Cooperative secretions facilitate host range expansion in bacteria

The majority of emergent human pathogens are zoonotic in origin, that is, they can transmit to humans from other animals. Understanding the factors underlying the evolution of pathogen host range is therefore of critical importance in protecting human health. There are two main evolutionary routes to generalism: organisms can tolerate multiple environments or they can modify their environments to forms to which they are adapted. Here we use a combination of theory and a phylogenetic comparative analysis of 191 pathogenic bacterial species to show that bacteria use cooperative secretions that modify their environment to extend their host range and infect multiple host species. Our results suggest that cooperative secretions are key determinants of host range in bacteria, and that monitoring for the acquisition of secreted proteins by horizontal gene transfer can help predict emerging zoonoses

Polynomial diffeomorphisms of C^2, IV: The measure of maximal entropy and laminar currents

This paper concerns the dynamics of polynomial automorphisms of ${\bf C}^2$. One can associate to such an automorphism two currents $\mu^\pm$ and the equilibrium measure $\mu=\mu^+\wedge\mu^-$. In this paper we study some geometric and dynamical properties of these objects. First, we characterize $\mu$ as the unique measure of maximal entropy. Then we show that the measure $\mu$ has a local product structure and that the currents $\mu^\pm$ have a laminar structure. This allows us to deduce information about periodic points and heteroclinic intersections. For example, we prove that the support of $\mu$ coincides with the closure of the set of saddle points. The methods used combine the pluripotential theory with the theory of non-uniformly hyperbolic dynamical systems

The Cost of Simplifying Air Travel When Modeling Disease Spread

BACKGROUND: Air travel plays a key role in the spread of many pathogens. Modeling the long distance spread of infectious disease in these cases requires an air travel model. Highly detailed air transportation models can be over determined and computationally problematic. We compared the predictions of a simplified air transport model with those of a model of all routes and assessed the impact of differences on models of infectious disease. METHODOLOGY/PRINCIPAL FINDINGS: Using U.S. ticket data from 2007, we compared a simplified "pipe" model, in which individuals flow in and out of the air transport system based on the number of arrivals and departures from a given airport, to a fully saturated model where all routes are modeled individually. We also compared the pipe model to a "gravity" model where the probability of travel is scaled by physical distance; the gravity model did not differ significantly from the pipe model. The pipe model roughly approximated actual air travel, but tended to overestimate the number of trips between small airports and underestimate travel between major east and west coast airports. For most routes, the maximum number of false (or missed) introductions of disease is small (<1 per day) but for a few routes this rate is greatly underestimated by the pipe model. CONCLUSIONS/SIGNIFICANCE: If our interest is in large scale regional and national effects of disease, the simplified pipe model may be adequate. If we are interested in specific effects of interventions on particular air routes or the time for the disease to reach a particular location, a more complex point-to-point model will be more accurate. For many problems a hybrid model that independently models some frequently traveled routes may be the best choice. Regardless of the model used, the effect of simplifications and sensitivity to errors in parameter estimation should be analyzed

Induction of lung lesions in Wistar rats by 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone and its inhibition by aspirin and phenethyl isothiocyanate

<p>Abstract</p> <p>Background</p> <p>The development of effective chemopreventive agents against cigarette smoke-induced lung cancer could be greatly facilitated by suitable laboratory animal models, such as animals treated with the tobacco-specific lung carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). In the current study, we established a novel lung cancer model in Wistar rats treated with NNK. Using this model, we assessed the effects of two chemopreventive agents, aspirin and phenethyl isothiocyanate (PEITC), on tumor progression.</p> <p>Methods</p> <p>First, rats were treated with a single-dose of NNK by intratracheal instillation; control rats received iodized oil. The animals were then sacrificed on the indicated day after drug administration and examined for tumors in the target organs. PCNA, p63 and COX-2 expression were analyzed in the preneoplastic lung lesions. Second, rats were treated with a single-dose of NNK (25 mg/kg body weight) in the absence or presence of aspirin and/or PEITC in the daily diet. The control group received only the vehicle in the regular diet. The animals were sacrificed on day 91 after bronchial instillation of NNK. Lungs were collected and processed for histopathological and immunohistochemical assays.</p> <p>Results</p> <p>NNK induced preneoplastic lesions in lungs, including 33.3% alveolar hyperplasia and 55.6% alveolar atypical dysplasia. COX-2 expression increased similarly in alveolar hyperplasia and alveolar atypical dysplasia, while PCNA expression increased more significantly in the latter than the former. No p63 expression was detected in the preneoplastic lesions. In the second study, the incidences of alveolar atypical dysplasia were reduced to 10%, 10% and 0%, respectively, in the aspirin, PEITC and aspirin and PEITC groups, compared with 62.5% in the carcinogen-treated control group. COX-2 expression decreased after dietary aspirin or aspirin and PEITC treatment. PCNA expression was significantly reduced in the aspirin and PEITC group.</p> <p>Conclusion</p> <p>(1) A single dose of 25 mg/kg body weight NNK by intratracheal instillation is sufficient to induce preneoplastic lesions in Wistar rat lungs. (2) COX-2 takes part in NNK-induced tumorigenesis but is not involved in proliferation. (3) Aspirin and PEITC have protective effects in the early stages of tumor progression initiated by NNK.</p

Smoking and drinking in relation to oral potentially malignant disorders in Puerto Rico: a case-control study

<p>Abstract</p> <p>Background</p> <p>Oral cancer incidence is high on the Island of Puerto Rico (PR), particularly among males. As part of a larger study conducted in PR, we evaluated smoking and drinking as risk factors for oral potentially malignant disorders (OPMDs).</p> <p>Methods</p> <p>Persons diagnosed with either an OPMD (n = 86) [oral epithelial dysplasia (OED), oral hyperkeratosis/epithelial hyperplasia without OED] or a benign oral tissue condition (n = 155) were identified through PR pathology laboratories. Subjects were interviewed using a standardized, structured questionnaire that obtained information, including detailed histories of smoking and drinking. Odds ratios (ORs) for smoking and drinking in relation to having an OPMD, relative to persons with a benign oral tissue condition, were obtained using logistic regression and adjusted for age, gender, education, fruit/vegetable intake and smoking or drinking.</p> <p>Results</p> <p>For persons with an OPMD and relative to individuals with a benign oral tissue condition, the adjusted OR for current smoking was 4.32 (95% CI: 1.99-9.38), while for former smokers, the OR_adjwas 1.47 (95% CI: 0.67-3.21), each OR_adjrelative to never smokers. With regard to drinking, no adjusted ORs approached statistical significance, and few point estimates exceeded 1.0, whether consumption was defined in terms of ever, current, level (drinks/week), or beverage type.</p> <p>Conclusions</p> <p>In this study, conducted in Puerto Rico, current smoking was a substantial risk factor for OPMDs while former smokers had a considerably reduced risk compared to current smokers. There was little evidence suggesting that alcohol consumption was positively associated with OPMD risk.</p

Effect of Biodiversity Changes in Disease Risk: Exploring Disease Emergence in a Plant-Virus System

The effect of biodiversity on the ability of parasites to infect their host and cause disease (i.e. disease risk) is a major question in pathology, which is central to understand the emergence of infectious diseases, and to develop strategies for their management. Two hypotheses, which can be considered as extremes of a continuum, relate biodiversity to disease risk: One states that biodiversity is positively correlated with disease risk (Amplification Effect), and the second predicts a negative correlation between biodiversity and disease risk (Dilution Effect). Which of them applies better to different host-parasite systems is still a source of debate, due to limited experimental or empirical data. This is especially the case for viral diseases of plants. To address this subject, we have monitored for three years the prevalence of several viruses, and virus-associated symptoms, in populations of wild pepper (chiltepin) under different levels of human management. For each population, we also measured the habitat species diversity, host plant genetic diversity and host plant density. Results indicate that disease and infection risk increased with the level of human management, which was associated with decreased species diversity and host genetic diversity, and with increased host plant density. Importantly, species diversity of the habitat was the primary predictor of disease risk for wild chiltepin populations. This changed in managed populations where host genetic diversity was the primary predictor. Host density was generally a poorer predictor of disease and infection risk. These results support the dilution effect hypothesis, and underline the relevance of different ecological factors in determining disease/infection risk in host plant populations under different levels of anthropic influence. These results are relevant for managing plant diseases and for establishing conservation policies for endangered plant species

Financial considerations in the conduct of multi-centre randomised controlled trials: evidence from a qualitative study.

National Coordinating Centre for Research Methodology; Medical Research Council, UK Department of Health; Chief Scientist OfficeNot peer reviewedPublisher PD

Phenethyl isothiocyanate exhibits antileukemic activity in vitro and in vivo by inactivation of Akt and activation of JNK pathways

Effects of phenethyl isothiocyanate (PEITC) have been investigated in human leukemia cells (U937, Jurkat, and HL-60) as well as in primary human acute myeloid leukemia (AML) cells in relation to apoptosis and cell signaling events. Exposure of cells to PEITC resulted in pronounced increase in the activation of caspase-3, -8, -9, cleavage/degradation of PARP, and apoptosis in dose- and time-dependent manners. These events were accompanied by the caspase-independent downregulation of Mcl-1, inactivation of Akt, as well as activation of Jun N-terminal kinase (JNK). Inhibition of PI3K/Akt by LY294002 significantly enhanced PEITC-induced apoptosis. Conversely, enforced activation of Akt by a constitutively active Akt construct markedly abrogated PEITC-mediated JNK activation, Mcl-1 downregulation, caspase activation, and apoptosis, and also interruption of the JNK pathway by pharmacological or genetically (e.g., siRNA) attenuated PEITC-induced apoptosis. Finally, administration of PEITC markedly inhibited tumor growth and induced apoptosis in U937 xenograft model in association with inactivation of Akt, activation of JNK, as well as downregulation of Mcl-1. Taken together, these findings represent a novel mechanism by which agents targeting Akt/JNK/Mcl-1 pathway potentiate PEITC lethality in transformed and primary human leukemia cells and inhibitory activity of tumor growth of U937 xenograft model

Time series modeling for syndromic surveillance

BACKGROUND: Emergency department (ED) based syndromic surveillance systems identify abnormally high visit rates that may be an early signal of a bioterrorist attack. For example, an anthrax outbreak might first be detectable as an unusual increase in the number of patients reporting to the ED with respiratory symptoms. Reliably identifying these abnormal visit patterns requires a good understanding of the normal patterns of healthcare usage. Unfortunately, systematic methods for determining the expected number of (ED) visits on a particular day have not yet been well established. We present here a generalized methodology for developing models of expected ED visit rates. METHODS: Using time-series methods, we developed robust models of ED utilization for the purpose of defining expected visit rates. The models were based on nearly a decade of historical data at a major metropolitan academic, tertiary care pediatric emergency department. The historical data were fit using trimmed-mean seasonal models, and additional models were fit with autoregressive integrated moving average (ARIMA) residuals to account for recent trends in the data. The detection capabilities of the model were tested with simulated outbreaks. RESULTS: Models were built both for overall visits and for respiratory-related visits, classified according to the chief complaint recorded at the beginning of each visit. The mean absolute percentage error of the ARIMA models was 9.37% for overall visits and 27.54% for respiratory visits. A simple detection system based on the ARIMA model of overall visits was able to detect 7-day-long simulated outbreaks of 30 visits per day with 100% sensitivity and 97% specificity. Sensitivity decreased with outbreak size, dropping to 94% for outbreaks of 20 visits per day, and 57% for 10 visits per day, all while maintaining a 97% benchmark specificity. CONCLUSIONS: Time series methods applied to historical ED utilization data are an important tool for syndromic surveillance. Accurate forecasting of emergency department total utilization as well as the rates of particular syndromes is possible. The multiple models in the system account for both long-term and recent trends, and an integrated alarms strategy combining these two perspectives may provide a more complete picture to public health authorities. The systematic methodology described here can be generalized to other healthcare settings to develop automated surveillance systems capable of detecting anomalies in disease patterns and healthcare utilization