PReS-FINAL-2146: Trends in prescription of biologics and outcomes of juvenile idiopathic arthritis; results of the Dutch national arthritis and biologicals in children register

Transplantation and immunomodulatio

Analysis of urinary oligosaccharides in lysosomal storage disorders by capillary high-performance anion-exchange chromatography–mass spectrometry

Many lysosomal storage diseases are characterized by an increased urinary excretion of glycoconjugates and oligosaccharides that are characteristic for the underlying enzymatic defect. Here, we have used capillary high-performance anion-exchange chromatography (HPAEC) hyphenated to mass spectrometry to analyze free oligosaccharides from urine samples of patients suffering from the lysosomal storage disorders fucosidosis, α-mannosidosis, GM1-gangliosidosis, GM2-gangliosidosis, and sialidosis. Glycan fingerprints were registered, and the patterns of accumulated oligosaccharides were found to reflect the specific blockages of the catabolic pathway. Our analytical approach allowed structural analysis of the excreted oligosaccharides and revealed several previously unpublished oligosaccharides. In conclusion, using online coupling of HPAEC with mass spectrometric detection, our study provides characteristic urinary oligosaccharide fingerprints with diagnostic potential for lysosomal storage disorders

Prevalence and Characterization of Motile Salmonella in Commercial Layer Poultry Farms in Bangladesh

Salmonella is a globally widespread food-borne pathogen having major impact on public health. All motile serovars of Salmonella enterica of poultry origin are zoonotic, and contaminated meat and raw eggs are an important source to human infections. Information on the prevalence of Salmonella at farm/holding level, and the zoonotic serovars circulating in layer poultry in the South and South-East Asian countries including Bangladesh, where small-scale commercial farms are predominant, is limited. To investigate the prevalence of Salmonella at layer farm level, and to identify the prevalent serovars we conducted a cross-sectional survey by randomly selecting 500 commercial layer poultry farms in Bangladesh. Faecal samples from the selected farms were collected following standard procedure, and examined for the presence of Salmonella using conventional bacteriological procedures. Thirty isolates were randomly selected, from the ninety obtained from the survey, for serotyping and characterized further by plasmid profiling and pulsed-field gel electrophoresis (PFGE). Results of the survey showed that the prevalence of motile Salmonella at layer farm level was 18% (95% confidence interval 15–21%), and Salmonella Kentucky was identified to be the only serovar circulating in the study population. Plasmid analysis of the S. Kentucky and non-serotyped isolates revealed two distinct profiles with a variation of two different sizes (2.7 and 4.8 kb). PFGE of the 30 S. Kentucky and 30 non-serotyped isolates showed that all of them were clonally related because only one genotype and three subtypes were determined based on the variation in two or three bands. This is also the first report on the presence of any specific serovar of Salmonella enterica in poultry in Bangladesh

Impact of Dendritic Size and Dendritic Topology on Burst Firing in Pyramidal Cells

Neurons display a wide range of intrinsic firing patterns. A particularly relevant pattern for neuronal signaling and synaptic plasticity is burst firing, the generation of clusters of action potentials with short interspike intervals. Besides ion-channel composition, dendritic morphology appears to be an important factor modulating firing pattern. However, the underlying mechanisms are poorly understood, and the impact of morphology on burst firing remains insufficiently known. Dendritic morphology is not fixed but can undergo significant changes in many pathological conditions. Using computational models of neocortical pyramidal cells, we here show that not only the total length of the apical dendrite but also the topological structure of its branching pattern markedly influences inter- and intraburst spike intervals and even determines whether or not a cell exhibits burst firing. We found that there is only a range of dendritic sizes that supports burst firing, and that this range is modulated by dendritic topology. Either reducing or enlarging the dendritic tree, or merely modifying its topological structure without changing total dendritic length, can transform a cell's firing pattern from bursting to tonic firing. Interestingly, the results are largely independent of whether the cells are stimulated by current injection at the soma or by synapses distributed over the dendritic tree. By means of a novel measure called mean electrotonic path length, we show that the influence of dendritic morphology on burst firing is attributable to the effect both dendritic size and dendritic topology have, not on somatic input conductance, but on the average spatial extent of the dendritic tree and the spatiotemporal dynamics of the dendritic membrane potential. Our results suggest that alterations in size or topology of pyramidal cell morphology, such as observed in Alzheimer's disease, mental retardation, epilepsy, and chronic stress, could change neuronal burst firing and thus ultimately affect information processing and cognition

Evaluating alternate models to estimate genetic parameters of calving traits in United Kingdom Holstein-Friesian dairy cattle

<p>Abstract</p> <p>Background</p> <p>The focus in dairy cattle breeding is gradually shifting from production to functional traits and genetic parameters of calving traits are estimated more frequently. However, across countries, various statistical models are used to estimate these parameters. This study evaluates different models for calving ease and stillbirth in United Kingdom Holstein-Friesian cattle.</p> <p>Methods</p> <p>Data from first and later parity records were used. Genetic parameters for calving ease, stillbirth and gestation length were estimated using the restricted maximum likelihood method, considering different models i.e. sire (−maternal grandsire), animal, univariate and bivariate models. Gestation length was fitted as a correlated indicator trait and, for all three traits, genetic correlations between first and later parities were estimated. Potential bias in estimates was avoided by acknowledging a possible environmental direct-maternal covariance. The total heritable variance was estimated for each trait to discuss its theoretical importance and practical value. Prediction error variances and accuracies were calculated to compare the models.</p> <p>Results and discussion</p> <p>On average, direct and maternal heritabilities for calving traits were low, except for direct gestation length. Calving ease in first parity had a significant and negative direct-maternal genetic correlation. Gestation length was maternally correlated to stillbirth in first parity and directly correlated to calving ease in later parities. Multi-trait models had a slightly greater predictive ability than univariate models, especially for the lowly heritable traits. The computation time needed for sire (−maternal grandsire) models was much smaller than for animal models with only small differences in accuracy. The sire (−maternal grandsire) model was robust when additional genetic components were estimated, while the equivalent animal model had difficulties reaching convergence.</p> <p>Conclusions</p> <p>For the evaluation of calving traits, multi-trait models show a slight advantage over univariate models. Extended sire models (−maternal grandsire) are more practical and robust than animal models. Estimated genetic parameters for calving traits of UK Holstein cattle are consistent with literature. Calculating an aggregate estimated breeding value including direct and maternal values should encourage breeders to consider both direct and maternal effects in selection decisions.</p

The Number of X Chromosomes Causes Sex Differences in Adiposity in Mice

Sexual dimorphism in body weight, fat distribution, and metabolic disease has been attributed largely to differential effects of male and female gonadal hormones. Here, we report that the number of X chromosomes within cells also contributes to these sex differences. We employed a unique mouse model, known as the “four core genotypes,” to distinguish between effects of gonadal sex (testes or ovaries) and sex chromosomes (XX or XY). With this model, we produced gonadal male and female mice carrying XX or XY sex chromosome complements. Mice were gonadectomized to remove the acute effects of gonadal hormones and to uncover effects of sex chromosome complement on obesity. Mice with XX sex chromosomes (relative to XY), regardless of their type of gonad, had up to 2-fold increased adiposity and greater food intake during daylight hours, when mice are normally inactive. Mice with two X chromosomes also had accelerated weight gain on a high fat diet and developed fatty liver and elevated lipid and insulin levels. Further genetic studies with mice carrying XO and XXY chromosome complements revealed that the differences between XX and XY mice are attributable to dosage of the X chromosome, rather than effects of the Y chromosome. A subset of genes that escape X chromosome inactivation exhibited higher expression levels in adipose tissue and liver of XX compared to XY mice, and may contribute to the sex differences in obesity. Overall, our study is the first to identify sex chromosome complement, a factor distinguishing all male and female cells, as a cause of sex differences in obesity and metabolism

Causal Measures of Structure and Plasticity in Simulated and Living Neural Networks

A major goal of neuroscience is to understand the relationship between neural structures and their function. Recording of neural activity with arrays of electrodes is a primary tool employed toward this goal. However, the relationships among the neural activity recorded by these arrays are often highly complex making it problematic to accurately quantify a network's structural information and then relate that structure to its function. Current statistical methods including cross correlation and coherence have achieved only modest success in characterizing the structural connectivity. Over the last decade an alternative technique known as Granger causality is emerging within neuroscience. This technique, borrowed from the field of economics, provides a strong mathematical foundation based on linear auto-regression to detect and quantify “causal” relationships among different time series. This paper presents a combination of three Granger based analytical methods that can quickly provide a relatively complete representation of the causal structure within a neural network. These are a simple pairwise Granger causality metric, a conditional metric, and a little known computationally inexpensive subtractive conditional method. Each causal metric is first described and evaluated in a series of biologically plausible neural simulations. We then demonstrate how Granger causality can detect and quantify changes in the strength of those relationships during plasticity using 60 channel spike train data from an in vitro cortical network measured on a microelectrode array. We show that these metrics can not only detect the presence of causal relationships, they also provide crucial information about the strength and direction of that relationship, particularly when that relationship maybe changing during plasticity. Although we focus on the analysis of multichannel spike train data the metrics we describe are applicable to any stationary time series in which causal relationships among multiple measures is desired. These techniques can be especially useful when the interactions among those measures are highly complex, difficult to untangle, and maybe changing over time

Ageing, adipose tissue, fatty acids and inflammation

A common feature of ageing is the alteration in tissue distribution and composition, with a shift in fat away from lower body and subcutaneous depots to visceral and ectopic sites. Redistribution of adipose tissue towards an ectopic site can have dramatic effects on metabolic function. In skeletal muscle, increased ectopic adiposity is linked to insulin resistance through lipid mediators such as ceramide or DAG, inhibiting the insulin receptor signalling pathway. Additionally, the risk of developing cardiovascular disease is increased with elevated visceral adipose distribution. In ageing, adipose tissue becomes dysfunctional, with the pathway of differentiation of preadipocytes to mature adipocytes becoming impaired; this results in dysfunctional adipocytes less able to store fat and subsequent fat redistribution to ectopic sites. Low grade systemic inflammation is commonly observed in ageing, and may drive the adipose tissue dysfunction, as proinflammatory cytokines are capable of inhibiting adipocyte differentiation. Beyond increased ectopic adiposity, the effect of impaired adipose tissue function is an elevation in systemic free fatty acids (FFA), a common feature of many metabolic disorders. Saturated fatty acids can be regarded as the most detrimental of FFA, being capable of inducing insulin resistance and inflammation through lipid mediators such as ceramide, which can increase risk of developing atherosclerosis. Elevated FFA, in particular saturated fatty acids, maybe a driving factor for both the increased insulin resistance, cardiovascular disease risk and inflammation in older adults