Monte Carlo simulation of pathogen behavior during the sprout production process

Food-borne disease outbreaks linked to the consumption of raw sprouts have become a concern over the past decade. A Monte Carlo simulation model of the sprout production process was created to determine the most-effective points for pathogen control. Published literature was reviewed, and relevant data were compiled. Appropriate statistical distributions were determined and used to create the Monte Carlo model with Analytica software. Factors modeled included initial pathogen concentration and prevalence, seed disinfection effectiveness, and sampling of seeds prior to sprouting, sampling of irrigation water, or sampling of the finished product. Pathogen concentration and uniformity of seed contamination had a large effect on the fraction of contaminated batches predicted by the simulation. The model predicted that sprout sampling and irrigation water sampling at the end of the sprouting process would be more effective in pathogen detection than seed sampling prior to production. Day of sampling and type of sample (sprout or water) taken had a minimal effect on rate of detection. Seed disinfection reduced the proportion of contaminated batches, but in some cases it also reduced the ability to detect the pathogen when it was present, because cell numbers were reduced below the detection limit. Both the amount sampled and the pathogen detection limit were shown to be important variables in determining sampling effectiveness. This simulation can also be used to guide further research and compare the levels of effectiveness of different risk reduction strategies.     

Differences in growth of Salmonella enterica and Escherichia coli O157:H7 on alfalfa sprouts

Sprout producers have recently been faced with several Salmonella enterica and Escherichia coli O157:H7 outbreaks. Many of the outbreaks have been traced to sprout seeds contaminated with low levels of human pathogens. Alfalfa seeds were inoculated with S. enterica and E. coli O157:H7 strains isolated from alfalfa seeds or other environmental sources and sprouted to examine growth of these human pathogens in association with sprouting seeds. S. enterica strains grew an average of 3.7 log(10) on sprouting seeds over 2 days, while E. coli O157:H7 strains grew significantly less, an average of 2.3 log(10). The initial S. enterica or E. coli O157:H7 inoculum dose and seed-sprouting temperature significantly affected the levels of both S. enterica and E. coli O157:H7 on the sprouts and in the irrigation water, while the frequency of irrigation water replacement affected only the levels of E. coli O157:H7. Colonization of sprouting alfalfa seeds by S. enterica serovar Newport and E. coli O157:H7 strains transformed with a plasmid encoding the green fluorescent protein was examined with fluorescence microscopy. Salmonella serovar Newport colonized both seed coats and sprout roots as aggregates, while E. coli O157:H7 colonized only sprout roots.     

Differences in Growth of Salmonella enterica and Escherichia coli O157:H7 on Alfalfa Sprouts

Sprout producers have recently been faced with several Salmonella enterica and Escherichia coli O157:H7 outbreaks. Many of the outbreaks have been traced to sprout seeds contaminated with low levels of human pathogens. Alfalfa seeds were inoculated with S. enterica and E. coli O157:H7 strains isolated from alfalfa seeds or other environmental sources and sprouted to examine growth of these human pathogens in association with sprouting seeds. S. enterica strains grew an average of 3.7 log₁₀ on sprouting seeds over 2 days, while E. coli O157:H7 strains grew significantly less, an average of 2.3 log₁₀. The initial S. enterica or E. coli O157:H7 inoculum dose and seed-sprouting temperature significantly affected the levels of both S. enterica and E. coli O157:H7 on the sprouts and in the irrigation water, while the frequency of irrigation water replacement affected only the levels of E. coli O157:H7. Colonization of sprouting alfalfa seeds by S. enterica serovar Newport and E. coli O157:H7 strains transformed with a plasmid encoding the green fluorescent protein was examined with fluorescence microscopy. Salmonella serovar Newport colonized both seed coats and sprout roots as aggregates, while E. coli O157:H7 colonized only sprout roots.     

Comparison of primers for the detection of pathogenic Escherichia coli using real-time PCR

AIMS: To evaluate PCR primers for the detection of pathogenic Escherichia coli in a real-time PCR assay and determine their utility in produce irrigation water testing. METHODS AND RESULTS: Three previously published PCR primer sets and one set designed for this study were tested for their ability to produce amplification products for several pathogenic E. coli serotypes from whole cells as template. Two of the previously published primer sets were chosen for real-time PCR detection limit determination. The coneaeA and PEH detection limit of E. coli O157:H7 was 10(0) and 10(1) CFU rxn(-1) in sterile water respectively. To detect E. coli O157:H7 in sprout irrigation water, the water required dilution due to PCR inhibitors. The detection limit of the coneaeA and PEH was 10(1) and between 10(2) and 10(3) CFU rxn(-1) in diluted sprout irrigation water respectively. CONCLUSIONS: The primer set coneaeA was able to produce an amplification product from each E. coli serotype, except O128:H7 and most sensitive for real-time PCR detection of pathogenic E. coli in diluted sprout irrigation water. SIGNIFICANCE AND IMPACT OF THE STUDY: The necessity of a dissociation analysis to distinguish positive samples from those with fluorescence of random dsDNA generation for real-time PCR in a complex background was established.     

Bayesian prediction of spatial count data using generalized linear mixed models

Spatial weed count data are modeled and predicted using a generalized linear mixed model combined with a Bayesian approach and Markov chain Monte Carlo. Informative priors for a data set with sparse sampling are elicited using a previously collected data set with extensive sampling. Furthermore, we demonstrate that so-called Langevin-Hastings updates are useful for efficient simulation of the posterior distributions, and we discuss computational issues concerning prediction.     

Density guided importance sampling: application to a reduced model of protein folding

MOTIVATION: Monte Carlo methods are the most effective means of exploring the energy landscapes of protein folding. The rugged topography of folding energy landscapes causes sampling inefficiencies however, particularly at low, physiological temperatures. RESULTS: A hybrid Monte Carlo method, termed density guided importance sampling (DGIS), is presented that overcomes these sampling inefficiencies. The method is shown to be highly accurate and efficient in determining Boltzmann weighted structural metrics of a discrete off-lattice protein model. In comparison to the Metropolis Monte Carlo method, and the hybrid Monte Carlo methods, jump-walking, smart-walking and replica-exchange, the DGIS method is shown to be more efficient, requiring no parameter optimization. The method guides the simulation towards under-sampled regions of the energy spectrum and recognizes when equilibrium has been reached, avoiding arbitrary and excessively long simulation times. AVAILABILITY: Fortran code available from authors upon request. CONTACT: m.j.parker@leeds.ac.uk.     

The ecology of germination and reproduction of less frequent and vanishing species of the Czechoslovak flora IV.Melilotus altissima Thuill

The ecology of seed germination was examined in air-conditioned boxes in the laboratory, and the sprouting of seeds was investigated in an experimental plot at Pr?honice. The seeds show a marked dormancy caused by the impermeability of testa to water (seed hardcoatness). 72–100% of hard seeds were found in 16 seed samples. Seed hardcoatness is an important protective strategy of the species against the frost killing of seedlings and, on the other hand, for the longevity of seeds (Table 3) and for the possibility of endochoric spreading. It is also important to establish seed supply in the soil. The seed sprout from the first decade of April till the beginning of May. The soft seed sprout as early as in autumn, and the seedlings freeze out (Table 4).     

Two-step validation of a Monte Carlo dosimetry framework for general radiology

The Monte Carlo technique is considered gold standard when it comes to patient-specific dosimetry. Any newly developed Monte Carlo simulation framework, however, has to be carefully calibrated and validated prior to its use. For many researchers this is a tedious work. We propose a two-step validation procedure for our newly built Monte Carlo framework and provide all input data to make it feasible for future related application by the wider community. The validation was at first performed by benchmarking against simulation data available in literature. The American Association of Physicists in Medicine (AAPM) report of task group 195 (case 2) was considered most appropriate for our application. Secondly, the framework was calibrated and validated against experimental measurements for trunk X-ray imaging protocols using a water phantom. The dose results obtained from all simulations and measurements were compared. Our Monte Carlo framework proved to agree with literature data, by showing a maximal difference below 4% to the AAPM report. The mean difference with the water phantom measurements was around 7%. The statistical uncertainty for clinical applications of the dosimetry model is expected to be within 10%. This makes it reliable for clinical dose calculations in general radiology. Input data and the described procedure allow for the validation of other Monte Carlo frameworks.     

Comparison of an immunochromatographic method and the TaqMan E. coli O157:H7 assay for detection of Escherichia coli O157:H7 in alfalfa sprout spent irrigation water and in sprouts after blanching

An immunochromatographic-based assay (Quixtrade mark E. coli O157 Sprout Assay) and a polymerase chain reaction (PCR)-based assay (TaqMan E. coli O157:H7 Kit) were used to detect Escherichia coli O157:H7 strain 380-94 in spent irrigation water from alfalfa sprouts grown from artificially contaminated seeds. Ten, 25, 60, or 100 seeds contaminated by immersion for 15 min in a suspension of E. coli O157:H7 at concentrations of 10(6) or 10(8) cfu/ml were mixed with 20 g of non-inoculated seeds in plastic trays for sprouting. The seeds were sprayed with tap water for 15 s every hour and spent irrigation water was collected at intervals and tested. E. coli O157:H7 was detected in non-enriched water by both the TaqMan PCR (30 of 30 samples) and the immunoassay (9 of 24 samples) in water collected 30 h from the start of the sprouting process. However, enrichment of the spent irrigation water in brain heart infusion (BHI) broth at 37 degrees C for 20 h permitted detection of E. coli O157:H7 in water collected 8 h from the start of sprouting using both methods, even in trays containing as few as 10 inoculated seeds. The TaqMan PCR assay was more sensitive (more positive samples were observed earlier in the sprouting process) than the immunoassay; however, the immunoassay was easier to perform and was more rapid. At 72 h after the start of the sprouting process, the sprouts were heated at 100 degrees C for 30 s to determine the effectiveness of blanching for inactivation of E. coli O157:H7. All of the 32 samples tested with the TaqMan assay and 16 of 32 samples tested with the Quixtrade mark assay gave positive results for E. coli O157:H7 after enrichment of the blanched sprouts at 37 degrees C for 24 h. In addition, the organism was detected on Rainbow Agar O157 in 9 of 32 samples after 24 h of enrichment of the blanched sprouts. In conclusion, E. coli O157:H7 was detected in spent irrigation water collected from sprouts grown from artificially contaminated seeds by both the TaqMan and Quixtrade mark assays. The data also revealed that blanching may not be effective to completely inactivate all the E. coli O157:H7 that may be present in sprouts.     

Growth of Escherichia coli O157:H7 during sprouting of alfalfa seeds

AIMS: Escherichia coli O157:H7 was monitored daily during sprouting of alfalfa seeds inoculated at high (3.92 log10 cfu g(-1)) and low (1.86 log10 cfu g(-1)) levels to assess the extent of pathogen growth during production. METHODS AND RESULTS: Sprouts and rinse water were tested by direct and membrane filter plating on modified sorbitol MacConkey agar and BCM O157:H7(+) agar; the antibody-direct epifluorescent filter technique; and rapid immunoassays. The pathogen reached maximum populations after one and two days of sprouting seeds inoculated at high and low levels, respectively; in either case, populations of 5-6 log10 cfu g(-1) were reached. Detection limits of two rapid immunoassays, Reveal and VIP, without enrichment were determined to be 5-7 log10 cfu ml(-1). CONCLUSION: These results show the ability of E. coli O157:H7 to grow to high levels during sprouting; however, because these levels may be below detection limits, it is necessary to include enrichment when monitoring sprout production for E. coli O157:H7 by the rapid test kits. SIGNIFICANCE AND IMPACT OF THE STUDY: The data indicate that sprouts may harbor high levels of pathogens. The appropriate use of rapid test methods for pathogen monitoring during sprouting is indicated.     

Age of potato seed-tubers influences protein synthesis during sprouting

The effect of seed-tuber age on the ability of tuber tissue to synthesize protein during sprouting was examined. As seed-tuber age advanced from 4 to 32 months (at 4°C, 95% relative humidity), soluble protein concentration of tubers decreased linearly, with a concomitant increase in free amino acid concentration. The age-induced loss of tuber protein may thus be due to increased proteolysis, decreased protein synthesis, or both. Five- and 17-month-old seed-tubers were compared for their ability to incorporate radiolabeled amino acids into soluble protein at equivalent stages of sprout development. Tuber respiration was profiled through each sprouting stage to characterize the physiological status of the seed-tubers prior to incorporation studies. Five-month-old seed-tubers maintained a constant rate of respiration during sprouting. In contrast, respiration of 17-month-old tubers increased as sprout dry matter increased, resulting in a 2- to 3-fold greater respiratory rate from the older tubers, relative to the younger tubers, at similar stages of sprout development. Prior to sprouting, the rate of incorporation of amino acids into trichloroacetic acid-precipitable protein of tissue from 5-month-old tubers was 2. 9-fold higher than that from 17-month-old tubers. More importantly, protein-synthetic capacity of tissue from younger tubers increased about 1. 7-fold during sprout development. Despite the higher respiratory activity and faster total sprout dry matter accumulation from older seed-tubers, protein synthesis remained at a low and constant level through all stages of sprouting. Protein-synthetic capacity thus declines with advancing tuber age, and this may contribute to reduced growth potential during the latter stages of establishment by affecting the ability of seed-tubers to synthesize enzymes involved in mobilization and translocation of tuber reserves to developing plants.     

Local energy landscape flattening: parallel hyperbolic Monte Carlo sampling of protein folding

Among the major difficulties in protein structure prediction is the roughness of the energy landscape that must be searched for the global energy minimum. To address this issue, we have developed a novel Monte Carlo algorithm called parallel hyperbolic sampling (PHS) that logarithmically flattens local high-energy barriers and, therefore, allows the simulation to tunnel more efficiently through energetically inaccessible regions to low-energy valleys. Here, we show the utility of this approach by applying it to the SICHO (SIde-CHain-Only) protein model. For the same CPU time, the parallel hyperbolic sampling method can identify much lower energy states and explore a larger region phase space than the commonly used replica sampling (RS) Monte Carlo method. By clustering the simulated structures obtained in the PHS implementation of the SICHO model, we can successfully predict, among a representative benchmark 65 proteins set, 50 cases in which one of the top 5 clusters have a root-mean-square deviation (RMSD) from the native structure below 6.5 A. Compared with our previous calculations that used RS as the conformational search procedure, the number of successful predictions increased by four and the CPU cost is reduced. By comparing the structure clusters produced by both PHS and RS, we find a strong correlation between the quality of predicted structures and the minimum relative RMSD (mrRMSD) of structures clusters identified by using different search engines. This mrRMSD correlation may be useful in blind prediction as an indicator of the likelihood of successful folds.     

Test of the Inverse Monte Carlo Method for the Calculation of Interatomic Potential Energies in Atomic Liquids

Abstract

The principle purpose of this paper is to demonstrate the use of the Inverse Monte Carlo technique for calculating pair interaction energies in monoatomic liquids from a given equilibrium property. This method is based on the mathematical relation between transition probability and pair potential given by the fundamental equation of the “importance sampling” Monte Carlo method. In order to have well defined conditions for the test of the Inverse Monte Carlo method a Metropolis Monte Carlo simulation of a Lennard Jones liquid is carried out to give the equilibrium pair correlation function determined by the assumed potential. Because an equilibrium configuration is prerequisite for an Inverse Monte Carlo simulation a model system is generated reproducing the pair correlation function, which has been calculated by the Metropolis Monte Carlo simulation and therefore representing the system in thermal equilibrium. This configuration is used to simulate virtual atom displacements. The resulting changes in atom distribution for each single simulation step are inserted in a set of non-linear equations defining the transition probability for the virtual change of configuration. The solution of the set of equations for pair interaction energies yields the Lennard Jones potential by which the equilibrium configuration has been determined.     

Nonconjugate Bayesian analysis of variance component models

We consider the usual normal linear mixed model for variance components from a Bayesian viewpoint. With conjugate priors and balanced data, Gibbs sampling is easy to implement; however, simulating from full conditionals can become difficult for the analysis of unbalanced data with possibly nonconjugate priors, thus leading one to consider alternative Markov chain Monte Carlo schemes. We propose and investigate a method for posterior simulation based on an independence chain. The method is customized to exploit the structure of the variance component model, and it works with arbitrary prior distributions. As a default reference prior, we use a version of Jeffreys' prior based on the integrated (restricted) likelihood. We demonstrate the ease of application and flexibility of this approach in familiar settings involving both balanced and unbalanced data.     

Shift in the Microbial Ecology of a Hospital Hot Water System following the Introduction of an On-Site Monochloramine Disinfection System

Drinking water distribution systems, including premise plumbing, contain a diverse microbiological community that may include opportunistic pathogens. On-site supplemental disinfection systems have been proposed as a control method for opportunistic pathogens in premise plumbing. The majority of on-site disinfection systems to date have been installed in hospitals due to the high concentration of opportunistic pathogen susceptible occupants. The installation of on-site supplemental disinfection systems in hospitals allows for evaluation of the impact of on-site disinfection systems on drinking water system microbial ecology prior to widespread application. This study evaluated the impact of supplemental monochloramine on the microbial ecology of a hospital’s hot water system. Samples were taken three months and immediately prior to monochloramine treatment and monthly for the first six months of treatment, and all samples were subjected to high throughput Illumina 16S rRNA region sequencing. The microbial community composition of monochloramine treated samples was dramatically different than the baseline months. There was an immediate shift towards decreased relative abundance of Betaproteobacteria, and increased relative abundance of Firmicutes, Alphaproteobacteria, Gammaproteobacteria, Cyanobacteria and Actinobacteria. Following treatment, microbial populations grouped by sampling location rather than sampling time. Over the course of treatment the relative abundance of certain genera containing opportunistic pathogens and genera containing denitrifying bacteria increased. The results demonstrate the driving influence of supplemental disinfection on premise plumbing microbial ecology and suggest the value of further investigation into the overall effects of premise plumbing disinfection strategies on microbial ecology and not solely specific target microorganisms.     

Monte carlo simulation of bacterial disinfection: Nonlinear and time‐explicit intensity of transition

Bacteria being disinfected in fluid media are discrete entities and mesoscopic in size; moreover, they are incessantly as well as irregularly in motion and in collision among themselves or with the surrounding solid surfaces. As such, it is highly likely that some of the attributes of the bacterial population, for example, their number concentration, will fluctuate randomly. This is especially the case at the tail‐end of disinfection when the population of bacteria is sparse. It might be effectual, therefore, to explore the resultant random fluctuations via a stochastic paradigm. Proposed herein is a Markovian stochastic model for the rate of bacterial disinfection, whose intensity of transition takes into account the contact time of the bacteria with the disinfecting agent to eliminate any given percentage of the bacteria in terms of a nonlinear function of time. The model's master equation has been simulated by resorting to the Monte Carlo method to circumvent the undue complexities in solving it analytically or numerically via conventional numerical techniques. For illustration, the mean, the variance (standard deviation), and the coefficient of variation of the number concentration of bacteria during disinfection have been estimated through Monte Carlo simulation. The results of simulation compare favorably with the available experimental data as well as with those computed from the corresponding deterministic model. © 2010 American Institute of Chemical Engineers Biotechnol. Prog., 2010     

Single- and multiple-trait mapping analysis of linked quantitative trait loci. Some asymptotic analytical approximations.

Estimating the resolution power of mapping analysis of linked quantitative trait loci (QTL) remains a difficult problem, which has been previously addressed mainly by Monte Carlo simulations. The analytical method of evaluation of the expected LOD developed in this article spreads the "deterministic sampling" approach for the case of two linked QTL for single- and two-trait analysis. Several complicated questions are addressed through this evaluation: the dependence of QTL detection power on the QTL effects, residual correlation between the traits, and the effect of epistatic interaction between the QTL for one or both traits on expected LOD (ELOD), etc. Although this method gives only an asymptotic estimation of ELOD, it allows one to get an approximate assessment of a broad spectrum of mapping situations. A good correspondence was found between the ELODs predicted by the model and LOD values averaged over Monte Carlo simulations.     

Fate of Escherichia coli O157:H7 in irrigation water on soils and plants as validated by culture method and real-time PCR

One of the most common vehicles by which Escherichia coli O157:H7 may be introduced into crops is contaminated irrigation water. Water contamination is becoming more common in rural areas of the United States as a result of large animal operations, and up to 40% of tested drinking-water wells are contaminated with E. coli. In this study, 2 contrasting soil samples were inoculated with E. coli O157:H7 expressing green fluorescent protein through irrigation water. Real-time PCR and culture methods were used to quantify the fate of this pathogen in phyllosphere (leaf surface), rhizosphere (volume of soil tightly held by plant roots), and non-rhizosphere soils. A real-time PCR assay was designed with the eae gene of E. coli O157:H7. The probe was incorporated into real-time PCR containing DNA extracted from the phyllosphere, rhizosphere, and non-rhizosphere soils. The detection limit for E. coli O157:H7 quantification by real-time PCR was 1.2 x 10(3) in the rhizosphere, phyllosphere, and non-rhizosphere samples. E. coli O157:H7 concentrations were higher in the rhizosphere than in the non-rhizosphere soils and leaf surfaces, and persisted longer in clay soil. The persistence of E. coli O157:H7 in phyllosphere, rhizosphere, and non-rhizosphere soils over 45 days may play a significant part in the recontamination cycle of produce in the environment. Therefore, the rapidity of the real-time PCR assay may be a useful tool for quantification and monitoring of E. coli O157:H7 in irrigation water and on contaminated fresh produce.     

Taboo-based Monte Carlo Search as a Method to Improve Sampling Efficiency

Abstract

Taboo-based Monte Carlo search which restricts the sampling of the region near an old configuration, is developed. In this procedure, Monte Carlo simulation and random search method are combined to improve the sampling efficiency. The feasibility of this method is tested on global optimization of a continuous model function, melting of the 256 Lennard-Jones particles at T? = 0.680 and ρ? = 0.850 and polypeptides (alanine dipeptide and Metenkephalin). From the comparison of results for the model function between our method and other methods, we find the increase of convergence rate and the high possibility of escaping from the local energy minima. The results of the Lennard-Jones solids and polypeptides show that the convergence property to reach the equilibrium state is better than that of others. It is also found that no significant bias in ensemble distribution is detected, though taboo-based Monte Carlo search does not sample the correct ensemble distribution owing to the restriction of the sampling of the region near an old configuration.     

白芨胚发育与种子萌发的关系

随着白芨胚龄增大,胚成熟度不断增加,有胚率和萌发率逐渐提高,种子萌发时间逐渐变短。胚龄为20周后采收最好,有胚率最高,萌发率为100%,萌发时间只需1周。种子萌发时胚先发育成原球茎,原球茎再分化出叶片和根系,形成完整的小植株;花宝一号1g/L+花宝二号2g/L+10%椰子汁培养基可促进种子萌发及幼苗生长,比常用的基本培养基加生长调节剂更简捷,幼苗生长健壮。