138 research outputs found

    RNA interference of three up-regulated transcripts associated with insecticide resistance in an imidacloprid resistant population of Leptinotarsa decemlineata

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    AbstractThe Colorado potato beetle, Leptinotarsa decemlineata (Say), is a major agricultural pest of potatoes in the Central Sands production region of Wisconsin. Previous studies have shown that populations of L. decemlineata have become resistant to many classes of insecticides, including the neonicotinoid insecticide, imidacloprid. Furthermore, L. decemlineata has multiple mechanisms of resistance to deal with a pesticide insult, including enhanced metabolic detoxification by cytochrome p450s and glutathione S-transferases. With recent advances in the transcriptomic analysis of imidacloprid susceptible and resistant L. decemlineata populations, it is possible to investigate the role of candidate genes involved in imidacloprid resistance. A recently annotated transcriptome analysis of L. decemlineata was obtained from select populations of L. decemlineata collected in the Central Sands potato production region, which revealed a subset of mRNA transcripts constitutively up-regulated in resistant populations. We hypothesize that a portion of the up-regulated transcripts encoding for genes within the resistant populations also encode for pesticide resistance and can be suppressed to re-establish a susceptible phenotype. In this study, a discrete set of three up-regulated targets were selected for RNA interference experiments using a resistant L. decemlineata population. Following the successful suppression of transcripts encoding for a cytochrome p450, a cuticular protein, and a glutathione synthetase protein in a select L. decemlineata population, we observed reductions in measured resistance to imidacloprid that strongly suggest these genes control essential steps in imidacloprid metabolism in these field populations

    An Integrated Vehicle-Mounted Telemetry System for VHF Telemetry Applications

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    We designed and developed a vehicle-mounted very high frequency–based telemetry system that integrated an on-board antenna, receiver, electronic compass, Global Positioning System, computer, and Geographic Information System. The system allows users to accurately and quickly obtain fixes, estimate and confirm locations of radiomarked animals, and immediately record data into an electronic spreadsheet or database. The total cost of materials to build the system was $7,349 (United States currency). Mean error angle of 2.63 ± 12.18 (SD; range =-33.7–42.2°) and mean location error distance of 128 ± 91.3 m (SD; range = 0–408 m) suggested precision and accuracy of our system were comparable to other reported systems. Mean time to record 5 bearings/test transmitter was 6.28 ± 0.24 minutes (SE), which is the most efficient system reported to locate animals in the field. Vehicle-mounted telemetry systems like ours provide additional value to studies that involve tracking highly mobile species because investigators need not take bearings from established receiving stations and because investigators can immediately recognize bounced signals and take additional bearings and optimize accuracy of location estimates

    Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review

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    Background: Tuberculosis (TB) transmission often occurs within a household or community, leading to heterogeneous spatial patterns. However, apparent spatial clustering of TB could reflect ongoing transmission or co-location of risk factors and can vary considerably depending on the type of data available, the analysis methods employed and the dynamics of the underlying population. Thus, we aimed to review methodological approaches used in the spatial analysis of TB burden. Methods: We conducted a systematic literature search of spatial studies of TB published in English using Medline, Embase, PsycInfo, Scopus and Web of Science databases with no date restriction from inception to 15 February 2017. The protocol for this systematic review was prospectively registered with PROSPERO (CRD42016036655). Results: We identified 168 eligible studies with spatial methods used to describe the spatial distribution (n = 154), spatial clusters (n = 73), predictors of spatial patterns (n = 64), the role of congregate settings (n = 3) and the household (n = 2) on TB transmission. Molecular techniques combined with geospatial methods were used by 25 studies to compare the role of transmission to reactivation as a driver of TB spatial distribution, finding that geospatial hotspots are not necessarily areas of recent transmission. Almost all studies used notification data for spatial analysis (161 of 168), although none accounted for undetected cases. The most common data visualisation technique was notification rate mapping, and the use of smoothing techniques was uncommon. Spatial clusters were identified using a range of methods, with the most commonly employed being Kulldorff's spatial scan statistic followed by local Moran's I and Getis and Ord's local Gi(d) tests. In the 11 papers that compared two such methods using a single dataset, the clustering patterns identified were often inconsistent. Classical regression models that did not account for spatial dependence were commonly used to predict spatial TB risk. In all included studies, TB showed a heterogeneous spatial pattern at each geographic resolution level examined. Conclusions: A range of spatial analysis methodologies has been employed in divergent contexts, with all studies demonstrating significant heterogeneity in spatial TB distribution. Future studies are needed to define the optimal method for each context and should account for unreported cases when using notification data where possible. Future studies combining genotypic and geospatial techniques with epidemiologically linked cases have the potential to provide further insights and improve TB control

    Comorbidities, exposure to medications, and the risk of community-acquired clostridium difficile infection: a systematic review and meta-analysis

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    Background. Clostridium difficile infection (CDI) has been extensively escribedin healthcare settings; however, risk factor sassociated with community-acquired (CA) CDI remain uncertain. This study aimed to synthesize the current evidence for an association between commonly prescribed medications and comorbidities with CA-CDI. methods. A systematic search was conducted in 5 electronic databases for epidemiologicstudi esthatexamined the associtation between the presence of comorbidities and exposure to medications with the risk of CA-CDI. Pooled odds ratios were estimated using 3 meta-analytic methods. Subgroup analyses by location of studies and by life stages were conducted. results. Twelve publications (n=56,776 patients) met inclusion criteria. Antimicrobial (odds ratio, 6.18; 95% CI, 3.80-10.04) and corticosteroid (1.81; 1.15-2.84) exposure were associated with increased risk of CA-CDI. Among the comorbidities, inflammatory bowel disease (odds ratio, 3.72; 95% CI, 1.52-9.12), renal failure (2.64; 1.23-5.68), hematologic cancer (1.75; 1.02-5.68), and diabetes mellitus (1.15; 1.05-1.27) were associated with CA-CDI. By location, antimicrobial exposure was associated with a higher risk of CA-CDI in the United States, whereas proton-pump inhibitor exposure was associated with a higher risk in Europe. By life stages, the risk of CA-CDI associated with antimicrobial exposure greatly increased in adults older than 65 years. conclusions. Antimicrobial exposure was the strongest risk factor associated with CA-CDI. Further studies are required to investigate the risk of CA-CDI associated with medications commonly prescribed in the community. Patients with diarrhea who have inflammatory bowel disease, renal failure, hematologic cancer, or diabetes are appropriate populations for interventional studies of screening

    Comparative effectiveness of malaria prevention measures: a systematic review and network meta-analysis.

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    Malaria causes significant morbidity and mortality worldwide. There are several preventive measures that are currently employed, including insecticide-treated nets (ITNs, including long-lasting insecticidal nets and insecticidal-treated bed nets), indoor residual spraying (IRS), prophylactic drugs (PD), and untreated nets (UN). However, it is unclear which measure is the most effective for malaria prevention. We therefore undertook a network meta-analysis to compare the efficacy of different preventive measures on incidence of malaria infection. A systematic literature review was undertaken across four medical and life sciences databases (PubMed, Cochrane Central, Embase, and Web of Science) from their inception to July 2016 to compare the effectiveness of different preventive measures on malaria incidence. Data from the included studies were analysed for the effectiveness of several measures against no intervention (NI). This was carried out using an automated generalized pairwise modeling (GPM) framework for network meta-analysis to generate mixed treatment effects against a common comparator of no intervention (NI). There were 30 studies that met the inclusion criteria from 1998-2016. The GPM framework led to a final ranking of effectiveness of measures in the following order from best to worst: PD, ITN, IRS and UN, in comparison with NI. However, only ITN (RR: 0.49, 95% CI: 0.32-0.74) showed precision while other methods [PD (RR: 0.24, 95% CI: 0.004-15.43), IRS (RR: 0.55, 95% CI: 0.20-1.56) and UN (RR: 0.73, 95% CI: 0.28-1.90)] demonstrating considerable uncertainty associated with their point estimates. Current evidence is strong for the protective effect of ITN interventions in malaria prevention. Even though ITNs were found to be the only preventive measure with statistical support for their effectiveness, the role of other malaria control measures may be important adjuncts in the global drive to eliminate malaria

    Probabilistic movement model with emigration simulates movements of deer in Nebraska, 1990–2006

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    Movements of deer can affect population dynamics, spatial redistribution, and transmission and spread of diseases. Our goal was to model the movement of deer in Nebraska in an attempt to predict the potential for spread of chronic wasting disease (CWD) into eastern Nebraska. We collared and radio-tracked \u3e600 white-tailed deer (Odocoileus virginianus) and mule deer (Odocoileus hemionus) in Nebraska during 1990–2006.We observed large displacements (\u3e10 km) for both species and sexes of deer, including migrations up to 100 km and dispersals up to 50 km. Average distance traveled between successive daily locations was 166m for male and 173 for female deer in eastern Nebraska, and 427m for male and 459 for female deer in western Nebraska. Average daily displacement from initial capture point was 10m for male and 14m for female deer in eastern Nebraska, and 27m for male and 28m for female deer in western Nebraska.We used these data on naturally occurring movements to create and test 6 individual-based models of movement for white-tailed deer and mule deer in Nebraska, including models that incorporated sampling from empirical distributions of movement lengths and turn angles (DIST), correlated random walks (CRW), home point fidelity (FOCUS), shifting home point (SHIFT), probabilistic movement acceptance (MOVE), and probabilistic movement with emigration (MOVEwEMI). We created models in sequence in an attempt to account for the shortcomings of the previous model(s). We used the Kolmogrov–Smirnov goodness-of-fit test to verify improvement of simulated annual displacement distributions to empirical displacement distributions. The best-fit model (D = 0.07 and 0.08 for eastern and western Nebraska, respectively) included a probabilistic-movement chance with emigration (MOVEwEMI) and resulted in an optimal daily movement length of 350m (maximum daily movement length of 2800m for emigrators) for eastern Nebraska and 370m (maximum of 2960m) for western Nebraska. The proportion of deer that moved as emigrators was 0.10 and 0.13 for eastern and western Nebraska, respectively. We propose that the observed spread of CWD may be driven by large movements of a small proportion of deer that help to establish a low prevalence of the disease in areas east of the current endemic area. Our movement models will be used in a larger individual-based simulation of movement, survival, and transmission of CWD to help determine future surveillance and management actions

    Invasive annual grasses—Reenvisioning approaches in a changing climate

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    For nearly a century, invasive annual grasses have increasingly impacted terrestrial ecosystems across the western United States. Weather variability associated with climate change and increased atmospheric carbon dioxide (CO2) are making even more difficult the challenges of managing invasive annual grasses. As part of a special issue on climate change impacts on soil and water conservation, the topic of invasive annual grasses is being addressed by scientists at the USDA Agricultural Research Service to emphasize the need for additional research and future studies that build on current knowledge and account for (extreme) changes in abiotic and biotic conditions. Much research has focused on understanding the mechanisms underlying annual grass invasion, as well as assessing patterns and responses from a wide range of disturbances and management approaches. Weather extremes and the increasing occurrences of wildfire are contributing to the complexity of the problem. In broad terms, invasive annual grass management, including restoration, must be proactive to consider human values and ecosystem resiliency. Models capable of synthesizing vast amounts of diverse information are necessary for creating trajectories that could result in the establishment of perennial systems. Organization and collaboration are needed across the research community and with land managers to strategically develop and implement practices that limit invasive annual grasses. In the future, research will need to address invasive annual grasses in an adaptive integrated weed management (AIWM) framework that utilizes models and accounts for climate change that is resulting in altered/new approaches to management and restoration

    Regional Endothermy in a Coral Reef Fish?

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    Although a few pelagic species exhibit regional endothermy, most fish are regarded as ectotherms. However, we document significant regional endothermy in a benthic reef fish. Individual steephead parrotfish, Chlorurus microrhinos (Labridae, formerly Scaridae) were tagged and their internal temperatures were monitored for a 24 h period using active acoustic telemetry. At night, on the reef, C. microrhinos were found to maintain a consistent average peritoneal cavity temperature 0.16±0.005°C (SE) warmer than ambient. Diurnal internal temperatures were highly variable for individuals monitored on the reef, while in tank-based trials, peritoneal cavity temperatures tracked environmental temperatures. The mechanisms responsible for a departure of the peritoneal cavity temperature from environmental temperature occurred in C. microrhinos are not yet understood. However, the diet and behavior of the species suggests that heat in the peritoneal cavity may result primarily from endogenous thermogenesis coupled with physiological heat retention mechanisms. The presence of limited endothermy in C. microrhinos indicates that a degree of uncertainty may exist in the manner that reef fish respond to their thermal environment. At the very least, they do not always appear to respond to environmental temperatures as neutral thermal vessels and do display limited, but significant, visceral warming
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