance their transmission, but the variables that affect the duration of probing by mosquitoes have not been defined. We sought to resolve this complexity by identifying and quantifying relevant parameters of probing behavior. Mosquitoes thrust their mouthparts repeatedly through their host's skin while searching for blood. Female A. aegypti thrust at 7-sec intervals. If this search results in success, feeding ensues. Alternatively, the mosquito "desists," the mouthparts stylets are withdrawn, and the mosquito attempts to feed at another site. Even after previous desistance, the probability of finding blood remains undiminished. Functions for the probability of feeding success and desistance over time were derived using data from observations on 300 mosquitoes. The probability of feeding success was interpreted as being a function of the density of vessels in the skin, their geometric distribution, and the conditions locally affecting hemostasis. During each probe, the probability of desisting increased linearly with time, and after desisting once, mosquitoes tended to desist more rapidly. A model was developed incorporating Monte Carlo simulation which closely fit observed data. By changing values for the several parameters of the probability functions, we predicted modes in which parasites may manipulate their hosts to enhance transmission, both to and from the vector. In particular, parasite strategies in the vector would include induced salivary pathology; increased duration of probing thrusts; decreased desistance time; and inhibited phagoreception. Predicted parasite strategies in the reservoir host would include increased skin vascular volume and impaired host hemostasis. Our model supports the hypothesis of a mutualistic interaction of malaria and mosquitoes.     

Homology modeling by the ICM method

Five models have been built by the ICM method for the Comparative Modeling section of the Meeting on the Critical Assessment of Techniques for Protein Structure Prediction. The targets have homologous proteins with known three-dimensional structure with sequence identity ranging from 25 to 77%. After alignment of the target sequence with the related three-dimensional structure, the modeling procedure consists of two subproblems: side-chain prediction and loop prediction. The ICM method approaches these problems with the following steps: (1) a starting model is created based on the homologous structure with the conserved portion fixed and the noncon-served portion having standard covalent geometry and free torsion angles; (2) the Biased Probability Monte Carlo (BPMC) procedure is applied to search the subspaces of either all the nonconservative side-chain torsion angles or torsion angles in a loop backbone and surrounding side chains. A special algorithm was designed to generate low-energy loop deformations. The BPMC procedure globally optimizes the energy function consisting of ECEPP/3 and solvation energy terms. Comparison of the predictions with the NMR or crystallographic solutions reveals a high proportion of correctly predicted side chains. The loops were not correctly predicted because imprinted distortions of the backbone increased the energy of the near-native conformation and thus made the solution unrecognizable. Interestingly, the energy terms were found to be reliable and the sampling of conformational space sufficient. The implications of this finding for the strategies of future comparative modeling are discussed. © 1995 Wiley-Liss, Inc.     

Energetics and stability of transmembrane helix packing: a replica-exchange simulation with a knowledge-based membrane potential

The energetics and stability of the packing of transmembrane helices were investigated by Monte Carlo simulations with the replica-exchange method. The helices were modeled with a united atom representation, and the CHARMM19 force field was employed. Based on known experimental structures of membrane proteins, an implicit knowledge-based potential was developed to describe the helix-membrane interactions at the residue level, whose validity was tested through prediction of the orientations when single helices were inserted into a membrane. Two systems were studied in this article, namely the glycophorin A dimer, and helices A and B of Bacteriorhodopsin. For the glycophorin A dimer, the most stable structure (0.5 A away from the experimental structure) is mainly stabilized by the favorable helix-helix interactions, and has the most population regardless of the helix-membrane interaction. However, for helices A and B of Bacteriorhodopsin, it was found that the packing determined by helix-helix interactions is nonspecific, and a native-like structure (0.2 A from the experimental one) can be identified from several structural analogs as the most stable one only after applying the membrane potential. Our results suggest that the contribution from the helix-membrane interaction could be critical in the correct packing of transmembrane helices in the membrane.     

Dual-energy contrast-enhanced digital mammography: Glandular dose estimation using a Monte Carlo code and voxel phantom

PurposeTo estimate the mean glandular dose of contrast enhanced digital mammography, using the EGSnrc Monte Carlo code and female adult voxel phantom.MethodsAutomatic exposure control of full field digital mammography system was used for the selection of the X-ray spectrum and the exposure settings for dual energy imaging. Measurements of the air-kerma and of the half value layers were performed and a Monte Carlo simulation of the digital mammography system was used to compute the mean glandular dose, for breast phantoms of various thicknesses, glandularities and for different X-ray spectra (low and high energy).ResultsFor breast phantoms of 2.0–8.0 cm thick and 0.1–100% glandular fraction, CC view acquisition, from AEC settings, can result in a mean glandular dose of 0.450 ± 0.022 mGy −2.575 ± 0.033 mGy for low energy images and 0.061 ± 0.021 mGy – 0.232 ± 0.033 mGy for high energy images. In MLO view acquisition mean glandular dose values ranged between 0.488 ± 0.007 mGy – 2.080 ± 0.021 mGy for low energy images and 0.065 ± 0.012 mGy – 0.215 ± 0.010 mGy for high energy images.ConclusionThe low kV part of contrast enhanced digital mammography is the main contributor to total mean glandular breast dose. The results of this study can be used to provide an estimated mean glandular dose for individual cases.