Pressure-dependent EPANET extension

In water distribution systems (WDSs), the available flow at a demand node is dependent on the pressure at that node. When a network is lacking in pressure, not all consumer demands will be met in full. In this context, the assumption that all demands are fully satisfied regardless of the pressure in the system becomes unreasonable and represents the main limitation of the conventional demand driven analysis (DDA) approach to WDS modelling. A realistic depiction of the network performance can only be attained by considering demands to be pressure dependent. This paper presents an extension of the renowned DDA based hydraulic simulator EPANET 2 to incorporate pressure-dependent demands. This extension is termed “EPANET-PDX” (pressure-dependent extension) herein. The utilization of a continuous nodal pressure-flow function coupled with a line search and backtracking procedure greatly enhance the algorithm’s convergence rate and robustness. Simulations of real life networks consisting of multiple sources, pipes, valves and pumps were successfully executed and results are presented herein. Excellent modelling performance was achieved for analysing both normal and pressure deficient conditions of the WDSs. Detailed computational efficiency results of EPANET-PDX with reference to EPANET 2 are included as well

Atomoxetine for the treatment of Attention-Deficit/Hyperactivity Disorder (ADHD) in children with ADHD and dyslexia

<p>Abstract</p> <p>Background</p> <p>The objective of this study was to assess the effects of atomoxetine on treating attention-deficit/hyperactivity disorder (ADHD), on reading performance, and on neurocognitive function in youth with ADHD and dyslexia (ADHD+D).</p> <p>Methods</p> <p>Patients with ADHD (n = 20) or ADHD+D (n = 36), aged 10-16 years, received open-label atomoxetine for 16 weeks. Data from the ADHD Rating Scale-IV (ADHDRS-IV), Kaufman Test of Educational Achievement (K-TEA), Working Memory Test Battery for Children (WMTB-C), and Life Participation Scale for ADHD-Child Version (LPS-C) were assessed.</p> <p>Results</p> <p>Atomoxetine demonstrated significant improvement for both groups on the ADHDRS-IV, LPS-C, and K-TEA reading comprehension standard and composite scores. K-TEA spelling subtest improvement was significant for the ADHD group, whereas the ADHD+D group showed significant reading decoding improvements. Substantial K-TEA reading and spelling subtest age equivalence gains (in months) were achieved for both groups. The WMTB-C central executive score change was significantly greater for the ADHD group. Conversely, the ADHD+D group showed significant phonological loop score enhancement by visit over the ADHD group. Atomoxetine was well tolerated, and commonly reported adverse events were similar to those previously reported.</p> <p>Conclusions</p> <p>Atomoxetine reduced ADHD symptoms and improved reading scores in both groups. Conversely, different patterns and magnitude of improvement in working memory component scores existed between ADHD and ADHD+D patients. Though limited by small sample size, group differences in relation to the comparable changes in improvement in ADHD symptoms could suggest that brain systems related to the therapeutic benefit of atomoxetine in reducing ADHD symptoms may be different in individuals with ADHD+D and ADHD without dyslexia.</p> <p>Trial Registration</p> <p>Clinical Trial Registry: ClinicalTrials.gov: NCT00191048</p

A framework for highly multiplexed dextramer mapping and prediction of T cell receptor sequences to antigen specificity.

T cell receptor (TCR) antigen-specific recognition is essential for the adaptive immune system. However, building a TCR-antigen interaction map has been challenging due to the staggering diversity of TCRs and antigens. Accordingly, highly multiplexed dextramer-TCR binding assays have been recently developed, but the utility of the ensuing large datasets is limited by the lack of robust computational methods for normalization and interpretation. Here, we present a computational framework comprising a novel method, ICON (Integrative COntext-specific Normalization), for identifying reliable TCR-pMHC (peptide-major histocompatibility complex) interactions and a neural network-based classifier TCRAI that outperforms other state-of-the-art methods for TCR-antigen specificity prediction. We further demonstrated that by combining ICON and TCRAI, we are able to discover novel subgroups of TCRs that bind to a given pMHC via different mechanisms. Our framework facilitates the identification and understanding of TCR-antigen-specific interactions for basic immunological research and clinical immune monitoring

A Key Role for Neurotensin in Chronic-Stress-Induced Anxiety-Like Behavior in Rats

Accepted ManuscriptChronic stress is a major cause of anxiety disorders that can be reliably modeled preclinically, providing insight into alternative therapeutic targets for this mental health illness. Neuropeptides have been targeted in the past to no avail possibly due to our lack of understanding of their role in pathological models. In this study we use a rat model of chronic stress-induced anxiety-like behaviors and hypothesized that neuropeptidergic modulation of synaptic transmission would be altered in the bed nucleus of the stria terminalis (BNST), a brain region suspected to contribute to anxiety disorders. We use brain slice neurophysiology and behavioral pharmacology to compare the role of locally released endogenous neuropeptides on synaptic transmission in the oval (ov) BNST of non-stressed (NS) or chronic unpredictably stressed (CUS) rats. We found that in NS rats, post-synaptic depolarization induced the release of vesicular neurotensin (NT) and corticotropin-releasing factor (CRF) that co-acted to increase ovBNST inhibitory synaptic transmission in 59% of recorded neurons. CUS bolstered this potentiation (100% of recorded neurons) through an enhanced contribution of NT over CRF. In contrast, locally released opioid neuropeptides decreased ovBNST excitatory synaptic transmission in all recorded neurons, regardless of stress. Consistent with CUS-induced enhanced modulatory effects of NT, blockade of ovBNST NT receptors completely abolished stress-induced anxiety-like behaviors in the elevated plus maze paradigm. The role of NT has been largely unexplored in stress and our findings highlight its potential contribution to an important behavioral consequence of chronic stress, that is, exaggerated avoidance of open space in rats.CPN was funded by CIHR Vanier Graduate Scholarship (338319); APVS was funded by Fundação para a Ciência e Tecnologia (SFRH/BPD/52078/2013); ERH was funded by CIHR Postdoctoral Fellowship (MFE-123712); SA was funded by a Queen Elizabeth II Graduate Scholarship in Science and Technology; ÉCD was funded by the Canadian Institute of Health Research (MOP-25953)info:eu-repo/semantics/publishedVersio

Genetic contributions to stability and change in intelligence from childhood to old age

Understanding the determinants of healthy mental ageing is a priority for society today1,2. So far, we know that intelligence differences show high stability from childhood to old age3,4 and there are estimates of the genetic contribution to intelligence at different ages5,6. However, attempts to discover whether genetic causes contribute to differences in cognitive ageing have been relatively uninformative7–10. Here we provide an estimate of the genetic and environmental contributions to stability and change in intelligence across most of the human lifetime. We used genome-wide single nucleotide polymorphism (SNP) data from 1,940 unrelated individuals whose intelligence was measured in childhood (age 11 years) and again in old age (age 65, 70 or 79 years)11,12. We use a statistical method that allows genetic (co)variance to be estimated from SNP data on unrelated individuals13–17. We estimate that causal genetic variants in linkage disequilibrium with common SNPs account for 0.24 of the variation in cognitive ability change from childhood to old age. Using bivariate analysis, we estimate a genetic correlation between intelligence at age 11 years and in old age of 0.62. These estimates, derived from rarely available data on lifetime cognitive measures, warrant the search for genetic causes of cognitive stability and change

Function and failure of the fetal membrane : modelling the mechanics of the chorion and amnion

The fetal membrane surrounds the fetus during pregnancy and is a thin tissue composed of two layers, the chorion and the amnion. While rupture of this membrane normally occurs at term, preterm rupture can result in increased risk of fetal mortality and morbidity, as well as danger of infection in the mother. Although structural changes have been observed in the membrane in such cases, the mechanical behaviour of the human fetal membrane in vivo remains poorly understood and is challenging to investigate experimentally. Therefore, the objective of this study was to develop simplified finite element models to investigate the mechanical behaviour and rupture of the fetal membrane, particularly its constituent layers, under various physiological conditions. It was found that modelling the chorion and amnion as a single layer predicts remarkably different behaviour compared with a more anatomically-accurate bilayer, significantly underestimating stress in the amnion and under-predicting the risk of membrane rupture. Additionally, reductions in chorion-amnion interface lubrication and chorion thickness (reported in cases of preterm rupture) both resulted in increased membrane stress. Interestingly, the inclusion of a weak zone in the fetal membrane that has been observed to develop overlying the cervix would likely cause it to fail at term, during labour. Finally, these findings support the theory that the amnion is the dominant structural component of the fetal membrane and is required to maintain its integrity. The results provide a novel insight into the mechanical effect of structural changes in the chorion and amnion, in cases of both normal and preterm rupture

Preliminary Findings of a Randomized Trial of Non-Pharmaceutical Interventions to Prevent Influenza Transmission in Households

Background: There are sparse data on whether non-pharmaceutical interventions can reduce the spread of influenza. We implemented a study of the feasibility and efficacy of face masks and hand hygiene to reduce influenza transmission among Hong Kong household members. Methodology/Principal Findings: We conducted a cluster randomized controlled trial of households (composed of at least 3 members) where an index subject presented with influenza-like-illness of <48 hours duration. After influenza was confirmed in an index case by the QuickVue Influenza A+B rapid test, the household of the index subject was randomised to 1) control or 2) surgical face masks or 3) hand hygiene. Households were visited within 36 hours, and 3, 6 and 9 days later. Nose and throat swabs were collected from index subjects and all household contact at each home visit and tested by viral culture. The primary outcome measure was laboratory culture confirmed influenza in a household contact; the secondary outcome was clinically diagnosed influenza (by self-reported symptoms). We randomized 198 households and completed follow up home visits in 128; the index cases in 122 of those households had laboratory-confirmed influenza. There were 21 household contacts with laboratory confirmed influenza corresponding to a secondary attack ratio of 6%. Clinical secondary attack ratios varied from 5% to 18% depending on case definitions. The laboratory-based or clinical secondary attack ratios old not significantly differ across the intervention arms. Adherence to interventions was variable. Conclusions/Significance: The secondary attack ratios were lower than anticipated, and lower than reported in other countries, perhaps due to differing patterns of susceptibility, lack of significant antigenic drift in circulating influenza virus strains recently, and/or issues related to the symptomatic recruitment design. Lessons learn from this pilot have informed changes for the main study in 2008.published_or_final_versio

Neighborhood socioeconomic status, Medicaid coverage and medical management of myocardial infarction: Atherosclerosis risk in communities (ARIC) community surveillance

<p>Abstract</p> <p>Background</p> <p>Pharmacologic treatments are efficacious in reducing post-myocardial infarction (MI) morbidity and mortality. The potential influence of socioeconomic factors on the receipt of pharmacologic therapy has not been systematically examined, even though healthcare utilization likely influences morbidity and mortality post-MI. This study aims to investigate the association between socioeconomic factors and receipt of evidence-based treatments post-MI in a community surveillance setting.</p> <p>Methods</p> <p>We evaluated the association of census tract-level neighborhood household income (nINC) and Medicaid coverage with pharmacologic treatments (aspirin, beta [β]-blockers and angiotensin converting enzyme [ACE] inhibitors; optimal therapy, defined as receipt of two or more treatments) received during hospitalization or at discharge among 9,608 MI events in the ARIC community surveillance study (1993-2002). Prevalence ratios (PR, 95% CI), adjusted for the clustering of hospitalized MI events within census tracts and within patients, were estimated using Poisson regression.</p> <p>Results</p> <p>Seventy-eight percent of patients received optimal therapy. Low nINC was associated with a lower likelihood of receiving β-blockers (0.93, 0.87-0.98) and a higher likelihood of receiving ACE inhibitors (1.13, 1.04-1.22), compared to high nINC. Patients with Medicaid coverage were less likely to receive aspirin (0.92, 0.87-0.98), compared to patients without Medicaid coverage. These findings were independent of other key covariates.</p> <p>Conclusions</p> <p>nINC and Medicaid coverage may be two of several socioeconomic factors influencing the complexities of medical care practice patterns.</p

Shared genetic aetiology between cognitive functions and physical and mental health in UK Biobank (<i>N</i>=112 151) and 24 GWAS consortia

Causes of the well-documented association between low levels of cognitive functioning and many adverse neuropsychiatric outcomes, poorer physical health and earlier death remain unknown. We used linkage disequilibrium regression and polygenic profile scoring to test for shared genetic aetiology between cognitive functions and neuropsychiatric disorders and physical health. Using information provided by many published genome-wide association study consortia, we created polygenic profile scores for 24 vascular–metabolic, neuropsychiatric, physiological–anthropometric and cognitive traits in the participants of UK Biobank, a very large population-based sample (N=112 151). Pleiotropy between cognitive and health traits was quantified by deriving genetic correlations using summary genome-wide association study statistics and to the method of linkage disequilibrium score regression. Substantial and significant genetic correlations were observed between cognitive test scores in the UK Biobank sample and many of the mental and physical health-related traits and disorders assessed here. In addition, highly significant associations were observed between the cognitive test scores in the UK Biobank sample and many polygenic profile scores, including coronary artery disease, stroke, Alzheimer’s disease, schizophrenia, autism, major depressive disorder, body mass index, intracranial volume, infant head circumference and childhood cognitive ability. Where disease diagnosis was available for UK Biobank participants, we were able to show that these results were not confounded by those who had the relevant disease. These findings indicate that a substantial level of pleiotropy exists between cognitive abilities and many human mental and physical health disorders and traits and that it can be used to predict phenotypic variance across samples

Mimicking human neuronal pathways in silico: an emergent model on the effective connectivity

International audienceWe present a novel computational model that detects temporal configurations of a given human neuronal pathway and constructs its artificial replication. This poses a great challenge since direct recordings from individual neurons are impossible in the human central nervous system and therefore the underlying neuronal pathway has to be considered as a black box. For tackling this challenge, we used a branch of complex systems modeling called artificial self-organization in which large sets of software entities interacting locally give rise to bottom-up collective behaviors. The result is an emergent model where each software entity represents an integrate-and-fire neuron. We then applied the model to the reflex responses of single motor units obtained from conscious human subjects. Experimental results show that the model recovers functionality of real human neuronal pathways by comparing it to appropriate surrogate data. What makes the model promising is the fact that, to the best of our knowledge, it is the first realistic model to self-wire an artificial neuronal network by efficiently combining neuroscience with artificial self-organization. Although there is no evidence yet of the model's connectivity mapping onto the human connectivity, we anticipate this model will help neuroscientists to learn much more about human neuronal networks, and could also be used for predicting hypotheses to lead future experiments