Recommendations for enterovirus diagnostics and characterisation within and beyond Europe.

Enteroviruses (EV) can cause severe neurological and respiratory infections, and occasionally lead to devastating outbreaks as previously demonstrated with EV-A71 and EV-D68 in Europe. However, these infections are still often underdiagnosed and EV typing data is not currently collected at European level. In order to improve EV diagnostics, collate data on severe EV infections and monitor the circulation of EV types, we have established European non-polio enterovirus network (ENPEN). First task of this cross-border network has been to ensure prompt and adequate diagnosis of these infections in Europe, and hence we present recommendations for non-polio EV detection and typing based on the consensus view of this multidisciplinary team including experts from over 20 European countries. We recommend that respiratory and stool samples in addition to cerebrospinal fluid (CSF) and blood samples are submitted for EV testing from patients with suspected neurological infections. This is vital since viruses like EV-D68 are rarely detectable in CSF or stool samples. Furthermore, reverse transcriptase PCR (RT-PCR) targeting the 5'noncoding regions (5'NCR) should be used for diagnosis of EVs due to their sensitivity, specificity and short turnaround time. Sequencing of the VP1 capsid protein gene is recommended for EV typing; EV typing cannot be based on the 5'NCR sequences due to frequent recombination events and should not rely on virus isolation. Effective and standardized laboratory diagnostics and characterisation of circulating virus strains are the first step towards effective and continuous surveillance activities, which in turn will be used to provide better estimation on EV disease burden

Brain derived neurotrophic factor expression and DNA methylation in response to subchronic valproic acid and/or aldosterone treatment

Aim To test the hypothesis that valproic acid treatment positively affects brain-derived neurotrophic factor (BDNF) expression and DNA methylation in the hippocampus and brain cortex of rats simultaneously treated with aldosterone. Methods Male Sprague-Dawley rats (N = 40) were treated for two weeks with valproic acid (100 mg/1 kg body weight/d) in drinking water and aldosterone (2 μg/100 g body weight/d) or placebo via subcutaneous osmotic minipumps. Results Treatment with valproic acid did not modify BDNF gene expression in the hippocampus but reduced BDNF mRNA levels in the brain cortex. Valproic acid treatment marginally enhanced global DNA methylation in the frontal cortex. BDNF expression negatively correlated with DNA methylation in the hippocampus of valproic acidtreated rats. An unexpected finding was that aldosterone treatment significantly decreased global DNA methylation in the hippocampus. Conclusion The effect of valproic acid on BDNF expression in the brain may depend on the extent of pathological changes present at the time of treatment onset. The observed negative correlation between BDNF expression and DNA methylation in the hippocampus of valproic acid- treated rats encourages further studies

Characterization of Emulsified Non-encapsulated Thermochromic Liquid Crystal Micro-particles

In this paper, the process for obtaining non-encapsulated Thermochromic Liquid Crystal (TLC) micro-particles from commercial bulk material (UN R25C10W) is described. The bulk material is analyzed in terms of morphology and rheological properties (i.e. viscosity, maximum shear rate). An experimental evaluation of surface tension values and contact angle measurements is made to complement the rheological data. On the basis of the obtained thermophysical values, an emulsification procedure is proposed and non-encapsulated TLC droplets with a dimension lower than 10 \u3bcm were acquired. Further, attention has been focused on the calibration process of TLC bulk material before and after the emulsification. A relation between the local temperature value, RGB and colour intensities (HSI) is obtained by analyzing the digital images with MATLAB Image Processing Toolbox. The obtained results indicate that the commercial bulk material UN R25C10W TLC can be used to obtain stable oil-in-water emulsion by proposed emulsification procedure in this paper

Predicting News Values from Headline Text and Emotions

We present a preliminary study on predicting news values from headline text and emotions. We perform a multivariate analysis on a dataset manually annotated with news values and emotions, discovering interesting correlations among them. We then train two competitive machine learning models – an SVM and a CNN – to predict news values from headline text and emotions as features. We find that, while both models yield a satisfactory performance, some news values are more difficult to detect than others, while some profit more from including emotion information