Functional genomics studies shed light on the nutrition and gene expression of non-typhoidal Salmonella and enterovirulent E. coli in produce

Despite the fact that plants are not traditionally considered as hosts for human enteric pathogens, recent evidence suggests that non-typhoidal Salmonella and enterovirulent Escherichia coli recognize plants and rely on a specific set of genes to multiply in plant-associated environments, eventually causing dramatic outbreaks of illness. The advent of sensitive functional genomics tools, including differential fluorescence induction and in vivo expression technology, set the stage for the characterization of the genes and behaviors used by enterics to colonize, persist and proliferate within plants and the associated microbial communities. Meta-analysis of published data suggests that Salmonella and enterovirulent E. coli persist in plants using strategies that differ from those in phytobacteria. Virulence genes were upregulated in E. coli O157:H7 in the presence of lettuce leaf exudates, however Salmonella SPI-1 genes associated with gastroenteritis were dispensable during plant growth. Microarray and mutant studies of plant responses to human pathogens reveal that plants generally do not recognize Salmonella and enterovirulent E. coli as phytopathogens or beneficial symbionts, although the full spectrum of plant responses to enterics remains to be elucidated. Defining plant responses to human enteric pathogens becomes increasingly important as the feasibility of breeding for resistance to these organisms is being evaluated.     

Current Therapies and Technological Advances in Aqueous Aerosol Drug Delivery

Recent advances in aerosolization technology have led to renewed interest in pulmonary delivery of a variety of drugs. Pressurized metered dose inhalers (pMDIs) and dry powder inhalers (DPIs) have experienced success in recent years; however, many limitations are presented by formulation difficulties, inefficient delivery, and complex device designs. Simplification of the formulation process as well as adaptability of new devices has led many in the pharmaceutical industry to reconsider aerosolization in an aqueous carrier. In the acute care setting, breath-enhanced air-jet nebulizers are controlling and minimizing the amount of wasted medication, while producing a high percentage of respirable droplets. Vibrating mesh nebulizers offer advantages in higher respirable fractions (RFs) and slower velocity aerosols when compared with air-jet nebulizers. Vibrating mesh nebulizers incorporating formulation and patient adaptive components provide improvements to continuous nebulization technology by generating aerosol only when it is most likely to reach the deep lung. Novel innovations in generation of liquid aerosols are now being adapted for propellant-free pulmonary drug delivery to achieve unprecedented control over dose delivered and are leading the way for the adaptation of systemic drugs for delivery via the pulmonary route. Devices designed for the metered dose delivery of insulin, morphine, sildenafil, triptans, and various peptides are all currently under investigation for pulmonary delivery to treat nonrespiratory diseases. Although these devices are currently still in clinical testing (with the exception of the Respimat®), metered dose liquid inhalers (MDLIs) have already shown superior outcomes to current pulmonary and systemic delivery methods.     

Control point policy optimization using genetic algorithms

This paper describes the application of an integrated Genetic Algorithm (GA)/Discrete Event Simulation model for selecting optimum values for Critical Point Policy (CPP) hedging time and buffer size parameters. The CPP is shown to perform well, when compared with the Critical Ratio priority rule, in terms of improving service levels, particularly when subject to conditions where buffer sizes and Takt times are required to be small. The technique developed involves buffer sizes being chosen by a GA according to a constraint on the total storage space available within the system. A method is described for reducing the number of variables that the GA needs to deal with, hence, improving the efficiency of the GA optimization process. The development and application work reported also provides further understanding into how and when the CPP should be applied.     

Oral and intestinal digestion of oligosaccharides as potential sweeteners: A systematic evaluation

The utilisation of oligosaccharides by oral microorganisms and intestinal enzymes are important factors in determining their effectiveness as alternative sweeteners. In this study, classes of naturally occurring sugars were assessed using in vitro models for oral and intestinal digestibility, in order to test the influence of chemical structure on functional properties. Amongst the classes of sucrose isomers, α-glucobioses, β-glucobioses and sucrose-based oligosaccharides, structures were identified that were not utilised by the common oral bacterium Streptococcus mutans, and would therefore contribute to the non-cariogenic potential of a sweetener. Analysis of the rate and products of digestion by a rat glucosidase mixture was used to determine the relative intestinal digestibility. The results showed that oligosaccharides containing a (1 → 6)-β-Glc group, including gentiobiose and gentiobiitol, together with melezitose, a sucrose-derived oligosaccharide containing a α-Glc-(1 → 3)-Fru moiety were resistant to digestion by both S. mutans and mammalian intestinal enzymes, highlighting their potential as dietary sugar substitutes.     

Estimating percent impervious cover from Landsat-based land cover with a simple and transferable regression model

Percent impervious cover (PIC) is a widely used metric in ecological and hydrological analyses because it is highly correlated with pollutant and storm water run-off. The moderate-resolution satellite data (e.g. Landsat), that are typically used to calculate PIC, tend to overestimate PIC for all but very rural and very urban landscapes. Existing models for calibrating PIC estimates (e.g. ISAT, ETIS) are limited in that they are applicable only for specific land cover datasets and may also require population data; furthermore, these models have not been tested for performance outside of the geographic locations in which they were developed. The goal of this study was to explore simple but widely applicable regression models as tools for calibrating PIC estimates based on moderate resolution satellite data. The regression models used impervious land cover, from Landsat-based datasets, as the sole predictor of actual PIC. PIC was calculated for analysis units, ranging in size from 2.25 ha to ≥100 ha, for locations in Connecticut, Massachusetts, and Ohio in the United States. Regression models were fit for each size class of analysis unit at each study location; generalized versions of the models were created by fitting a regression to all size classes of analysis units at a given study location. Calibrated PIC estimates had root mean square error (RMSE) values that ranged from 1.5–10.7%; these values were considerably better than RMSE values for uncalibrated PIC estimates which ranged from 10.1–23.3%. For both calibrated and uncalibrated PIC, the accuracy of the estimates improved with the increasing size of the analysis units. Model regression coefficients were similar regardless of the analysis unit size, geographic location, or land cover dataset; model performance declined only slightly when applied outside the area in which it was developed. The simple regression models developed in this study had similar performance to previous calibration models (i.e. ISAT, ETIS) but are easier to apply and more widely applicable.     

Complex and dynamic population structures: synthesis, open questions, and future directions

The population structure of an evolutionary algorithm influences the dissemination and mixing of advantageous alleles, and therefore affects search performance. Much recent attention has focused on the analysis of complex population structures, characterized by heterogeneous connectivity distributions, non-trivial clustering properties, and degree–degree correlations. Here, we synthesize the results of these recent studies, discuss their limitations, and highlight several open questions regarding (1) unsolved theoretical issues and (2) the practical utility of complex population structures for evolutionary search. In addition, we will discuss an alternative complex population structure that is known to significantly influence dynamical processes, but has yet to be explored for evolutionary optimization. We then shift our attention toward dynamic population structures, which have received markedly less attention than their static counterparts. We will discuss the strengths and limitations of extant techniques and present open theoretical and experimental questions and directions for future research. In particular, we will focus on the prospects of “active linking,” wherein edges are dynamically rewired according to the genotypic or phenotypic properties of individuals, or according to the success of prior inter-individual interactions.     

RB Regulates DNA Double Strand Break Repair Pathway Choice by Mediating CtIP Dependent End Resection

Inactivation of the retinoblastoma tumor suppressor gene (RB1) leads to genome instability, and can be detected in retinoblastoma and other cancers. One damaging effect is causing DNA double strand breaks (DSB), which, however, can be repaired by homologous recombination (HR), classical non-homologous end joining (C-NHEJ), and micro-homology mediated end joining (MMEJ). We aimed to study the mechanistic roles of RB in regulating multiple DSB repair pathways. Here we show that HR and C-NHEJ are decreased, but MMEJ is elevated in RB-depleted cells. After inducing DSB by camptothecin, RB co-localizes with CtIP, which regulates DSB end resection. RB depletion leads to less RPA and native BrdU foci, which implies less end resection. In RB-depleted cells, less CtIP foci, and a lack of phosphorylation on CtIP Thr847, are observed. According to the synthetic lethality principle, based on the altered DSB repair pathway choice, after inducing DSBs by camptothecin, RB depleted cells are more sensitive to co-treatment with camptothecin and MMEJ blocker poly-ADP ribose polymerase 1 (PARP1) inhibitor. We propose a model whereby RB can regulate DSB repair pathway choice by mediating the CtIP dependent DNA end resection. The use of PARP1 inhibitor could potentially improve treatment outcomes for RB-deficient cancers.