Inferring metabolic mechanisms of interaction within a defined gut microbiota

The diversity and number of species present within microbial communities create the potential for a multitude of interspecies metabolic interactions. Here, we develop, apply, and experimentally test a framework for inferring metabolic mechanisms associated with interspecies interactions. We perform pairwise growth and metabolome profiling of co-cultures of strains from a model mouse microbiota. We then apply our framework to dissect emergent metabolic behaviors that occur in co-culture. Based on one of the inferences from this framework, we identify and interrogate an amino acid cross-feeding interaction and validate that the proposed interaction leads to a growth benefit in vitro. Our results reveal the type and extent of emergent metabolic behavior in microbial communities composed of gut microbes. We focus on growth-modulating interactions, but the framework can be applied to interspecies interactions that modulate any phenotype of interest within microbial communities

Prediction of Mortality in Very Premature Infants: A Systematic Review of Prediction Models

CONTEXT Being born very preterm is associated with elevated risk for neonatal mortality. The aim of this review is to give an overview of prediction models for mortality in very premature infants, assess their quality, identify important predictor variables, and provide recommendations for development of future models. METHODS Studies were included which reported the predictive performance of a model for mortality in a very preterm or very low birth weight population, and classified as development, validation, or impact studies. For each development study, we recorded the population, variables, aim, predictive performance of the model, and the number of times each model had been validated. Reporting quality criteria and minimum methodological criteria were established and assessed for development studies. RESULTS We identified 41 development studies and 18 validation studies. In addition to gestational age and birth weight, eight variables frequently predicted survival: being of average size for gestational age, female gender, non-white ethnicity, absence of serious congenital malformations, use of antenatal steroids, higher 5-minute Apgar score, normal temperature on admission, and better respiratory status. Twelve studies met our methodological criteria, three of which have been externally validated. Low reporting scores were seen in reporting of performance measures, internal and external validation, and handling of missing data. CONCLUSIONS Multivariate models can predict mortality better than birth weight or gestational age alone in very preterm infants. There are validated prediction models for classification and case-mix adjustment. Additional research is needed in validation and impact studies of existing models, and in prediction of mortality in the clinically important subgroup of infants where age and weight alone give only an equivocal prognosis.Stephanie Medlock, Anita C. J. Ravelli, Pieter Tamminga, Ben W. M. Mol, Ameen Abu-Hann

Finite to infinite steady state solutions, bifurcations of an integro-differential equation

We consider a bistable integral equation which governs the stationary solutions of a convolution model of solid--solid phase transitions on a circle. We study the bifurcations of the set of the stationary solutions as the diffusion coefficient is varied to examine the transition from an infinite number of steady states to three for the continuum limit of the semi--discretised system. We show how the symmetry of the problem is responsible for the generation and stabilisation of equilibria and comment on the puzzling connection between continuity and stability that exists in this problem

Health effects of drought: a systematic review of the evidence

Introduction: Climate change projections indicate that droughts will become more intense in the 21 century in some areas of the world. The El Niño Southern Oscillation is associated with drought in some countries, and forecasts can provide advance warning of the increased risk of adverse climate conditions. The most recent available data from EMDAT estimates that over 50 million people globally were affected by drought in 2011. Documentation of the health effects of drought is difficult, given the complexity in assigning a beginning/end and because effects tend to accumulate over time. Most health impacts are indirect because of its link to other mediating circumstances like loss of livelihoods. Methods: The following databases were searched: MEDLINE; CINAHL; Embase; PsychINFO, Cochrane Collection. Key references from extracted papers were hand-searched, and advice from experts was sought for further sources of literature. Inclusion criteria for papers summarised in tables include: explicit link made between drought as exposure and human health outcomes; all study designs/methods; all countries/contexts; any year of publication. Exclusion criteria include: drought meaning shortage unrelated to climate; papers not published in English; studies on dry/arid climates unless drought was noted as an abnormal climatological event. No formal quality evaluation was used on papers meeting inclusion criteria. Results: 87 papers meeting the inclusion criteria are summarised in tables. Additionally, 59 papers not strictly meeting the inclusion criteria are used as supporting text in relevant parts of the results section. Main categories of findings include: nutrition-related effects (including general malnutrition and mortality, micronutrient malnutrition, and anti-nutrient consumption); water-related disease (including E coli, cholera and algal bloom); airborne and dust-related disease (including silo gas exposure and coccidioidomycosis); vector borne disease (including malaria, dengue and West Nile Virus); mental health effects (including distress and other emotional consequences); and other health effects (including wildfire, effects of migration, and damage to infrastructure). Conclusions: The probability of drought-related health impacts varies widely and largely depends upon drought severity, baseline population vulnerability, existing health and sanitation infrastructure, and available resources with which to mitigate impacts as they occur. The socio-economic environment in which drought occurs influences the resilience of the affected population. Forecasting can be used to provide advance warning of the increased risk of adverse climate conditions and can support the disaster risk reduction process. Despite the complexities involved in documentation, research should continue and results should be shared widely in an effort to strengthen drought preparedness and response activities

Evaluation of the vector competence of a native UK mosquito Ochlerotatus detritus (Aedes detritus) for dengue, chikungunya and West Nile viruses

BACKGROUND: To date there has been no evidence of mosquito-borne virus transmission of public health concern in the UK, despite the occurrence of more than 30 species of mosquito, including putative vectors of arboviruses. The saltmarsh mosquito Ochlerotatus detritus [syn. Aedes (Ochlerotatus) detritus] is locally common in parts of the UK where it can be a voracious feeder on people. METHODS: Here, we assess the competence of O. detritus for three major arboviruses: dengue virus (DENV), chikungunya virus (CHIKV) and West Nile virus (WNV) using adult mosquitoes reared from wild, field-obtained immatures. RESULTS: We demonstrate laboratory competence for WNV at 21 °C, with viral RNA detected in the mosquito’s saliva 17 days after oral inoculation. By contrast, there was no evidence of laboratory competence of O. detritus for either DENV or CHIKV. CONCLUSIONS: To our knowledge, this is the first study to demonstrate competence of a UK mosquito for WNV and confirms that O. detritus may present a potential risk for arbovirus transmission in the UK and that further investigation of its vector role in the wild is required

Mosquito Magnet ® traps as a potential means of monitoring blackflies of medical and veterinary importance

Mosquito Magnet® traps, deployed in widespread parts of England as part of nationwide mosquito surveillance projects, also caught blackflies. As many as 1242 blackflies were caught in a trapping session lasting 4 days. Principal among the species caught were Simulium equinum, Simulium lineatum and Simulium ornatum s.l. As S. ornatum s.l. is a vector that transmits Onchocerca linealis to cattle and S. equinum is responsible for dermatitis ('sweet itch') in cattle and horses, it is suggested that Mosquito Magnet® traps could be used to monitor and partially control these pests, as well as nuisance anthropophilic blackflies such as Simulium posticatum that can cause simuliidosis in southern England

Enhanced West Nile virus surveillance in the North Kent marshes, UK

Background As part of efforts to more fully understand the potential risks posed by West Nile virus (WNV) and Usutu virus (USUV) in the UK, and following on from previous reports of a potential bridge vector Culex modestus for these viruses, at wetland sites in North Kent, mosquito surveillance was undertaken more widely across the Isle of Sheppey, the Hoo Peninsula and the Kent mainland. Methods Larval surveys were conducted and Mosquito Magnet® adult traps were used to collect adult mosquitoes. Pools of female mosquitoes were tested for the presence of WNV using real-time reverse transcriptase polymerase chain reaction. A subset of samples was tested for USUV. Results Culex modestus was found in both the pre-imaginal and imago stage at all five locations surveyed, accounting for 90% of adult mosquitoes collected. WNV or USUV were not detected in any sample. Conclusions Although no mosquitoes have been shown to be virus positive, the field survey data from this study demonstrated the dominance of an important bridge vector species for WNV in this region. Its wide geographical distribution highlights the need to update risk assessments on WNV introduction, and to maintain vigilance for WNV in the South East of England

Discovery of a single male Aedes aegypti (L.) in Merseyside, England

© The Author(s). 2017. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. The file attached is the published (publishers PDF) version of the article

The passive surveillance of ticks using companion animal electronic health records

Ticks represent a large global reservoir of zoonotic disease. Current surveillance systems can be time and labour intensive. We propose that the passive surveillance of companion animal electronic health records (EHRs) could provide a novel methodology for describing temporal and spatial tick activity. A total of 16 58 857 EHRs were collected over a 2-year period (31 March 2014 and 29 May 2016) from companion animals attending a large sentinel network of 192 veterinary clinics across Great Britain (the Small Animal Veterinary Surveillance Network - SAVSNET). In total, 2180 EHRs were identified where a tick was recorded on an animal. The relative risk of dogs presenting with a tick compared with cats was 0·73 (95% confidence intervals 0·67-0·80). The highest number of tick records were in the south central regions of England. The presence of ticks showed marked seasonality with summer peaks, and a secondary smaller peak in autumn for cats; ticks were still being found throughout most of Great Britain during the winter. This suggests that passive surveillance of companion animal EHRs can describe tick activity temporally and spatially in a large cohort of veterinary clinics across Great Britain. These results and methodology could help inform veterinary and public health messages as well as increase awareness of ticks and tick-borne diseases in the general population

Bayesian Best-Arm Identification for Selecting Influenza Mitigation Strategies

Pandemic influenza has the epidemic potential to kill millions of people. While various preventive measures exist (i.a., vaccination and school closures), deciding on strategies that lead to their most effective and efficient use remains challenging. To this end, individual-based epidemiological models are essential to assist decision makers in determining the best strategy to curb epidemic spread. However, individual-based models are computationally intensive and it is therefore pivotal to identify the optimal strategy using a minimal amount of model evaluations. Additionally, as epidemiological modeling experiments need to be planned, a computational budget needs to be specified a priori. Consequently, we present a new sampling technique to optimize the evaluation of preventive strategies using fixed budget best-arm identification algorithms. We use epidemiological modeling theory to derive knowledge about the reward distribution which we exploit using Bayesian best-arm identification algorithms (i.e., Top-two Thompson sampling and BayesGap). We evaluate these algorithms in a realistic experimental setting and demonstrate that it is possible to identify the optimal strategy using only a limited number of model evaluations, i.e., 2-to-3 times faster compared to the uniform sampling method, the predominant technique used for epidemiological decision making in the literature. Finally, we contribute and evaluate a statistic for Top-two Thompson sampling to inform the decision makers about the confidence of an arm recommendation