Psychiatric characterization of children with genetic causes of hyperandrogenism

Objective: Very little is known about the mental health status in children with genetic causes of hyperandrogenism. This study sought to characterize psychiatric morbidity in this group. Design/methods: Children (8-18 years) with the diagnosis of classic congenital adrenal hyperplasia (CAH) or familial male precocious puberty (FMPP) underwent a semi-structured psychiatric interview, the Kiddie Schedule for Affective Disorders and Schizophrenia-Present and Lifetime Version. According to sex and the literature, incidence of identified psychopathology was compared between the two endocrinological groups. We evaluated 72 patients: 54 CAH (21 females) and 18 FMPP. Results: Twenty-four (44.4%) CAH patients and 10 (55.6%) FMPP patients met the criteria for at least one lifetime psychiatric diagnosis. Attention-deficit hyperactivity disorder (ADHD) was present in 18.2% of CAH males, 44.4% of FMPP males, and one case (4.8%) in CAH females. A high rate of anxiety disorders was also found in all the three groups (17-21%). Relative to females with CAH, the FMPP patients exhibited higher rates of ADHD. Age at diagnosis and the treatment modalities were not associated with psychopathology. Rates of psychiatric disorder, specifically ADHD and anxiety disorders, were higher than in the general population. Conclusion: Although anxiety disorders may occur at an increased rate in children with chronic illness, androgens may contribute to higher risk for psychopathology in pediatric patients with genetic cause of excess androgen. Early diagnosis and treatment of childhood hyperandrogenism is essential for optimal development. The results suggest that assessment for psychiatric disorders should be part of the routine evaluation of these patients

Grey matter volume correlates with virtual water maze task performance in boys with androgen excess

Major questions remain about the specific role of testosterone in human spatial navigation. We tested 10 boys (mean age 11.65 years) with an extremely rare disorder of androgen excess (Familial Male Precocious Puberty, FMPP) and 40 healthy boys (mean age 12.81 years) on a virtual version of the Morris Water Maze task. In addition, anatomical magnetic resonance images were collected for all patients and a subsample of the controls (n=21) after task completion. Behaviourally, no significant differences were found between both groups. However, in the MRI analyses, grey matter volume (GMV) was correlated with performance using voxel-based morphometry (VBM). Group differences in correlations of performance with GMV were apparent in medial regions of the prefrontal cortex as well as the middle occipital gyrus and the cuneus. By comparison, similar correlations for both groups were found in the inferior parietal lobule. These data provide novel insight into the relation between testosterone and brain development and suggest that morphological differences in a spatial navigation network covary with performance in spatial ability. Published by Elsevier Ltd on behalf of IBRO

Challenges of data management and analytics in omni-channel CRM

Data Management and Data Analytics are of huge importance to Business Process Outsourcing Providers in Customer Relationship Management (CRM) in order to offer tailor-made CRM Solutions to their business clients during presales, sales and aftersales. These solutions support business clients to improve their internal processes, as well as their customer service in a variety of communication channels (including e-mail, chat, social media, private messages, etc.) to reach out to end customers in an efficient way. As customer interactions may happen via various channels basically at any time, a crucial challenge is to efficiently store and integrate the data of the various channels in order to obtain a unified customer profile. This paper abstracts from the underlying platforms and instead considers the requirements to CRM solutions for the various communication channels, in order to devise a uniform and corporate-wide data architecture for an omni-channel customer view to maximize the business clients' value in customer retention and customer centric analytics. Especially, online customer segmentation integrating channel usage and preferences is presented as a very promising means for constructing a self-energising information loop which will lead to highly improved customer service along the whole customer journey

Effects of human growth hormone on gonadotropin-releasing hormone neurons in mice

PurposeRecombinant human growth hormone (rhGH) has been widely used to treat short stature. However, there are some concerns that growth hormone treatment may induce skeletal maturation and early onset of puberty. In this study, we investigated whether rhGH can directly affect the neuronal activities of of gonadotropin-releasing hormone (GnRH).MethodsWe performed brain slice gramicidin-perforated current clamp recording to examine the direct membrane effects of rhGH on GnRH neurons, and a whole-cell voltage-clamp recording to examine the effects of rhGH on spontaneous postsynaptic events and holding currents in immature (postnatal days 13-21) and adult (postnatal days 42-73) mice.ResultsIn immature mice, all 5 GnRH neurons recorded in gramicidin-perforated current clamp mode showed no membrane potential changes on application of rhGH (0.4, 1 µg/mL). In adult GnRH neurons, 7 (78%) of 9 neurons tested showed no response to rhGH (0.2-1 µg/mL) and 2 neurons showed slight depolarization. In 9 (90%) of 10 immature neurons tested, rhGH did not induce any membrane holding current changes or spontaneous postsynaptic currents (sPSCs). There was no change in sPSCs and holding current in 4 of 5 adult GnRH neurons.ConclusionThese findings demonstrate that rhGH does not directly affect the GnRH neuronal activities in our experimental model

A Genome-Wide Association Study of Diabetic Kidney Disease in Subjects With Type 2 Diabetes

dentification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication samples, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 x 10(-8)) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased sample sizes will continue to provide more robust inference regarding risk variant discovery for DKD.Peer reviewe

Benchmarking recommender systems

Recommender Systeme unterstützen aus einem Angebot von Diensten und Produkten auf bspw. Verkaufs- oder Unterhaltungsplattformen, diejenigen zu finden, die die persönlichen Präferenzen bestmöglich abdecken. Durch die Nutzung von Kanälen wie dem Web, sozialen Medien oder E-Mail können zur weiteren Personalisierung auch Produktbewertungen und -betrachtungen oder Interaktionen in sozialen Medien genutzt werden. Diese Arbeit beleuchtet, ob das Aggregieren von diesen Omni-Kanal-Daten die Empfehlungen positiv beeinflusst. Dazu wird zunächst ein Benchmark-Konzept für die Evaluierung kollaborativer Recommender Systeme entwickelt, das ein generisches Datenmodell und Aspekte der Datengenerierung und -aggregation umfasst. Anschließend wird das Konzept durch etablierte Implementierungen auf realen Daten eines Online-Händlers angewendet und die Ergebnisse werden ausführlich diskutiert. Dabei werden neben der Genauigkeit der Empfehlungen auch technische und geschäftliche Perspektiven betrachtet.Recommender systems support finding services and products on, for instance, e-commerce or entertainment platforms, which best cover personal preferences. Through the usage of channels as the Web, social media, and email, product reviews and views or social media interactions can be used for further personalization. This thesis considers whether the aggregation of this omni-channel data influences recommendations positively. In this regard, first, a benchmark concept for the evaluation of collaborative recommender systems is developed, which includes a generic data model as well as data generation and data aggregation aspects. Subsequently, the concept is applied to a real-world data set of an online retailer based on established implementations, and the results are discussed elaborately. Besides the recommendation accuracy, this also includes to consider technical and business perspectives