Comparison of four models simulating phosphorus dynamics in Lake Vänern, Sweden

International audienceThis paper compares four water quality models applied to Lake Vänern, Sweden. The comparison is focused on phosphorus, the primary limiting nutrient in Lake Vänern. Two of the models, FYRISÅ and HBV­NP, are simple and were developed as parts of catchment models. Two other models, called LEEDS and BIOLA, are more comprehensive lake models. The models were calibrated using data from the period 1985?1992 and validated using data from the period 1993?2000. The fit to calibration data is similar for the FYRISÅ, HBV­NP, and LEEDS models, and slightly worse for the BIOLA model. All models fit the validation data almost as well as the calibration data. The models' behaviour was tested in two representative scenarios. An increase of emissions by 40% from a pulp and paper mill has a negligible effect on the water quality, while a decrease in phosphorus load by 14% (accomplished by better waste-water treatment in rural households) gives a considerable decrease in phosphorus concentration in the lake. Still, the results of the scenarios vary between the models. Keywords: lake, phosphorus, model, scenarios, simulatio

INEF12Basketball Dataset and the Group Behavior Recognition Issue

Proceedings of: 9th Conference on Practical Applications of Agents and Multi-Agent Systems. Workshop on User-Centric Technologies and Applications (CONTEXTS 2012), Salamanca, March 28-30, 2012Activity recognition is one of the most prolific fields of research. For this reason, there are new fields of research that expand the possibilities of the activity recognition: Group behavior recognition. This field does not limit the number of elements in the scene, and there are a lot of new elements that must be analyzed. Each group, like each individual element, has its behavior, but this behavior depends on their elements, and the relationships between these elements. All these new elements cause that group behavior recognition was a new field of research, with some similar elements but it must be studied apart. This way, group behavior recognition is a novel field, in which there are not many researches and there are not many datasets that could be used by researchers. This situation causes the slow advance of the science in this field. This paper tries to show a complete description of the problem domain, with all the possible variants, a formal description and show a novel architecture used to solve this issue. Also describes a specific group behavior recognition dataset, and shows how it could be usedThis work was supported in part by Projects CICYT TIN2011-28620-C02-01, CICYT TEC2011-28626-C02-02, CAMCONTEXTS (S2009/TIC-1485) and DPS2008-07029-C02-02Publicad

Comparative Network Analysis of Preterm vs. Full-Term Infant-Mother Interactions

Several studies have reported that interactions of mothers with preterm infants show differential characteristics compared to that of mothers with full-term infants. Interaction of preterm dyads is often reported as less harmonious. However, observations and explanations concerning the underlying mechanisms are inconsistent. In this work 30 preterm and 42 full-term mother-infant dyads were observed at one year of age. Free play interactions were videotaped and coded using a micro-analytic coding system. The video records were coded at one second resolution and studied by a novel approach using network analysis tools. The advantage of our approach is that it reveals the patterns of behavioral transitions in the interactions. We found that the most frequent behavioral transitions are the same in the two groups. However, we have identified several high and lower frequency transitions which occur significantly more often in the preterm or full-term group. Our analysis also suggests that the variability of behavioral transitions is significantly higher in the preterm group. This higher variability is mostly resulted from the diversity of transitions involving non-harmonious behaviors. We have identified a maladaptive pattern in the maternal behavior in the preterm group, involving intrusiveness and disengagement. Application of the approach reported in this paper to longitudinal data could elucidate whether these maladaptive maternal behavioral changes place the infant at risk for later emotional, cognitive and behavioral disturbance

A distinct adipose tissue gene expression response to caloric restriction predicts 6-mo weight maintenance in obese subjects

BACKGROUND: Weight loss has been shown to reduce risk factors associated with cardiovascular disease and diabetes; however, successful maintenance of weight loss continues to pose a challenge. OBJECTIVE: The present study was designed to assess whether changes in subcutaneous adipose tissue (scAT) gene expression during a low-calorie diet (LCD) could be used to differentiate and predict subjects who experience successful short-term weight maintenance from subjects who experience weight regain. DESIGN: Forty white women followed a dietary protocol consisting of an 8-wk LCD phase followed by a 6-mo weight-maintenance phase. Participants were classified as weight maintainers (WMs; 0-10% weight regain) and weight regainers (WRs; 50-100% weight regain) by considering changes in body weight during the 2 phases. Anthropometric measurements, bioclinical variables, and scAT gene expression were studied in all individuals before and after the LCD. Energy intake was estimated by using 3-d dietary records. RESULTS: No differences in body weight and fasting insulin were observed between WMs and WRs at baseline or after the LCD period. The LCD resulted in significant decreases in body weight and in several plasma variables in both groups. WMs experienced a significant reduction in insulin secretion in response to an oral-glucose-tolerance test after the LCD; in contrast, no changes in insulin secretion were observed in WRs after the LCD. An ANOVA of scAT gene expression showed that genes regulating fatty acid metabolism, citric acid cycle, oxidative phosphorylation, and apoptosis were regulated differently by the LCD in WM and WR subjects. CONCLUSION: This study suggests that LCD-induced changes in insulin secretion and scAT gene expression may have the potential to predict successful short-term weight maintenanc

Parent-of-origin-specific allelic associations among 106 genomic loci for age at menarche.

Age at menarche is a marker of timing of puberty in females. It varies widely between individuals, is a heritable trait and is associated with risks for obesity, type 2 diabetes, cardiovascular disease, breast cancer and all-cause mortality. Studies of rare human disorders of puberty and animal models point to a complex hypothalamic-pituitary-hormonal regulation, but the mechanisms that determine pubertal timing and underlie its links to disease risk remain unclear. Here, using genome-wide and custom-genotyping arrays in up to 182,416 women of European descent from 57 studies, we found robust evidence (P < 5 × 10(-8)) for 123 signals at 106 genomic loci associated with age at menarche. Many loci were associated with other pubertal traits in both sexes, and there was substantial overlap with genes implicated in body mass index and various diseases, including rare disorders of puberty. Menarche signals were enriched in imprinted regions, with three loci (DLK1-WDR25, MKRN3-MAGEL2 and KCNK9) demonstrating parent-of-origin-specific associations concordant with known parental expression patterns. Pathway analyses implicated nuclear hormone receptors, particularly retinoic acid and γ-aminobutyric acid-B2 receptor signalling, among novel mechanisms that regulate pubertal timing in humans. Our findings suggest a genetic architecture involving at least hundreds of common variants in the coordinated timing of the pubertal transition

Shared genetic variants suggest common pathways in allergy and autoimmune diseases.

BACKGROUND: The relationship between allergy and autoimmune disorders is complex and poorly understood. OBJECTIVE: To investigate commonalities in genetic loci and pathways between allergy and autoimmune diseases to elucidate shared disease mechanisms. METHODS: We meta-analyzed two GWAS on self-reported allergy and sensitization comprising a total of 62,330 individuals. These results were used to calculate enrichment for SNPs previously associated with autoimmune diseases. Furthermore, we probed for enrichment within genetic pathways and of transcription factor binding sites, and characterized commonalities in the variant burden on tissue-specific regulatory sites by calculating the enrichment of allergy SNPs falling in gene regulatory regions in various cells using Encode Roadmap DHS data, and compared the allergy data with all known diseases. RESULTS: Among 290 loci previously associated with 16 autoimmune diseases, we found a significant enrichment of loci also associated with allergy (p=1.4e-17) encompassing 29 loci at a false discovery rate<0.05. Such enrichment seemed to be a general characteristic for all autoimmune diseases. Among the common loci, 48% had the same direction of effect for allergy and autoimmune diseases. Additionally, we observed an enrichment of allergy SNPs falling within immune pathways and regions of chromatin accessible in immune cells that was also represented in autoimmune diseases, but not in other diseases. CONCLUSION: We identified shared susceptibility loci and commonalities in pathways between allergy and autoimmune diseases, suggesting shared diseases mechanisms. Further studies of these shared genetic mechanisms might help understanding the complex relationship between these diseases, including the parallel increase in disease prevalence

Genome-wide association study identifies 30 loci associated with bipolar disorder.

Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study (GWAS) including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P &lt; 1 × 10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (P &lt; 5 × 10-8) in the discovery GWAS were not genome-wide significant in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis, 30 loci were genome-wide significant, including 20 newly identified loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene sets, including regulation of insulin secretion and endocannabinoid signaling. Bipolar I disorder is strongly genetically correlated with schizophrenia, driven by psychosis, whereas bipolar II disorder is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential biological mechanisms for bipolar disorder

Genome-wide association and HLA fine-mapping studies identify risk loci and genetic pathways underlying allergic rhinitis

Allergic rhinitis is the most common clinical presentation of allergy, affecting 400 million people worldwide, with increasing incidence in westernized countries1,2. To elucidate the genetic architecture and understand the underlying disease mechanisms, we carried out a meta-analysis of allergic rhinitis in 59,762 cases and 152,358 controls of European ancestry and identified a total of 41 risk loci for allergic rhinitis, including 20 loci not previously associated with allergic rhinitis, which were confirmed in a replication phase of 60,720 cases and 618,527 controls. Functional annotation implicated genes involved in various immune pathways, and fine mapping of the HLA region suggested amino acid variants important for antigen binding. We further performed genome-wide association study (GWAS) analyses of allergic sensitization against inhalant allergens and nonallergic rhinitis, which suggested shared genetic mechanisms across rhinitis-related traits. Future studies of the identified loci and genes might identify novel targets for treatment and prevention of allergic rhinitis