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Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation of factors that may influence performance of such models, how they might apply to and vary across clinical populations, and what the implications might be in the clinical setting. Here, we performed a meta-analysis of seven large Neisseria gonorrhoeae datasets, as well as Klebsiella pneumoniae and Acinetobacter baumannii datasets, with whole genome sequence data and antibiotic susceptibility phenotypes using set covering machine classification, random forest classification, and random forest regression models to predict resistance phenotypes from genotype. We demonstrate how model performance varies by drug, dataset, resistance metric, and species, reflecting the complexities of generating clinically relevant conclusions from machine learning-derived models. Our findings underscore the importance of incorporating relevant biological and epidemiological knowledge into model design and assessment and suggest that doing so can inform tailored modeling for individual drugs, pathogens, and clinical populations. We further suggest that continued comprehensive sampling and incorporation of up-to-date whole genome sequence data, resistance phenotypes, and treatment outcome data into model training will be crucial to the clinical utility and sustainability of machine learning-based molecular diagnostics. [ABSTRACT FROM AUTHOR]

It is estimated that approximately 24% of the US population has at least one tattoo. However, tattoo ink ingredients include heavy metals (high atomic number Z) that are not regulated, which can cause skin reactions. This study investigates the dosimetric effects in surface dose due to high-Z elements in tattoo ink under electron beam irradiation. Four commercially available tattoo ink colors, black, red, yellow, and blue were chosen. The elemental composition of the tattoo ink samples was analyzed using X-ray Fluorescence (XRF). An ultrathin-window parallel plate ion chamber was used to measure the surface dose perturbation (ratio of ionizations with and without tattoo ink) for 6 − 20 MeV electron beams. The elemental concentration in the tattoo ink samples showed high-Z elements, with Z ranging from 11 to 92. The dose perturbation ranged from 1.4% up to 6% for the yellow ink for the 6 MeV electron beam, with similar values across the rest of the electron energies, whereas the black, red, and blue inks presented up to 3% dose perturbation for the same range of energies. Based on this initial study, we conclude that commercially available tattoo inks contain large amounts of high-Z metals that may contribute to dose perturbation. Therefore treatment of superficial lesions with electron beams in a tattooed area should be monitored for signs of early skin reaction during radiation therapy treatments. [ABSTRACT FROM AUTHOR]

Estimation of influenza-like illness (ILI) using search trends activity was intended to supplement traditional surveillance systems, and was a motivation behind the development of Google Flu Trends (GFT). However, several studies have previously reported large errors in GFT estimates of ILI in the US. Following recent release of time-stamped surveillance data, which better reflects real-time operational scenarios, we reanalyzed GFT errors. Using three data sources—GFT: an archive of weekly ILI estimates from Google Flu Trends; ILIf: fully-observed ILI rates from ILINet; and, ILIp: ILI rates available in real-time based on partial reporting—five influenza seasons were analyzed and mean square errors (MSE) of GFT and ILIp as estimates of ILIf were computed. To correct GFT errors, a random forest regression model was built with ILI and GFT rates from the previous three weeks as predictors. An overall reduction in error of 44% was observed and the errors of the corrected GFT are lower than those of ILIp. An 80% reduction in error during 2012/13, when GFT had large errors, shows that extreme failures of GFT could have been avoided. Using autoregressive integrated moving average (ARIMA) models, one- to four-week ahead forecasts were generated with two separate data streams: ILIp alone, and with both ILIp and corrected GFT. At all forecast targets and seasons, and for all but two regions, inclusion of GFT lowered MSE. Results from two alternative error measures, mean absolute error and mean absolute proportional error, were largely consistent with results from MSE. Taken together these findings provide an error profile of GFT in the US, establish strong evidence for the adoption of search trends based 'nowcasts' in influenza forecast systems, and encourage reevaluation of the utility of this data source in diverse domains. [ABSTRACT FROM AUTHOR]

The Medical Monitoring Project (MMP) is an HIV surveillance system that provides national estimates of HIV-related behaviors and clinical outcomes. When first implemented, MMP excluded persons living with HIV not receiving HIV care. This analysis will describe new case-surveillance-based methods to identify and recruit persons living with HIV who are out of care and at elevated risk for mortality and ongoing HIV transmission. Stratified random samples of all persons living with HIV were selected from the National HIV Surveillance System in five public health jurisdictions from 2012–2014. Sampled persons were located and contacted through seven different data sources and five methods of contact to collect interviews and medical record abstractions. Data were weighted for non-response and case reporting delay. The modified sampling methodology yielded 1159 interviews (adjusted response rate, 44.5%) and matching medical record abstractions for 1087 (93.8%). Of persons with both interview and medical record data, 264 (24.3%) would not have been included using prior MMP methods. Significant predictors were identified for successful contact (e.g., retention in care, adjusted Odds Ratio [aOR] 5.02; 95% Confidence Interval [CI] 1.98–12.73), interview (e.g. moving out of jurisdiction, aOR 0.24; 95% CI: 0.12–0.46) and case reporting delay (e.g. rural residence, aOR 3.18; 95% CI: 2.09–4.85). Case-surveillance-based sampling resulted in a comparable response rate to existing MMP methods while providing information on an important new population. These methods have since been adopted by the nationally representative MMP surveillance system, offering a model for public health program, research and surveillance endeavors seeking inclusion of all persons living with HIV. [ABSTRACT FROM AUTHOR]

Downscaled climate projections need to be linked to downscaled projections of population and economic growth to fully develop implications for land, natural resources, and ecosystems for future scenarios. We develop an empirical spatiotemporal approach for jointly projecting population and income at the county scale in the United States that is consistent with neoclassical economic growth theory and overlapping labor markets and that accounts for labor migration and spatial spillovers. Downscaled projections generated for the five Shared Socioeconomic Pathways used to support global scenario analysis generally show growth focused around relatively few centers especially in the southeast and western regions, with some areas in the Midwest and northeast experiencing population declines. Results are consistent with economic growth theory and with historical trends in population change and convergence of per capita personal income across US counties. [ABSTRACT FROM AUTHOR]

Residential segregation into spatial neighborhoods and boroughs is a well-known spatial dynamic process that characterise complex urban environments. Existing models of segregation, including the pioneering Schelling ones, often do not consider all the factors that can contribute to this process. Segregation as well as aggregation emerges from local interactions among individuals, and is rooted in the complexity of social, economic and environmental interactions. The main objective of this study is to develop and implement a geospatial agent-based model to simulate the decision-making process of location of new household for incoming immigrant populations. Particularly this study aims to simulate and analyse the dynamics of the new immigrant populations arriving in the bilingual cities and boroughs of the island of Montreal. The model was implemented in NetLogo software, using real geospatial datasets. The obtained simulation results indicate realistic spatial patterns of spatial composition of the ethnographic fabric on the island of Montreal. The proposed model has the potential to be used as part of the city planning purposes. [ABSTRACT FROM AUTHOR]

Coffee berry borer (CBB, Hypothenemus hampei) (Coleoptera: Curculionidae: Scolytinae) is the most destructive pest of coffee worldwide. Information on CBB development times can be used to predict the initiation of new infestation cycles early in the coffee-growing season and thus inform the timing of insecticide applications. While laboratory estimates of CBB development under constant conditions exist, they have not been applied under the heterogeneous environmental conditions that characterize many coffee-growing regions. We measured CBB development times and abundance in commercial coffee farms across an elevational gradient on Hawai‘i Island and applied thermal accumulation models from previous laboratory studies to test their fit to field data. Artificial lures were used to infest coffee berries at five farms ranging in elevation from 279–792 m, and weather variables were monitored at macro (farm-level) and micro (branch-level) scales. CBB development was followed in the field from the time of initial berry infestation by the founding female through the development of F1 mature adults. Mean development time from egg to adult across all sites was 38.5 ± 3.46 days, while the mean time required for the completion of a full life cycle (from time of infestation to presence of mature F1 females) was 50.9 ± 3.35 days. Development time increased with increasing elevation and decreasing temperature. Using macro-scale temperature data and two different estimates for the lower temperature threshold (14.9°C and 13.9°C), we estimated a mean requirement of 332 ± 14 degree-days and 386 ± 16 degree-days, respectively, from the time of berry infestation to the initiation of a new reproductive cycle in mature coffee berries. Similar estimates were obtained using micro-scale temperature data, indicating that macro-scale temperature monitoring is sufficient for life-cycle prediction. We also present a model relating elevation to number of CBB generations per month. Our findings suggest that CBB development times from laboratory studies are generally applicable to field conditions on Hawai‘i Island and can be used as a decision support tool to improve IPM strategies for this worldwide pest of coffee. [ABSTRACT FROM AUTHOR]

Objective: To investigate the accuracy and precision of ultrasound shear wave elasticity measurements as a function of target elasticity and acquisition depth. Materials and methods: Using five ultrasound systems (VTQ, VTIQ, EPIQ 5, Aixplorer, and Aplio 500), two operators independently measured shear wave elasticities in two phantoms containing five different target elasticities (8±3, 14±4, 25±6, 45±8, and 80±12 kPa) at depths of 15, 30, 35, and 60 mm. Accuracy was assessed by evaluating measurement errors and the proportions of outliers, while factors affecting accuracy were assessed using logistic regression analysis. Measurement errors were defined as differences between the measured values and 1) the margins of the target elasticity, and 2) the median values of the target elasticity. Outliers were defined as measured values outside the margins of the target elasticity. Precision was assessed by calculating the reproducibility of measurements using the within-subject coefficient of variation (wCV). Results: Mean measurement errors and the proportions of outliers were higher for high than for low target elasticities (p<0.001), but did not differ in relation to acquisition depth, either within an elastography system or across the different systems. Logistic regression analysis showed that target elasticity (p<0.001) significantly affected accuracy, whereas acquisition depth (p>0.05) did not. The wCV for the 80±12 kPa target (31.33%) was significantly higher than that for lower elasticity targets (6.96–10.43 kPa; p<0.001). The wCV did not differ across acquisition depths. The individual elastography systems showed consistent results. Conclusions: Targets with high elasticity showed lower accuracy and lower precision than targets with low elasticity, while acquisition depth did not show consistent patterns in either accuracy or precision. [ABSTRACT FROM AUTHOR]

Several studies have shown that the performance of a supply chain is heavily influenced by the pattern of relationships among firms. This paper analyzes the structure of relationships (network topology) that leads to the highest agility of a food supply chain when sudden demand changes occur. To do this, a simulation model that represents a supply chain and specific rules to allocate orders is built. The supply chain in the model follows the specific characteristics of trade in the primary sector. The model is fitted to the conditions of a real seafood supply chain in Mexico. Agility is measured through the effect on the order fulfillment of a sudden demand shock and the recovery time of this rate to previous values. The simulation results show that the most suitable structure depends on how product is distributed among suppliers. If product is evenly shared, supply chains with homogeneous topologies are more agile than supply chains with heterogeneous topologies, but the result is the opposite if product is unevenly shared among suppliers. Other previous recommendations, such as having multiple suppliers and horizontal links, are confirmed by the simulations. These findings contribute to the general debate on which is the optimal topology for an agile supply chain. [ABSTRACT FROM AUTHOR]

Linden (Tilia spp.), a profusely flowering temperate tree that provides bees with vital pollen and nectar, has been associated with bumble bee (Bombus spp.) mortality in Europe and North America. Bee deaths have been attributed, with inadequate evidence, to toxicity from mannose in nectar or starvation due to low nectar in late blooming linden. Here, we investigated both factors via untargeted metabolomic analyses of nectar from five T. cordata trees beneath which crawling/dead bumble bees (B. vosnesenskii) were observed, and of thoracic muscle of 28 healthy foraging and 29 crawling bees collected from linden trees on cool mornings (< 30°C). Nectar contained the pyridine alkaloid trigonelline, a weak acetylcholinesterase inhibitor, but no mannose. Principal component analysis of muscle metabolites produced distinct clustering of healthy and crawling bees, with significant differences (P<0.05) in 34 of 123 identified metabolites. Of these, TCA (Krebs) cycle intermediates were strongly represented (pathway analysis; P<0.01), suggesting that the central metabolism is affected in crawling bees. Hence, we propose the following explanation: when ambient temperature is low, bees with energy deficit are unable to maintain the thoracic temperature required for flight, and consequently fall, crawl, and ultimately, die. Energy deficit could occur when bees continue to forage on linden despite limited nectar availability either due to loyalty to a previously energy-rich source or trigonelline-triggered memory/learning impairment, documented earlier with other alkaloids. Thus, the combination of low temperature and nectar volume, resource fidelity, and alkaloids in nectar could explain the unique phenomenon of bumble bee mortality associated with linden. [ABSTRACT FROM AUTHOR]

A real-time understanding of the distribution and duration of power outages after a major disaster is a precursor to minimizing their harmful consequences. Here, we develop an approach for using daily satellite nighttime lights data to create spatially disaggregated power outage estimates, tracking electricity restoration efforts after disasters strike. In contrast to existing utility data, these estimates are independent, open, and publicly-available, consistently measured across regions that may be serviced by several different power companies, and inclusive of distributed power supply (off-grid systems). We apply the methodology in Puerto Rico following Hurricane Maria, which caused the longest blackout in US history. Within all of the island’s settlements, we track outages and recovery times, and link these measures to census-based demographic characteristics of residents. Our results show an 80% decrease in lights, in total, immediately after Hurricane Maria. During the recovery, a disproportionate share of long-duration power failures (> 120 days) occurred in rural municipalities (41% of rural municipalities vs. 29% of urban municipalities), and in the northern and eastern districts. Unexpectedly, we also identify large disparities in electricity recovery between neighborhoods within the same urban area, based primarily on the density of housing. For many urban areas, poor residents, the most vulnerable to increased mortality and morbidity risks from power losses, shouldered the longest outages because they lived in less dense, detached housing where electricity restoration lagged. The approach developed in this study demonstrates the potential of satellite-based estimates of power recovery to improve the real-time monitoring of disaster impacts, globally, at a spatial resolution that is actionable for the disaster response community. [ABSTRACT FROM AUTHOR]

Aluminum is increasingly globally bioavailable with acidification from industrial emissions and poor mining practices. This bioavailability increases uptake by flora, contaminating products such as fruit, pollen, and nectar. Concentrations of aluminum in fruit and pollen have been reported between 0.05 and 670mg/L in North America. This is particularly concerning for pollinators that ingest pollen and nectar. Honey bees represent a globally present species experiencing decline in Europe and North America. Region specific decline may be a result of differential toxicity of exposure between subspecies. We find that European honey bees (Apis mellifera mellifera) may have differential toxicity as compared to two allopatric Mediterranean subspecies (Apis mellifera carnica and Apis mellifera caucasica) which showed no within subspecies exposure differences. European honey bees were then used in a laboratory experiment and exposed to aluminum in their daily water supply to mimic nectar contamination at several concentrations. After approximately 3 weeks of aluminum ingestion these bees showed significantly shorter captive longevity than controls at concentrations as low as 10.4mg/L and showed a possible hormetic response in motility. We also compared European honey bees to Africanized/European hybrid bees (Apis mellifera mellifera/scutellata hybrid) in short-term free-flight experiments. Neither the European honey bee nor the hybrid showed immediate foraging deficits in flight time, color choice, or floral manipulation after aluminum exposure. We conclude that European honey bees are at the greatest risk of aluminum related decline from chronic ingestion as compared to other subspecies and offer new methods for future use in honey bee toxicology. [ABSTRACT FROM AUTHOR]

Floating Catchment Area (FCA) methods are a popular tool to investigate accessibility to public facilities, in particular health care services. FCA approaches are attractive because, unlike other accessibility measures, they take into account the potential for congestion of facilities. This is done by 1) considering the population within the catchment area of a facility to calculate a variable that measures level of service, and then 2) aggregating the level of service by population centers subject to catchment area constraints. In this paper we discuss an effect of FCA approaches, an artifact that we term demand and level of service inflation. These artifacts are present in previous implementations of FCA methods. We argue that inflation makes interpretation of estimates of accessibility difficult, which has possible deleterious consequences for decision making. Next, we propose a simple and intuitive approach to proportionally allocate demandand and level of service in FCA calculations. The approach is based on a standardization of the impedance matrix, similar to approaches popular in the spatial statistics and econometrics literature. The result is a more intiuitive measure of accessibility that 1) provides a local version of the provider-to-population ratio; and 2) preserves the level of demand and the level of supply in a system. We illustrate the relevant issues with some examples, and then empirically by means of a case study of accessibility to family physicians in the Hamilton Census Metropolitan Area (CMA), in Ontario, Canada. Results indicate that demand and supply inflation/deflation affect the interpretation of accessibility analysis using existing FCA methods, and that the proposed adjustment can lead to more intuitive results. [ABSTRACT FROM AUTHOR]

Evidence of involvement of novel biomarkers in disease pathogenesis from research cohorts often precedes an understanding of their distributions in broader populations. This study aimed to estimate the distribution of fibroblast growth factor 23 (FGF-23), an endocrine hormone that helps to regulate serum phosphate levels, in the overall US population and in important subgroups. We used a predictive model generated using data from the Framingham Health Study to estimate FGF-23 values for adults in the US National Health and Nutrition Examination Survey and the size of patient subgroups with levels of FGF-23 above selected thresholds. To assess the face validity of our FGF-23 estimates, we examined the relationship between estimated FGF-23 and cardiovascular and all-cause mortality within NHANES using Kaplan-Meier estimates and Cox proportional-hazards regression models and compared it to that observed in Framingham. Estimated FGF-23 values from NHANES were lower (median [interquartile range] 47.4 [35.8, 64.0] vs. 67.0 [54.0, 85.0] RU/mL) than the observed FGF-23 values from the Framingham cohort. Age- and sex-adjusted 10-year all-cause mortality was significantly higher (hazard ratio 2.43 [95% confidence interval: 1.42, 4.16]) for subjects with estimated FGF-23 levels in the highest versus lowest quartile. Estimating the distribution of biomarker values in the general population by applying predictive equations from smaller research cohorts is feasible and can inform drug research decision making. [ABSTRACT FROM AUTHOR]

Aims: Statin-related myopathy (SRM), which includes rhabdomyolysis, is an uncommon but important adverse drug reaction because the number of people prescribed statins world-wide is large. Previous association studies of common genetic variants have had limited success in identifying a genetic basis for this adverse drug reaction. We conducted a multi-site whole-exome sequencing study to investigate whether rare coding variants confer an increased risk of SRM. Methods and results: SRM 3–5 cases (N = 505) and statin treatment-tolerant controls (N = 2047) were recruited from multiple sites in North America and Europe. SRM 3–5 was defined as symptoms consistent with muscle injury and an elevated creatine phosphokinase level >4 times upper limit of normal without another likely cause of muscle injury. Whole-exome sequencing and variant calling was coordinated from two analysis centres, and results of single-variant and gene-based burden tests were meta-analysed. No genome-wide significant associations were identified. Given the large number of cases, we had 80% power to identify a variant with minor allele frequency of 0.01 that increases the risk of SRM 6-fold at genome-wide significance. Conclusions: In this large whole-exome sequencing study of severe statin-related muscle injury conducted to date, we did not find evidence that rare coding variants are responsible for this adverse drug reaction. Larger sample sizes would be required to identify rare variants with small effects, but it is unclear whether such findings would be clinically actionable. [ABSTRACT FROM AUTHOR]

The adoption of the shared prosperity goal by the World Bank in 2013 and Sustainable Development Goal 10, on inequality, by the United Nations in 2015 should strengthen the focus of development interventions and cooperation on the income growth of the bottom 40 percent of the income distribution. This paper contributes to the incipient literature on within-country allocations of development institutions and assesses the geographic targeting of World Bank projects to the bottom 40 percent. Bivariate correlations between the allocation of project funding approved over 2005–14 and the geographical distribution of the bottom 40 as measured by survey income or consumption data are complemented by regressions with population and other potential factors affecting the within-country allocations as controls. The correlation analysis shows that, of the 58 countries in the sample, 41 exhibit a positive correlation between the shares of the bottom 40 and World Bank funding, and, in almost half of these, the correlation is above 0.5. Slightly more than a quarter of the countries, mostly in Sub-Saharan Africa, exhibit a negative correlation. The regression analysis shows that, once one controls for population, the correlation between the bottom 40 and World Bank funding switches sign and becomes significant and negative on average. This is entirely driven by Sub-Saharan Africa and not observed in the other regions. Hence, the significant and positive correlation in the estimations without controlling for population suggests that World Bank project funding is concentrated in administrative areas in which more people live (including the bottom 40) rather than in poorer administrative areas. Furthermore, capital cities receive disproportionally high shares of World Bank funding on average. [ABSTRACT FROM AUTHOR]

Latent tuberculosis infection (LTBI) treatment in persons at increased risk of disease progression is a key strategy with the strong potential to increase rate of tuberculosis (TB) decline in the United States. However, LTBI treatment in homeless persons, a population at high-risk of active TB disease, is usually associated with poor adherence. We describe the impact of using directly observed treatment (DOT) versus self-administered treatments (SAT) as an adherence-improving intervention to administer four months of daily rifampin regimen for LTBI treatment among homeless adults in Atlanta. Retrospective analysis of clinical care data on 274 homeless persons who initiated daily rifampin treatment for LTBI treatment at a county health department between January 2014 and December 2016 was performed. To reduce bias from non-random assignment of treatment, an inverse probability of treatment weighted (IPTW) logistic regression model was used to assess the effect of treatment type on treatment completion. Subgroup analyses were performed to assess heterogeneity of treatment effect on LTBI completion. Of 274 LTBI treatment initiators, 177 (65%) completed treatment [DOT 118/181 (65%), SAT 59/93 (63%)]. In the fully adjusted and weighted analysis, the odds of completing LTBI treatment on DOT was 40% higher than the odds of completing treatment by SAT [adjusted odds ratio (95% CI), aOR: 1.40 (1.07, 1.82), p = 0.014]. The unstable nature of homeless persons’ lifestyle makes LTBI treatment difficult for many reasons. Our study lends support to the use of DOT to improve LTBI treatment completion among subgroups of homeless persons on treatment with daily rifampin. [ABSTRACT FROM AUTHOR]

Background: Persons with dementia have twice the acute hospital use as older persons without dementia. In addition to straining overburdened healthcare systems, acute hospital use impacts patient and caregiver quality of life and is associated with increased risk of adverse outcomes including death. Reducing avoidable acute hospital use in persons with dementia is thus a global healthcare priority. However, evidence regarding the impact of health service interventions as defined by the Effective Practice and Organization of Care Cochrane Group on acute hospital use is scant and inconclusive. The aim of this systematic review and meta-analysis was to synthesize available evidence on the impact of health service interventions on acute hospital use in community-dwelling persons with dementia compared to usual care. Methods: Data Sources: MEDLINE, EMBASE, CINAHL and Cochrane CENTRAL (from 01/1995 to 08/2017). Study eligibility criteria: Randomised controlled trials measuring the impact of health service interventions on acute hospital use (proportion and mean number of emergency department visits and hospitalisations, mean number of hospital days, measured at 12 months, and at longest follow-up) in community-dwelling persons with dementia, compared to usual care. Study selection, appraisal and synthesis methods: Reviewers independently identified studies, extracted data, and assessed the risk of bias, with the Cochrane risk of bias tool. Authors of relevant trials were queried about unpublished data. Random effects model was used for meta-analyses. Effect heterogeneity was assessed through prediction intervals, and explored using sub-group analyses. Findings: Seventeen trials provided data on 4,549 persons. Unpublished data were obtained for 13 trials, representing 65% of synthesized data. Most interventions included a case management or a self-management component. None of the outcome comparisons provided conclusive evidence supporting the hypothesis that these interventions would lead to a decrease in acute hospital use. Furthermore, prediction intervals indicated possible and important increased service use associated with these interventions, such as emergency department visits, hospital admissions, and hospital days. Subgroup analyses did not favour any type of intervention. A limitation of this study is the inclusion of any type of health service intervention, which may have increased the observed heterogeneity. Conclusion: Despite a comprehensive systematic review and meta-analysis, including predominantly unpublished data, no health service intervention beyond usual care was found to reduce acute hospital use in community-dwelling persons with dementia. An important increase in service use may be associated with these interventions. Further research is urgently needed to identify effective interventions for this vulnerable population to limit rising acute hospital use, associated costs and adverse outcomes. Systematic review registration PROSPERO CRD42016046444. [ABSTRACT FROM AUTHOR]

Sugarcane ripening in Louisiana is necessary to ensure adequate sucrose levels in early-season harvested sugarcane. The response of nine sugarcane cultivar’s yield components to glyphosate and trinexapac-ethyl ripeners was determined in field trials. Glyphosate (210 g ae ha-1) and trinexapac-ethyl (200 g ai ha-1) treatments failed to increase sucrose yields more than non-ripened sugarcane. Sugarcane ripened with glyphosate or trinexapac-ethyl increased theoretical recoverable sucrose (TRS) 4 to 12% more than non-ripened sugarcane in seven out of nine cultivars, but greater TRS values were counterpoised by lower sugarcane stalk weight. An unintentional consequence of reduced late-season vegetative growth may benefit growers by allowing them to harvest more sugarcane hectares to meet their daily load quota and exposes fewer hectares to a freeze event. The cultivars HoCP 00–950, Ho 09–804, and HoCP 09–840 were not responsive to glyphosate or trinexapac-ethyl ripeners and should not be treated. A delayed harvest from 28 to 49 days after treatment (DAT) coincided with greater TRS values and 17% more sucrose yield. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity–having two or more coexisting chronic conditions–is highly prevalent, costly, and disabling to older adults. Questions remain regarding chronic diseases accumulation over time and whether this differs by racial and ethnic background. Answering this knowledge gap, this study identifies differences in rates of chronic disease accumulation and multimorbidity development among non-Hispanic white, non-Hispanic black, and Hispanic study participants starting in middle-age and followed up to 16 years. Methods and findings: We analyzed data from the Health and Retirement Study (HRS), a biennial, ongoing, publicly-available, longitudinal nationally-representative study of middle-aged and older adults in the United States. We assessed the change in chronic disease burden among 8,872 non-Hispanic black, non-Hispanic white, and Hispanic participants who were 51–55 years of age at their first interview any time during the study period (1998–2014) and all subsequent follow-up observations until 2014. Multimorbidity was defined as having two or more of seven somatic chronic diseases: arthritis, cancer, heart disease (myocardial infarction, coronary heart disease, angina, congestive heart failure, or other heart problems), diabetes, hypertension, lung disease, and stroke. We used negative binomial generalized estimating equation models to assess the trajectories of multimorbidity burden over time for non-Hispanic black, non-Hispanic white, and Hispanic participants. In covariate-adjusted models non-Hispanic black respondents had initial chronic disease counts that were 28% higher than non-Hispanic white respondents (IRR 1.279, 95% CI 1.201, 1.361), while Hispanic respondents had initial chronic disease counts that were 15% lower than non-Hispanic white respondents (IRR 0.852, 95% CI 0.775, 0.938). Non-Hispanic black respondents had rates of chronic disease accumulation that were 1.1% slower than non-Hispanic whites (IRR 0.989, 95% CI 0.981, 0.998) and Hispanic respondents had rates of chronic disease accumulation that were 1.5% faster than non-Hispanic white respondents (IRR 1.015, 95% CI 1.002, 1.028). Using marginal effects commands, this translates to predicted values of chronic disease for white respondents who begin the study period with 0.98 chronic diseases and end with 2.8 chronic diseases; black respondents who begin the study period with 1.3 chronic diseases and end with 3.3 chronic diseases; and Hispanic respondents who begin the study period with 0.84 chronic diseases and end with 2.7 chronic diseases. Conclusions: Middle-aged non-Hispanic black adults start at a higher level of chronic disease burden and develop multimorbidity at an earlier age, on average, than their non-Hispanic white counterparts. Hispanics, on the other hand, accumulate chronic disease at a faster rate relative to non-Hispanic white adults. Our findings have important implications for improving primary and secondary chronic disease prevention efforts among non-Hispanic black and Hispanic Americans to stave off greater multimorbidity-related health impacts. [ABSTRACT FROM AUTHOR]

Freely-available satellite data streams and the ability to process these data on cloud-computing platforms such as Google Earth Engine have made frequent, large-scale landcover mapping at high resolution a real possibility. In this paper we apply these technologies, along with machine learning, to the mapping of peatlands–a landcover class that is critical for preserving biodiversity, helping to address climate change impacts, and providing ecosystem services, e.g., carbon storage–in the Boreal Forest Natural Region of Alberta, Canada. We outline a data-driven, scientific framework that: compiles large amounts of Earth observation data sets (radar, optical, and LiDAR); examines the extracted variables for suitability in peatland modelling; optimizes model parameterization; and finally, predicts peatland occurrence across a large boreal area (397, 958 km2) of Alberta at 10 m spatial resolution (equalling 3.9 billion pixels across Alberta). The resulting peatland occurrence model shows an accuracy of 87% and a kappa statistic of 0.57 when compared to our validation data set. Differentiating peatlands from mineral wetlands achieved an accuracy of 69% and kappa statistic of 0.37. This data-driven approach is applicable at large geopolitical scales (e.g., provincial, national) for wetland and landcover inventories that support long-term, responsible resource management. [ABSTRACT FROM AUTHOR]

As emerging and re-emerging infectious arboviruses like dengue, chikungunya, and Zika threaten new populations worldwide, officials scramble to assess local severity and transmissibility, with little to no epidemiological history to draw upon. Indirect estimates of risk from vector habitat suitability maps are prone to great uncertainty, while direct estimates from epidemiological data are only possible after cases accumulate and, given environmental constraints on arbovirus transmission, cannot be widely generalized beyond the focal region. Combining these complementary methods, we use disease importation and transmission data to improve the accuracy and precision of a priori ecological risk estimates. We demonstrate this approach by estimating the spatiotemporal risks of Zika virus transmission throughout Texas, a high-risk region in the southern United States. Our estimates are, on average, 80% lower than published ecological estimates—with only six of 254 Texas counties deemed capable of sustaining a Zika epidemic—and they are consistent with the number of autochthonous cases detected in 2017. Importantly our method provides a framework for model comparison, as our mechanistic understanding of arbovirus transmission continues to improve. Real-time updating of prior risk estimates as importations and outbreaks arise can thereby provide critical, early insight into local transmission risks as emerging arboviruses expand their global reach. [ABSTRACT FROM AUTHOR]

Objective: Assessing the epidemiological association between herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) infections in the United States, and characterizing the trends in the standardized HSV-1 and HSV-2 antibody prevalences (seroprevalences), 1999–2016. Methods: Source of data was the cross-sectional and nationally-representative biennial surveys of the National Health and Nutrition Examination Survey (NHANES). All nine NHANES rounds for 1999–2016 were included in analysis. Datasets of these rounds were combined and analyzed accounting for survey design and applying weighting procedures. Logistic regressions were used to identify associations with seropositivity. Sensitivity analyses were conducted. Results: Odds of HSV-1 infection declined by 2.84% (95% CI: 1.70%-4.00%) annually among men, and by 2.22% (95% CI: 1.23%-3.21%) among women. Declines were highest at younger ages. Odds of HSV-2 infection declined by 2.23% (95% CI: 0.71%-3.82%) annually among men, and by 2.89% (95% CI: 1.57%-4.28%) among women. Odds ratio of the association between HSV-2 and HSV-1 seropositivity was 0.71 (95% CI: 0.60–0.84) for men and 0.81 (95% CI: 0.72–0.91) for women, after adjustment for age, ethnicity, and year. Conclusion: HSV-1 and HSV-2 seroprevalences showed a strong declining trend for at least two decades, for both sexes and for the different ethnicities, possibly reflecting improvements in hygiene and living conditions (for HSV-1), and safer sexual behavior (for HSV-2). HSV-1 seroprevalence declines are most pronounced among young individuals. There is evidence for cross protection between the two infections, suggestive of HSV-1 seropositivity being partially protective against HSV-2 infection. [ABSTRACT FROM AUTHOR]

West Nile virus (WNV; Flaviviridae: Flavivirus) is a widely distributed arthropod-borne virus that has negatively affected human health and animal populations. WNV infection rates of mosquitoes and human cases have been shown to be correlated with climate. However, previous studies have been conducted at a variety of spatial and temporal scales, and the scale-dependence of these relationships has been understudied. We tested the hypothesis that climate variables are important to understand these relationships at all spatial scales. We analyzed the influence of climate on WNV infection rate of mosquitoes and number of human cases in New York and Connecticut using Random Forests, a machine learning technique. During model development, 66 climate-related variables based on temperature, precipitation and soil moisture were tested for predictive skill. We also included 20–21 non-climatic variables to account for known environmental effects (e.g., land cover and human population), surveillance related information (e.g., relative mosquito abundance), and to assess the potential explanatory power of other relevant factors (e.g., presence of wastewater treatment plants). Random forest models were used to identify the most important climate variables for explaining spatial-temporal variation in mosquito infection rates (abbreviated as MLE). The results of the cross-validation support our hypothesis that climate variables improve the predictive skill for MLE at county- and trap-scales and for human cases at the county-scale. Of the climate-related variables selected, mean minimum temperature from July–September was selected in all analyses, and soil moisture was selected for the mosquito county-scale analysis. Models demonstrated predictive skill, but still over- and under-estimated WNV MLE and numbers of human cases. Models at fine spatial scales had lower absolute errors but had greater errors relative to the mean infection rates. [ABSTRACT FROM AUTHOR]

Detection of clusters of Legionnaires’ disease, a leading waterborne cause of pneumonia, is challenging. Clusters vary in size and scope, are associated with a diverse range of aerosol-producing devices, including exposures such as whirlpool spas and hotel water systems typically associated with travel, and can occur without an easily identified exposure source. Recently, jurisdictions have begun to use SaTScan spatio-temporal analysis software prospectively as part of routine cluster surveillance. We used data collected by the Active Bacterial Core surveillance platform to assess the ability of SaTScan to detect Legionnaires’ disease clusters. We found that SaTScan analysis using traditional surveillance data and geocoded residential addresses was unable to detect many common Legionnaires’ disease cluster types, such as those associated with travel or a prolonged time between cases. Additionally, signals from an analysis designed to simulate a real-time search for clusters did not align with clusters identified by traditional surveillance methods or a retrospective SaTScan analysis. A geospatial analysis platform better tailored to the unique characteristics of Legionnaires’ disease epidemiology would improve cluster detection and decrease time to public health action. [ABSTRACT FROM AUTHOR]

The maximum entropy model, a commonly used species distribution model (SDM) normally combines observations of the species occurrence with environmental information to predict the geographic distributions of animal or plant species. However, it only produces point estimates for the probability of species existence. To understand the uncertainty of the point estimates, we analytically derived the variance of the outputs of the maximum entropy model from the variance of the input. We applied the analytic method to obtain the standard deviation of dengue importation probability and Aedes aegypti suitability. Dengue occurrence data and Aedes aegypti mosquito abundance data, combined with demographic and environmental data, were applied to obtain point estimates and the corresponding variance. To address the issue of not having the true distributions for comparison, we compared and contrasted the performance of the analytical expression with the bootstrap method and Poisson point process model which proved of equivalence of maximum entropy model with the assumption of independent point locations. Both Dengue importation probability and Aedes aegypti mosquito suitability examples show that the methods generate comparatively the same results and the analytic method we introduced is dramatically faster than the bootstrap method and directly apply to maximum entropy model. [ABSTRACT FROM AUTHOR]

Despite considerable air pollution prevention and control measures that have been put into practice in recent years, outdoor air pollution remains one of the most important risk factors for health outcomes. To identify the potential research gaps, we conducted a scoping review focused on health outcomes affected by outdoor air pollution across the broad research area. Of the 5759 potentially relevant studies, 799 were included in the final analysis. The included studies showed an increasing publication trend from 1992 to 2008, and most of the studies were conducted in Asia, Europe, and North America. Among the eight categorized health outcomes, asthma (category: respiratory diseases) and mortality (category: health records) were the most common ones. Adverse health outcomes involving respiratory diseases among children accounted for the largest group. Out of the total included studies, 95.2% reported at least one statistically positive result, and only 0.4% showed ambiguous results. Based on our study, we suggest that the time frame of the included studies, their disease definitions, and the measurement of personal exposure to outdoor air pollution should be taken into consideration in any future research. The main limitation of this study is its potential language bias, since only English publications were included. In conclusion, this scoping review provides researchers and policy decision makers with evidence taken from multiple disciplines to show the increasing prevalence of outdoor air pollution and its adverse effects on health outcomes. [ABSTRACT FROM AUTHOR]

Adequate identification of estrus is crucial to achieve satisfactory reproductive performance in dairy farms. Even though several studies evaluated expression and identification of estrus at the cow level, limited data exist regarding estrus identification parameters at the herd level. The objectives of this study were to use data from large dairy farms located in Kansas to describe temporal patterns of insemination risk (IR), and to investigate associations between IR and various herd-level factors. Nine herds that housed lactating cows in dry-lots or free-stalls were used in the study. Data from 2012 to 2017 were extracted and categorized in 21-day intervals in a total of 85 cycles, which were classified by season of the year. Mean (SD) IR was 67.6% (4.0) and increased 0.067% (0.009) for each 21-day cycle during the period evaluated. Annual, semi-annual, and trimestral IR peaks were detected using autoregressive integrated moving average analysis. Most of these variations, however, were considered minimal and likely not of economic concern for commercial herds. Insemination risk was greatest during autumn, but did not differ among winter, spring, and summer. Insemination risk was not associated with herd milk yield per season, incidence risk of mastitis during first 21 days in milk, proportion of primiparous cows in the milking herd, or voluntary waiting period of multiparous cows. Herds that housed lactating dairy cows in dry-lots had IR 2.4 percentage points greater than free-stall herds. In addition, mortality during the first 60 days in milk, and category of voluntary waiting period for primiparous cows were associated with IR. In conclusion, seasonal variability in IR was minimal, with increased values observed during the autumn. Insemination risk was greater for dry-lot than free-stall herds. In addition, reduced mortality of lactating cows by 60 days in milk and longer voluntary waiting period for primiparous cows seem to favor greater IR. [ABSTRACT FROM AUTHOR]

The mountain pine beetle (MPB; Dendroctonus ponderosae) is a forest insect pest that attacks several different pine (Pinus) species in its native range of distribution in western North America. MPB are exposed for most of their life cycle to the chemical defenses of their hosts. These defenses are dominated by oleoresin secretions containing mostly various monoterpenes and diterpene resin acids (DRAs). Cytochrome P450 enzymes (P450s) of the MPB are thought to be involved in the metabolism of at least some of these defense compounds. Here we describe the cloning and characterization of three MPB P450s, CYP6DJ1, CYP6BW1 and CYP6BW3, and their functions in the oxidation of various monoterpenes and diterpene resin acids. CYP6DJ1 oxidizes the monoterpenes (+)-(4R)-limonene, (–)-(4S)-limonene and terpinolene and produces (4R,8R)-limonene-8,9-epoxide, (4R,8S)-limonene-8,9-epoxide, (4S,8S)-limonene-8,9-epoxide, (4S,8R)-limonene-8,9-epoxide, perilla alcohol and several unidentified oxidized compounds. These products of CYP6DJ1 were also identified in extracts of MPB treated with the same monoterpenes. CYP6BW1 and CYP6BW3 both oxidize the DRAs abietic acid, dehydroabietic acid, neoabietic acid, levopimaric acid, palustric acid, and isopimaric acid, producing hydroxylated and epoxidized DRAs. CYP6DJ1, CYP6BW1 and CYP6BW3 appear to contribute to the metabolism of oleoresin terpenes as part of the MPB’s ability to cope with host defenses. [ABSTRACT FROM AUTHOR]

Rationale: As part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI). Objectives: To estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California. Methods: We created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained. Measurements and main results: In the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4–16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was $20 billion (non-USB and MRF) to $48 billion. These had an incremental cost per QALY of $657,000 to $3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY. Conclusions: Substantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks. [ABSTRACT FROM AUTHOR]

Based on the entire population of Nobel laureates in science from 1901 to 2017, we show that North America’s rise as global power in science started in the 1920s. Following a transition period (1940s to 1960s), its scientific hegemony was consolidated in the 1970s. Yet since the 2000s, North America’s global leadership in science has come under pressure. In that time, its share of laureates across disciplines dropped, although it has retained its attractiveness as a destination for future laureates from Europe and the Asia-Pacific region. In addition, we find that North America has become apparently less effective since 2010 in transferring capacities for conducting ground-breaking research from one generation of scientists to another. Furthermore, both Europe and the Asia-Pacific region have similarly high shares of newcomer organizations with regard to where prize-winning work is conducted, indicating that these two regions are very active in the inter-organizational competition for scientific talent. Despite this competition, however, we find no support for the rise of a new global center of science. [ABSTRACT FROM AUTHOR]

'HoneySweet', a transgenic plum (Prunus domestica) resistant to plum pox virus through RNAi, was deregulated in the U.S. in 2011. The compositional study of 'HoneySweet' fruit was expanded to include locations outside of the US as well as utilizing a wide variety of comparators and different collection years to see the variability possible. The results revealed that plums have a wide variation in composition and that variation among locations was greater than variation among cultivars. This was also the case for different years at one location. The results supported the supposition that the transgene and insertion event had no significant effect on the composition of 'HoneySweet' fruit even under virus pressure, and that it fell in the normal range of composition of commercially grown plums. It also suggested that the effect of environment is as great as that of genetics on the fruit composition of plums. [ABSTRACT FROM AUTHOR]

Purpose: The Ponseti Method has dramatically altered the management of clubfoot, with particular implications for limited-resource settings. We sought to describe outcomes of care and risk factors for sub-optimal results using the Ponseti Method in Haiti. Methods: We conducted a records review of patients presenting from 2011–2015 to a CURE Clubfoot clinic in Port-au-Prince, Haiti. We report patient characteristics (demographics and clinical), treatment patterns (cast number/duration and tenotomy rates), and outcomes (relapse and complications). We compared treatment with benchmarks in high-income nations and used generalized linear models to identify risk factors for delayed presentation, increased number of casts, and relapse. Results: Amongst 168 children, age at presentation ranged from 0 days (birth) to 4.4 years, 62% were male, 35% were born at home, 63% had bilateral disease, and 46% had idiopathic clubfeet. Prior treatment (RR 6.33, 95% CI 3.18–12.62) was associated with a higher risk of delayed presentation. Risk factors for requiring ≥ 10 casts included having a non-idiopathic diagnosis (RR 2.28, 95% CI 1.08–4.83) and higher Pirani score (RR 2.78 per 0.5 increase, 95% CI 1.17–6.64). Female sex (RR 1.54, 95% CI 1.01–2.34) and higher Pirani score (RR 1.09 per 0.5 increase, 95% CI 1.00–1.17) were risk factors for relapse. Compared to North American benchmarks, children presented later (median 4.1 wks [IQR 1.6–18.1] vs. 1 wk), with longer casting (12.5 wks [SD 9.8] vs. 7.1 wks), and higher relapse (43% vs. 22%). Conclusions: Higher Pirani score, prior treatment, non-idiopathic diagnosis, and female sex were associated with a higher risk of sub-optimal outcomes in this low-resource setting. Compared to high-income nations, serial casting began later, with longer duration and higher relapse. Identifying patients at risk for poor outcomes in a low-resource setting can guide counseling, program development, and resource allocation. [ABSTRACT FROM AUTHOR]

The coastal tailed frog (Ascaphus truei) is endemic to the Pacific Northwest of North America and is listed as a species of Special Concern under the Canadian Species at Risk Act. Its range is limited to British Columbia where it occurs widely west of the Coast Mountain Ranges extending north almost to the Alaskan Panhandle. The present study focused on surveying within the Cayoosh, Bridge (Shulaps), Seton, Anderson, Carpenter, and Downton Lake drainages. Four years of previous inventory efforts using conventional time-constrained search (TCS) methods detected tailed frog at 23/292 discrete sites (7.9% detection rate) in seven watersheds. Non-invasive environmental DNA (eDNA) methods hold promise for cryptic and low-abundance species detection. We rigorously validated a quantitative real-time polymerase chain reaction (qPCR)-based tool for detecting coastal tailed frog eDNA in water samples. This eASTR4 test is highly specific and sensitive. We applied a two-step targeted eDNA analysis approach on duplicate filtered water samples from a total of 72 sites collected over five days. The first IntegritE-DNA step mitigates false negative results and tests all DNA samples for the ability to support amplification from endogenous plant chloroplast DNA as a measure of sample viability. Three DNA samples failed this step even after inhibitor clean up suggesting that these samples were poor quality and not reliable for targeted species’ DNA analyses. All other DNA samples were deemed viable and were then tested for species-specific DNA. Coastal tailed frog eDNA was detected in 55/72 (76%) discrete stream reaches; nine sites with historical known occurrence were all eDNA positive. The false negative rate for TCS compared to eDNA methods was 58%. The results expand known coastal tailed frog distribution to 24 watersheds effectively more than tripling extant occurrences and confirm a previously suspected, apparently isolated coastal tailed frog metapopulation in the Shulaps drainage. [ABSTRACT FROM AUTHOR]

Acarological surveys in areas outside the currently believed leading edge of the distribution of lone star ticks (Amblyomma americanum), coupled with recent reports of their identification in previously uninvaded areas in the public health literature, suggest that this species is more broadly distributed in North America than currently understood. Therefore, we evaluated the potential geographic extent under present and future conditions using ecological niche modeling approach based on museum records available for this species at the Walter Reed Biosystematics Unit (WRBU). The median prediction of a best fitting model indicated that lone star ticks are currently likely to be present in broader regions across the Eastern Seaboard as well as in the Upper Midwest, where this species could be expanding its range. Further northward and westward expansion of these ticks can be expected as a result of ongoing climate change, under both low- and high-emissions scenarios. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study was to clarify whether serum matrix metalloproteinase 3 (MMP-3) levels are associated with an effect of iguratimod as add-on therapy to biological DMARDs (bDMARDs) in patients with rheumatoid arthritis (RA). Methods: Forty three patients with RA were treated with iguratimod as add-on therapy to bDMARDs. They were classified into remission and non-remission groups at 24 weeks of iguratimod therapy. Remission was defined as a state with a disease activity score (DAS) <2.6 in 28 joints (termed DAS remission) and total power Doppler ultrasound (US) score <3 (termed US remission). The serum MMP-3 levels at baseline and at 12 weeks were compared between these two groups. Results: There were no significant differences in the serum MMP-3 levels at baseline between the DAS and US remission groups and the non-remission group. The serum MMP-3 levels at 12 weeks in the US remission group were significantly lower than those in the non-remission group. The ratios of the serum MMP-3 levels at baseline to those at 12 weeks in both the DAS and US remission groups were significantly lower than those in the non-remission group. An MMP-3 ratio <0.86 was determined as the cut-off value to predict US remission at 24 weeks. Conclusion: Our findings suggest that the ratios of the serum MMP-3 levels at baseline to those at 12 weeks could be used to predict remission in RA patients who are administered iguratimod as an add-on to bDMARDs. [ABSTRACT FROM AUTHOR]

Species may become invasive after introduction to a new range because phenotypic traits pre-adapt them to spread and become dominant. In addition, adaptation to novel selection pressures in the introduced range may further increase their potential to become invasive. The diploid Leucanthemum vulgare and the tetraploid L. ircutianum are native to Eurasia and have been introduced to North America, but only L. vulgare has become invasive. To investigate whether phenotypic differences between the two species in Eurasia could explain the higher abundance of L. vulgare in North America and whether rapid evolution in the introduced range may have contributed to its invasion success, we grew 20 L. vulgare and 21 L. ircutianum populations from Eurasia and 21 L. vulgare populations from North America under standardized conditions and recorded performance and functional traits. In addition, we recorded morphological traits to investigate whether the two closely related species can be clearly distinguished by morphological means and to what extent morphological traits have changed in L. vulgare post-introduction. We found pronounced phenotypic differences between L. vulgare and L. ircutianum from the native range as well as between L. vulgare from the native and introduced ranges. The two species differed significantly in morphology but only moderately in functional or performance traits that could have explained the higher invasion success of L. vulgare in North America. In contrast, leaf morphology was similar between L. vulgare from the native and introduced range, but plants from North America flowered later, were larger and had more and larger flower heads than those from Eurasia. In summary, we found litte evidence that specific traits of L. vulgare may have pre-adapted this species to become more invasive than L. ircutianum, but our results indicate that rapid evolution in the introduced range likely contributed to the invasion success of L. vulgare. [ABSTRACT FROM AUTHOR]

Predicting wildfire under future conditions is complicated by complex interrelated drivers operating across large spatial scales. Annual area burned (AAB) is a useful index of global wildfire activity. Current and antecedent seasonal climatic conditions, and the timing of snowpack melt, have been suggested as important drivers of AAB. As climate warms, seasonal climate and snowpack co-vary in intricate ways, influencing fire at continental and sub-continental scales. We used independent records of seasonal climate and snow cover duration (last date of permanent snowpack, LDPS) and cell-based Structural Equation Models (SEM) to separate direct (climatic) and indirect (snow cover) effects on relative changes in AAB under future climatic scenarios across western and boreal North America. To isolate seasonal climate variables with the greatest effect on AAB, we ran multiple regression models of log-transformed AAB on seasonal climate variables and LDPS. We used the results of multiple regressions to project future AAB using GCM ensemble climate variables and LDPS, and validated model predictions with recent AAB trends. Direct influences of spring and winter temperatures on AAB are larger and more widespread than the indirect effect mediated by changes in LDPS in most areas. Despite significant warming trends and reductions in snow cover duration, projected responses of AAB to early-mid 21st century are heterogeneous across the continent. Changes in AAB range from strongly increasing (one order of magnitude increases in AAB) to moderately decreasing (more than halving of baseline AAB). Annual wildfire area burned in coming decades is likely to be highly geographically heterogeneous, reflecting interacting regional and seasonal climate drivers of fire occurrence and spread. [ABSTRACT FROM AUTHOR]

Beaver are an integral component of hydrologic, geomorphic, and biotic processes within North American stream systems, and their propensity to build dams alters stream and riparian structure and function to the benefit of many aquatic and terrestrial species. Recognizing this, beaver relocation efforts and/or application of structures designed to mimic the function of beaver dams are increasingly being utilized as effective and cost-efficient stream and riparian restoration approaches. Despite these verities, the notion that beaver dams negatively impact stream habitat remains common, specifically the assumption that beaver dams increase stream temperatures during summer to the detriment of sensitive biota such as salmonids. In this study, we tracked beaver dam distributions and monitored water temperature throughout 34 km of stream for an eight-year period between 2007 and 2014. During this time the number of natural beaver dams within the study area increased by an order of magnitude, and an additional 4 km of stream were subject to a restoration manipulation that included installing a high-density of Beaver Dam Analog (BDA) structures designed to mimic the function of natural beaver dams. Our observations reveal several mechanisms by which beaver dam development may influence stream temperature regimes; including longitudinal buffering of diel summer temperature extrema at the reach scale due to increased surface water storage, and creation of cool—water channel scale temperature refugia through enhanced groundwater—surface water connectivity. Our results suggest that creation of natural and/or artificial beaver dams could be used to mitigate the impact of human induced thermal degradation that may threaten sensitive species. [ABSTRACT FROM AUTHOR]

The fate of Northern peatlands under climate change is important because of their contribution to global carbon (C) storage. Peatlands are maintained via greater plant productivity (especially of Sphagnum species) than decomposition, and the processes involved are strongly mediated by climate. Although some studies predict that warming will relax constraints on decomposition, leading to decreased C sequestration, others predict increases in productivity and thus increases in C sequestration. We explored the lack of congruence between these predictions using single-species and integrated species distribution models as proxies for understanding the environmental correlates of North American Sphagnum peatland occurrence and how projected changes to the environment might influence these peatlands under climate change. Using Maximum entropy and BIOMOD modelling platforms, we generated single and integrated species distribution models for four common Sphagnum species in North America under current climate and a 2050 climate scenario projected by three general circulation models. We evaluated the environmental correlates of the models and explored the disparities in niche breadth, niche overlap, and climate suitability among current and future models. The models consistently show that Sphagnum peatland distribution is influenced by the balance between soil moisture deficit and temperature of the driest quarter-year. The models identify the east and west coasts of North America as the core climate space for Sphagnum peatland distribution. The models show that, at least in the immediate future, the area of suitable climate for Sphagnum peatland could expand. This result suggests that projected warming would be balanced effectively by the anticipated increase in precipitation, which would increase Sphagnum productivity. [ABSTRACT FROM AUTHOR]

Aedes albopictus is a major nuisance pest and also a public health concern because of the role it plays in the transmission of arboviruses. There is a continuing demand for effective surveillance tools for this species. The first generation of Biogents Sentinel (BGS1) traps have proven to be an effective tool for surveillance of Ae. albopictus throughout its range, however, some defects in construction led to the eventual development of the next generation. We compared the performance of the new generation prototype trap (BGS2P) to the original. Studies were conducted in suburban and urban areas in Florida, Louisiana, New Jersey, and Virginia, USA in the summer of 2014 (July-October). BGS1 traps collected significantly more Ae. albopictus when compared to the BGS2P with or without CO2 in all locations (P<0.05). When a white cloth was wrapped around the BGS2P traps, efficiency did not change in Louisiana, New Jersey, and Virginia; however, numbers of adult Ae. albopictus collected from the BGS2P and the BGS1 were significantly different based on lure type (P< 0.0001). Results from Florida showed that BGS1with the BG lure and CO2 collected significantly higher adult numbers compared to BGS2P with a three component cartridge lure and CO2 (P< 0.0001). Overall, our results indicate that despite improvements in construction and durability of the BGS2P, this newer trap type did not increase the capture rates of Ae. albopictus in North America. Biogents modified BGS2P based on the data collected from the current study and updated as Biogents Sentinel 2 is now commercially available and its efficacy in comparison to the original will require further study. [ABSTRACT FROM AUTHOR]

University scientific research ability is an important indicator to express the strength of universities. In this paper, the evaluation of university scientific research ability is investigated based on the output of sci-tech papers. Four university alliances from North America, UK, Australia, and China, are selected as the case study of the university scientific research evaluation. Data coming from Thomson Reuters InCites are collected to support the evaluation. The work has contributed new framework to the issue of university scientific research ability evaluation. At first, we have established a hierarchical structure to show the factors that impact the evaluation of university scientific research ability. Then, a new MCDM method called D-AHP model is used to implement the evaluation and ranking of different university alliances, in which a data-driven approach is proposed to automatically generate the D numbers preference relations. Next, a sensitivity analysis has been given to show the impact of weights of factors and sub-factors on the evaluation result. At last, the results obtained by using different methods are compared and discussed to verify the effectiveness and reasonability of this study, and some suggestions are given to promote China’s scientific research ability. [ABSTRACT FROM AUTHOR]

The seasonal and interannual variability of vertical transport (upwelling/downwelling) has been relatively well studied, mainly for the California Current System, including low-frequency changes and latitudinal heterogeneity. The aim of this work was to identify potentially predictable patterns in upwelling/downwelling activity along the North American west coast and discuss their plausible mechanisms. To this purpose we applied the min/max Autocorrelation Factor technique and time series analysis. We found that spatial co-variation of seawater vertical movements present three dominant low-frequency signals in the range of 33, 19 and 11 years, resembling periodicities of: atmospheric circulation, nodal moon tides and solar activity. Those periodicities might be related to the variability of vertical transport through their influence on dominant wind patterns, the position/intensity of pressure centers and the strength of atmospheric circulation cells (wind stress). The low-frequency signals identified in upwelling/downwelling are coherent with temporal patterns previously reported at the study region: sea surface temperature along the Pacific coast of North America, catch fluctuations of anchovy Engraulis mordax and sardine Sardinops sagax, the Pacific Decadal Oscillation, changes in abundance and distribution of salmon populations, and variations in the position and intensity of the Aleutian low. Since the vertical transport is an oceanographic process with strong biological relevance, the recognition of their spatio-temporal patterns might allow for some reasonable forecasting capacity, potentially useful for marine resources management of the region. [ABSTRACT FROM AUTHOR]

Quantifying historical fire regimes provides important information for managing contemporary forests. Historical fire frequency and severity can be estimated using several methods; each method has strengths and weaknesses and presents challenges for interpretation and verification. Recent efforts to quantify the timing of historical high-severity fire events in forests of western North America have assumed that the “stand age” variable from the US Forest Service Forest Inventory and Analysis (FIA) program reflects the timing of historical high-severity (i.e. stand-replacing) fire in ponderosa pine and mixed-conifer forests. To test this assumption, we re-analyze the dataset used in a previous analysis, and compare information from fire history records with information from co-located FIA plots. We demonstrate that 1) the FIA stand age variable does not reflect the large range of individual tree ages in the FIA plots: older trees comprised more than 10% of pre-stand age basal area in 58% of plots analyzed and more than 30% of pre-stand age basal area in 32% of plots, and 2) recruitment events are not necessarily related to high-severity fire occurrence. Because the FIA stand age variable is estimated from a sample of tree ages within the tree size class containing a plurality of canopy trees in the plot, it does not necessarily include the oldest trees, especially in uneven-aged stands. Thus, the FIA stand age variable does not indicate whether the trees in the predominant size class established in response to severe fire, or established during the absence of fire. FIA stand age was not designed to measure the time since a stand-replacing disturbance. Quantification of historical “mixed-severity” fire regimes must be explicit about the spatial scale of high-severity fire effects, which is not possible using FIA stand age data. [ABSTRACT FROM AUTHOR]

Striped skunks are one of the most important terrestrial reservoirs of rabies virus in North America, and yet the prevalence of rabies among this host is only passively monitored and the disease among this host remains largely unmanaged. Oral vaccination campaigns have not efficiently targeted striped skunks, while periodic spillovers of striped skunk variant viruses to other animals, including some domestic animals, are routinely recorded. In this study we evaluated the spatial and spatio-temporal patterns of infection status among striped skunk cases submitted for rabies testing in the North Central Plains of US in a Bayesian hierarchical framework, and also evaluated potential eco-climatological drivers of such patterns. Two Bayesian hierarchical models were fitted to point-referenced striped skunk rabies cases [n = 656 (negative), and n = 310 (positive)] received at a leading rabies diagnostic facility between the years 2007–2013. The first model included only spatial and temporal terms and a second covariate model included additional covariates representing eco-climatic conditions within a 4km2 home-range area for striped skunks. The better performing covariate model indicated the presence of significant spatial and temporal trends in the dataset and identified higher amounts of land covered by low-intensity developed areas [Odds ratio (OR) = 3.41; 95% Bayesian Credible Intervals (CrI) = 2.08, 3.85], higher level of patch fragmentation (OR = 1.70; 95% CrI = 1.25, 2.89), and diurnal temperature range (OR = 0.54; 95% CrI = 0.27, 0.91) to be important drivers of striped skunk rabies incidence in the study area. Model validation statistics indicated satisfactory performance for both models; however, the covariate model fared better. The findings of this study are important in the context of rabies management among striped skunks in North America, and the relevance of physical and climatological factors as risk factors for skunk to human rabies transmission and the space-time patterns of striped skunk rabies are discussed. [ABSTRACT FROM AUTHOR]

In North America, cerambycid beetles can have significant ecological and economic effects on forest ecosystems, and the rate of introduction and/or detection of exotic species is increasing. Detection and survey programs rely on semiochemical-baited intercept traps which are often ineffective for large woodborers like cerambycid beetles. This study examined the effects of flight intercept trap design on the capture of cerambycid beetles in the subfamilies Lamiinae and Cerambycinae. These subfamilies are the two largest in the Cerambycidae and they include many of the most damaging cerambycid pests and species on regulatory watch lists in North America. This study demonstrates that intercept trap design, treatment of trap surfaces with a lubricant, and the type of collection cup all influence the capture of beetles from the subfamilies Lamiinae and Cerambycinae. It also demonstrates that the addition of a large lubricant-treated collar to the bottom funnel of a multiple-funnel trap significantly increases the capture of some Lamiinae. The best trap design for both subfamilies was a lubricant treated multiple-funnel [MF] trap equipped with a wet cup and lubricant treated large collar on the bottom funnel. This design captured between 4 and 14 times more Lamiinae and Cerambycinae than commercially-available MF and panel traps. [ABSTRACT FROM AUTHOR]

The pre-cold-frontal low-level jet within oceanic extratropical cyclones represents the lower-tropospheric component of a deeper corridor of concentrated water vapor transport in the cyclone warm sector. These corridors are referred to as atmospheric rivers (ARs) because they are narrow relative to their length scale and are responsible for most of the poleward water vapor transport at midlatitudes. This paper investigates landfalling ARs along adjacent north- and south-coast regions of western North America. Special Sensor Microwave Imager (SSM/I) satellite observations of long, narrow plumes of enhanced integrated water vapor (IWV) were used to detect ARs just offshore over the eastern Pacific from 1997 to 2005. The north coast experienced 301 AR days, while the south coast had only 115. Most ARs occurred during the warm season in the north and cool season in the south, despite the fact that the cool season is climatologically wettest for both regions. Composite SSM/I IWV analyses showed landfalling wintertime ARs extending northeastward from the tropical eastern Pacific, whereas the summertime composites were zonally oriented and, thus, did not originate from this region of the tropics. Companion SSM/I composites of daily rainfall showed significant orographic enhancement during the landfall of winter (but not summer) ARs. The NCEP–NCAR global reanalysis dataset and regional precipitation networks were used to assess composite synoptic characteristics and overland impacts of landfalling ARs. The ARs possess strong vertically integrated horizontal water vapor fluxes that, on average, impinge on the West Coast in the pre-cold-frontal environment in winter and post-cold-frontal environment in summer. Even though the IWV in the ARs is greater in summer, the vapor flux is stronger in winter due to much stronger flows associated with more intense storms. The landfall of ARs in winter and north-coast summer coincides with anomalous warmth, a trough offshore, and ridging over the Intermountain West, whereas the south-coast summer ARs coincide with relatively cold conditions and a near-coast trough. ARs have a much more profound impact on near-coast precipitation in winter than summer, because the terrain-normal vapor flux is stronger and the air more nearly saturated in winter. During winter, ARs produce roughly twice as much precipitation as all storms. In addition, wintertime ARs with the largest SSM/I IWV are tied to more intense storms with stronger flows and vapor fluxes, and more precipitation. ARs generally increase snow water equivalent (SWE) in autumn/winter and decrease SWE in spring. On average, wintertime SWE exhibits normal gains during north-coast AR storms and above-normal gains during the south-coast AR storms. The north-coast sites are mostly lower in altitude, where warmer-than-normal conditions more frequently yield rain. During those events when heavy rain from a warm AR storm falls on a preexisting snowpack, flooding is more likely to occur. [ABSTRACT FROM AUTHOR]