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Institute
- Institut für Biochemie und Biologie (190)
- Institut für Physik und Astronomie (177)
- Institut für Geowissenschaften (168)
- Institut für Chemie (146)
- Institut für Umweltwissenschaften und Geographie (76)
- Fachgruppe Politik- & Verwaltungswissenschaft (65)
- Department Psychologie (57)
- Department Linguistik (54)
- Institut für Mathematik (47)
- Fachgruppe Betriebswirtschaftslehre (45)
The main objective of this study was to identify genomic regions involved in biomass heterosis using QTL, generation means, and mode-of-inheritance classification analyses. In a modified North Carolina Design III we backcrossed 429 recombinant inbred line and 140 introgression line populations to the two parental accessions, C24 and Col-0, whose F 1 hybrid exhibited 44% heterosis for biomass. Mid-parent heterosis in the RILs ranged from −31 to 99% for dry weight and from −58 to 143% for leaf area. We detected ten genomic positions involved in biomass heterosis at an early developmental stage, individually explaining between 2.4 and 15.7% of the phenotypic variation. While overdominant gene action was prevalent in heterotic QTL, our results suggest that a combination of dominance, overdominance and epistasis is involved in biomass heterosis in this Arabidopsis cross.
Prediction of hybrid biomass in Arabidopsis thaliana by selected parental SNP and metabolic markers
(2009)
A recombinant inbred line (RIL) population, derived from two Arabidopsis thaliana accessions, and the corresponding testcrosses with these two original accessions were used for the development and validation of machine learning models to predict the biomass of hybrids. Genetic and metabolic information of the RILs served as predictors. Feature selection reduced the number of variables (genetic and metabolic markers) in the models by more than 80% without impairing the predictive power. Thus, potential biomarkers have been revealed. Metabolites were shown to bear information on inherited macroscopic phenotypes. This proof of concept could be interesting for breeders. The example population exhibits substantial mid-parent biomass heterosis. The results of feature selection could therefore be used to shed light on the origin of heterosis. In this respect, mainly dominance effects were detected.
A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and traitbased models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.
Im Auftrag des Staates
(2011)
Folter ist ein Akt extremer kollektiver Gewalt, der im Auftrag eines Staates im Geheimen ausgeübt wird. Die Frage, was Menschen dazu bringt, anderen Menschen diese extreme Gewalt anzutun, verengt den Blick für ein Verständnis der Folter allzu schnell auf individualistische Erklärungsversuche. Der vorliegende Aufsatz geht im Gegensatz dazu von der Gruppe der Folterer aus und rückt die sozialen Beziehungen dieser Form der Vergesellschaftung und die von ihnen ausgehenden sozialen Dynamiken und Effekte in den Mittelpunkt. In einem ersten Schritt werden Georg Simmels formale Bestimmungen der geheimen Gesellschaft rekonstruiert und auf die geheime Gesellschaft der Folterer angewandt und spezifiziert; auf dieser Grundlage werden im zweiten Schritt Handlungsbedingungen der Mitglieder der geheimen Gesellschaft der Folterer herausgearbeitet; der dritte Schritt bestimmt die eigendynamischen Prozesse des Phänomens der Folter, die aus der Eskalation politischer Konflikte, der Gruppe der Folterer und der Situation der Folter erwachsen. Die These lautet, dass sich aus der Perspektive einer relationalen Soziologie ein theoretischer Zugriff auf das Problem der Folter ergibt, der weiterführende Erklärungen des Phänomens ermöglicht.
Gewalttätige soziale und politische Auseinandersetzungen, wie sie sich jüngst in den Staaten Nordafrikas und des Nahen Ostens, in den französischen Banlieues oder in London ereignet haben, deuten darauf hin, dass die sozialen Ordnungen, in denen sie entstehen, nicht länger ungeteilt als legitim erachtet werden. Vielmehr werden sie von alternativen Ordnungsvorstellungen infrage gestellt und herausgefordert. Auf die Erklärung derartiger Ordnungskonflikte ist die Soziologie nicht gut vorbereitet. Der Aufsatz skizziert deshalb zunächst Probleme und offene Fragen einer Soziologie der Gewalt – von der klassischen Soziologie über begrifflich-konzeptionelle und theoretisch-methodologische Probleme bis hin zu problematischen modernisierungs- und zivilisationstheoretischen Annahmen über eine künftige Rolle von Gewalt in sozialen Prozessen. Eine Erklärung der genannten Phänomene, so die These, wird nur dann möglich, wenn eine Soziologie der Gewalt den konstitutiven Zusammenhang von Phänomenen physischer Gewalt und Formen sozialer Ordnung in den Mittelpunkt stellt. Eine erklärende Soziologie, die „Warum“- und „Wie“-Fragen nicht auseinanderreißt, muss sich dazu auf die sozialen Mechanismen der Gewaltentstehung in Prozessen der Produktion und Reproduktion sozialer Ordnung konzentrieren.
Was sollten Mitarbeiter in einem empirisch ausgerichteten Forschungsprojekt können, und welche Kernkompetenzen sollte die Ausbildung an den Universitäten daher vermitteln? Die Antworten auf diese Fragen hängen – wie sollte es anders sein – von der inhaltlichen Fragestellung und methodischen Ausrichtung des jeweiligen Forschungsprojektes ab. Natürlich sollten Projektmitarbeiter über Vorkenntnisse zum Forschungsthema verfügen. Natürlich sollten Kenntnisse des projektspezifischen (statistischen) Methodenarsenals vorliegen.
Aims: The MARLINA-T2D study (ClinicalTrials. gov, NCT01792518) was designed to investigate the glycaemic and renal effects of linagliptin added to standard-of-care in individuals with type 2 diabetes and albuminuria. Methods: A total of 360 individuals with type 2 diabetes, HbA1c 6.5% to 10.0% (48-86 mmol/ mol), estimated glomerular filtration rate (eGFR) >= 30 mL/min/1.73 m(2) and urinary albumin-tocreatinine ratio (UACR) 30-3000 mg/g despite single agent renin-angiotensin-system blockade were randomized to double-blind linagliptin (n = 182) or placebo (n = 178) for 24 weeks. The primary and key secondary endpoints were change from baseline in HbA1c at week 24 and time-weighted average of percentage change from baseline in UACR over 24 weeks, respectively. Results: Baseline mean HbA1c and geometric mean (gMean) UACR were 7.8% +/- 0.9% (62.2 +/- 9.6 mmol/mol) and 126 mg/g, respectively; 73.7% and 20.3% of participants had microalbuminuria or macroalbuminuria, respectively. After 24 weeks, the placebo-adjusted mean change in HbA1c from baseline was -0.60% (-6.6 mmol/mol) (95% confidence interval [CI], -0.78 to -0.43 [-8.5 to -4.7 mmol/mol]; P <.0001). The placebo-adjusted gMean for time-weighted average of percentage change in UACR from baseline was -6.0% (95% CI, -15.0 to 3.0; P =.1954). The adverse-event profile, including renal safety and change in eGFR, was similar between the linagliptin and placebo groups. Conclusions: In individuals at early stages of diabetic kidney disease, linagliptin significantly improved glycaemic control but did not significantly lower albuminuria. There was no significant change in placebo-adjusted eGFR. Detection of clinically relevant renal effects of linagliptin may require longer treatment, as its main experimental effects in animal studies have been to reduce interstitial fibrosis rather than alter glomerular haemodynamics.
Cognitive or executive control is a critical mental ability, an important marker of mental illness, and among the most heritable of neurocognitive traits. Two candidate genes, catechol-O-methyltransferase (COMT) and DRD4, which both have a roles in the regulation of cortical dopamine, have been consistently associated with cognitive control. Here, we predicted that individuals with the COMT Met/Met allele would show improved response execution and inhibition as indexed by event-related potentials in a Go/NoGo task, while individuals with the DRD4 7-repeat allele would show impaired brain activity. We used independent component analysis (ICA) to separate brain source processes contributing to high-density EEG scalp signals recorded during the task. As expected, individuals with the DRD4 7-repeat polymorphism had reduced parietal P3 source and scalp responses to response (Go) compared to those without the 7-repeat. Contrary to our expectation, the COMT homozygous Met allele was associated with a smaller frontal P3 source and scalp response to response-inhibition (NoGo) stimuli, suggesting that while more dopamine in frontal cortical areas has advantages in some tasks, it may also compromise response inhibition function. An interaction effect emerged for P3 source responses to Go stimuli. These were reduced in those with both the 7-repeat DRD4 allele and either the COMT Val/Val or the Met/Met homozygous polymorphisms but not in those with the heterozygous Val/Met polymorphism. This epistatic interaction between DRD4 and COMT replicates findings that too little or too much dopamine impairs cognitive control. The anatomic and functional separated maximally independent cortical EEG sources proved more informative than scalp channel measures for genetic studies of brain function and thus better elucidate the complex mechanisms in psychiatric illness.
Potato (Solanum tuberosum L.) is one of the most important food crops worldwide. Current potato varieties are highly susceptible to drought stress. In view of global climate change, selection of cultivars with improved drought tolerance and high yield potential is of paramount importance. Drought tolerance breeding of potato is currently based on direct selection according to yield and phenotypic traits and requires multiple trials under drought conditions. Marker-assisted selection (MAS) is cheaper, faster and reduces classification errors caused by noncontrolled environmental effects. We analysed 31 potato cultivars grown under optimal and reduced water supply in six independent field trials. Drought tolerance was determined as tuber starch yield. Leaf samples from young plants were screened for preselected transcript and nontargeted metabolite abundance using qRT-PCR and GC-MS profiling, respectively. Transcript marker candidates were selected from a published RNA-Seq data set. A Random Forest machine learning approach extracted metabolite and transcript markers for drought tolerance prediction with low error rates of 6% and 9%, respectively. Moreover, by combining transcript and metabolite markers, the prediction error was reduced to 4.3%. Feature selection from Random Forest models allowed model minimization, yielding a minimal combination of only 20 metabolite and transcript markers that were successfully tested for their reproducibility in 16 independent agronomic field trials. We demonstrate that a minimum combination of transcript and metabolite markers sampled at early cultivation stages predicts potato yield stability under drought largely independent of seasonal and regional agronomic conditions.