Predicting cocaine consumption in Spain: A mathematical modelling approach

This is an author's accepted manuscript of an article published in “Drugs: Education, Prevention, and Policy "; Volume 18, Issue 2, 2011; copyright Taylor & Francis; available online at: http://dx.doi.org/10.3109/09687630903443299In this article, we analyse the evolution of cocaine consumption in Spain and we predict consumption trends over the next few years. Additionally, we simulate some scenarios which aim to reduce cocaine consumption in the future (sensitivity analysis). Assuming cocaine dependency is a socially transmitted epidemic disease, this leads us to propose an epidemiological-type mathematical model to study consumption evolution. Model sensitivity analysis allows us to design strategies and analyse their effects on cocaine consumption. The model predicts that 3.5% of the Spanish population will be habitual cocaine consumers by 2015. The simulations carried out suggest that cocaine consumption prevention strategies are the best policy to reduce the habitual consumer population. In this article, we show that epidemiological-type mathematical models can be a useful tool in the analysis of the repercussion of health policy proposals in the short-time future. © 2011 Informa UK Ltd.Sánchez, E.; Villanueva Micó, RJ.; Santonja, FJ.; Rubio, M. (2011). Predicting cocaine consumption in Spain: A mathematical modelling approach. Drugs: Education, Prevention, and Policy. 18(2):108-115. doi:10.3109/09687630903443299S108115182Blower, S. M., & Dowlatabadi, H. (1994). Sensitivity and Uncertainty Analysis of Complex Models of Disease Transmission: An HIV Model, as an Example. International Statistical Review / Revue Internationale de Statistique, 62(2), 229. doi:10.2307/1403510Dutra, L., Stathopoulou, G., Basden, S. L., Leyro, T. M., Powers, M. B., & Otto, M. W. (2008). A Meta-Analytic Review of Psychosocial Interventions for Substance Use Disorders. American Journal of Psychiatry, 165(2), 179-187. doi:10.1176/appi.ajp.2007.06111851Gorman, D. M., Mezic, J., Mezic, I., & Gruenewald, P. J. (2006). Agent-Based Modeling of Drinking Behavior: A Preliminary Model and Potential Applications to Theory and Practice. American Journal of Public Health, 96(11), 2055-2060. doi:10.2105/ajph.2005.063289Jódar, L., Santonja, F. J., & González-Parra, G. (2008). Modeling dynamics of infant obesity in the region of Valencia, Spain. Computers & Mathematics with Applications, 56(3), 679-689. doi:10.1016/j.camwa.2008.01.011JOHNSON, B., ROACHE, J., AITDAOUD, N., JAVORS, M., HARRISON, J., ELKASHEF, A., … BLOCH, D. (2006). A preliminary randomized, double-blind, placebo-controlled study of the safety and efficacy of ondansetron in the treatment of cocaine dependence. Drug and Alcohol Dependence, 84(3), 256-263. doi:10.1016/j.drugalcdep.2006.02.011Levin, F. R., Evans, S. M., Brooks, D. J., & Garawi, F. (2007). Treatment of cocaine dependent treatment seekers with adult ADHD: Double-blind comparison of methylphenidate and placebo. Drug and Alcohol Dependence, 87(1), 20-29. doi:10.1016/j.drugalcdep.2006.07.004Marino, S., Hogue, I. B., Ray, C. J., & Kirschner, D. E. (2008). A methodology for performing global uncertainty and sensitivity analysis in systems biology. Journal of Theoretical Biology, 254(1), 178-196. doi:10.1016/j.jtbi.2008.04.011Martcheva, M., & Castillo-Chavez, C. (2003). Diseases with chronic stage in a population with varying size. Mathematical Biosciences, 182(1), 1-25. doi:10.1016/s0025-5564(02)00184-0Nelder, J. A., & Mead, R. (1965). A Simplex Method for Function Minimization. The Computer Journal, 7(4), 308-313. doi:10.1093/comjnl/7.4.308Olsson, A., Sandberg, G., & Dahlblom, O. (2003). On Latin hypercube sampling for structural reliability analysis. Structural Safety, 25(1), 47-68. doi:10.1016/s0167-4730(02)00039-5Santonja, F. J., Tarazona, A. C., & Villanueva, R. J. (2008). A mathematical model of the pressure of an extreme ideology on a society. Computers & Mathematics with Applications, 56(3), 836-846. doi:10.1016/j.camwa.2008.01.001Schmitz, J. M., Stotts, A. L., Rhoades, H. M., & Grabowski, J. (2001). Naltrexone and relapse prevention treatment for cocaine-dependent patients. Addictive Behaviors, 26(2), 167-180. doi:10.1016/s0306-4603(00)00098-8Sharomi, O., & Gumel, A. B. (2008). Curtailing smoking dynamics: A mathematical modeling approach. Applied Mathematics and Computation, 195(2), 475-499. doi:10.1016/j.amc.2007.05.012Stotts, A. L., Mooney, M. E., Sayre, S. L., Novy, M., Schmitz, J. M., & Grabowski, J. (2007). Illusory predictors: Generalizability of findings in cocaine treatment retention research. Addictive Behaviors, 32(12), 2819-2836. doi:10.1016/j.addbeh.2007.04.020White, E., & Comiskey, C. (2007). Heroin epidemics, treatment and ODE modelling. Mathematical Biosciences, 208(1), 312-324. doi:10.1016/j.mbs.2006.10.00

A Meta-Brokering Framework for Science Gateways

Recently scientific communities produce a growing number of computation-intensive applications, which calls for the interoperation of distributed infrastructures including Clouds, Grids and private clusters. The European SHIWA and ER-flow projects have enabled the combination of heterogeneous scientific workflows, and their execution in a large-scale system consisting of multiple Distributed Computing Infrastructures. One of the resource management challenges of these projects is called parameter study job scheduling. A parameter study job of a workflow generally has a large number of input files to be consumed by independent job instances. In this paper we propose a meta-brokering framework for science gateways to support the execution of such workflows. In order to cope with the high uncertainty and unpredictable load of the utilized distributed infrastructures, we introduce the so called resource priority services. These tools are capable of determining and dynamically updating priorities of the available infrastructures to be selected for job instances. Our evaluations show that this approach implies an efficient distribution of job instances among the available computing resources resulting in shorter makespan for parameter study workflows

The D-score: a metric for interpreting the early development of infants and toddlers across global settings

Introduction: Early childhood development can be described by an underlying latent construct. Global comparisons of children’s development are hindered by the lack of a validated metric that is comparable across cultures and contexts, especially for children under age 3 years. We constructed and validated a new metric, the Developmental Score (D-score), using existing data from 16 longitudinal studies. / Methods: Studies had item-level developmental assessment data for children 0–48 months and longitudinal outcomes at ages >4–18 years, including measures of IQ and receptive vocabulary. Existing data from 11 low-income, middle-income and high-income countries were merged for >36 000 children. Item mapping produced 95 ‘equate groups’ of same-skill items across 12 different assessment instruments. A statistical model was built using the Rasch model with item difficulties constrained to be equal in a subset of equate groups, linking instruments to a common scale, the D-score, a continuous metric with interval-scale properties. D-score-for-age z-scores (DAZ) were evaluated for discriminant, concurrent and predictive validity to outcomes in middle childhood to adolescence. / Results: Concurrent validity of DAZ with original instruments was strong (average r=0.71), with few exceptions. In approximately 70% of data rounds collected across studies, DAZ discriminated between children above/below cut-points for low birth weight (<2500 g) and stunting (−2 SD below median height-for-age). DAZ increased significantly with maternal education in 55% of data rounds. Predictive correlations of DAZ with outcomes obtained 2–16 years later were generally between 0.20 and 0.40. Correlations equalled or exceeded those obtained with original instruments despite using an average of 55% fewer items to estimate the D-score. / Conclusion: The D-score metric enables quantitative comparisons of early childhood development across ages and sets the stage for creating simple, low-cost, global-use instruments to facilitate valid cross-national comparisons of early childhood development

Activation of Type 1 Cannabinoid Receptor (CB1R) promotes neurogenesis in murine subventricular zone cell cultures

The endocannabinoid system has been implicated in the modulation of adult neurogenesis. Here, we describe the effect of type 1 cannabinoid receptor (CB1R) activation on self-renewal, proliferation and neuronal differentiation in mouse neonatal subventricular zone (SVZ) stem/progenitor cell cultures. Expression of CB1R was detected in SVZ-derived immature cells (Nestin-positive), neurons and astrocytes. Stimulation of the CB1R by (R)-(+)-Methanandamide (R-m-AEA) increased self-renewal of SVZ cells, as assessed by counting the number of secondary neurospheres and the number of Sox2+/+ cell pairs, an effect blocked by Notch pathway inhibition. Moreover, R-m-AEA treatment for 48 h, increased proliferation as assessed by BrdU incorporation assay, an effect mediated by activation of MAPK-ERK and AKT pathways. Surprisingly, stimulation of CB1R by R-m-AEA also promoted neuronal differentiation (without affecting glial differentiation), at 7 days, as shown by counting the number of NeuN-positive neurons in the cultures. Moreover, by monitoring intracellular calcium concentrations ([Ca2+](i)) in single cells following KCl and histamine stimuli, a method that allows the functional evaluation of neuronal differentiation, we observed an increase in neuronal-like cells. This proneurogenic effect was blocked when SVZ cells were co-incubated with R-m-AEA and the CB1R antagonist AM 251, for 7 days, thus indicating that this effect involves CB1R activation. In accordance with an effect on neuronal differentiation and maturation, R-m-AEA also increased neurite growth, as evaluated by quantifying and measuring the number of MAP2-positive processes. Taken together, these results demonstrate that CB1R activation induces proliferation, self-renewal and neuronal differentiation from mouse neonatal SVZ cell cultures.Fundacao para a Ciencia e a Tecnologia - Portugal [POCTI/SAU-NEU/68465/2006, PTDC/SAU-NEU/104415/2008, PTDC/SAU-NEU/101783/2008, POCTI/SAU-NEU/110838/2009]; Fundacao Calouste Gulbenkian [96542]; Fundacao para a Ciencia e Tecnologiainfo:eu-repo/semantics/publishedVersio

Diets containing sea cucumber (Isostichopus badionotus) meals are hypocholesterolemic in young rats

Peer reviewedPublisher PD

Aspergillus fumigatus and aspergillosis: From basics to clinics

The airborne fungus Aspergillus fumigatus poses a serious health threat to humans by causing numerous invasive infections and a notable mortality in humans, especially in immunocompromised patients. Mould-active azoles are the frontline therapeutics employed to treat aspergillosis. The global emergence of azole-resistant A. fumigatus isolates in clinic and environment, however, notoriously limits the therapeutic options of mould-active antifungals and potentially can be attributed to a mortality rate reaching up to 100 %. Although specific mutations in CYP51A are the main cause of azole resistance, there is a new wave of azole-resistant isolates with wild-type CYP51A genotype challenging the efficacy of the current diagnostic tools. Therefore, applications of whole-genome sequencing are increasingly gaining popularity to overcome such challenges. Prominent echinocandin tolerance, as well as liver and kidney toxicity posed by amphotericin B, necessitate a continuous quest for novel antifungal drugs to combat emerging azole-resistant A. fumigatus isolates. Animal models and the tools used for genetic engineering require further refinement to facilitate a better understanding about the resistance mechanisms, virulence, and immune reactions orchestrated against A. fumigatus. This review paper comprehensively discusses the current clinical challenges caused by A. fumigatus and provides insights on how to address them.AA, RGR, and DSP were supported by NIH AI 109025. MH was supported by NIH UL1TR001442. AC was supported by the Fundação para a Ciência e a Tecnologia (FCT) (CEECIND/03628/2017 and PTDC/MED GEN/28778/2017). Additional support was provided by FCT (UIDB/50026/2020 and UIDP/50026/2020), the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (ERDF) (NORTE-01-0145-FEDER-000013 and NORTE-01-0145-FEDER-000023), the European Union's Horizon 2020 Research and Innovation programme under grant agreement no. 847507, and the “la Caixa” Foundation (ID 100010434) and FCT under the agreement LCF/PR/HP17/52190003. DJA was supported by CF Trust Strategic Research Centre TrIFIC (SRC015), Wellcome Trust Collaborative Award 219551/Z/19/Z and the NIHR Centre for Antimicrobial Optimisation.S

Bio-nanotechnology application in wastewater treatment

The nanoparticles have received high interest in the field of medicine and water purification, however, the nanomaterials produced by chemical and physical methods are considered hazardous, expensive, and leave behind harmful substances to the environment. This chapter aimed to focus on green-synthesized nanoparticles and their medical applications. Moreover, the chapter highlighted the applicability of the metallic nanoparticles (MNPs) in the inactivation of microbial cells due to their high surface and small particle size. Modifying nanomaterials produced by green-methods is safe, inexpensive, and easy. Therefore, the control and modification of nanoparticles and their properties were also discussed