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

Observation of Coulomb-Assisted Dipole-Forbidden Intraexciton Transitions in Semiconductors

We use terahertz pulses to induce resonant transitions between the eigenstates of optically generated exciton populations in a high-quality semiconductor quantum-well sample. Monitoring the excitonic photoluminescence, we observe transient quenching of the $1s$ exciton emission, which we attribute to the terahertz-induced $1s$-to-$2p$ excitation. Simultaneously, a pronounced enhancement of the $2s$-exciton emission is observed, despite the $1s$-to-$2s$ transition being dipole forbidden. A microscopic many-body theory explains the experimental observations as a Coulomb-scattering mixing of the 2$s$ and 2$p$ states, yielding an effective terahertz transition between the 1$s$ and 2$s$ populations.Comment: 5 pages, 3 figure

Soil fertility limits carbon sequestration by forest ecosystems in a CO2-enriched atmosphere

Northern mid-latitude forests are a large terrestrial carbon sink(1-4). Ignoring nutrient limitations, large increases in carbon sequestration from carbon dioxide (CO2) fertilization are expected in these forests(5). Yet, forests are usually relegated to sites of moderate to poor fertility, where tree growth is often limited by nutrient supply, in particular nitrogen(6,7). Here we present evidence that estimates of increases in carbon sequestration of forests, which is expected to partially compensate for increasing CO2 in the atmosphere, are unduly optimistic(8). In two forest experiments on maturing pines exposed to elevated atmospheric CO2, the CO2-induced biomass carbon increment without added nutrients was undetectable at a nutritionally poor site, and the stimulation at a nutritionally moderate site was transient, stabilizing at a marginal gain after three years. However, a large synergistic gain from higher CO2 and nutrients was detected with nutrients added. This gain was even larger at the poor site (threefold higher than the expected additive effect) than at the moderate site (twofold higher). Thus, fertility can restrain the response of wood carbon sequestration to increased atmospheric CO2. Assessment of future carbon sequestration should consider the limitations imposed by soil fertility, as well as interactions with nitrogen deposition.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/62517/1/411469a0.pd

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

Data on the use of dietary supplements in Danish patients with type 1 and type 2 diabetes

The data in this article describe the use of dietary supplements in Danish patients with type 1 diabetes (T1D) and type 2 diabetes (T2D). The data were collected from a web-based dietary survey on dietary habits in 774 patients with T1D (n = 426) and T2D (n = 348). The data demonstrate that 99% of the patients with diabetes use dietary supplements with no gender differences. In comparison, only 64% in the general population use dietary supplements [2].A higher proportion of people in the general population use multivitamin/mineral supplementation as compared to patients with diabetes (48% vs. 34–37%) and a higher proportion of women than men with diabetes use multivitamin/mineral supplementation (T1D: 43% women vs. 26% men and T2D: 45% women vs. 34% men). More patients with diabetes than the general population use supplements such as calcium together with vitamin D, vitamin D, vitamin B, vitamin C, vitamin E, magnesium, calcium, Q10, ginger, garlic, and other herbal supplements

Metal-saturated sulfide assemblages in NWA 2737: Evidence for impact-related sulfur devolatilization in Martian meteorites

International audienceNWA 2737, a Martian meteorite from the Chassignite subclass, contains minute amounts (0.010 ± 0.005 vol%) of metal-saturated Fe-Ni sulfides. These latter bear evidence of the strong shock effects documented by abundant Fe nanoparticles and planar defects in Northwest Africa (NWA) 2737 olivine. A Ni-poor troilite (Fe/S = 1.0 ± 0.01), sometimes Cr-bearing (up to 1 wt%), coexists with micrometer-sized taenite/tetrataenite-type native Ni-Fe alloys (Ni/Fe = 1) and Fe-Os-Ir-(Ru) alloys a few hundreds of nanometers across. The troilite has exsolved flame-like pentlandite (Fe/Fe + Ni = 0.5-0.6). Chalcopyrite is almost lacking, and no pyrite has been found. As a hot desert find, NWA 2737 shows astonishingly fresh sulfides. The composition of troilite coexisting with Ni-Fe alloys is completely at odds with Chassigny and Nahkla sulfides (pyrite + metal-deficient monoclinic-type pyrrhotite). It indicates strongly reducing crystallization conditions (close to IW), several log units below the fO2 conditions inferred from chromites compositions and accepted for Chassignites (FMQ-1 log unit). It is proposed that reduction in sulfides into base and precious metal alloys is operated via sulfur degassing, which is supported by the highly resorbed and denticulated shape of sulfide blebs and their spongy textures. Shock-related S degassing may be responsible for considerable damages in magmatic sulfide structures and sulfide assemblages, with concomitant loss of magnetic properties as documented in some other Martian meteorites

Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows

Background: Predicting progression from a stage of Mild Cognitive Impairment to dementia is a major pursuit in current research. It is broadly accepted that cognition declines with a continuum between MCI and dementia. As such, cohorts of MCI patients are usually heterogeneous, containing patients at different stages of the neurodegenerative process. This hampers the prognostic task. Nevertheless, when learning prognostic models, most studies use the entire cohort of MCI patients regardless of their disease stages. In this paper, we propose a Time Windows approach to predict conversion to dementia, learning with patients stratified using time windows, thus fine-tuning the prognosis regarding the time to conversion. Methods: In the proposed Time Windows approach, we grouped patients based on the clinical information of whether they converted (converter MCI) or remained MCI (stable MCI) within a specific time window. We tested time windows of 2, 3, 4 and 5 years. We developed a prognostic model for each time window using clinical and neuropsychological data and compared this approach with the commonly used in the literature, where all patients are used to learn the models, named as First Last approach. This enables to move from the traditional question "Will a MCI patient convert to dementia somewhere in the future" to the question "Will a MCI patient convert to dementia in a specific time window". Results: The proposed Time Windows approach outperformed the First Last approach. The results showed that we can predict conversion to dementia as early as 5 years before the event with an AUC of 0.88 in the cross-validation set and 0.76 in an independent validation set. Conclusions: Prognostic models using time windows have higher performance when predicting progression from MCI to dementia, when compared to the prognostic approach commonly used in the literature. Furthermore, the proposed Time Windows approach is more relevant from a clinical point of view, predicting conversion within a temporal interval rather than sometime in the future and allowing clinicians to timely adjust treatments and clinical appointments.FCT under the Neuroclinomics2 project [PTDC/EEI-SII/1937/2014, SFRH/BD/95846/2013]; INESC-ID plurianual [UID/CEC/50021/2013]; LASIGE Research Unit [UID/CEC/00408/2013

Can CNN-based species classification generalise across variation in habitat within a camera trap survey?

Camera trap surveys are a popular ecological monitoring tool that produce vast numbers of images making their annotation extremely time-consuming. Advances in machine learning, in the form of convolutional neural networks, have demonstrated potential for automated image classification, reducing processing time. These networks often have a poor ability to generalise, however, which could impact assessments of species in habitats undergoing change. Here, we (i) compare the performance of three network architectures in identifying species in camera trap images taken from tropical forest of varying disturbance intensities; (ii) explore the impacts of training dataset configuration; (iii) use habitat disturbance categories to investigate network generalisability and (iv) test whether classification performance and generalisability improve when using images cropped to bounding boxes. Overall accuracy (72.8%) was improved by excluding the rarest species and by adding extra training images (76.3% and 82.8%, respectively). Generalisability to new camera locations within a disturbance level was poor (mean F1-score: 0.32). Performance across unseen habitat disturbance levels was worse (mean F1-score: 0.27). Training the network on multiple disturbance levels improved generalisability (mean F1-score on unseen disturbance levels: 0.41). Cropping images to bounding boxes improved overall performance (F1-score: 0.77 vs. 0.47) and generalisability (mean F1-score on unseen disturbance levels: 0.73), but at a cost of losing images that contained animals which the detector failed to detect. These results suggest researchers should consider using an object detector before passing images to a classifier, and an improvement in classification might be seen if labelled images from other studies are added to their training data. Composition of training data was shown to be influential, but including rarer classes did not compromise performance on common classes, providing support for the inclusion of rare species to inform conservation efforts. These findings have important implications for use of these methods for long-term monitoring of habitats undergoing change, as they highlight the potential for misclassifications due to poor generalisability to impact subsequent ecological analyses. These methods therefore need to be considered as dynamic, in that changes to the study site would need to be reflected in the updated training of the network