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

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

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

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

Comparing Approaches to Deal with Non-Gaussianity of Rainfall Data in Kriging-Based Radar-Gauge Rainfall Merging

Merging radar and rain gauge rainfall data is a technique used to improve the quality of spatial rainfall estimates and in particular the use of Kriging with External Drift (KED) is a very effective radar-rain gauge rainfall merging technique. However, kriging interpolations assume Gaussianity of the process. Rainfall has a strongly skewed, positive, probability distribution, characterized by a discontinuity due to intermittency. In KED rainfall residuals are used, implicitly calculated as the difference between rain gauge data and a linear function of the radar estimates. Rainfall residuals are non-Gaussian as well. The aim of this work is to evaluate the impact of applying KED to non-Gaussian rainfall residuals, and to assess the best techniques to improve Gaussianity. We compare Box-Cox transformations with λ parameters equal to 0.5, 0.25, and 0.1, Box-Cox with time-variant optimization of λ, normal score transformation, and a singularity analysis technique. The results suggest that Box-Cox with λ = 0.1 and the singularity analysis is not suitable for KED. Normal score transformation and Box-Cox with optimized λ, or λ = 0.25 produce satisfactory results in terms of Gaussianity of the residuals, probability distribution of the merged rainfall products, and rainfall estimate quality, when validated through cross-validation. However, it is observed that Box-Cox transformations are strongly dependent on the temporal and spatial variability of rainfall and on the units used for the rainfall intensity. Overall, applying transformations results in a quantitative improvement of the rainfall estimates only if the correct transformations for the specific data set are used.ISSN:0043-1397ISSN:1944-797

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