Growing hybrid poplar for bioenergy in the PNW

This manual is intended for growers who are interested in the production of hybrid poplar trees (genus Populus) on short coppice rotations as feedstock for biorefineries. Although there are other methods for growing and harvesting hybrid poplar trees for other product markets, this manual is intended to specifically describe the feedstock production portion of the supply chain for biofuel and bio-based product industries. When grown as a coppice, hybrid poplar trees produce a consistent and readily available biomass feedstock for bio-based industries. Using the methods described in this manual, poplar growers can produce a reliable, high-quality, renewable feedstock with uniform chemical properties for ease of conversion that is free of dirt and debris and that can be delivered to the biorefinery at a consistent price

Automated Analysis of Flow Cytometry Data to Reduce Inter-Lab Variation in the Detection of Major Histocompatibility Complex Multimer-Binding T Cells

Manual analysis of flow cytometry data and subjective gate-border decisions taken by individuals continue to be a source of variation in the assessment of antigen-specific T cells when comparing data across laboratories, and also over time in individual labs. Therefore, strategies to provide automated analysis of major histocompatibility complex (MHC) multimer-binding T cells represent an attractive solution to decrease subjectivity and technical variation. The challenge of using an automated analysis approach is that MHC multimer-binding T cell populations are often rare and therefore difficult to detect. We used a highly heterogeneous dataset from a recent MHC multimer proficiency panel to assess if MHC multimer-binding CD8+ T cells could be analyzed with computational solutions currently available, and if such analyses would reduce the technical variation across different laboratories. We used three different methods, FLOw Clustering without K (FLOCK), Scalable Weighted Iterative Flow-clustering Technique (SWIFT), and ReFlow to analyze flow cytometry data files from 28 laboratories. Each laboratory screened for antigen-responsive T cell populations with frequency ranging from 0.01 to 1.5% of lymphocytes within samples from two donors. Experience from this analysis shows that all three programs can be used for the identification of high to intermediate frequency of MHC multimer-binding T cell populations, with results very similar to that of manual gating. For the less frequent populations (<0.1% of live, single lymphocytes), SWIFT outperformed the other tools. As used in this study, none of the algorithms offered a completely automated pipeline for identification of MHC multimer populations, as varying degrees of human interventions were needed to complete the analysis. In this study, we demonstrate the feasibility of using automated analysis pipelines for assessing and identifying even rare populations of antigen-responsive T cells and discuss the main properties, differences, and advantages of the different methods tested

The effects of induced emotions on pro-social behaviour

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Emotions are commonly experienced and expressed in human societies; however, their consequences on economic behaviour have received only limited attention. This paper investigates the effects of induced positive and negative emotions on cooperation and sanctioning behaviour in a one-shot voluntary contributions mechanism game, where personal and social interests are at odds. We concentrate on two specific emotions: anger and happiness. Our findings provide clear evidence that measures of social preferences are sensitive to subjects' current emotional states. Specifically, angry subjects contribute, on average, less than happy subjects and overall welfare as measured by average net earnings is lower when subjects are in an angry mood. We also find that how punishment is used is affected by moods: angry subjects punish harsher than happy subjects, ceteris paribus. These findings suggest that anger, when induced, can have a negative impact on economic behaviour

Children s Acceptance of a Collaborative Problem Solving Game Based on Physical Versus Digital Learning Spaces

[EN] Collaborative problem solving (CPS) is an essential soft skill that should be fostered from a young age. Research shows that a good way of teaching such skills is through video games; however, the success and viability of this method may be affected by the technological platform used. In this work we propose a gameful approach to train CPS skills in the form of the CPSbot framework and describe a study involving 80 primary school children on user experience and acceptance of a game, Quizbot, using three different technological platforms: two purely digital (tabletop and handheld tablets) and another based on tangible interfaces and physical spaces. The results show that physical spaces proved to be more effective than the screen-based platforms in several ways, as well as being considered more fun and easier to use by the children. Finally, we propose a set of design considerations for future gameful CPS systems based on the observations made during this study.Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (project TIN2014-60077-R); Spanish Ministry of Education, Culture and Sport (with fellowship FPU14/00136) and Conselleria d'Educacio, Cultura i Esport (Generalitat Valenciana, Spain) (grant ACIF/2014/214).Jurdi, S.; García Sanjuan, F.; Nácher-Soler, VE.; Jaén Martínez, FJ. (2018). Children s Acceptance of a Collaborative Problem Solving Game Based on Physical Versus Digital Learning Spaces. Interacting with Computers. 30(3):187-206. https://doi.org/10.1093/iwc/iwy006S18720630

Interventions to Influence Consulting and Antibiotic Use for Acute Respiratory Tract Infections in Children: A Systematic Review and Meta-Analysis

BACKGROUND: Respiratory tract infections (RTIs) are common in children and generally self-limiting, yet often result in consultations to primary care. Frequent consultations divert resources from care for potentially more serious conditions and increase the opportunity for antibiotic overuse. Overuse of antibiotics is associated with adverse effects and antimicrobial resistance, and has been shown to influence how patients seek care in ensuing illness episodes. METHODOLOGY/PRINCIPAL FINDINGS: We conducted a systematic review and meta-analysis to assess the effectiveness of interventions directed towards parents or caregivers which were designed to influence consulting and antibiotic use for respiratory tract infections (RTIs) in children in primary care. Main outcomes were parental consulting rate, parental knowledge, and proportion of children subsequently consuming antibiotics. Of 5,714 references, 23 studies (representing 20 interventions) met inclusion criteria. Materials designed to engage children in addition to parents were effective in modifying parental knowledge and behaviour, resulting in reductions in consulting rates ranging from 13 to 40%. Providing parents with delayed prescriptions significantly decreased reported antibiotic use (Risk Ratio (RR) 0.46 (0.40, 0.54); moreover, a delayed or no prescribing approach did not diminish parental satisfaction. CONCLUSIONS: IN ORDER TO BE MOST EFFECTIVE, INTERVENTIONS TO INFLUENCE PARENTAL CONSULTING AND ANTIBIOTIC USE SHOULD: engage children, occur prior to an illness episode, employ delayed prescribing, and provide guidance on specific symptoms. These results support the wider implementation of interventions to reduce inappropriate antibiotic use in children

Novel Blood Pressure Locus and Gene Discovery Using Genome-Wide Association Study and Expression Data Sets From Blood and the Kidney.

Elevated blood pressure is a major risk factor for cardiovascular disease and has a substantial genetic contribution. Genetic variation influencing blood pressure has the potential to identify new pharmacological targets for the treatment of hypertension. To discover additional novel blood pressure loci, we used 1000 Genomes Project-based imputation in 150 134 European ancestry individuals and sought significant evidence for independent replication in a further 228 245 individuals. We report 6 new signals of association in or near HSPB7, TNXB, LRP12, LOC283335, SEPT9, and AKT2, and provide new replication evidence for a further 2 signals in EBF2 and NFKBIA Combining large whole-blood gene expression resources totaling 12 607 individuals, we investigated all novel and previously reported signals and identified 48 genes with evidence for involvement in blood pressure regulation that are significant in multiple resources. Three novel kidney-specific signals were also detected. These robustly implicated genes may provide new leads for therapeutic innovation

The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals

To dissect the genetic architecture of blood pressure and assess effects on target-organ damage, we analyzed 128,272 SNPs from targeted and genome-wide arrays in 201,529 individuals of European ancestry and genotypes from an additional 140,886 individuals were used for validation. We identified 66 blood pressure loci, of which 17 were novel and 15 harbored multiple distinct association signals. The 66 index SNPs were enriched for cis-regulatory elements, particularly in vascular endothelial cells, consistent with a primary role in blood pressure control through modulation of vascular tone across multiple tissues. The 66 index SNPs combined in a risk score showed comparable effects in 64,421 individuals of non-European descent. The 66-SNP blood pressure risk score was significantly associated with target-organ damage in multiple tissues, with minor effects in the kidney. Our findings expand current knowledge of blood pressure pathways and highlight tissues beyond the classic renal system in blood pressure regulation

Dictator Games: A Meta Study

Over the last 25 years, more than a hundred dictator game experiments have been published. This meta study summarizes the evidence. Exploiting the fact that most experiments had to fix parameters they did not intend to test, the meta study explores a rich set of control variables for multivariate analysis. It shows that Tobit models (assuming that dictators would even want to take money) and hurdle models (assuming that the decision to give a positive amount is separate from the choice of amount, conditional on giving) outperform mere meta-regression and OLS