Impact‐based forecasting for pluvial floods

Pluvial floods in urban areas are caused by local, fast storm events with very high rainfall rates, which lead to inundation of streets and buildings before the storm water reaches a watercourse. An increase in frequency and intensity of heavy rainfall events and an ongoing urbanization may further increase the risk of pluvial flooding in many urban areas. Currently, warnings for pluvial floods are mostly limited to information on rainfall intensities and durations over larger areas, which is often not detailed enough to effectively protect people and goods. We present a proof-of-concept for an impact-based forecasting system for pluvial floods. Using a model chain consisting of a rainfall forecast, an inundation, a contaminant transport and a damage model, we are able to provide predictions for the expected rainfall, the inundated areas, spreading of potential contamination and the expected damage to residential buildings. We use a neural network-based inundation model, which significantly reduces the computation time of the model chain. To demonstrate the feasibility, we perform a hindcast of a recent pluvial flood event in an urban area in Germany. The required spatio-temporal accuracy of rainfall forecasts is still a major challenge, but our results show that reliable impact-based warnings can be forecasts are available up to 5 min before the peak of an extreme rainfall event. Based on our results, we discuss how the outputs of the impact-based forecast could be used to disseminate impact-based early warnings

The crystal structure of human Rogdi provides insight into the causes of Kohlschutter-Tonz Syndrome

Kohlschutter-Tönz syndrome (KTS) is a rare autosomal-recessive disorder of childhood onset characterized by global developmental delay, spasticity, epilepsy, and amelogenesis imperfecta. Rogdi, an essential protein, is highly conserved across metazoans, and mutations in Rogdi are linked to KTS. However, how certain mutations in Rogdi abolish its physiological functions and cause KTS is not known. In this study, we determined the crystal structure of human Rogdi protein at atomic resolution. Rogdi forms a novel elongated curved structure comprising the ?? domain, a leucine-zipper-like four-helix bundle, and a characteristic ??-sheet domain. Within the ?? domain, the N-terminal H1 helix (residues 19-45) pairs with the C-terminal H6 helix (residues 252-287) in an antiparallel manner, indicating that the integrity of the four-helix bundle requires both N- and C-terminal residues. The crystal structure, in conjunction with biochemical data, indicates that the ?? domain might undergo a conformational change and provide a structural platform for protein-protein interactions. Disruption of the four-helix bundle by mutation results in significant destabilization of the structure. This study provides structural insights into how certain mutations in Rogdi affect its structure and cause KTS, which has important implications for the development of pharmaceutical agents against this debilitating neurological disease

Analysis of Large Scale Spatial Variability of Soil Moisture Using a Geostatistical Method

Spatial and temporal soil moisture dynamics are critically needed to improve the parameterization for hydrological and meteorological modeling processes. This study evaluates the statistical spatial structure of large-scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial in calibration and validation of large-scale satellite based data assimilation systems. Spatial analysis using geostatistical approaches was used to validate modeled soil moisture by the Agriculture Meteorological (AGRMET) model using in situ measurements of soil moisture from a state-wide environmental monitoring network (Oklahoma Mesonet). The results show that AGRMET data produces larger spatial decorrelation compared to in situ based soil moisture data. The precipitation storms drive the soil moisture spatial structures at large scale, found smaller decorrelation length after precipitation. This study also evaluates the geostatistical approach for mitigation for quality control issues within in situ soil moisture network to estimates at soil moisture at unsampled stations

Changes over time in characteristics, resource use and outcomes among ICU patients with COVID-19-A nationwide, observational study in Denmark

BACKGROUND: Characteristics and care of intensive care unit (ICU) patients with COVID‐19 may have changed during the pandemic, but longitudinal data assessing this are limited. We compared patients with COVID‐19 admitted to Danish ICUs in the first wave with those admitted later. METHODS: Among all Danish ICU patients with COVID‐19, we compared demographics, chronic comorbidities, use of organ support, length of stay and vital status of those admitted 10 March to 19 May 2020 (first wave) versus 20 May 2020 to 30 June 2021. We analysed risk factors for death by adjusted logistic regression analysis. RESULTS: Among all hospitalised patients with COVID‐19, a lower proportion was admitted to ICU after the first wave (13% vs. 8%). Among all 1374 ICU patients with COVID‐19, 326 were admitted during the first wave. There were no major differences in patient's characteristics or mortality between the two periods, but use of invasive mechanical ventilation (81% vs. 58% of patients), renal replacement therapy (26% vs. 13%) and ECMO (8% vs. 3%) and median length of stay in ICU (13 vs. 10 days) and in hospital (20 vs. 17 days) were all significantly lower after the first wave. Risk factors for death were higher age, larger burden of comorbidities (heart failure, pulmonary disease and kidney disease) and active cancer, but not admission during or after the first wave. CONCLUSIONS: After the first wave of COVID‐19 in Denmark, a lower proportion of hospitalised patients with COVID‐19 were admitted to ICU. Among ICU patients, use of organ support was lower and length of stay was reduced, but mortality rates remained at a relatively high level

Paediatric autoimmune encephalopathies:Clinical features, laboratory investigations and outcomes in patients with or without antibodies to known central nervous system autoantigens

Objective: To report the clinical and investigative features of children with a clinical diagnosis of probable autoimmune encephalopathy, both with and without antibodies to central nervous system antigens. Method: Patients with encephalopathy plus one or more of neuropsychiatric symptoms, seizures, movement disorder or cognitive dysfunction, were identified from 111 paediatric serum samples referred from five tertiary paediatric neurology centres to Oxford for antibody testing in 2007-2010. A blinded clinical review panel identified 48 patients with a diagnosis of probable autoimmune encephalitis whose features are described. All samples were tested/retested for antibodies to N-methyl-D-aspartate receptor (NMDAR), VGKC-complex, LGI1, CASPR2 and contactin-2, GlyR, D1R, D2R, AMPAR, GABA(B)R and glutamic acid decarboxylase. Results Seizures (83%), behavioural change (63%), confusion (50%), movement disorder (38%) and hallucinations (25%) were common. 52% required intensive care support for seizure control or profound encephalopathy. An acute infective organism (15%) or abnormal cerebrospinal fluid (32%), EEG (70%) or MRI (37%) abnormalities were found. One 14-year-old girl had an ovarian teratoma. Serum antibodies were detected in 21/48 (44%) patients: NMDAR 13/48 (27%), VGKC-complex 7/48(15%) and GlyR 1/48(2%). Antibody negative patients shared similar clinical features to those who had specific antibodies detected. 18/34 patients (52%) who received immunotherapy made a complete recovery compared to 4/14 (28%) who were not treated; reductions in modified Rankin Scale for children scores were more common following immunotherapies. Antibody status did not appear to in fluence the treatment effect. Conclusions: Our study outlines the common clinical and paraclinical features of children and adolescents with probable autoimmune encephalopathies. These patients, irrespective of positivity for the known antibody targets, appeared to benefit from immunotherapies and further antibody targets may be defined in the future

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

16p11.2 600 kb Duplications confer risk for typical and atypical Rolandic epilepsy

Rolandic epilepsy (RE) is the most common idiopathic focal childhood epilepsy. Its molecular basis is largely unknown and a complex genetic etiology is assumed in the majority of affected individuals. The present study tested whether six large recurrent copy number variants at 1q21, 15q11.2, 15q13.3, 16p11.2, 16p13.11 and 22q11.2 previously associated with neurodevelopmental disorders also increase risk of RE. Our association analyses revealed a significant excess of the 600 kb genomic duplication at the 16p11.2 locus (chr16: 29.5-30.1 Mb) in 393 unrelated patients with typical (n = 339) and atypical (ARE; n = 54) RE compared with the prevalence in 65 046 European population controls (5/393 cases versus 32/65 046 controls; Fisher's exact test P = 2.83 × 10−6, odds ratio = 26.2, 95% confidence interval: 7.9-68.2). In contrast, the 16p11.2 duplication was not detected in 1738 European epilepsy patients with either temporal lobe epilepsy (n = 330) and genetic generalized epilepsies (n = 1408), suggesting a selective enrichment of the 16p11.2 duplication in idiopathic focal childhood epilepsies (Fisher's exact test P = 2.1 × 10−4). In a subsequent screen among children carrying the 16p11.2 600 kb rearrangement we identified three patients with RE-spectrum epilepsies in 117 duplication carriers (2.6%) but none in 202 carriers of the reciprocal deletion. Our results suggest that the 16p11.2 duplication represents a significant genetic risk factor for typical and atypical R

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

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

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