@article{WillmannHeniLinderetal.2019,
  author    = {Willmann, Caroline and Heni, Martin and Linder, Katarzyna and Wagner, Robert and Stefan, Norbert and Machann, J{\"u}rgen and Schulze, Matthias Bernd and Joost, Hans-Georg and Haring, Hans-Ulrich and Fritsche, Andreas},
  title     = {Potential effects of reduced red meat compared with increased fiber intake on glucose metabolism and liver fat content},
  series = {The American journal of clinical nutrition : a publication of the American Society for Nutrition, Inc.},
  volume    = {109},
  journal   = {The American journal of clinical nutrition : a publication of the American Society for Nutrition, Inc.},
  number    = {2},
  publisher = {Oxford Univ. Press},
  address   = {Oxford},
  issn      = {0002-9165},
  doi       = {10.1093/ajcn/nqy307},
  pages     = {288 -- 296},
  year      = {2019},
  abstract  = {Background: Epidemiological studies suggest that an increased red meat intake is associated with a higher risk of type 2 diabetes, whereas an increased fiber intake is associated with a lower risk. Objectives: We conducted an intervention study to investigate the effects of these nutritional factors on glucose and lipid metabolism, body-fat distribution, and liver fat content in subjects at increased risk of type 2 diabetes. Methods: This prospective, randomized, and controlled dietary intervention study was performed over 6 mo. All groups decreased their daily caloric intake by 400 kcal. The "control" group (N = 40) only had this requirement. The "no red meat" group (N = 48) in addition aimed to avoid the intake of red meat, and the "fiber" group (N = 44) increased intake of fibers to 40 g/d. Anthropometric parameters and frequently sampled oral glucose tolerance tests were performed before and after intervention. Body-fat mass and distribution, liver fat, and liver iron content were assessed by MRI and single voxel proton magnetic resonance spectroscopy. Results: Participants in all groups lost weight (mean 3.3 +/- 0.5 kg, P < 0.0001). Glucose tolerance and insulin sensitivity improved (P < 0.001), and body and visceral fat mass decreased in all groups (P < 0.001). These changes did not differ between groups. Liver fat content decreased significantly (P < 0.001) with no differences between the groups. The decrease in liver fat correlated with the decrease in ferritin during intervention (r(2) = 0.08, P = 0.0021). This association was confirmed in an independent lifestyle intervention study (Tuebingen Lifestyle Intervention Program, N = 229, P = 0.0084). Conclusions: Our data indicate that caloric restriction leads to a marked improvement in glucose metabolism and body-fat composition, including liver-fat content. The marked reduction in liver fat might be mediated via changes in ferritin levels. In the context of caloric restriction, there seems to be no additional beneficial impact of reduced red meat intake and increased fiber intake on the improvement in cardiometabolic risk parameters. This trial was registered at clinicaltrials.gov as NCT03231839.},
  language  = {en}
}
@misc{RianoPachonNagelNeigenfindetal.2009,
  author    = {Riano-Pachon, Diego Mauricio and Nagel, Axel and Neigenfind, Jost and Wagner, Robert and Basekow, Rico and Weber, Elke and M{\"u}ller-R{\"o}ber, Bernd and Diehl, Svenja and Kersten, Birgit},
  title     = {GabiPD : the GABI primary database - a plant integrative "omics" database},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-45075},
  year      = {2009},
  abstract  = {The GABI Primary Database, GabiPD (http:// www.gabipd.org/), was established in the frame of the German initiative for Genome Analysis of the Plant Biological System (GABI). The goal of GabiPD is to collect, integrate, analyze and visualize primary information from GABI projects. GabiPD constitutes a repository and analysis platform for a wide array of heterogeneous data from high-throughput experiments in several plant species. Data from different 'omics' fronts are incorporated (i.e. genomics, transcriptomics, proteomics and metabolomics), originating from 14 different model or crop species. We have developed the concept of GreenCards for textbased retrieval of all data types in GabiPD (e.g. clones, genes, mutant lines). All data types point to a central Gene GreenCard, where gene information is integrated from genome projects or NCBI UniGene sets. The centralized Gene GreenCard allows visualizing ESTs aligned to annotated transcripts as well as displaying identified protein domains and gene structure. Moreover, GabiPD makes available interactive genetic maps from potato and barley, and protein 2DE gels from Arabidopsis thaliana and Brassica napus. Gene expression and metabolic-profiling data can be visualized through MapManWeb. By the integration of complex data in a framework of existing knowledge, GabiPD provides new insights and allows for new interpretations of the data.},
  language  = {en}
}
@article{GieseWagner2009,
  author    = {Giese, Holger and Wagner, Robert},
  title     = {From model transformation to incremental bidirectional model synchronization},
  issn      = {1619-1366},
  doi       = {10.1007/s10270-008-0089-9},
  year      = {2009},
  abstract  = {The model-driven software development paradigm requires that appropriate model transformations are applicable in different stages of the development process. The transformations have to consistently propagate changes between the different involved models and thus ensure a proper model synchronization. However, most approaches today do not fully support the requirements for model synchronization and focus only on classical one-way batch-oriented transformations. In this paper, we present our approach for an incremental model transformation which supports model synchronization. Our approach employs the visual, formal, and bidirectional transformation technique of triple graph grammars. Using this declarative specification formalism, we focus on the efficient execution of the transformation rules and how to achieve an incremental model transformation for synchronization purposes. We present an evaluation of our approach and demonstrate that due to the speedup for the incremental processing in the average case even larger models can be tackled.},
  language  = {en}
}