Multi-objective and multi-variate global sensitivity analysis of the soil-crop model XN-CERES in Southwest Germany

Soil-crop models enjoy ever-greater popularity as tools to assess the im- pact of environmental changes or management strategies on agricultural production. Soil-crop models are designed to coherently simulate the crop, nitrogen (N) and water dynamics of agricultural fields. However, soil-crop models depend on a vast number of uncertain model inputs, i.e., initial conditions and parameters. To assess the uncertainty in the simulation results (UCSR) and how they can be apportioned among the model inputs of the XN-CERES soil-crop model, an uncertainty and global sensitivity analysis (GSA) was conducted. We applied two different GSA methods, moment-independent and variance-based methods in the sense of the Factor Prioritization and the Factor Fixing setting. The former identifies the key drivers of uncertainty, i.e., which model input, if fixed to its true value, would lead to the greatest reduction of the UCSR. The latter identifies the model inputs that cannot be fixed at any value within their value range without affecting the UCSR. In total we calculated six sensitivity indices (SIs). The overall objective was to assess the cross-sub-model impact of parameters and the overall determinability of the XN-CERES applied on a deep loess soil profile in Southwest Germany. Therefore, we selected 39 parameters and 16 target variables (TGVs) to be included in the GSA. Furthermore, we assessed a weekly time series of the parameter sensitivities. The sub-models were crop, water, nitrogen and flux. In addition, we also compared moment-independent (MI) and variance-based (VB) GSA methods for their suitability for the two settings. The results show that the parameters of the TGVs of the four groups cannot be considered independently. Each group is impacted by the parameters of the other groups. Crop parameters are most important, followed by the Mualem van Genuchten (MvG) parameters. The nitrate (NO3-) content and the matric potential are the two TGVs that are most affected by the inter- action of parameters, especially crop and MvG parameters. However, the model output of these two TGVs is highly skewed and leptokrutic. Therefore, the variance is an unsuitable representation of the UCSR, and the reliability of the variance-based sensitivity indices SIVB is curtailed. Nitrogen group parameters play an overall minor role for the uncertainty of the whole XN-CERES, but nitrification rates can be calibrated on ammonium (NH4+) measurements. Considering the initial conditions shows the high importance of the initial NO3-; content. If it could be fixed, the uncertainty of crop groups TGVs, the matric potential and the N content in the soil could be reduced. Hence, multi-year predictions of yield suffer from uncertainty due to the simulated NO3-; content. Temporally resolved parameter show the big dependence between the crops development stage and the other 15 TGVs becomes visible. High temporally resolved measurements of the development stage are important to univocally estimate the crop parameters and reduce the uncertainty in the vegetative and generative biomass. Furthermore, potential periods of water and N-limiting situations are assessed, which is helpful for deriving management strategies. In addition, it become clear that measurement campaigns should be conducted at the simulation start and during the vegetation period to have enough information to calibrate the XN-CERES. Regarding the performance of the different GSA methods and the different SIs, we conclude that the sensitivity measure relying on the Kolmogorov-Smirnov metric (betaks) is most stable. It converges quickly and has no issues with highly skewed and leptokrutic model output distributions. The assessments of the first-effect index and the betaks provide information on the additivity of the model and parameters that cannot be fixed without impacting the simulation results. In summary, we could only identify three parameters that have no direct impact on any TGV at any time and are hence not determinable from any measurements of the TGVs considered. Furthermore, we can conclude that the groups parameters should not be calibrated independently because they always affect the uncertainty of the selected TGV directly or via interacting. However, no TGV is suitable to calibrate all parameters. Hence, the calibration of the XN-CERES requires measurements of TGVs from each group, even if the modeler is only interested in one specific TGV, e.g., yield. The GSA should be repeated in a drier climate or with restricted rooting depth. The convergence of the values for the Sobol indices remains an issue. Even larger sample sizes, another convergence criteria or graphical inspection cannot alleviate the issue. However, we can conclude that the sub-models of the XN-CERES cannot be considered in- dependently and that the model does what it is designed for: coherently simulating the crop, N and water dynamics with their interactions.Boden-Pflanze Modelle erfreuen sich immer größerer Beliebtheit, um die Auswirkungen von Umweltveränderungen und Managementstrategien auf die landwirtschaftliche Produktion zu bestimmen. Boden-Pflanzen Modelle sind so konzipiert, dass sie kohärent die Pflanzen-, Stickstoff- (N) und Wasserdynamik in landwirtschaftlichen Feldern simulieren. Leider hängen Boden-Pflanze Modelle von einer Vielzahl unsicherer Modellinputs wie Anfangs- und Randbedingungen sowie Parametern ab. Zur Bestimmung der Unsicherheit in den Simulationsergebnissen (UCSR) und in welchem Ausmaß diese von den Modellinputs des Boden-Pflanze Modells XN-CERES abhängt, wird in dieser Arbeit eine Unsicherheits- und Global Sensitivitäts Analyse (GSA) durchgeführt. Wir verwendeten zwei verschiedene GSA-Methoden, momentunabhängige und varianzbasierte Methoden, im Sinne der Settings: Faktor Priorisierung und Faktor Fixing. Ersteres identifiziert die Parameter, die durch Fixierung zur größten Reduktion der UCSR führen. Letzteres identifiziert die Parameter, die nicht fixiert werden können, ohne die UCSR zu beeinflussen. Insgesamt haben wir sechs verschiedene Sensitivitäts Indices (SIs) berechnet. Das übergeordnete Ziel der Arbeit war es die Teilmodell-übergreifende Wirkung der Parameter und die allgemeinen Bestimmbarkeit des Boden-Pflanzen Modells XN-CERES auf einem Lössstandort in Südwest Deutschland zu quantifizieren. Wir haben insgesamt 39 Parameter und 16 Zielvariablen (TGV) für die GSA ausgewählt. Darüber hinaus lösen wir die Parametersensitivitäten für die vier Teilmodelle Pflanze, Wasser, Stickstoff und Flüsse wöchentlich auf. Darüber hinaus vergleichen wir Moment unabhängige (MI) und Varianz basierte (VB) GSA Methoden und ihre Eignung für die beiden Settings für ein Boden-Pflanze Model. Die Ergebnisse zeigen, dass die Parameter der vier Gruppen im hohen Maße voneinander abhängen. Die Pflanzenparameter haben einen Einfluss auf jede der 16 TGVs. Es folgen die Mualem van Genuchten (MvG) Parameter. Der Nitrat (NO3-) Gehalt und das Matrixpotential am stärksten von Parameterinteraktionen betroffen sind. Allerdings sind die Verteilungen dieser beiden TGVs schief und leptokurtisch. Daher ist die Varianz eine schlechte Repräsentation für die UCSR und die Zuverlässigkeit der Varianz basierten Sensitivitätsindices (SIVB) entsprechend eingeschränkt. Die Parameter der Stickstoffgruppe spielen insgesamt eine untergeordnete Rolle. Die Betrachtung der Anfangsbedingungen zeigt, dass die Unsicherheit in der Simulation der TGVs der Pflanzengruppen, des Matrixpotentials und des N-Gehalts im Boden durch deren akurate Messung stark reduziert werden kann. Vorhersagen für Fruchtfolgen sind folglich unsicher, da der simulierte Ertrag der Hauptfrucht vom Zustand des Bodens nach der Vorfrucht abhängt. Zeitaufgelöste Parametersensitivitäten zeigen die große Abhängigkeit zwischen dem Entwicklungsstadium der Pflanze und den andern 15 TGVs wird sichtbar. Hochauflösende Messungen des Entwicklungsstadiums der Pflanze sind wichtig, um die Pflanzenparameter eindeutig kalibrieren zu können. Ebenfalls können durch zeitaufgelöste Parametersensitivitäten, Zeiträume von möglicher Wasser- und N-Knappheit identifiziert werden. Dies ist besonders wichtig für die Erstellung von Managementstrategien. Messungen sollten vorrangig zu Simulationsbeginn und während der Vegetationsperiode durchgeführt werden, um genügend Informationen für die Kalibrierung des Modells zu erhalten. Bezüglich der Leistung der verschiedenen GSA Methoden und der unterschiedlichen SIs, kommen wir zu dem Ergebnis, dass das auf der Kolmogorov-Smirnov Metrik basierte Sensitivitätsmaß (betaks) am stabilsten ist. Es konvergiert schnell und hat keine Probleme mit stark schiefen und leptokurtischen Verteilungen. Die Kombination aus First-Effect Index und betaks gibt Aufschluss über die Additivität des Modells und identifiziert Parameter, die nicht fixiert werden können. Zusammenfassend lässt sich sagen, dass wir nur drei Parameter identifizieren konnten, die keinen direkten Einfluss auf eine der untersuchten TGV haben. Der direkte Einfluss weiterer acht Parameter ist so gering, dass deren Kalibrierung schwierig ist. Darüber hinaus kommen wir zu dem Schluss, dass die Parameter der verschiedenen Gruppen nicht unabhängig voneinander kalibriert werden können. Weiter ist nicht jede TGV zur Kalibrierung aller Parameter geeignet. Für die Kalibrierung der gewählten Modellkombination sind daher Messungen von TGVs jeder Gruppe erforderlich, auch wenn nur Interesse an einer bestimmten TGV wie zum Beispiel dem Ertrag besteht. Aus der Arbeit ergeben sich einige generelle Empfehlungen. So sollte die GSA in einem trockeneren Klima oder mit eingeschränkter Durchwurzelungstiefe durchgeführt werden. Die Konvergenz der Werte für die Sobol-Indizes ist problematisch. Noch größere Stichprobengrößen, weitere Konvergenzkriterien oder grafische Prüfungen könnten hier Abhilfe schaffen

Feasibility of strip-tillage for field grown vegetables

Gemüsekulturen mit einem weiten Reihenabstand, wie beispielsweise Weißkohl (Brassica oleracea convar. capitata var. alba) sind bei Starkniederschlägen einem hohen Erosionsrisiko ausgesetzt. Konservierende Bodenbearbeitungsverfahren wie das Strip-Tillage Verfahren können die Gefahr der Bodenerosion reduzieren. Aus diesem Grund wurde in den Jahren 2011 und 2012 in einem Feldversuch in Südwestdeutschland das Erosionsschutzpotential des Strip-Tillage Verfahrens in Kopfsalat (Lactuca sativa var. capitata L.) und Weißkohl geprüft und untersucht, ob das Verfahren eine Alternative zur konventionellen, wendenden Bodenbearbeitung mit dem Pflug darstellen kann. Bei Beregnungsversuchen konnte gezeigt werden, dass der Bodenabtrag im Strip-Tillage Verfahren (ST) im Vergleich zur konventionell bearbeiteten Pflugvariante (MP) signifikant geringer war. Die Bodenabträge lagen nach einer Beregnungsmenge von 40 Litern in 20 Minuten in MP im Jahr 2011 bei 512 g m–2 und 2012 bei 210 g m–2. Im Vergleich hierzu waren die Bodenabträge in ST 2011 um 80% und 2012 um 90% geringer als in MP. Für die bodenkundlichen Untersuchungen wurde in den Strip-Tillage Parzellen sowohl im bearbeiteten Bereich, innerhalb der Pflanzreihe (IR), als auch im unbearbeiteten Bereich, zwischen den Pflanzreihen (BR) gemessen. Die Lagerungsdichte im Oberboden (0–10 cm) war in ST_IR (1,24 g cm–3) am geringsten gefolgt von MP (1,33 g cm–3) und ST_BR (1,53 g cm–3). Beim Eindringwiderstand im Oberboden wurden ebenfalls die geringsten Werte in ST_IR und die höchsten in MP gemessen. Die Menge an pflanzenverfügbarem Wasser [L m–2] von 0–40 cm Bodentiefe war in ST_BR höher als in MP und ST_IR. Im Jahr 2011 wurde kein signifikanter Unterschied im durchschnittlichen Kopfgewicht zwischen MP und ST gemessen. 2012 wurde in ST mit durchschnittlich 1,85 kg ein sig­nifikant höheres Kopfgewicht als in MP (1,62 kg) festgestellt. Somit kann das Strip­Tillage Verfahren für ero­sionsanfällige Kulturen wie Weißkohl eine Alternative zum konventionellen Pfluganbau darstellen. DOI: 10.5073/JfK.2014.11.01, https://doi.org/10.5073/JfK.2014.11.01Row crops and field grown vegetables, such as white cabbage (Brassica oleracea convar. capitata var. alba), are affected by soil erosion caused by rainfall energy. Conservation tillage, such as strip-tillage, is the most effective way to reduce soil erosion. Hence, the objectives of this study were to develop and modify the strip-tillage system for white cabbage and lettuce (Lactuca sativa var. capitata L.), and to assess its potential towards controlling soil erosion. In 2011 and 2012 rainfall simulations showed significantly lower soil loss under strip-tillage (ST) than under the moldboard plow (MP). Soil loss under MP was 512 g m–2 in 2011 and 210 g m–2 in 2012, while ST reduced soil loss by 80% in 2011 and 90% in 2012. The ST sampling positions for soil property assessments were in the non-tilled zone i.e. between the planting row (ST_BR) and the tilled zone, within the planting row (ST_IR). Top soil bulk density (0­10 cm) was lowest in ST_IR (1.24 g cm–3), followed by MP (1.33 g cm–3) and ST_BR (1.53 g cm–3). Penetration resistance in the top soil was also lowest in ST_IR followed by MP and ST_BR. Plant available water [L m–2] from 0–40 cm was higher in ST_BR compared to MP and ST_IR. In 2011 average cabbage head weight was not affected by tillage treatment. In 2012 the cabbage head weight was significantly higher in ST (1.85 kg) than in MP (1.62 kg). The results show that strip-tillage can be a viable option for crops which are exposed to an erosion risk, such as white cabbage. DOI: 10.5073/JfK.2014.11.01, https://doi.org/10.5073/JfK.2014.11.0

Polymorphisms of an Innate Immune Gene, Toll-Like Receptor 4, and Aggressive Prostate Cancer Risk: A Systematic Review and Meta-Analysis

Background: Toll-like receptor 4 (TLR4) is one of the best known TLR members expressed on the surface of several leukocytes and tissue cells and has a key function in detecting pathogen and danger-associated molecular patterns. The role of TLR4 in the pathophysiology of several age-related diseases is also well recognized, such as prostate cancer (PCa). TLR4 polymorphisms have been related to PCa risk, but the relationship between TLR4 genotypes and aggressive PCa risk has not been evaluated by any systematic reviews. Methods: We performed a systematic review and meta-analysis of candidate-gene and genome-wide association studies analyzing this relationship and included only white population. Considering appropriate criteria, only nine studies were analyzed in the meta-analysis, including 3,937 aggressive PCa and 7,382 controls. Results: Using random effects model, no significant association was found in the ten TLR4 SNPs reported by at least four included studies under any inheritance model (rs2737191, rs1927914, rs10759932, rs1927911, rs11536879, rs2149356, rs4986790, rs11536889, rs7873784, and rs1554973). Pooled estimates from another ten TLR4 SNPs reported by three studies also showed no significant association (rs10759930, rs10116253, rs11536869, rs5030717, rs4986791, rs11536897, rs1927906, rs913930, rs1927905, and rs7045953). Meta-regression revealed that study type was not a significant source of between-study heterogeneity. Conclusions: TLR4 polymorphisms were not significantly associated with the risk of aggressive PCa

Proceedings of the 4th bwHPC Symposium

The bwHPC Symposium 2017 took place on October 4th, 2017, Alte Aula, Tübingen. It focused on the presentation of scientific computing projects as well as on the progress and the success stories of the bwHPC realization concept. The event offered a unique opportunity to engage in an active dialogue between scientific users, operators of bwHPC sites, and the bwHPC support team

DNA damage induced by cis- and carboplatin as indicator for in vitro sensitivity of ovarian carcinoma cells

<p>Abstract</p> <p>Background</p> <p>The DNA damage by platinum cytostatics is thought to be the main cause of their cytotoxicity. Therefore the measurement of the DNA damage induced by cis- and carboplatin should reflect the sensitivity of cancer cells toward the platinum chemotherapeutics.</p> <p>Methods</p> <p>DNA damage induced by cis- and carboplatin in primary cells of ovarian carcinomas was determined by the alkaline comet assay. In parallel, the reduction of cell viability was measured by the fluorescein diacetate (FDA) hydrolysis assay.</p> <p>Results</p> <p>While in the comet assay the isolated cells showed a high degree of DNA damage after a 24 h treatment, cell viability revealed no cytotoxicity after that incubation time. The individual sensitivities to DNA damage of 12 tumour biopsies differed up to a factor of about 3. DNA damage after a one day treatment with cis- or carboplatin correlated well with the cytotoxic effects after a 7 day treatment (r = 0,942 for cisplatin r = 0.971 for carboplatin). In contrast to the platinum compounds the correlation of DNA damage and cytotoxicity induced by adriamycin was low (r = 0,692), or did not exist for gemcitabine.</p> <p>Conclusion</p> <p>The measurement of DNA damage induced by cis- and carboplatin is an accurate method to determine the in vitro chemosensitivity of ovarian cancer cells towards these cytostatics, because of its quickness, sensitivity, and low cell number needed.</p

Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes.

The reanalysis of existing GWAS data represents a powerful and cost-effective opportunity to gain insights into the genetics of complex diseases. By reanalyzing publicly available type 2 diabetes (T2D) genome-wide association studies (GWAS) data for 70,127 subjects, we identify seven novel associated regions, five driven by common variants (LYPLAL1, NEUROG3, CAMKK2, ABO, and GIP genes), one by a low-frequency (EHMT2), and one driven by a rare variant in chromosome Xq23, rs146662057, associated with a twofold increased risk for T2D in males. rs146662057 is located within an active enhancer associated with the expression of Angiotensin II Receptor type 2 gene (AGTR2), a modulator of insulin sensitivity, and exhibits allelic specific activity in muscle cells. Beyond providing insights into the genetics and pathophysiology of T2D, these results also underscore the value of reanalyzing publicly available data using novel genetic resources and analytical approaches

Interaction of Rio1 Kinase with Toyocamycin Reveals a Conformational Switch That Controls Oligomeric State and Catalytic Activity

Rio1 kinase is an essential ribosome-processing factor required for proper maturation of 40 S ribosomal subunit. Although its structure is known, several questions regarding its functional remain to be addressed. We report that both Archaeoglobus fulgidus and human Rio1 bind more tightly to an adenosine analog, toyocamycin, than to ATP. Toyocamycin has antibiotic, antiviral and cytotoxic properties, and is known to inhibit ribosome biogenesis, specifically the maturation of 40 S. We determined the X-ray crystal structure of toyocamycin bound to Rio1 at 2.0 Å and demonstrated that toyocamycin binds in the ATP binding pocket of the protein. Despite this, measured steady state kinetics were inconsistent with strict competitive inhibition by toyocamycin. In analyzing this interaction, we discovered that Rio1 is capable of accessing multiple distinct oligomeric states and that toyocamycin may inhibit Rio1 by stabilizing a less catalytically active oligomer. We also present evidence of substrate inhibition by high concentrations of ATP for both archaeal and human Rio1. Oligomeric state studies show both proteins access a higher order oligomeric state in the presence of ATP. The study revealed that autophosphorylation by Rio1 reduces oligomer formation and promotes monomerization, resulting in the most active species. Taken together, these results suggest the activity of Rio1 may be modulated by regulating its oligomerization properties in a conserved mechanism, identifies the first ribosome processing target of toyocamycin and presents the first small molecule inhibitor of Rio1 kinase activity

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele