Altered functional and structural brain network organization in autism.

Structural and functional underconnectivity have been reported for multiple brain regions, functional systems, and white matter tracts in individuals with autism spectrum disorders (ASD). Although recent developments in complex network analysis have established that the brain is a modular network exhibiting small-world properties, network level organization has not been carefully examined in ASD. Here we used resting-state functional MRI (n = 42 ASD, n = 37 typically developing; TD) to show that children and adolescents with ASD display reduced short and long-range connectivity within functional systems (i.e., reduced functional integration) and stronger connectivity between functional systems (i.e., reduced functional segregation), particularly in default and higher-order visual regions. Using graph theoretical methods, we show that pairwise group differences in functional connectivity are reflected in network level reductions in modularity and clustering (local efficiency), but shorter characteristic path lengths (higher global efficiency). Structural networks, generated from diffusion tensor MRI derived fiber tracts (n = 51 ASD, n = 43 TD), displayed lower levels of white matter integrity yet higher numbers of fibers. TD and ASD individuals exhibited similar levels of correlation between raw measures of structural and functional connectivity (n = 35 ASD, n = 35 TD). However, a principal component analysis combining structural and functional network properties revealed that the balance of local and global efficiency between structural and functional networks was reduced in ASD, positively correlated with age, and inversely correlated with ASD symptom severity. Overall, our findings suggest that modeling the brain as a complex network will be highly informative in unraveling the biological basis of ASD and other neuropsychiatric disorders

Motif Discovery in Protein Sequences

Biology has become a data‐intensive research field. Coping with the flood of data from the new genome sequencing technologies is a major area of research. The exponential increase in the size of the datasets produced by “next‐generation sequencing” (NGS) poses unique computational challenges. In this context, motif discovery tools are widely used to identify important patterns in the sequences produced. Biological sequence motifs are defined as short, usually fixed length, sequence patterns that may represent important structural or functional features in nucleic acid and protein sequences such as transcription binding sites, splice junctions, active sites, or interaction interfaces. They can occur in an exact or approximate form within a family or a subfamily of sequences. Motif discovery is therefore an important field in bioinformatics, and numerous methods have been developed for the identification of motifs shared by a set of functionally related sequences. This chapter will review the existing motif discovery methods for protein sequences and their ability to discover biologically important features as well as their limitations for the discovery of new motifs. Finally, we will propose new horizons for motif discovery in order to address the short comings of the existent methods

Scaling of continuous twin screw wet granulation

Scaling rules were developed and tested for a continuous twin screw wet granulation process using three scales (11, 16, and 24 mm barrel diameter) of twin screw granulators (TSG). The distributive feed screw configuration used produced high porosity granules (50-60%) with broad bimodal size distributions, especially in the 16 and 24 mm TSGs. Three dimensionless numbers, Froude number (Fr), liquid-to-solid ratio (LSR), and powder feed number (PFN), were identified and their effect on granule size distribution (GSD), porosity and liquid distribution tested. Granule size increased with increasing LSR as expected. However, Fr and PFN had no significant effect on d10 or d50 and only a small effect on d90. In contrast, granulator scale had a strong effect on GSD, with d90 increasing almost linearly with barrel diameter. This is consistent with breakage of large granules being a dominant mechanism and directly controlled by the geometry of the screw

Prospects and challenges of concentrated solar photovoltaics and enhanced geothermal energy technologies

Reducing the total emissions of energy generation systems is a pragmatic approach for limiting the environmental pollution and associated climate change problems. Socio economic activities in the 21st century is highly determined by the energy generation mediums, particularly the renewable resources, across the world. Therefore, a thorough investigation into the technologies used in harnessing these energy generation mediums should contribute to their further advancement. Concentrated Solar Photovoltaics (CSP) and Enhanced Geothermal Energy (EGE) are considered as emerging renewable energy technologies with high potential to be used as suitable replacements for fossil products (petroleum, coal, natural gas etc.). Despite the accelerated developments in these technologies, they are still facing many challenges in terms of cost. This review paper presents a detailed background about these renewable energy technologies and their main types such as solar tower, parabolic trough, and so on. Also, the principle challenges impeding the advancement of these energy technologies into commercialisation are discussed. Possible solutions for the main challenges are presented and the future prospects for such energy generation mediums are reported

Relativistic Meson Spectroscopy and In-Medium Effects

We extend our earlier model of $q\bar q$ mesons using relativistic quasipotential (QP) wave equations to include open-flavor states and running quark-gluon coupling effects. Global fits to meson spectra are achieved with rms deviations from experiment of 43-50 MeV. We examine in-medium effects through their influence on the confining interaction and predict the confining strength at which the masses of certain mesons fall below the threshold of their dominant decay channel.Comment: 12 Pages, 2 Postscript figures (appended at the end with instructions, available also from [email protected]

A reference relative time-scale as an alternative to chronological age for cohorts with long follow-up

Background: Epidemiologists have debated the appropriate time-scale for cohort survival studies; chronological age or time-on-study being two such time-scales. Importantly, assessment of risk factors may depend on the choice of time-scale. Recently, chronological or attained age has gained support but a case can be made for a ‘reference relative time-scale’ as an alternative which circumvents difficulties that arise with this and other scales. The reference relative time of an individual participant is the integral of a reference population hazard function between time of entry and time of exit of the individual. The objective here is to describe the reference relative time-scale, illustrate its use, make comparison with attained age by simulation and explain its relationship to modern and traditional epidemiologic methods. Results: A comparison was made between two models; a stratified Cox model with age as the time-scale versus an un-stratified Cox model using the reference relative time-scale. The illustrative comparison used a UK cohort of cotton workers, with differing ages at entry to the study, with accrual over a time period and with long follow-up. Additionally, exponential and Weibull models were fitted since the reference relative time-scale analysis need not be restricted to the Cox model. A simulation study showed that analysis using the reference relative time-scale and analysis using chronological age had very similar power to detect a significant risk factor and both were equally unbiased. Further, the analysis using the reference relative time-scale supported fully-parametric survival modelling and allowed percentile predictions and mortality curves to be constructed. Conclusions: The reference relative time-scale was a viable alternative to chronological age, led to simplification of the modelling process and possessed the defined features of a good time-scale as defined in reliability theory. The reference relative time-scale has several interpretations and provides a unifying concept that links contemporary approaches in survival and reliability analysis to the traditional epidemiologic methods of Poisson regression and standardised mortality ratios. The community of practitioners has not previously made this connection

Dietary nitrate modulates cerebral blood flow parameters and cognitive performance in humans: A double-blind, placebo-controlled, crossover investigation.

This is the author accepted manuscript. The final version is available from the publisher via the DOI in this record.Nitrate derived from vegetables is consumed as part of a normal diet and is reduced endogenously via nitrite to nitric oxide. It has been shown to improve endothelial function, reduce blood pressure and the oxygen cost of sub-maximal exercise, and increase regional perfusion in the brain. The current study assessed the effects of dietary nitrate on cognitive performance and prefrontal cortex cerebral blood-flow (CBF) parameters in healthy adults. In this randomised, double-blind, placebo-controlled, parallel-groups study, 40 healthy adults received either placebo or 450 ml beetroot juice (~5.5 mmol nitrate). Following a 90 minute drink/absorption period, participants performed a selection of cognitive tasks that activate the frontal cortex for 54 min. Near-Infrared Spectroscopy (NIRS) was used to monitor CBF and hemodynamics, as indexed by concentration changes in oxygenated and deoxygenated-haemoglobin, in the frontal cortex throughout. The bioconversion of nitrate to nitrite was confirmed in plasma by ozone-based chemi-luminescence. Dietary nitrate modulated the hemodynamic response to task performance, with an initial increase in CBF at the start of the task period, followed by consistent reductions during the least demanding of the three tasks utilised. Cognitive performance was improved on the serial 3s subtraction task. These results show that single doses of dietary nitrate can modulate the CBF response to task performance and potentially improve cognitive performance, and suggest one possible mechanism by which vegetable consumption may have beneficial effects on brain function