Spatial patterns of Bovine Corona Virus and Bovine Respiratory Syncytial Virus in the Swedish beef cattle population

Background  

Both bovine coronavirus (BCV) and bovine respiratory syncytial virus (BRSV) infections are currently wide-spread in the Swedish dairy cattle population. Surveys of antibody levels in bulk tank milk have shown very high nationwide prevalences of both BCV and BRSV, with large variations between regions. In the Swedish beef cattle population however, no investigations have yet been performed regarding the prevalence and geographical distribution of BCV and BRSV. A cross-sectional serological survey for BCV and BRSV was carried out in Swedish beef cattle to explore any geographical patterns of these infections.     

Autism and intellectual disability are differentially related to sociodemographic background at birth

Background

Research findings investigating the sociodemographics of autism spectrum disorder (ASD) have been inconsistent and rarely considered the presence of intellectual disability (ID).

Methods

We used population data on Western Australian singletons born from 1984 to 1999 (n = 398,353) to examine the sociodemographic characteristics of children diagnosed with ASD with or without ID, or ID without ASD compared with non-affected children.

Results

The profiles for the four categories examined, mild-moderate ID, severe ID, ASD without ID and ASD with ID varied considerably and we often identified a gradient effect where the risk factors for mild-moderate ID and ASD without ID were at opposite extremes while those for ASD with ID were intermediary. This was demonstrated clearly with increased odds of ASD without ID amongst older mothers aged 35 years and over (odds ratio (OR) = 1.69 [CI: 1.18, 2.43]), first born infants (OR = 2.78; [CI: 1.67, 4.54]), male infants (OR = 6.57 [CI: 4.87, 8.87]) and increasing socioeconomic advantage. In contrast, mild-moderate ID was associated with younger mothers aged less than 20 years (OR = 1.88 [CI: 1.57, 2.25]), paternal age greater than 40 years (OR = 1.59 [CI: 1.36, 1.86]), Australian-born and Aboriginal mothers (OR = 1.60 [CI: 1.41, 1.82]), increasing birth order and increasing social disadvantage (OR = 2.56 [CI: 2.27, 2.97]). Mothers of infants residing in regional or remote areas had consistently lower risk of ASD or ID and may be linked to reduced access to services or under-ascertainment rather than a protective effect of location.

Conclusions

The different risk profiles observed between groups may be related to aetiological differences or ascertainment factors or both. Untangling these pathways is challenging but an urgent public health priority in view of the supposed autism epidemic.     

Phylogenetic relationships within Echinococcus and Taenia tapeworms (Cestoda: Taeniidae): an inference from nuclear protein-coding genes

The family Taeniidae of tapeworms is composed of two genera, Echinococcus and Taenia, which obligately parasitize mammals including humans. Inferring phylogeny via molecular markers is the only way to trace back their evolutionary histories. However, molecular dating approaches are lacking so far. Here we established new markers from nuclear protein-coding genes for RNA polymerase II second largest subunit (rpb2), phosphoenolpyruvate carboxykinase (pepck) and DNA polymerase delta (pold). Bayesian inference and maximum likelihood analyses of the concatenated gene sequences allowed us to reconstruct phylogenetic trees for taeniid parasites. The tree topologies clearly demonstrated that Taenia is paraphyletic and that the clade of Echinococcus oligarthrus and Echinococcusvogeli is sister to all other members of Echinococcus. Both species are endemic in Central and South America, and their definitive hosts originated from carnivores that immigrated from North America after the formation of the Panamanian land bridge about 3 million years ago (Ma). A time-calibrated phylogeny was estimated by a Bayesian relaxed-clock method based on the assumption that the most recent common ancestor of E. oligarthrus and E. vogeli existed during the late Pliocene (3.0 Ma). The results suggest that a clade of Taenia including human-pathogenic species diversified primarily in the late Miocene (11.2 Ma), whereas Echinococcus started to diversify later, in the end of the Miocene (5.8 Ma). Close genetic relationships among the members of Echinococcus imply that the genus is a young group in which speciation and global radiation occurred rapidly.     

The apparent uptake of fluorescently labeled siRNAs by electroporated cells depends on the fluorochrome

Transfection of mammalian cells with preformed small interfering RNAs (siRNAs) permits a transient and often specific reduction of gene expression. It is possible to rapidly examine the uptake of siRNAs by transfection with fluorescently labeled siRNAs. We examined the apparent uptake of such siRNAs by several leukemic cell lines after electroporation. We show that Cy3 and Cy5-labeled siRNAs cause a significant amount of cell fluorescence, as judged by flow cytometry. In contrast, several fluorescein-labeled siRNAs could not be detected. Nevertheless, such fluoresceinated siRNAs efficiently suppressed a leukemic target gene, demonstrating that siRNA uptake must have taken place. Therefore, for cell electroporation, fluorescein-labeled siRNAs may lead to false negative results and should not be used to examine electroporation-mediated siRNA uptake.     

Plant proteomics in India and Nepal: current status and challenges ahead

Plant proteomics has made tremendous contributions in understanding the complex processes of plant biology. Here, its current status in India and Nepal is discussed. Gel-based proteomics is predominantly utilized on crops and non-crops to analyze majorly abiotic (49 %) and biotic (18 %) stress, development (11 %) and post-translational modifications (7 %). Rice is the most explored system (36 %) with major focus on abiotic mainly dehydration (36 %) stress. In spite of expensive proteomics setup and scarcity of trained workforce, output in form of publications is encouraging. To boost plant proteomics in India and Nepal, researchers have discussed ground level issues among themselves and with the International Plant Proteomics Organization (INPPO) to act in priority on concerns like food security. Active collaboration may help in translating this knowledge to fruitful applications.     

Microclimate and tree community linked to differences in lepidopteran larval communities between forest fragments and continuous forest

Aim  We aim to assess the impact of forest fragmentation on lepidopteran larval community and study the associations of microclimate and tree community with lepidopteran assemblage.
Location  Kibale National Park, Uganda.
Methods  We investigated the effects of forest fragmentation on leaf herbivory, density of lepidopteran caterpillars, species richness and diversity as well as the composition of herbivorous lepidopteran larval community. Microclimate, size of the fragment, distance to the continuous forest, and tree diversity were studied as possible explanatory factors. We sampled 10 Neoboutonia macrocalyx Pax. (Euphorbiaceae) trees in each fragment during dry and rainy season, total of four times, in a year to cover the seasonal variation.
Results  The rates of herbivory, total larval density and species richness were significantly lower in the forest fragments than in the continuous forest but species diversity expressed as Fisher's alpha did not differ. The dominance structure and community composition of the larval communities in the fragments was different from that of the continuous forest. None of the differences we observed were related to the fragment area or distance to the continuous forest. Instead, we found an indication of association between the herbivore and the tree communities. The fragments had significantly lower humidity during most of the day and higher temperature during the afternoons (14–17 h), which might partially explain the differences in lepidopteran larval communities.
Main conclusions  Decreased larval density and species richness as well as differences in the community composition and structure all highlight the importance of large continuous forest areas for maintaining larval biodiversity.     

Psoriatic arthritis and sacroiliitis are associated with increased vascular inflammation by 18-fluorodeoxyglucose positron emission tomography computed tomography: baseline report from the Psoriasis Atherosclerosis and Cardiometabolic Disease Initiative

Introduction

Psoriasis and psoriatic arthritis (PsA) increase cardiovascular disease (CVD) risk, but surrogate markers for CVD in these disorders are inadequate. Because the presence of sacroiliitis may portend more severe PsA, we hypothesized that sacroiliitis defined by computed tomography (CT) would be associated with increased vascular inflammation defined by 18-fluorodeoxyglucose-positron emission tomography/computed tomography (FDG-PET/CT), which is an established measure of CVD.

Methods

Participants (n = 65) underwent whole-body FDG-PET/CT. Metabolic activity of the aorta was measured using the maximal standardized uptake value (SUV_max), a measure of atherosclerotic plaque activity. The primary outcome was aortic vascular inflammation. Linear regression (with β-coefficients (β) and P-values reported for PsA and sacroiliitis) was used to adjust for CVD risk factors to determine associations of PsA or sacroiliitis with vascular inflammation. Likelihood ratio testing was performed to evaluate the contribution of sacroiliitis to vascular disease estimation compared to the effects of PsA and traditional CVD risk factors.

Results

Vascular inflammation (measured as SUV_max) was greater (P < 0.001) in patients with sacroiliitis (mean ± SD = 7.33 ± 2.09) defined by CT compared to those without sacroiliitis (6.39 ± 1.49, P = 0.038). There were associations between PsA and aortic inflammation (β = 0.124, P < 0.001) and between sacroiliitis and aortic inflammation (β = 0.270, P < 0.001) after adjusting for CVD risk factors. Sacroiliitis predicted vascular inflammation beyond PsA and CVD risk factors (χ² = 124.6, P < 0.001).

Conclusions

Sacroiliitis is associated with increased vascular inflammation detected by FDG-PET/CT, suggesting that sacroiliac joint disease may identify patients at greater risk for CVD. Large, ongoing prospective studies are required to confirm these findings.

Electronic supplementary material

The online version of this article (doi:10.1186/ar4676) contains supplementary material, which is available to authorized users.     

Large amounts of labile organic carbon in permafrost soils of northern Alaska

Permafrost‐affected soils of the northern circumpolar region represent 50% of the terrestrial soil organic carbon (SOC) reservoir and are most strongly affected by climatic change. There is growing concern that this vast SOC pool could transition from a net C sink to a source. But so far little is known on how the organic matter (OM) in permafrost soils will respond in a warming future, which is governed by OM composition and possible stabilization mechanisms. To investigate if and how SOC in the active layer and adjacent permafrost is protected against degradation, we employed density fractionation to separate differently stabilized SOM fractions. We studied the quantity and quality of OM in different compartments using elemental analysis, ¹³C solid‐phase nuclear magnetic resonance (¹³C‐NMR) spectroscopy, and ¹⁴C analyses. The soil samples were derived from 16 cores from drained thaw lake basins, ranging from 0 to 5500 years of age, representing a unique series of developing Arctic soils over time. The normalized SOC stocks ranged between 35.5 and 86.2 kg SOC m^?3, with the major amount of SOC located in the active layers. The SOC stock is dominated by large amounts of particulate organic matter (POM), whereas mineral‐associated OM especially in older soils is of minor importance on a mass basis. We show that tremendous amounts of over 25 kg OC per square meter are stored as presumably easily degradable OM rich in carbohydrates. Only about 10 kg OC per square meter is present as presumably more stable, mineral‐associated OC. Significant amounts of the easily degradable, carbohydrate‐rich OM are preserved in the yet permanently frozen soil below the permafrost table. Forced by global warming, this vast labile OM pool could soon become available for microbial degradation due to the continuous deepening of the annually thawing active layer.     

Systematic Artifacts in Support Vector Regression-Based Compound Potency Prediction Revealed by Statistical and Activity Landscape Analysis

Support vector machines are a popular machine learning method for many classification tasks in biology and chemistry. In addition, the support vector regression (SVR) variant is widely used for numerical property predictions. In chemoinformatics and pharmaceutical research, SVR has become the probably most popular approach for modeling of non-linear structure-activity relationships (SARs) and predicting compound potency values. Herein, we have systematically generated and analyzed SVR prediction models for a variety of compound data sets with different SAR characteristics. Although these SVR models were accurate on the basis of global prediction statistics and not prone to overfitting, they were found to consistently mispredict highly potent compounds. Hence, in regions of local SAR discontinuity, SVR prediction models displayed clear limitations. Compared to observed activity landscapes of compound data sets, landscapes generated on the basis of SVR potency predictions were partly flattened and activity cliff information was lost. Taken together, these findings have implications for practical SVR applications. In particular, prospective SVR-based potency predictions should be considered with caution because artificially low predictions are very likely for highly potent candidate compounds, the most important prediction targets.     

Modelling interactions of acid–base balance and respiratory status in the toxicity of metal mixtures in the American oyster Crassostrea virginica

Heavy metals, such as copper, zinc and cadmium, represent some of the most common and serious pollutants in coastal estuaries. In the present study, we used a combination of linear and artificial neural network (ANN) modelling to detect and explore interactions among low-dose mixtures of these heavy metals and their impacts on fundamental physiological processes in tissues of the Eastern oyster, Crassostrea virginica. Animals were exposed to Cd (0.001–0.400 μM), Zn (0.001–3.059 μM) or Cu (0.002–0.787 μM), either alone or in combination for 1 to 27 days. We measured indicators of acid–base balance (hemolymph pH and total CO₂), gas exchange (Po₂), immunocompetence (total hemocyte counts, numbers of invasive bacteria), antioxidant status (glutathione, GSH), oxidative damage (lipid peroxidation; LPx), and metal accumulation in the gill and the hepatopancreas. Linear analysis showed that oxidative membrane damage from tissue accumulation of environmental metals was correlated with impaired acid–base balance in oysters. ANN analysis revealed interactions of metals with hemolymph acid–base chemistry in predicting oxidative damage that were not evident from linear analyses. These results highlight the usefulness of machine learning approaches, such as ANNs, for improving our ability to recognize and understand the effects of sub-acute exposure to contaminant mixtures.