Implementation of European cohesion policy at the sub-national level: evidence from beneficiary data in Eastern Germany

Regional governments' discretion in allocating structural funds is mainly limited by the competences of the Commission to control implementation and fiscal activities of decentralized governments. In this paper, we analyse implementation of ERDF funds in Eastern Germany in the financial perspective 2007 to 2013 to show how allocation of the funds follows the objectives formulated in the programmes. We find that less rural regions and some economic sectors benefit by more than others. A few beneficiaries control the highest share of the funds. This indicates that political economy forces in the allocation process may benefit well organised groups

Lung tumour growth kinetics in SPC-c-Raf-1-BB transgenic mice assessed by longitudinal in-vivo micro-CT quantification

<p>Abstract</p> <p>Background</p> <p>SPC-c-Raf-1-BxB transgenic mice develop genetically induced disseminated lung adenocarcinoma allowing examination of carcinogenesis and evaluation of novel treatment strategies. We report on assessment of lung tumour growth kinetics using a semiautomated region growing segmentation algorithm.</p> <p>Methods</p> <p>156 non contrast-enhanced respiratory gated micro-CT of the lungs were obtained in 12 SPC-raf transgenic (n = 9) and normal (n = 3) mice at different time points. Region-growing segmentation of the aerated lung areas was obtained as an inverse surrogate for tumour burden. Time course of segmentation volumes was assessed to demonstrate the potential of the method for follow-up studies.</p> <p>Results</p> <p>Micro-CT allowed assessment of tumour growth kinetics and semiautomated region growing enabled quantitative analysis. Significant changes of the segmented lung volumes over time could be shown (<it>p </it>= 0.009). Significant group differences could be detected between transgenic and normal animals for time points 8 to 13 months (<it>p </it>= 0.043), when marked tumour progression occurred.</p> <p>Conclusion</p> <p>The presented region-growing segmentation algorithm allows in-vivo quantification of multifocal lung adenocarcinoma in SPC-raf transgenic mice. This enables the assessment of tumour load and progress for the study of carcinogenesis and the evaluation of novel treatment strategies.</p

Adaptable-radius, time-orbiting magnetic ring trap for Bose-Einstein condensates

We theoretically investigate an adjustable-radius magnetic storage ring for laser-cooled and Bose-condensed atoms. Additionally, we discuss a novel time-dependent variant of this and other ring traps. Time-orbiting ring traps provide a high optical access method for spin-flip loss prevention near a storage ring's circular magnetic field zero. Our scalable storage ring will allow one to probe the fundamental limits of condensate Sagnac interferometry.Comment: 5 pages, 3 figures. accepted in J Phys

Degradation of D-2-hydroxyglutarate in the presence of isocitrate dehydrogenase mutations

D-2-Hydroxyglutarate (D-2-HG) is regarded as an oncometabolite. It is found at elevated levels in certain malignancies such as acute myeloid leukaemia and glioma. It is produced by a mutated isocitrate dehydrogenase IDH1/2, a low-affinity/high-capacity enzyme. Its degradation, in contrast, is catalysed by the high-affinity/low-capacity enzyme D-2-hydroxyglutarate dehydrogenase (D2HDH). So far, it has not been proven experimentally that the accumulation of D-2-HG in IDH mutant cells is the result of its insufficient degradation by D2HDH. Therefore, we developed an LC-MS/MS-based enzyme activity assay that measures the temporal drop in substrate and compared this to the expression of D2HDH protein as measured by Western blot. Our data clearly indicate, that the maximum D-2-HG degradation rate by D2HDH is reached in vivo, as v(max) is low in comparison to production of D-2-HG by mutant IDH1/2. The latter seems to be limited only by substrate availability. Further, incubation of IDH wild type cells for up to 48 hours with 5 mM D-2-HG did not result in a significant increase in either D2HDH protein abundance or enzyme activity

D-2-hydroxyglutarate interferes with HIF-1α stability skewing T-cell metabolism towards oxidative phosphorylation and impairing Th17 polarization

D-2-hydroxyglutarate (D-2HG) is released by various types of malignant cells including acute myeloid leukemia (AML) blasts carrying isocitrate dehydrogenase (IDH) gain-of-function mutations. D-2HG acting as an oncometabolite promotes proliferation, anoikis, and differentiation block of hematopoietic cells in an autocrine fashion. However, prognostic impact of IDH mutations and high D-2HG levels remains controversial and might depend on the overall mutational context. An increasing number of studies focus on the permissive environment created by AML blasts to promote immune evasion. Impact of D-2HG on immune cells remains incompletely understood. Here, we sought out to investigate the effects of D-2HG on T-cells as key mediators of anti-AML immunity. D-2HG was efficiently taken up by T-cells in vitro, which is in line with high 2-HG levels measured in T-cells isolated from AML patients carrying IDH mutations. T-cell activation was slightly impacted by D-2HG. However, D-2HG triggered HIF-1a protein destabilization resulting in metabolic skewing towards oxidative phosphorylation, increased regulatory T-cell (Treg) frequency, and reduced T helper 17 (Th17) polarization. Our data suggest for the first time that D-2HG might contribute to fine tuning of immune responses

Differences between Human Plasma and Serum Metabolite Profiles

BACKGROUND: Human plasma and serum are widely used matrices in clinical and biological studies. However, different collecting procedures and the coagulation cascade influence concentrations of both proteins and metabolites in these matrices. The effects on metabolite concentration profiles have not been fully characterized. METHODOLOGY/PRINCIPAL FINDINGS: We analyzed the concentrations of 163 metabolites in plasma and serum samples collected simultaneously from 377 fasting individuals. To ensure data quality, 41 metabolites with low measurement stability were excluded from further analysis. In addition, plasma and corresponding serum samples from 83 individuals were re-measured in the same plates and mean correlation coefficients (r) of all metabolites between the duplicates were 0.83 and 0.80 in plasma and serum, respectively, indicating significantly better stability of plasma compared to serum (p = 0.01). Metabolite profiles from plasma and serum were clearly distinct with 104 metabolites showing significantly higher concentrations in serum. In particular, 9 metabolites showed relative concentration differences larger than 20%. Despite differences in absolute concentration between the two matrices, for most metabolites the overall correlation was high (mean r = 0.81±0.10), which reflects a proportional change in concentration. Furthermore, when two groups of individuals with different phenotypes were compared with each other using both matrices, more metabolites with significantly different concentrations could be identified in serum than in plasma. For example, when 51 type 2 diabetes (T2D) patients were compared with 326 non-T2D individuals, 15 more significantly different metabolites were found in serum, in addition to the 25 common to both matrices. CONCLUSIONS/SIGNIFICANCE: Our study shows that reproducibility was good in both plasma and serum, and better in plasma. Furthermore, as long as the same blood preparation procedure is used, either matrix should generate similar results in clinical and biological studies. The higher metabolite concentrations in serum, however, make it possible to provide more sensitive results in biomarker detection

Mass-spectrometry-based metabolomics: limitations and recommendations for future progress with particular focus on nutrition research

Mass spectrometry (MS) techniques, because of their sensitivity and selectivity, have become methods of choice to characterize the human metabolome and MS-based metabolomics is increasingly used to characterize the complex metabolic effects of nutrients or foods. However progress is still hampered by many unsolved problems and most notably the lack of well established and standardized methods or procedures, and the difficulties still met in the identification of the metabolites influenced by a given nutritional intervention. The purpose of this paper is to review the main obstacles limiting progress and to make recommendations to overcome them. Propositions are made to improve the mode of collection and preparation of biological samples, the coverage and quality of mass spectrometry analyses, the extraction and exploitation of the raw data, the identification of the metabolites and the biological interpretation of the results

Transdimensional inference of archeomagnetic intensity change

One of the main goals of archeomagnetism is to document the secular changes of Earth's magnetic field by laboratory analysis of the magnetization carried by archeological artefacts. Typical techniques for creating a time-dependent model assume a prescribed temporal discretisation which, when coupled with sparse data coverage, require strong regularisation generally applied over the entire time series in order to ensure smoothness. Such techniques make it difficult to characterise uncertainty and frequency content, and robustly detect rapid changes. Key to proper modelling (and physical understanding) is a method that places a minimum level of regularisation on any fit to the data. Here we apply a transdimensional Bayesian technique based on piecewise linear interpolation to sparse archeointensity datasets, in which the temporal complexity of the model is not set a priori, but is self-selected by the data. The method produces two key outputs: (i) a posterior distribution of intensity as a function of time, a useful tool for archeomagnetic dating, whose statistics are smooth but formally unregularised; (ii) by including the data ages in the model of unknown parameters, the method also produces posterior age statistics of each individual contributing datum. We test the technique using synthetic datasets and confirm agreement of our method with an integrated likelihood approach. We then apply the method to three archeomagnetic datasets all reduced to a single location: one temporally well-sampled within 700km from Paris (here referred to as Paris700), one that is temporally sparse centred on Hawaii, and a third (from Lübeck, Germany and Paris700) that has additional ordering constraints on age from stratification. Compared with other methods, our average posterior distributions largely agree, however our credible intervals appear to much better reflect the uncertainty during periods of sparse data coverage. Because each ensemble member of the posterior distribution is piecewise linear, we only fit oscillations when required by the data. As an example, we show that an oscillatory signal, associated with temporally-localised intensity maxima reported for a sparse Hawaiian dataset, is not required by the data. However, we do recover the previously reported oscillation of period 260 yrs for the Paris700 dataset and compute the probability distribution of the period of oscillation. We further demonstrate that such an oscillation is unresolved when accounting for age uncertainty by using a fixed age and with an artificially inflated error budget on intensity