Relative validity of a web-based food frequency questionnaire for patients with type 1 and type 2 diabetes in Denmark

BACKGROUND: Diet has an important role in the management of diabetes. However, little is known about dietary intake in Danish diabetes patients. A food frequency questionnaire (FFQ) focusing on most relevant nutrients in diabetes including carbohydrates, dietary fibres and simple sugars was developed and validated. OBJECTIVES: To examine the relative validity of nutrients calculated by a web-based food frequency questionnaire for patients with diabetes. DESIGN: The FFQ was validated against a 4-day pre-coded food diary (FD). Intakes of nutrients were calculated. Means of intake were compared and cross-classifications of individuals according to intake were performed. To assess the agreement between the two methods, Pearson and Spearman's correlation coefficients and weighted kappa coefficients were calculated. SUBJECTS: Ninety patients (64 with type 1 diabetes and 26 with type 2 diabetes) accepted to participate in the study. Twenty-six were excluded from the final study population. SETTING: 64 volunteer diabetes patients at the Steno Diabetes Center. RESULTS: Intakes of carbohydrates, simple sugars, dietary fibres and total energy were higher according to the FFQ compared with the FD. However, intakes of nutrients were grossly classified in the same or adjacent quartiles with an average of 82% of the selected nutrients when comparing the two methods. In general, moderate agreement between the two methods was found. CONCLUSION: The FFQ was validated for assessment of a range of nutrients. Comparing the intakes of selected nutrients (carbohydrates, dietary fibres and simple sugars), patients were classified correctly according to low and high intakes. The FFQ is a reliable dietary assessment tool to use in research and evaluation of patient education for patients with diabetes

When a tree dies in the forest : scaling climate-driven tree mortality to ecosystem water and carbon fluxes

Altres ajuts: COST FP1106 network STReESS.Drought- and heat-driven tree mortality, along with associated insect outbreaks, have been observed globally in recent decades and are expected to increase in future climates. Despite its potential to profoundly alter ecosystem carbon and water cycles, how tree mortality scales up to ecosystem functions and fluxes is uncertain. We describe a framework for this scaling where the effects of mortality are a function of the mortality attributes, such as spatial clustering and functional role of the trees killed, and ecosystem properties, such as productivity and diversity. We draw upon remote-sensing data and ecosystem flux data to illustrate this framework and place climate-driven tree mortality in the context of other major disturbances. We find that emerging evidence suggests that climate-driven tree mortality impacts may be relatively small and recovery times are remarkably fast (~4 years for net ecosystem production). We review the key processes in ecosystem models necessary to simulate the effects of mortality on ecosystem fluxes and highlight key research gaps in modeling. Overall, our results highlight the key axes of variation needed for better monitoring and modeling of the impacts of tree mortality and provide a foundation for including climate-driven tree mortality in a disturbance framework

Factors Determining Mortality of Adult Chaparral Shrubs in an Extreme Drought Year in California

We measured dieback and mortality in a chaparral shrub community at a chaparral/desert ecotone following four years of below-average rainfall. Ecotones are important systems in which to examine plant and community responses to extreme and prolonged drought conditions and the potential impact of global change on plant distributions and community composition. Following a particularly severe drought year, dieback and mortality were documented for seven co-dominant shrub species. We examined whether mortality was related to species ecology, leaf traits, or water relations. Dieback and mortality were greatest in two non-sprouting species. These species also had high xylem cavitation resistance and low specific leaf area compared to several sprouting species. Among two sprouting congeners, mortality was greater in the more shallowly rooted species, even though this species was more cavitation resistant. Across all species, those that were more resistant to cavitation had greater mortality. Evidently, high resistance to xylem cavitation does not prevent adult plant mortality at chaparral/desert ecotones. A series of extreme drought years could preferentially reduce or eliminate non-sprouting species from mixed chaparral populations, causing a shift in community structure and contributing to desertification

Biophysical suitability, economic pressure and land-cover change: a global probabilistic approach and insights for REDD+

There has been a concerted effort by the international scientific community to understand the multiple causes and patterns of land-cover change to support sustainable land management. Here, we examined biophysical suitability, and a novel integrated index of “Economic Pressure on Land” (EPL) to explain land cover in the year 2000, and estimated the likelihood of future land-cover change through 2050, including protected area effectiveness. Biophysical suitability and EPL explained almost half of the global pattern of land cover (R 2 = 0.45), increasing to almost two-thirds in areas where a long-term equilibrium is likely to have been reached (e.g. R 2 = 0.64 in Europe). We identify a high likelihood of future land-cover change in vast areas with relatively lower current and past deforestation (e.g. the Congo Basin). Further, we simulated emissions arising from a “business as usual” and two reducing emissions from deforestation and forest degradation (REDD) scenarios by incorporating data on biomass carbon. As our model incorporates all biome types, it highlights a crucial aspect of the ongoing REDD + debate: if restricted to forests, “cross-biome leakage” would severely reduce REDD + effectiveness for climate change mitigation. If forests were protected from deforestation yet without measures to tackle the drivers of land-cover change, REDD + would only reduce 30 % of total emissions from land-cover change. Fifty-five percent of emissions reductions from forests would be compensated by increased emissions in other biomes. These results suggest that, although REDD + remains a very promising mitigation tool, implementation of complementary measures to reduce land demand is necessary to prevent this leakage

Land use not litter quality is a stronger driver of decomposition in hyperdiverse tropical forest

Funded by Natural Environment Research Council. Grant Number: NE/K016253/1Peer reviewedPublisher PD

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Search for Heavy Neutral and Charged Leptons in e+ e- Annihilation at LEP

A search for exotic unstable neutral and charged heavy leptons as well as for stable charged heavy leptons is performed with the L3 detector at LEP. Sequential, vector and mirror natures of heavy leptons are considered. No evidence for their existence is found and lower limits on their masses are set

Measurement of the Tau Branching Fractions into Leptons

Using data collected with the L3 detector near the Z resonance, corresponding to an integrated luminosity of 150pb-1, the branching fractions of the tau lepton into electron and muon are measured to be B(tau->e nu nu) = (17.806 +- 0.104 (stat.) +- 0.076 (syst.)) %, B(tau->mu nu nu) = (17.342 +- 0.110 (stat.) +- 0.067 (syst.)) %. From these results the ratio of the charged current coupling constants of the muon and the electron is determined to be g_mu/g_e = 1.0007 +- 0.0051. Assuming electron-muon universality, the Fermi constant is measured in tau lepton decays as G_F = (1.1616 +- 0.0058) 10^{-5} GeV^{-2}. Furthermore, the coupling constant of the strong interaction at the tau mass scale is obtained as alpha_s(m_tau^2) = 0.322 +- 0.009 (exp.) +- 0.015 (theory)