Uncertainties regarding dengue modeling in Rio de Janeiro, Brazil

Dengue fever is currently the most important arthropod-borne viral disease in Brazil. Mathematical modeling of disease dynamics is a very useful tool for the evaluation of control measures. To be used in decision-making, however, a mathematical model must be carefully parameterized and validated with epidemiological and entomological data. In this work, we developed a simple dengue model to answer three questions: (i) which parameters are worth pursuing in the field in order to develop a dengue transmission model for Brazilian cities; (ii) how vector density spatial heterogeneity influences control efforts; (iii) with a degree of uncertainty, what is the invasion potential of dengue virus type 4 (DEN-4) in Rio de Janeiro city. Our model consists of an expression for the basic reproductive number (R0) that incorporates vector density spatial heterogeneity. To deal with the uncertainty regarding parameter values, we parameterized the model using a priori probability density functions covering a range of plausible values for each parameter. Using the Latin Hypercube Sampling procedure, values for the parameters were generated. We conclude that, even in the presence of vector spatial heterogeneity, the two most important entomological parameters to be estimated in the field are the mortality rate and the extrinsic incubation period. The spatial heterogeneity of the vector population increases the risk of epidemics and makes the control strategies more complex. At last, we conclude that Rio de Janeiro is at risk of a DEN-4 invasion. Finally, we stress the point that epidemiologists, mathematicians, and entomologists need to interact more to find better approaches to the measuring and interpretation of the transmission dynamics of arthropod-borne diseases.

Survey of salt levels in soup in catering establishments on the island of Ireland

The aim of this survey was to provide a snap shot of the salt content of soup from a range of catering outlets on the island.

Pulmonary tuberculosis: evaluation of interferon-gamma levels as an immunological healing marker based on the response to the Bacillus Calmette-Guerin

Tuberculosis (TB) is a disease caused by Mycobacterium tuberculosis whose interaction with the host may lead to a cell-mediated protective immune response. The presence of interferon-g (IFN-gamma) is related to this response. With the purpose of understanding the immunological mechanisms involved in this protection, the lymphoproliferative response, IFN-g and other cytokines like interleukin (IL-5, IL-10), and tumor necrosis factor alpha (TNF-a) were evaluated before and after the use of anti-TB drugs on 30 patients with active TB disease, 24 healthy household contacts of active TB patients, with positive purified protein derivative (PPD) skin tests (induration > 10 mm), and 34 asymptomatic individuals with negative PPD skin test results (induration < 5 mm). The positive lymphoproliferative response among peripheral blood mononuclear cells of patients showed high levels of IFN-g, TNF-a, and IL-10. No significant levels of IL-5 were detected. After treatment with rifampicina, isoniazida, and pirazinamida, only the levels of IFN-g increased significantly (p < 0.01). These results highlight the need for further evaluation of IFN-g production as a healing prognostic of patients treated.

COMMIT: Convex Optimization Modeling for Microstructure Informed Tractography.

Tractography is a class of algorithms aiming at in vivo mapping the major neuronal pathways in the white matter from diffusion magnetic resonance imaging (MRI) data. These techniques offer a powerful tool to noninvasively investigate at the macroscopic scale the architecture of the neuronal connections of the brain. However, unfortunately, the reconstructions recovered with existing tractography algorithms are not really quantitative even though diffusion MRI is a quantitative modality by nature. As a matter of fact, several techniques have been proposed in recent years to estimate, at the voxel level, intrinsic microstructural features of the tissue, such as axonal density and diameter, by using multicompartment models. In this paper, we present a novel framework to reestablish the link between tractography and tissue microstructure. Starting from an input set of candidate fiber-tracts, which are estimated from the data using standard fiber-tracking techniques, we model the diffusion MRI signal in each voxel of the image as a linear combination of the restricted and hindered contributions generated in every location of the brain by these candidate tracts. Then, we seek for the global weight of each of them, i.e., the effective contribution or volume, such that they globally fit the measured signal at best. We demonstrate that these weights can be easily recovered by solving a global convex optimization problem and using efficient algorithms. The effectiveness of our approach has been evaluated both on a realistic phantom with known ground-truth and in vivo brain data. Results clearly demonstrate the benefits of the proposed formulation, opening new perspectives for a more quantitative and biologically plausible assessment of the structural connectivity of the brain.

Association of urinary calcium excretion with serum calcium and vitamin D levels.

BACKGROUND AND OBJECTIVES: Population-based data on urinary calcium excretion are scarce. The association of serum calcium and circulating levels of vitamin D [25(OH)D2 or D3] with urinary calcium excretion in men and women from a population-based study was explored. DESIGN, SETTINGS, PARTICIPANTS, & MEASUREMENTS: Multivariable linear regression was used to explore factors associated with square root-transformed 24-hour urinary calcium excretion (milligrams per 24 hours) taken as the dependent variable with a focus on month-specific vitamin D tertiles and serum calcium in the Swiss Survey on Salt Study. RESULTS: In total, 624 men and 669 women were studied with mean ages of 49.2 and 47.0 years, respectively (age range=15-95 years). Mean urinary calcium excretion was higher in men than in women (183.05 versus 144.60 mg/24 h; P<0.001). In adjusted models, the association (95% confidence interval) of square root urinary calcium excretion with protein-corrected serum calcium was 1.78 (95% confidence interval, 1.21 to 2.34) mg/24 h per milligram per deciliter in women and 0.59 (95% confidence interval, -0.11 to 1.29) mg/24 h per milligram per deciliter in men. Men in the third 25(OH)D3 tertile had higher square root urinary calcium excretion than men in the first tertile (0.99; 95% confidence interval, 0.36 to 1.63 mg/24 h per nanogram per milliliter), and the corresponding association was 0.32 (95% confidence interval, -0.22 to 0.85) mg/24 h per nanogram per milliliter in women. These sex differences were more marked under conditions of high urinary sodium or urea excretions. CONCLUSIONS: There was a positive association of serum calcium with urinary calcium excretion in women but not men. Vitamin 25(OH)D3 was associated with urinary calcium excretion in men but not women. These results suggest important sex differences in the hormonal and dietary control of urinary calcium excretion.

An introductory review on gravitational-deformation induced structures, fabrics and modeling

Recent studies have pointed out a similarity between tectonics and slope tectonic-induced structures. Numerous studies have demonstrated that structures and fabrics previously interpreted as of purely geodynamical origin are instead the result of large slope deformation, and this led in the past to erroneous interpretations. Nevertheless, their limit seems not clearly defined, but it is somehow transitional. Some studies point out continuity between failures developing at surface with upper crust movements. In this contribution, the main studies which examine the link between rock structures and slope movements are reviewed. The aspects regarding model and scale of observation are discussed together with the role of pre-existing weaknesses in the rock mass. As slope failures can develop through progressive failure, structures and their changes in time and space can be recognized. Furthermore, recognition of the origin of these structures can help in avoiding misinterpretations of regional geology. This also suggests the importance of integrating different slope movement classifications based on distribution and pattern of deformation and the application of structural geology techniques. A structural geology approach in the landslide community is a tool that can greatly support the hazard quantification and related risks, because most of the physical parameters, which are used for landslide modeling, are derived from geotechnical tests or the emerging geophysical approaches.

Therapeutic drug monitoring of imatinib: Bayesian and alternative methods to predict trough levels

Background: The imatinib trough plasma concentration (C(min)) correlates with clinical response in cancer patients. Therapeutic drug monitoring (TDM) of plasma C(min) is therefore suggested. In practice, however, blood sampling for TDM is often not performed at trough. The corresponding measurement is thus only remotely informative about C(min) exposure. Objectives: The objectives of this study were to improve the interpretation of randomly measured concentrations by using a Bayesian approach for the prediction of C(min), incorporating correlation between pharmacokinetic parameters, and to compare the predictive performance of this method with alternative approaches, by comparing predictions with actual measured trough levels, and with predictions obtained by a reference method, respectively. Methods: A Bayesian maximum a posteriori (MAP) estimation method accounting for correlation (MAP-ρ) between pharmacokinetic parameters was developed on the basis of a population pharmacokinetic model, which was validated on external data. Thirty-one paired random and trough levels, observed in gastrointestinal stromal tumour patients, were then used for the evaluation of the Bayesian MAP-ρ method: individual C(min) predictions, derived from single random observations, were compared with actual measured trough levels for assessment of predictive performance (accuracy and precision). The method was also compared with alternative approaches: classical Bayesian MAP estimation assuming uncorrelated pharmacokinetic parameters, linear extrapolation along the typical elimination constant of imatinib, and non-linear mixed-effects modelling (NONMEM) first-order conditional estimation (FOCE) with interaction. Predictions of all methods were finally compared with 'best-possible' predictions obtained by a reference method (NONMEM FOCE, using both random and trough observations for individual C(min) prediction). Results: The developed Bayesian MAP-ρ method accounting for correlation between pharmacokinetic parameters allowed non-biased prediction of imatinib C(min) with a precision of ±30.7%. This predictive performance was similar for the alternative methods that were applied. The range of relative prediction errors was, however, smallest for the Bayesian MAP-ρ method and largest for the linear extrapolation method. When compared with the reference method, predictive performance was comparable for all methods. The time interval between random and trough sampling did not influence the precision of Bayesian MAP-ρ predictions. Conclusion: Clinical interpretation of randomly measured imatinib plasma concentrations can be assisted by Bayesian TDM. Classical Bayesian MAP estimation can be applied even without consideration of the correlation between pharmacokinetic parameters. Individual C(min) predictions are expected to vary less through Bayesian TDM than linear extrapolation. Bayesian TDM could be developed in the future for other targeted anticancer drugs and for the prediction of other pharmacokinetic parameters that have been correlated with clinical outcomes.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

Behaviour change at population, community and individual levels: NICE Public Health Guidance 6

This guidance is aimed at those responsible for helping people to change their behaviour to improve their health. This includes policy makers and those working in local authorities and the community and voluntary sectors. It gives advice on how to plan and run relevant initiatives. The recommendations include the following advice: base interventions on a proper assessment of the target group, where they are located and the behaviour which is to be changed: careful planning is the cornerstone of success  work with other organisations and the community itself to decide on and develop initiatives build on the skills and knowledge that already exists in the community, for example, by encouraging networks of people who can support each other take account of and resolve problems that prevent people changing their behaviour (for example, the costs involved in taking part in exercise programmes or buying fresh fruit and vegetables, or lack of knowledge about how to make changes) base all interventions on evidence of what works train staff to help people change their behaviour evaluate all interventions.This resource was contributed by The National Documentation Centre on Drug Use.

Trends in overweight and obesity levels in Geneva: time for optimism?

Background/Introduction: ln Switzerland, most trends in overweight and obesity levels have been assessed using reported data, a methodology which is prone to reporting bias. ln this study, we aimed at assessing trends in overweight and obesity levels using objectively measured data. Methods: We used independent cross-sectional data collected between 2005 and 2011 by the Bus Santé study on representative samples of the Geneva population. Trends were assessed overall and according to different characteristics of the participants. Overweight and obesity were defined as a body mass index (BMI) between 25 and 29.9 kg/m2 and >=30 kg/m2, respectively. Results: Data from 4093 participants (2012 men) was assessed. Mean BMI was 25.2 ± 4.3 kg/m2 (mean ±standard deviation) in 2005 and 25.4 ± 4.3 in 2011 (p for trend using linear regression=0.98). For men, mean BMI was 26.3 ± 3.8 kg/m2 in 2005 and 26.1 ± 3.7 in 2011 (p for trend=0.37); for women, the corresponding values were 24.3 ± 4.6 and 24.7 ± 4.7 kg/m2 (p for trend=0.42). Overall prevalence of overweight and obesity was 32.2% and 13.3%, respectively, in 2005 and 33.6% and 13.7% in 2011 (p for trend using polytomous logistic regression adjusting for gender, age and smoking=0.49 and 0.94 for overweight and obesity, respectively). For men, prevalence of overweight and obesity was 45.9% and 12.2% in 2005 and 42.1 % and 14.6% in 2011 (P for trend=0.03 for overweight and 0.81 for obesity); for women, the corresponding values were 20.4% and 14.2% in 2005 and 25.4% and 12.9% in 2011 (p for trend=0.13 for overweight and 0.99 for obesity). Conclusion: Overweight and obesity levels appear to have levelled in Geneva, with a possible decrease in overweight levels in men. These favorable findings should be replicated in other geographical locations.

Evaluation of the natural killer cytotoxicity and the levels of cytokines in rats with type I diabetes mellitus

Type I diabetes mellitus (insulin-dependent DM = IDDM) is a chronic disease characterized by specific destruction of pancreatic beta cells, resulting in an absolute lack of insulin. Immune mechanisms, genetic susceptibility, and environmental factors are all implicated in the pathogenesis of Type 1 diabetes. This study was aimed at determining the efficiency of cytokines, natural killer (NK) cells in the pathophysiology of IDDM. Therefore, we evaluated the plasma levels of cytokines by specific enzyme-linked immunosorbent assay (ELISA) and the cytotoxicity activity of NK cells by anti-candididal index in rats with type I diabetes. We found that the cytotoxicity activity of NK cells in IDDM groups significantly decreased compared to the control groups. The levels of interferon-g (IFN-g) in IDDM groups were slightly higher than in healthy controls. These results indicate that the changes of T H1 type cytokines such as IFN-g and NK cell activity can play a role in the etiology of IDDM. The data may provide new strategies for the treatment of IDDM.

Multifaceted roles of peroxisome proliferator-activated receptors (PPARs) at the cellular and whole organism levels.

Chronic disorders, such as obesity, diabetes, inflammation, non-alcoholic fatty liver disease and atherosclerosis, are related to alterations in lipid and glucose metabolism, in which peroxisome proliferator-activated receptors (PPAR)α, PPARβ/δ and PPARγ are involved. These receptors form a subgroup of ligand-activated transcription factors that belong to the nuclear hormone receptor family. This review discusses a selection of novel PPAR functions identified during the last few years. The PPARs regulate processes that are essential for the maintenance of pregnancy and embryonic development. Newly found hepatic functions of PPARα are the mediation of female-specific gene repression and the protection of the liver from oestrogen induced toxicity. PPARα also controls lipid catabolism and is the target of hypolipidaemic drugs, whereas PPARγ controls adipocyte differentiation and regulates lipid storage; it is the target for the insulin sensitising thiazolidinediones used to treat type 2 diabetes. Activation of PPARβ/δ increases lipid catabolism in skeletal muscle, the heart and adipose tissue. In addition, PPARβ/δ ligands prevent weight gain and suppress macrophage derived inflammation. In fact, therapeutic benefits of PPAR ligands have been confirmed in inflammatory and autoimmune diseases, such as encephalomyelitis and inflammatory bowel disease. Furthermore, PPARs promote skin wound repair. PPARα favours skin healing during the inflammatory phase that follows injury, whilst PPARβ/δ enhances keratinocyte survival and migration. Due to their collective functions in skin, PPARs represent a major research target for our understanding of many skin diseases. Taken altogether, these functions suggest that PPARs serve as physiological sensors in different stress situations and remain valuable targets for innovative therapies.

Elevated levels of MIC-1/GDF15 in the cerebrospinal fluid of patients are associated with glioblastoma and worse outcome.

For patients with brain tumors identification of diagnostic and prognostic markers in easy accessible biological material, such as plasma or cerebrospinal fluid (CSF), would greatly facilitate patient management. MIC-1/GDF15 (growth differentiation factor 15) is a secreted protein of the TGF-beta superfamily and emerged as a candidate marker exhibiting increasing mRNA expression during malignant progression of glioma. Determination of MIC-1/GDF15 protein levels by ELISA in the CSF of a cohort of 94 patients with intracranial tumors including gliomas, meningioma and metastasis revealed significantly increased concentrations in glioblastoma patients (median, 229 pg/ml) when compared with control cohort of patients treated for non-neoplastic diseases (median below limit of detection of 156 pg/ml, p < 0.0001, Mann-Whitney test). However, plasma MIC-1/GDF15 levels were not elevated in the matching plasma samples from these patients. Most interestingly, patients with glioblastoma and increased CSF MIC-1/GDF15 had a shorter survival (p = 0.007, log-rank test). In conclusion, MIC-1/GDF15 protein measured in the CSF may have diagnostic and prognostic value in patients with intracranial tumors.