@misc{WoodfieldHorneGlauertetal.2018,
  author    = {Woodfield, Emma E. and Horne, Richard B. and Glauert, Sarah A. and Menietti, John D. and Shprits, Yuri Y. and Kurth, William S.},
  title     = {Formation of electron radiation belts at Saturn by Z-mode wave acceleration},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {1032},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-46834},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-468342},
  pages     = {9},
  year      = {2018},
  abstract  = {At Saturn electrons are trapped in the planet's magnetic field and accelerated to relativistic energies to form the radiation belts, but how this dramatic increase in electron energy occurs is still unknown. Until now the mechanism of radial diffusion has been assumed but we show here that in-situ acceleration through wave particle interactions, which initial studies dismissed as ineffectual at Saturn, is in fact a vital part of the energetic particle dynamics there. We present evidence from numerical simulations based on Cassini spacecraft data that a particular plasma wave, known as Z-mode, accelerates electrons to MeV energies inside 4 R-S (1 R-S = 60,330 km) through a Doppler shifted cyclotron resonant interaction. Our results show that the Z-mode waves observed are not oblique as previously assumed and are much better accelerators than O-mode waves, resulting in an electron energy spectrum that closely approaches observed values without any transport effects included.},
  language  = {en}
}
@misc{WeberKochlikDemuthetal.2020,
  author    = {Weber, Daniela and Kochlik, Bastian Max and Demuth, Ilja and Steinhagen-Thiessen, Elisabeth and Grune, Tilman and Norman, Kristina},
  title     = {Plasma carotenoids, tocopherols and retinol},
  series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-51599},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-515996},
  pages     = {10},
  year      = {2020},
  abstract  = {Regular consumption of fruits and vegetables, which is related to high plasma levels of lipid-soluble micro-nutrients such as carotenoids and tocopherols, is linked to lower incidences of various age-related diseases. Differences in lipid-soluble micronutrient blood concentrations seem to be associated with age. Our retrospective analysis included men and women aged 22-37 and 60-85 years from the Berlin Aging Study II. Participants with simultaneously available plasma samples and dietary data were included (n = 1973). Differences between young and old groups were found for plasma lycopene, alpha-carotene, alpha-tocopherol, beta-cryptoxanthin (only in women), and gamma-tocopherol (only in men). beta-Carotene, retinol and lutein/zeaxanthin did not differ between young and old participants regardless of the sex. We found significant associations for lycopene, alpha-carotene (both inverse), alpha-tocopherol, gamma-tocopherol, and beta-carotene (all positive) with age. Adjusting for BMI, smoking status, season, cholesterol and dietary intake confirmed these associations, except for beta-carotene. These micronutrients are important antioxidants and associated with lower incidence of age-related diseases, therefore it is important to understand the underlying mechanisms in order to implement dietary strategies for the prevention of age-related diseases. To explain the lower lycopene and alpha-carotene concentration in older subjects, bioavailability studies in older participants are necessary.},
  language  = {en}
}
@misc{StuetzWeberDolleetal.2016,
  author    = {Stuetz, Wolfgang and Weber, Daniela and Doll{\´e}, Martijn E. T. and Jansen, Eug{\`e}ne and Grubeck-Loebenstein, Beatrix and Fiegl, Simone and Toussaint, Olivier and Bernhardt, Juergen and Gonos, Efstathios S. and Franceschi, Claudio and Sikora, Ewa and Moreno-Villanueva, Mar{\´i}a and Breusing, Nicolle and Grune, Tilman and B{\"u}rkle, Alexander},
  title     = {Plasma carotenoids, tocopherols, and retinol in the age-stratified (35-74 years) general population},
  series = {Nutrients},
  journal   = {Nutrients},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407659},
  pages     = {17},
  year      = {2016},
  abstract  = {Blood micronutrient status may change with age. We analyzed plasma carotenoids, α-/γ-tocopherol, and retinol and their associations with age, demographic characteristics, and dietary habits (assessed by a short food frequency questionnaire) in a cross-sectional study of 2118 women and men (age-stratified from 35 to 74 years) of the general population from six European countries. Higher age was associated with lower lycopene and α-/β-carotene and higher β-cryptoxanthin, lutein, zeaxanthin, α-/γ-tocopherol, and retinol levels. Significant correlations with age were observed for lycopene (r = -0.248), α-tocopherol (r = 0.208), α-carotene (r = -0.112), and β-cryptoxanthin (r = 0.125; all p < 0.001). Age was inversely associated with lycopene (-6.5\% per five-year age increase) and this association remained in the multiple regression model with the significant predictors (covariables) being country, season, cholesterol, gender, smoking status, body mass index (BMI (kg/m2)), and dietary habits. The positive association of α-tocopherol with age remained when all covariates including cholesterol and use of vitamin supplements were included (1.7\% vs. 2.4\% per five-year age increase). The association of higher β-cryptoxanthin with higher age was no longer statistically significant after adjustment for fruit consumption, whereas the inverse association of α-carotene with age remained in the fully adjusted multivariable model (-4.8\% vs. -3.8\% per five-year age increase). We conclude from our study that age is an independent predictor of plasma lycopene, α-tocopherol, and α-carotene.},
  language  = {en}
}
@misc{HischeLarhlimiSchwarzetal.2012,
  author    = {Hische, Manuela and Larhlimi, Abdelhalim and Schwarz, Franziska and Fischer-Rosinsk{\´y}, Antje and Bobbert, Thomas and Assmann, Anke and Catchpole, Gareth S. and Pfeiffer, Andreas F. H. and Willmitzer, Lothar and Selbig, Joachim and Spranger, Joachim},
  title     = {A distinct metabolic signature predictsdevelopment of fasting plasma glucose},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch Naturwissenschaftliche Reihe},
  number    = {850},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-42740},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-427400},
  pages     = {12},
  year      = {2012},
  abstract  = {Background High blood glucose and diabetes are amongst the conditions causing the greatest losses in years of healthy life worldwide. Therefore, numerous studies aim to identify reliable risk markers for development of impaired glucose metabolism and type 2 diabetes. However, the molecular basis of impaired glucose metabolism is so far insufficiently understood. The development of so called 'omics' approaches in the recent years promises to identify molecular markers and to further understand the molecular basis of impaired glucose metabolism and type 2 diabetes. Although univariate statistical approaches are often applied, we demonstrate here that the application of multivariate statistical approaches is highly recommended to fully capture the complexity of data gained using high-throughput methods. Methods We took blood plasma samples from 172 subjects who participated in the prospective Metabolic Syndrome Berlin Potsdam follow-up study (MESY-BEPO Follow-up). We analysed these samples using Gas Chromatography coupled with Mass Spectrometry (GC-MS), and measured 286 metabolites. Furthermore, fasting glucose levels were measured using standard methods at baseline, and after an average of six years. We did correlation analysis and built linear regression models as well as Random Forest regression models to identify metabolites that predict the development of fasting glucose in our cohort. Results We found a metabolic pattern consisting of nine metabolites that predicted fasting glucose development with an accuracy of 0.47 in tenfold cross-validation using Random Forest regression. We also showed that adding established risk markers did not improve the model accuracy. However, external validation is eventually desirable. Although not all metabolites belonging to the final pattern are identified yet, the pattern directs attention to amino acid metabolism, energy metabolism and redox homeostasis. Conclusions We demonstrate that metabolites identified using a high-throughput method (GC-MS) perform well in predicting the development of fasting plasma glucose over several years. Notably, not single, but a complex pattern of metabolites propels the prediction and therefore reflects the complexity of the underlying molecular mechanisms. This result could only be captured by application of multivariate statistical approaches. Therefore, we highly recommend the usage of statistical methods that seize the complexity of the information given by high-throughput methods.},
  language  = {en}
}