Neighbour identity hardly affects litter-mixture effects on decomposition rates of New Zealand forest species.

The mass loss of litter mixtures is often different than expected based on the mass loss of the component species. We investigated if the identity of neighbour species affects these litter-mixing effects. To achieve this, we compared decomposition rates in monoculture and in all possible two-species combinations of eight tree species, widely differing in litter chemistry, set out in two contrasting New Zealand forest types. Litter from the mixed-species litter bags was separated into its component species, which allowed us to quantify the importance of litter-mixing effects and neighbour identity, relative to the effects of species identity, litter chemistry and litter incubation environment. Controlling factors on litter decomposition rate decreased in importance in the order: species identity (litter quality) >> forest type >> neighbour species. Species identity had the strongest influence on decomposition rate. Interspecific differences in initial litter lignin concentration explained a large proportion of the interspecific differences in litter decomposition rate. Litter mass loss was higher and litter-mixture effects were stronger on the younger, more fertile alluvial soils than on the older, less-fertile marine terrace soils. Litter-mixture effects only shifted percentage mass loss within the range of 1.5%. There was no evidence that certain litter mixtures consistently showed interactive effects. Contrary to common theory, adding a relatively fast-decomposing species generally slowed down the decomposition of the slower decomposing species in the mixture. This study shows that: (1) species identity, litter chemistry and forest type are quantitatively the most important drivers of litter decomposition in a New Zealand rain forest; (2) litter-mixture effects—although statistically significant—are far less important and hardly depend on the identity and the chemical characteristics of the neighbour species; (3) additive effects predominate in this ecosystem, so that mass dynamics of the mixtures can be predicted from the monocultures

Development and validation of the Self-Regulation of Eating Behaviour Questionnaire for adults

Background Eating self-regulatory capacity can help individuals to cope with the obesogenic environment and achieve, as well as maintain, a healthy weight and diet. At present, there is no comprehensive, reliable and valid questionnaire for assessing this capacity and measuring change in response to self-regulation interventions in adults. This paper reports the development of the Self-regulation of Eating Behaviour Questionnaire (SREBQ) for use in UK adults, and presents evidence for its reliability and construct validity. The development of the SREBQ involved generation of an item pool, followed by two pilot studies (Samples 1 and 2) and a test of the questionnaire’s underlying factor structure (Sample 3). The final version of the SREBQ was then assessed for reliability and construct validity (Sample 4). Results Development of the SREBQ resulted in a 5-item questionnaire. The face validity was satisfactory, as assessed by the pilot studies. The factor structure analysis (Sample 3) suggested that it has a single underlying factor, which was confirmed in a second sample (Sample 4). The SREBQ had strong construct validity, showing a positive correlation with general measures of self-regulation. It was also positively correlated with motivation and behavioural automaticity, and negatively correlated with food responsiveness and emotional over-eating (p < 0.001). It showed good discriminant validity, as it was only weakly associated with satiety responsiveness, food fussiness and slowness in eating. Conclusions The SREBQ is a reliable and valid measure for assessment of eating self-regulatory capacity in the general UK adult population

Uncovering the nutritional landscape of food

Recent progresses in data-driven analysis methods, including network-based approaches, are revolutionizing many classical disciplines. These techniques can also be applied to food and nutrition, which must be studied to design healthy diets. Using nutritional information from over 1,000 raw foods, we systematically evaluated the nutrient composition of each food in regards to satisfying daily nutritional requirements. The nutrient balance of a food was quantified herein as nutritional fitness, using the food's frequency of occurrence in nutritionally adequate food combinations. Nutritional fitness offers prioritization of recommendable foods within a global network of foods, in which foods are connected based on the similarities of their nutrient compositions. We identified a number of key nutrients, such as choline and alpha-linolenic acid, whose levels in foods can critically affect the foods' nutritional fitness. Analogously, pairs of nutrients can have the same effect. In fact, two nutrients can impact the nutritional fitness synergistically, although the individual nutrients alone may not. This result, involving the tendency among nutrients to show correlations in their abundances across foods, implies a hidden layer of complexity when exploring for foods whose balance of nutrients within pairs holistically helps meet nutritional requirements. Interestingly, foods with high nutritional fitness successfully maintain this nutrient balance. This effect expands our scope to a diverse repertoire of nutrient-nutrient correlations, integrated under a common network framework that yields unexpected yet coherent associations between nutrients. Our nutrient-profiling approach combined with a network-based analysis provides a more unbiased, global view of the relationships between foods and nutrients, and can be extended towards nutritional policies, food marketing, and personalized nutrition.Comment: Supplementary material is available at the journal websit

Oxygen saturation and outcomes in preterm infants

BACKGROUN

Legacy Effects of Canopy Disturbance on Ecosystem Functioning in Macroalgal Assemblages

Macroalgal assemblages are some of the most productive systems on earth and they contribute significantly to nearshore ecosystems. Globally, macroalgal assemblages are increasingly threatened by anthropogenic activities such as sedimentation, eutrophication and climate change. Despite this, very little research has considered the potential effects of canopy loss on primary productivity, although the literature is rich with evidence showing the ecological effects of canopy disturbance. In this study we used experimental removal plots of habitat-dominating algae (Order Fucales) that had been initiated several years previously to construct a chronosequence of disturbed macroalgal communities and to test if there were legacy effects of canopy loss on primary productivity. We used in situ photo-respirometry to test the primary productivity of algal assemblages in control and removal plots at two intertidal elevations. In the mid tidal zone assemblage, the removal plots at two sites had average primary productivity values of only 40% and 60% that of control areas after 90 months. Differences in productivity were associated with lower biomass and density of the fucoid algal canopy and lower taxa richness in the removal plots after 90 months. Low-shore plots, established three years earlier, showed that the loss of the large, dominant fucoid resulted in at least 50% less primary productivity of the algal assemblage than controls, which lasted for 90 months; other smaller fucoid species had recruited but they were far less productive. The long term reduction in primary productivity following a single episode of canopy loss of a dominant species in two tidal zones suggests that these assemblages are not very resilient to large perturbations. Decreased production output may have severe and long-lasting consequences on the surrounding communities and has the potential to alter nutrient cycling in the wider nearshore environment

Longitudinal Replication Studies of GWAS Risk SNPs Influencing Body Mass Index over the Course of Childhood and Adulthood

Genome-wide association studies (GWAS) have identified multiple common variants associated with body mass index (BMI). In this study, we tested 23 genotyped GWAS-significant SNPs (p-value<5*10-8) for longitudinal associations with BMI during childhood (3–17 years) and adulthood (18–45 years) for 658 subjects. We also proposed a heuristic forward search for the best joint effect model to explain the longitudinal BMI variation. After using false discovery rate (FDR) to adjust for multiple tests, childhood and adulthood BMI were found to be significantly associated with six SNPs each (q-value<0.05), with one SNP associated with both BMI measurements: KCTD15 rs29941 (q-value<7.6*10-4). These 12 SNPs are located at or near genes either expressed in the brain (BDNF, KCTD15, TMEM18, MTCH2, and FTO) or implicated in cell apoptosis and proliferation (FAIM2, MAP2K5, and TFAP2B). The longitudinal effects of FAIM2 rs7138803 on childhood BMI and MAP2K5 rs2241423 on adulthood BMI decreased as age increased (q-value<0.05). The FTO candidate SNPs, rs6499640 at the 5 ′-end and rs1121980 and rs8050136 downstream, were associated with childhood and adulthood BMI, respectively, and the risk effects of rs6499640 and rs1121980 increased as birth weight decreased. The best joint effect model for childhood and adulthood BMI contained 14 and 15 SNPs each, with 11 in common, and the percentage of explained variance increased from 0.17% and 9.0*10−6% to 2.22% and 2.71%, respectively. In summary, this study evidenced the presence of long-term major effects of genes on obesity development, implicated in pathways related to neural development and cell metabolism, and different sets of genes associated with childhood and adulthood BMI, respectively. The gene effects can vary with age and be modified by prenatal development. The best joint effect model indicated that multiple variants with effects that are weak or absent alone can nevertheless jointly exert a large longitudinal effect on BMI

Impact of socio-economic factors on stroke prevalence among urban and rural residents in Mainland China

<p>Abstract</p> <p>Background</p> <p>An inverse relationship between better socioeconomic status (total household income, education or occupation) and stroke has been established in developed communities, but family size has generally not been considered in the use of socioeconomic status indices. We explored the utility of Family Average Income (FAI) as a single index of socioeconomic status to examine the association with stroke prevalence in a region of China, and we also compared its performance as a single index of socioeconomic status with that of education and occupation.</p> <p>Methods</p> <p>A population-based cross-sectional study was conducted in Nanjing municipality of China during the period between October 2000 and March 2001. A total of 45 administrative villages were randomly selected using a multi-stage sampling approach and all regular local residents aged 35 years or above were included. Descriptive statistics and logistic regression models were used in analysis.</p> <p>Results</p> <p>The overall prevalence of diagnosed stroke was 1.54% in all 29,340 eligible participants. An elevated prevalence of stroke was associated with increasing levels of FAI. After adjustment for basic demographic variables (age, urban/rural area and gender) and a group of defined conventional risk factors, this gradient still remained significant, with participants in the highest (OR = 1.94, 95% CI = 1.40, 2.70) and middle (OR = 1.43, 95% CI = 1.01, 2.02) categories of FAI having higher risks compared with the lowest category. A significantly elevated OR of stroke prevalence was found in white collar workers compared to blue collar workers, while no significant relationship was observed with education.</p> <p>Conclusion</p> <p>Our study consistently revealed that the prevalence of stroke was associated with increasing levels of all SES indices, including FAI, education, and occupation. However, a significant gradient was only observed with FAI after controlling for important confounding factors. The findings suggested that, compared with occupation and education, FAI could be used as a more sensitive index of socio-economic status for public health studies in China.</p

Seabird Modulations of Isotopic Nitrogen on Islands

The transport of nutrients by migratory animals across ecosystem boundaries can significantly enrich recipient food webs, thereby shaping the ecosystems’ structure and function. To illustrate the potential role of islands in enabling the transfer of matter across ecosystem boundaries to be gauged, we investigated the influence of seabirds on nitrogen input on islands. Basing our study on four widely differing islands in terms of their biogeography and ecological characteristics, sampled at different spatial and temporal intervals, we analyzed the nitrogen isotopic values of the main terrestrial ecosystem compartments (vascular plants, arthropods, lizards and rodents) and their relationship to seabird values. For each island, the isotopic values of the ecosystem were driven by those of seabirds, which ultimately corresponded to changes in their marine prey. First, terrestrial compartments sampled within seabird colonies were the most enriched in δ15N compared with those collected at various distances outside colonies. Second, isotopic values of the whole terrestrial ecosystems changed over time, reflecting the values of seabirds and their prey, showing a fast turnover throughout the ecosystems. Our results demonstrate that seabird-derived nutrients not only spread across the terrestrial ecosystems and trophic webs, but also modulate their isotopic values locally and temporally on these islands. The wealth of experimental possibilities in insular ecosystems justifies greater use of these model systems to further our understanding of the modalities of trans-boundary nutrient transfers

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Compressed representation of a partially defined integer function over multiple arguments

In OLAP (OnLine Analitical Processing) data are analysed in an n-dimensional cube. The cube may be represented as a partially defined function over n arguments. Considering that often the function is not defined everywhere, we ask: is there a known way of representing the function or the points in which it is defined, in a more compact manner than the trivial one