Host genetic risk factors for community-acquired pneumonia

This study was conducted to establish the contribution of genetic host factors in the susceptibility to community acquired pneumonia (CAP) in the Russian population. Patients with CAP (n = 334), volunteers without a previous history of CAP, constantly exposed to infectious agents, control A group (n = 141) and a second control group B consisted of healthy persons (n = 314) were included in the study. All subjects were genotyped for 13 polymorphic variants in the genes of xenobiotics detoxification CYP1A1 (rs2606345, rs4646903, and rs1048943), GSTM1 (Ins/del), GSTT1 (Ins/del), ABCB1 rs1045642); immune and inflammation response IL-6 (rs1800795), TNF-a (rs1800629), MBL2 (rs7096206), CCR5 (rs333), NOS3 (rs1799983), angiotensin-converting enzyme ACE (rs4340), and occlusive vascular disease/hyperhomocysteinemia MTHFR (rs1801133). Seven polymorphic variants in genes CYP1A1, GSTM1, ABCB1, NOS3, IL6, CCR5 and ACE were associated with CAP. For two genes CYP1A1 and GSTM1 associations remained significant after correction for multiple comparisons. Multiple analysis by the number of all risk genotypes showed a highly significant association with CAP (P = 2.4 × 10^− 7, OR = 3.03, 95% CI 1.98–4.64) with the threshold for three risk genotypes. Using the ROC-analysis, the AUC value for multi-locus model was estimated as 68.38.     

A laboratory-based method to measure relative pesticide and spray oil efficacy against broad mite, Polyphagotarsonemus latus (Banks)(Acari: Tarsonemidae)

Six pesticides and two spray oils were tested against Polyphagotarsonemus latus. The chemicals were evaluated under laboratory conditions, requiring the development of a novel bioassay method, which is reported here. The pesticide toxicities fell into three distinct groups, namely abamectin, conventional pesticides and oils. The relative pesticide toxicities at the LC₅₀ level were abamectin 4.9×10^-8 g ai l^-1, endosulfan 1.1×10^-3 g ai l^-1, fenpyroximate 2.3×10^-3 g ai l^-1, pyridaben 4.1×10^-3 g ai l^-1, tebufenpyrad 4.4×10^-3 g ai l^-1, dicofol 4.5×10^-3 g ai l^-1, petroleum spray oil 3.4×10^-1 g ai l^-1 and canola oil 4.1×10^-1 g ai l^-1. The calculation of the LC_99.9 values allows for resistance monitoring in P. latus and the suggested discriminating concentrations are abamectin 1.0×10^-4 g ai l^-1; endosulfan, pyridaben and dicofol 1.0×10^-1 g ai l^-1 fenpyroximate and tebufenpyrad 5.0×10^-1 g ai l^-1.     

Rutile TiO2 Inverse Opal Anodes for Li‐Ion Batteries with Long Cycle Life,High‐Rate Capability,and High Structural Stability

Rutile TiO₂ inverse opals provide long cycle life and impressive structural stability when tested as anode materials for Li‐ion batteries. The capacity retention of TiO₂ inverse opals (IOs) is greater than previously reported values for other rutile TiO₂ nanomaterials, and the cycled crystalline phase and material interconnectivity is maintained over thousands of cycles. Consequently, this paper offers insight into the importance of optimizing the relationship between the structure and morphology on improving electrochemical performance of this abundant and low environmental impact material. TiO₂ IOs show gradual capacity fading over 1000 and 5000 cycles, when cycled at specific currents of 75 and 450 mA g^?1, respectively, while maintaining a high capacity and a stable overall cell voltage. TiO₂ IOs achieve a reversible capacity of ≈170 and 140 mA h g^?1 after the 100th and 1000th cycles, respectively, at a specific current of 75 mA g^?1, corresponding to a capacity retention of ≈82.4%. The structural stability of the 3D IO phase from pristine rutile TiO₂ to the conductive orthorhombic Li_0.5TiO₂ is remarkable and maintains its structural integrity. Image analysis conclusively shows that volumetric swelling is accommodated into the predefined pore space, and the IO periodicity remains constant and does not degrade over 5000 cycles.     

Dynamic Modeling of In‐Use Cement Stocks in the United States

A dynamic substance‐flow model is developed to characterize the stocks and flows of cement utilized during the 20th century in the United States, using the generic cement life cycle as a systems boundary. The motivation for estimating historical inventories of cement stocks and flows is to provide accurate estimates of contemporary cement in‐use stocks in U.S. infrastructure and future discards to relevant stakeholders in U.S. infrastructure, such as the federal and state highway administrators, departments of transportation, public and private utilities, and the construction and cement industries. Such information will assist in planning future rehabilitation projects and better life cycle management of infrastructure systems. In the present policy environment of climate negotiations, estimates of in‐use cement infrastructure can provide insights about to what extent built environment can act as a carbon sink over its lifetime. The rate of addition of new stock, its composition, and the repair of existing stock are key determinants of infrastructure sustainability. Based upon a probability of failure approach, a dynamic stock and flow model was developed utilizing three statistical lifetime distributions—Weibull, gamma, and lognormal—for each cement end‐use. The model‐derived estimate of the “in‐use” cement stocks in the United States is in the range of 4.2 to 4.4 billion metric tons (gigatonnes, Gt). This indicates that 82% to 87% of cement utilized during the last century is still in use. On a per capita basis, this is equivalent to 14.3 to 15.0 tonnes of in‐use cement stock per person. The in‐use cement stock per capita has doubled over the last 50 years, although the rate of growth has slowed.     

A simple technique for estimation ofDrechslera nodulosa (Berk. & Curt.) Subram. and Jain propagules in soil

Summary A baiting technique was developed to estimate the population ofDrechslera nodulosa (Berk. and Curt.) Subram. and Jain in soil by using susceptible ragi (Eleusine coracana Gaertn.) culms. The number of lesions developed on baited culms were reduced with the reduction in concentration ofD. nodulosa propagules in both sterilized and unsterilized soils. Based on this a standard correlation (concentrationvs infection probability) was established which was found to be quite efficient method to estimate the population in soil and to bait even when the inoculum level was 4 propagules per g of soil.     

Spotlight surveys for white-tailed deer: Monitoring panacea or exercise in futility?

Many monitoring programs for white-tailed deer (Odocoileus virginianus) on both private and public lands across the United States have long relied on the use of road-based spotlight surveys for monitoring population size and trends. Research has suggested spotlight surveys are ineffective and that road-based surveys for deer are biased because of highly variable detection rates. To evaluate variability in detection rates relative to the assumption that repeated surveys along roads will provide reliable trend data for use in calculating deer density estimates, we collected 5 years of thermal-imager and spotlight survey data using a multiple-observer, closed-capture approach. Using a Huggin's closed capture model, data bootstrapping, and variance components analyses, our results suggest that density estimates for white-tailed deer generated from data collected during road-based spotlight surveys are likely not reflective of the standing deer population. Detection probabilities during individual spotlight surveys ranged from 0.00 to 0.80 (median = 0.45) across all surveys, and differed by observer, survey, management unit, and survey transect replicate. Mean spotlight detection probability (0.41) and process standard deviation (0.12) estimates indicated considerable variability across surveys, observers, transects, and years, which precludes the generation of a correction factor or use of spotlight data to evaluate long-term trends at any scale. Although recommended by many state, federal, and non-governmental agencies, our results suggest that the benefit of spotlight survey data for monitoring deer populations is limited and likely represents a waste of resources with no appreciable management information gained. © 2012 The Wildlife Society.     

Comparison of Methods for Estimating Bird Abundance and Trends From Historical Count Data

Abstract: The use of bird counts as indices has come under increasing scrutiny because assumptions concerning detection probabilities may not be met, but there also seems to be some resistance to use of model-based approaches to estimating abundance. We used data from the United States Forest Service, Southern Region bird monitoring program to compare several common approaches for estimating annual abundance or indices and population trends from point-count data. We compared indices of abundance estimated as annual means of counts and from a mixed-Poisson model to abundance estimates from a count-removal model with 3 time intervals and a distance model with 3 distance bands. We compared trend estimates calculated from an autoregressive, exponential model fit to annual abundance estimates from the above methods and also by estimating trend directly by treating year as a continuous covariate in the mixed-Poisson model. We produced estimates for 6 forest songbirds based on an average of 621 and 459 points in 2 physiographic areas from 1997 to 2004. There was strong evidence that detection probabilities varied among species and years. Nevertheless, there was good overall agreement across trend estimates from the 5 methods for 9 of 12 comparisons. In 3 of 12 comparisons, however, patterns in detection probabilities potentially confounded interpretation of uncorrected counts. Estimates of detection probabilities differed greatly between removal and distance models, likely because the methods estimated different components of detection probability and the data collection was not optimally designed for either method. Given that detection probabilities often vary among species, years, and observers investigators should address detection probability in their surveys, whether it be by estimation of probability of detection and abundance, estimation of effects of key covariates when modeling count as an index of abundance, or through design-based methods to standardize these effects.     

Does variation between dry and wet seasons affect tropical forest mammals' occupancy and detectability by camera traps? Case study from the Udzungwa Mountains,Tanzania

The increasing use of camera trapping coupled to occupancy analysis to study terrestrial mammals has opened the way to inferential studies that besides estimating the probability of presence explicitly consider detectability. This in turn allows considering factors that can potentially confound the estimation of occupancy and detection probability, including seasonal variations in rainfall. To address this, we conducted a systematic camera trapping survey in the Udzungwa Mountains of Tanzania by deploying twenty camera traps for 30 days in dry and wet seasons and used dynamic occupancy modelling to determine the effect of season on estimated occupancy and detection probability for species with >10 capture events. The sampling yielded 7657 and 6015 images in dry and wet seasons, respectively, belonging to 21 mammal species. Models with no season dependency and with season‐dependent detectability were best supported, indicating that neither colonization nor extinction varied with seasons and hence occupancy did not vary. Only bush pig (Potamochoerus larvatus) showed a significant decrease in detectability from dry to wet seasons. Our study indicates that seasonal variation in rainfall may have limited effect on occupancy and detectability of resident mammals in Udzungwa rainforests; however, it remains a factor to consider when designing future studies.