Estimation of radar-based area–depth–duration–frequency curves with special focus on spatial sampling problems

Radar-based area–depth–duration–frequency (ADDF) curves offer the possibility of incorporating a space dimension into the analysis of rainfall extremes. This solves some shortcomings of the traditional point-based depth–duration–frequency (DDF) curves which characterize design rainfall. In this study, ADDF curves are calculated from a radar-based rainfall data set, a product of the conditional merging of corrected radar data and station data, covering a large area in the north part of Germany. The initial results show implausible behavior in the curves where the rainfall quantiles increase with increasing area. It is discussed in detail in this paper that the implausible behavior persists due to the shortcoming of fixed-area sampling methods which are missing the most extreme annual maximum rainfall events within the area of interest. Three alternative sampling strategies are developed to address this issue. Among the introduced methods the multiple-location extreme sampling (MLES) and the single-location extreme sampling (SLES) methods successfully reduced the number of study locations with implausible behavior by 67 % and 43 % respectively. The SLES method is recommended as the best method for calculating areal design rainfall directly from high-resolution radar-based data sets. This method tackles the spatial sampling issue, and it can result in area-reduction-factor values compatible with station-based point design rainfall values.</p

Evaluation of presumably disease causing SCN1A variants in a cohort of common epilepsy syndromes

Objective: The SCN1A gene, coding for the voltage-gated Na+ channel alpha subunit NaV1.1, is the clinically most relevant epilepsy gene. With the advent of high-throughput next-generation sequencing, clinical laboratories are generating an ever-increasing catalogue of SCN1A variants. Variants are more likely to be classified as pathogenic if they have already been identified previously in a patient with epilepsy. Here, we critically re-evaluate the pathogenicity of this class of variants in a cohort of patients with common epilepsy syndromes and subsequently ask whether a significant fraction of benign variants have been misclassified as pathogenic. Methods: We screened a discovery cohort of 448 patients with a broad range of common genetic epilepsies and 734 controls for previously reported SCN1A mutations that were assumed to be disease causing. We re-evaluated the evidence for pathogenicity of the identified variants using in silico predictions, segregation, original reports, available functional data and assessment of allele frequencies in healthy individuals as well as in a follow up cohort of 777 patients. Results and Interpretation: We identified 8 known missense mutations, previously reported as path

Plant cell culture technology in the cosmetics and food industries : current state and future trends

The production of drugs, cosmetics, and food which are derived from plant cell and tissue cultures has a long tradition. The emerging trend of manufacturing cosmetics and food products in a natural and sustainable manner has brought a new wave in plant cell culture technology over the past 10 years. More than 50 products based on extracts from plant cell cultures have made their way into the cosmetics industry during this time, whereby the majority is produced with plant cell suspension cultures. In addition, the first plant cell culture-based food supplement ingredients, such as Echigena Plus and Teoside 10, are now produced at production scale. In this mini review, we discuss the reasons for and the characteristics as well as the challenges of plant cell culture-based productions for the cosmetics and food industries. It focuses on the current state of the art in this field. In addition, two examples of the latest developments in plant cell culture-based food production are presented, that is, superfood which boosts health and food that can be produced in the lab or at home

Dynamics of intracellular mannan and cell wall folding in the drought responses of succulent <i>Aloe</i> species

Plants have evolved a multitude of adaptations to survive extreme conditions. Succulent plants have the capacity to tolerate periodically dry environments, due to their ability to retain water in a specialized tissue, termed hydrenchyma. Cell wall polysaccharides are important components of water storage in hydrenchyma cells. However, the role of the cell wall and its polysaccharide composition in relation to drought resistance of succulent plants are unknown. We investigate the drought response of leaf-succulent Aloe (Asphodelaceae) species using a combination of histological microscopy, quantification of water content, and comprehensive microarray polymer profiling. We observed a previously unreported mode of polysaccharide and cell wall structural dynamics triggered by water shortage. Microscopical analysis of the hydrenchyma cell walls revealed highly regular folding patterns indicative of predetermined cell wall mechanics in the remobilization of stored water and the possible role of homogalacturonan in this process. The in situ distribution of mannans in distinct intracellular compartments during drought, for storage, and apparent upregulation of pectins, imparting flexibility to the cell wall, facilitate elaborate cell wall folding during drought stress. We conclude that cell wall polysaccharide composition plays an important role in water storage and drought response in Aloe

Computational Models of Classical Conditioning guest editors’ introduction

In the present special issue, the performance of current computational models of classical conditioning was evaluated under three requirements: (1) Models were to be tested against a list of previously agreed-upon phenomena; (2) the parameters were fixed across simulations; and (3) the simulations used to test the models had to be made available. These requirements resulted in three major products: (a) a list of fundamental classical-conditioning results for which there is a consensus about their reliability; (b) the necessary information to evaluate each of the models on the basis of its ordinal successes in accounting for the experimental data; and (c) a repository of computational models ready to generate simulations. We believe that the contents of this issue represent the 2012 state of the art in computational modeling of classical conditioning and provide a way to find promising avenues for future model development

Klimafolgenabschätzungen in der Wasserwirtschaft und deren Nutzen für die Praxis

KlimafolgenClimate ImpactsDer globale Klimawandel kann regional unterschiedliche Auswirkungen haben. Während sich die wissenschaftliche Forschung vor allem mit der Analyse der Daten beschäftigt, ist die fachliche Praxis darum bemüht, die Ergebnisse zu interpretieren und Handlungsempfehlungen daraus abzuleiten. Im Zuge des Projektes KliBiW (Globaler Klimawandel – Wasserwirtschaftliche Folgenabschätzung für das Binnenland) wurden die Auswirkungen des Klimawandels auf die Hochwasser- und Niedrigwasserverhältnisse in Niedersachsen untersucht. Hierzu wurden die Daten von zwei regionalen Klimamodellen (WETTREG2006 und REMO), beide angetrieben durch das Globalmodell ECHAM5/MPI-OM, räumlich interpoliert und die Niederschläge zum Teil zeitlich disaggregiert, um hoch aufgelöste Klimainformationen bereitzuhalten. Anschließend erfolgte die Kopplung mit einem hydrologischen Modellsystem (PANTA RHEI), das bereits in der Hochwasservorhersagezentrale des NLWKN im Einsatz ist. Über Langzeitsimulationen wurden zukünftige Veränderungen in den Abflussverhältnissen räumlich und zeitlich differenziert für das Aller-Leine Gebiet identifiziert. Als Betrachtungszeiträume dienten eine nahe Zukunftsphase (2021 – 2050) und eine ferne Zukunftsphase (2071 – 2100). Die Veränderungen verschiedener hydrologischer Hoch- und Niedrigwasser-Kenngrößen wurden gegenüber einem Kontrollzeitraum (1971 – 2000) aufgezeigt. Die Auswertungen an 8 Pegeln in Einzugsgebieten >1.000 km² auf Tageswertbasis und an 6 Pegeln in Einzugsgebieten <1.000 km² auf Stundenwertbasis zeigten, dass sich die Hochwassersituation zukünftig verschärfen kann. Während kleinere Hochwässer häufiger auftreten können, nehmen die Scheitelabflüsse insbesondere in der fernen Zukunft zu. Aussagen zu größeren Ereignissen sind aufgrund der großen Bandbreite der Ergebnisse jedoch mit erheblichen Unsicherheiten behaftet. Die Niedrigwasserverhältnisse zeigten eine Abnahme der Abflüsse, speziell im Sommer, sowie eine Zunahme der Dauer undnder Volumendefizite bei Trockenperioden. Hierbei erschien die Variabilität und Ausprägung der Trockenheit in kleineren Einzugsgebieten etwas größer. Die Nutzung dieser Erkenntnisse stellt die fachliche Praxis vor die Herausforderung, die Ergebnisse zu interpretieren und zu kommunizieren. Unsicherheiten in den Modellketten müssen berücksichtigt und, wenn möglich, quantifiziert werden. Die abgeleiteten hydrologischen Konsequenzen des Klimawandels können z.B. Anwendung finden in der gesetzlich geforderten Berücksichtigung der Auswirkungen des Klimawandels auf die Risikogebiete entsprechend der Hochwasserrisikomanagement-Richtlinie (2007/60/EG). Dieser Beitrag gibt einen Überblick über wasserwirtschaftlich relevante Auswertungen von Klimamodelldaten auf unterschiedlichen räumlichen Skalen und zeigt anhand ausgewählter Beispiele auf, wie primär im wissenschaftlichen Kontext erhobene Ergebnisse effektiv für praxisrelevante Fragestellungen genutzt werden können

Negative Priming Under Rapid Serial Visual Presentation

Negative priming (NP) was examined under a new paradigm wherein a target and distractors were temporally separated using rapid serial visual presentation (RSVP). The results from the two experiments revealed that (a) NP was robust under RSVP, such that the responses to a target were slower when the target served as a distractor in a previous trial than when it did not; (b) NP was found regardless of whether the distractors appeared before or after the targets; and (c) NP was stronger when the distractor was more distinctive. These findings are generally similar to those on NP in the spatial search task. The implications for the processes causing NP under RSVP are discussed in the current paper

The influence of hygroscopic movement on seed dispersal in Daucus carota (Apiaceae)

The influence of hygroscopic movement on seed dispersal in Daucus carota was examined. When relative humidity increases, umbels containing mature fruits close; when relative humidity drops, umbels open. Tests of the effectiveness of smalland large-angled umbels on dispersing seeds under various conditions demonstrate that umbels responding greatly to relative humidity (i.e. opening wide) lose seeds more quickly than do umbels responding little, and do not disperse them as far. As relative humidity increases, number of dispersing seeds drops to near zero. Response to changes in relative humidity within an umbel progressively increases from late August when dispersal begins. Umbels that slowly increase their response retain some seeds that may disperse over snow in winter. Individual variation in response to relative humidity is high among plants beginning dispersal at the same time. This variability is probably maintained by the variable consequences of dispersing seeds at different times.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47734/1/442_2004_Article_BF00541784.pd

Evaluation of presumably disease causing SCN1A variants in a cohort of common epilepsy syndromes

Objective: The SCN1A gene, coding for the voltage-gated Na+ channel alpha subunit NaV1.1, is the clinically most relevant epilepsy gene. With the advent of high-throughput next-generation sequencing, clinical laboratories are generating an ever-increasing catalogue of SCN1A variants. Variants are more likely to be classified as pathogenic if they have already been identified previously in a patient with epilepsy. Here, we critically re-evaluate the pathogenicity of this class of variants in a cohort of patients with common epilepsy syndromes and subsequently ask whether a significant fraction of benign variants have been misclassified as pathogenic. Methods: We screened a discovery cohort of 448 patients with a broad range of common genetic epilepsies and 734 controls for previously reported SCN1A mutations that were assumed to be disease causing. We re-evaluated the evidence for pathogenicity of the identified variants using in silico predictions, segregation, original reports, available functional data and assessment of allele frequencies in healthy individuals as well as in a follow up cohort of 777 patients. Results and Interpretation: We identified 8 known missense mutations, previously reported as pathogenic, in a total of 17 unrelated epilepsy patients (17/448; 3.80%). Our re-evaluation indicates that 7 out of these 8 variants (p.R27T; p.R28C; p.R542Q; p.R604H; p.T1250M; p.E1308D; p.R1928G; NP-001159435.1) are not pathogenic. Only the p.T1174S mutation may be considered as a genetic risk factor for epilepsy of small effect size based on the enrichment in patients (P = 6.60 7 10-4; OR = 0.32, fishers exact test), previous functional studies but incomplete penetrance. Thus, incorporation of previous studies in genetic counseling of SCN1A sequencing results is challenging and may produce incorrect conclusions

Natural clusters of tuberous sclerosis complex (TSC)-associated neuropsychiatric disorders (TAND): new findings from the TOSCA TAND research project.

BACKGROUND: Tuberous sclerosis complex (TSC)-associated neuropsychiatric disorders (TAND) have unique, individual patterns that pose significant challenges for diagnosis, psycho-education, and intervention planning. A recent study suggested that it may be feasible to use TAND Checklist data and data-driven methods to generate natural TAND clusters. However, the study had a small sample size and data from only two countries. Here, we investigated the replicability of identifying natural TAND clusters from a larger and more diverse sample from the TOSCA study. METHODS: As part of the TOSCA international TSC registry study, this embedded research project collected TAND Checklist data from individuals with TSC. Correlation coefficients were calculated for TAND variables to generate a correlation matrix. Hierarchical cluster and factor analysis methods were used for data reduction and identification of natural TAND clusters. RESULTS: A total of 85 individuals with TSC (female:male, 40:45) from 7 countries were enrolled. Cluster analysis grouped the TAND variables into 6 clusters: a scholastic cluster (reading, writing, spelling, mathematics, visuo-spatial difficulties, disorientation), a hyperactive/impulsive cluster (hyperactivity, impulsivity, self-injurious behavior), a mood/anxiety cluster (anxiety, depressed mood, sleep difficulties, shyness), a neuropsychological cluster (attention/concentration difficulties, memory, attention, dual/multi-tasking, executive skills deficits), a dysregulated behavior cluster (mood swings, aggressive outbursts, temper tantrums), and an autism spectrum disorder (ASD)-like cluster (delayed language, poor eye contact, repetitive behaviors, unusual use of language, inflexibility, difficulties associated with eating). The natural clusters mapped reasonably well onto the six-factor solution generated. Comparison between cluster and factor solutions from this study and the earlier feasibility study showed significant similarity, particularly in cluster solutions. CONCLUSIONS: Results from this TOSCA research project in an independent international data set showed that the combination of cluster analysis and factor analysis may be able to identify clinically meaningful natural TAND clusters. Findings were remarkably similar to those identified in the earlier feasibility study, supporting the potential robustness of these natural TAND clusters. Further steps should include examination of larger samples, investigation of internal consistency, and evaluation of the robustness of the proposed natural clusters