Numerical study on the impulsive growth of a gaseous plug inside a cylindrical vein with compliant coating

Introduction: Employing of gaseous plugs inside a vein for preventing of blood flow to the damaged or cancerous tissues has been known as a gas embolism in the medicine. In this research, a numerical investigation has been carried out on the delivery of the liquid drug DDFP, encapsulated in the microlipidcoated spheres (MLCSs), to target the human vein for construction of the gaseous plug inside the veins. Methods: The encapsulated liquid drug DDFP were delivered to the vein by injection of an emulsion. Releasing of the liquid drug DDFP results in an explosive growth of a gaseous plug inside the vein. The targeted vein was served as a rigid cylinder with a compliant coating. The boundary integral equation method has been employed for the numerical simulation of the hydrodynamic behavior of the gaseous plug inside the vein. Results: Numerical results showed that in the case of a rigid cylinder vein with an internal compliant coating, the maximum volume of the gaseous plug was smaller than the case of just a rigid cylinder vein. Furthermore, its elapsed time from the instant of bubble generation to the instant when the bubble reaches its maximum volume was shorter. Numerical results also showed that the compliant coating on the internal wall of the rigid cylindrical vein had a tendency of reducing the impact of the explosive growth of the gaseous plug. Conclusion: This numerical research showed that the compliant coating on the internal wall of the rigid cylindrical vein had the tendency of reducing the impact of the impulsive growth of the gaseous plug. Therefore, in the case of having severed arteriosclerosis, treatment of the cancerous or damaged tissues by use of the gaseous embolism must be done very carefully in order to prevent the hazardous effects of the gaseous plug’s impulsive growth

The effects of Vitamin D and omega-3 fatty acids co-supplementation on biomarkers of inflammation, oxidative stress and pregnancy outcomes in patients with gestational diabetes

Background: This study was carried out to determine the effects of vitamin D and omega-3 fatty acids co- supplementation on biomarkers of inflammation, oxidative stress and pregnancy outcomes in gestational diabetes (GDM) patients. Methods: This randomized, double-blind, placebo-controlled trial was conducted among 120 GDM women. Participants were randomly divided into four groups to receive: 1) 1000 mg omega-3 fatty acids containing 180 mg eicosapentaenoic acid (EPA) and 120 mg docosahexaenoic acid (DHA) twice a day + vitamin D placebo (n = 30); 2) 50,000 IU vitamin D every 2 weeks + omega-3 fatty acids placebo (n = 30); 3) 50,000 IU vitamin D every 2 weeks + 1000 mg omega-3 fatty acids twice a day (n = 30) and 4) vitamin D placebo + omega-3 fatty acids placebo (n = 30) for 6 weeks. Results: Subjects who received vitamin D plus omega-3 fatty acids supplements compared with vitamin D, omega-3 fatty acids and placebo had significantly decreased high-sensitivity C-reactive protein (-2.0 ± 3.3 vs. -0.8 ± 4.4, -1.3 ± 2.4 and +0.9 ± 2.7 mg/L, respectively, P = 0.008), malondialdehyde (-0.5 ± 0.5 vs. -0.2 ± 0.5, -0.3 ± 0.9 and +0.5 ± 1.4 μmol/L, respectively, P < 0.001), and increased total antioxidant capacity (+92.1 ± 70.1 vs. +55.1 ± 123.6, +88.4 ± 95.2 and +1.0 ± 90.8 mmol/L, respectively, P = 0.001) and glutathione (+95.7 ± 86.7 vs. +23.0 ± 62.3, +30.0 ± 66.5 and -7.8 ± 126.5 μmol/L, respectively, P = 0.001). In addition, vitamin D and omega-3 fatty acids co-supplementation, compared with vitamin D, omega-3 fatty acids and placebo, resulted in lower incidences of newborns' hyperbilirubinemiain (P = 0.037) and newborns' hospitalization (P = 0.037). Conclusion: Overall, vitamin D and omega-3 fatty acids co-supplementation for 6 weeks among GDM women had beneficial effects on some biomarkers of inflammation, oxidative stress and pregnancy outcomes. © 2017 The Author(s)

The effects of Vitamin D and omega-3 fatty acids co-supplementation on biomarkers of inflammation, oxidative stress and pregnancy outcomes in patients with gestational diabetes

Background: This study was carried out to determine the effects of vitamin D and omega-3 fatty acids co- supplementation on biomarkers of inflammation, oxidative stress and pregnancy outcomes in gestational diabetes (GDM) patients. Methods: This randomized, double-blind, placebo-controlled trial was conducted among 120 GDM women. Participants were randomly divided into four groups to receive: 1) 1000 mg omega-3 fatty acids containing 180 mg eicosapentaenoic acid (EPA) and 120 mg docosahexaenoic acid (DHA) twice a day + vitamin D placebo (n = 30); 2) 50,000 IU vitamin D every 2 weeks + omega-3 fatty acids placebo (n = 30); 3) 50,000 IU vitamin D every 2 weeks + 1000 mg omega-3 fatty acids twice a day (n = 30) and 4) vitamin D placebo + omega-3 fatty acids placebo (n = 30) for 6 weeks. Results: Subjects who received vitamin D plus omega-3 fatty acids supplements compared with vitamin D, omega-3 fatty acids and placebo had significantly decreased high-sensitivity C-reactive protein (-2.0 ± 3.3 vs. -0.8 ± 4.4, -1.3 ± 2.4 and +0.9 ± 2.7 mg/L, respectively, P = 0.008), malondialdehyde (-0.5 ± 0.5 vs. -0.2 ± 0.5, -0.3 ± 0.9 and +0.5 ± 1.4 μmol/L, respectively, P < 0.001), and increased total antioxidant capacity (+92.1 ± 70.1 vs. +55.1 ± 123.6, +88.4 ± 95.2 and +1.0 ± 90.8 mmol/L, respectively, P = 0.001) and glutathione (+95.7 ± 86.7 vs. +23.0 ± 62.3, +30.0 ± 66.5 and -7.8 ± 126.5 μmol/L, respectively, P = 0.001). In addition, vitamin D and omega-3 fatty acids co-supplementation, compared with vitamin D, omega-3 fatty acids and placebo, resulted in lower incidences of newborns' hyperbilirubinemiain (P = 0.037) and newborns' hospitalization (P = 0.037). Conclusion: Overall, vitamin D and omega-3 fatty acids co-supplementation for 6 weeks among GDM women had beneficial effects on some biomarkers of inflammation, oxidative stress and pregnancy outcomes. © 2017 The Author(s)

How Can Selection of Biologically Inspired Features Improve the Performance of a Robust Object Recognition Model?

Humans can effectively and swiftly recognize objects in complex natural scenes. This outstanding ability has motivated many computational object recognition models. Most of these models try to emulate the behavior of this remarkable system. The human visual system hierarchically recognizes objects in several processing stages. Along these stages a set of features with increasing complexity is extracted by different parts of visual system. Elementary features like bars and edges are processed in earlier levels of visual pathway and as far as one goes upper in this pathway more complex features will be spotted. It is an important interrogation in the field of visual processing to see which features of an object are selected and represented by the visual cortex. To address this issue, we extended a hierarchical model, which is motivated by biology, for different object recognition tasks. In this model, a set of object parts, named patches, extracted in the intermediate stages. These object parts are used for training procedure in the model and have an important role in object recognition. These patches are selected indiscriminately from different positions of an image and this can lead to the extraction of non-discriminating patches which eventually may reduce the performance. In the proposed model we used an evolutionary algorithm approach to select a set of informative patches. Our reported results indicate that these patches are more informative than usual random patches. We demonstrate the strength of the proposed model on a range of object recognition tasks. The proposed model outperforms the original model in diverse object recognition tasks. It can be seen from the experiments that selected features are generally particular parts of target images. Our results suggest that selected features which are parts of target objects provide an efficient set for robust object recognition

A Stable Biologically Motivated Learning Mechanism for Visual Feature Extraction to Handle Facial Categorization

The brain mechanism of extracting visual features for recognizing various objects has consistently been a controversial issue in computational models of object recognition. To extract visual features, we introduce a new, biologically motivated model for facial categorization, which is an extension of the Hubel and Wiesel simple-to-complex cell hierarchy. To address the synaptic stability versus plasticity dilemma, we apply the Adaptive Resonance Theory (ART) for extracting informative intermediate level visual features during the learning process, which also makes this model stable against the destruction of previously learned information while learning new information. Such a mechanism has been suggested to be embedded within known laminar microcircuits of the cerebral cortex. To reveal the strength of the proposed visual feature learning mechanism, we show that when we use this mechanism in the training process of a well-known biologically motivated object recognition model (the HMAX model), it performs better than the HMAX model in face/non-face classification tasks. Furthermore, we demonstrate that our proposed mechanism is capable of following similar trends in performance as humans in a psychophysical experiment using a face versus non-face rapid categorization task

Global prevalence and genotype distribution of hepatitis C virus infection in 2015 : A modelling study

Publisher Copyright: © 2017 Elsevier LtdBackground The 69th World Health Assembly approved the Global Health Sector Strategy to eliminate hepatitis C virus (HCV) infection by 2030, which can become a reality with the recent launch of direct acting antiviral therapies. Reliable disease burden estimates are required for national strategies. This analysis estimates the global prevalence of viraemic HCV at the end of 2015, an update of—and expansion on—the 2014 analysis, which reported 80 million (95% CI 64–103) viraemic infections in 2013. Methods We developed country-level disease burden models following a systematic review of HCV prevalence (number of studies, n=6754) and genotype (n=11 342) studies published after 2013. A Delphi process was used to gain country expert consensus and validate inputs. Published estimates alone were used for countries where expert panel meetings could not be scheduled. Global prevalence was estimated using regional averages for countries without data. Findings Models were built for 100 countries, 59 of which were approved by country experts, with the remaining 41 estimated using published data alone. The remaining countries had insufficient data to create a model. The global prevalence of viraemic HCV is estimated to be 1·0% (95% uncertainty interval 0·8–1·1) in 2015, corresponding to 71·1 million (62·5–79·4) viraemic infections. Genotypes 1 and 3 were the most common cause of infections (44% and 25%, respectively). Interpretation The global estimate of viraemic infections is lower than previous estimates, largely due to more recent (lower) prevalence estimates in Africa. Additionally, increased mortality due to liver-related causes and an ageing population may have contributed to a reduction in infections. Funding John C Martin Foundation.publishersversionPeer reviewe

Global, regional, and national incidence and mortality for HIV, tuberculosis, and malaria during 1990–2013: a systematic analysis for the Global Burden of Disease Study 2013

BACKGROUND: The Millennium Declaration in 2000 brought special global attention to HIV, tuberculosis, and malaria through the formulation of Millennium Development Goal (MDG) 6. The Global Burden of Disease 2013 study provides a consistent and comprehensive approach to disease estimation for between 1990 and 2013, and an opportunity to assess whether accelerated progress has occured since the Millennium Declaration. METHODS: To estimate incidence and mortality for HIV, we used the UNAIDS Spectrum model appropriately modified based on a systematic review of available studies of mortality with and without antiretroviral therapy (ART). For concentrated epidemics, we calibrated Spectrum models to fit vital registration data corrected for misclassification of HIV deaths. In generalised epidemics, we minimised a loss function to select epidemic curves most consistent with prevalence data and demographic data for all-cause mortality. We analysed counterfactual scenarios for HIV to assess years of life saved through prevention of mother-to-child transmission (PMTCT) and ART. For tuberculosis, we analysed vital registration and verbal autopsy data to estimate mortality using cause of death ensemble modelling. We analysed data for corrected case-notifications, expert opinions on the case-detection rate, prevalence surveys, and estimated cause-specific mortality using Bayesian meta-regression to generate consistent trends in all parameters. We analysed malaria mortality and incidence using an updated cause of death database, a systematic analysis of verbal autopsy validation studies for malaria, and recent studies (2010-13) of incidence, drug resistance, and coverage of insecticide-treated bednets. FINDINGS: Globally in 2013, there were 1·8 million new HIV infections (95% uncertainty interval 1·7 million to 2·1 million), 29·2 million prevalent HIV cases (28·1 to 31·7), and 1·3 million HIV deaths (1·3 to 1·5). At the peak of the epidemic in 2005, HIV caused 1·7 million deaths (1·6 million to 1·9 million). Concentrated epidemics in Latin America and eastern Europe are substantially smaller than previously estimated. Through interventions including PMTCT and ART, 19·1 million life-years (16·6 million to 21·5 million) have been saved, 70·3% (65·4 to 76·1) in developing countries. From 2000 to 2011, the ratio of development assistance for health for HIV to years of life saved through intervention was US$4498 in developing countries. Including in HIV-positive individuals, all-form tuberculosis incidence was 7·5 million (7·4 million to 7·7 million), prevalence was 11·9 million (11·6 million to 12·2 million), and number of deaths was 1·4 million (1·3 million to 1·5 million) in 2013. In the same year and in only individuals who were HIV-negative, all-form tuberculosis incidence was 7·1 million (6·9 million to 7·3 million), prevalence was 11·2 million (10·8 million to 11·6 million), and number of deaths was 1·3 million (1·2 million to 1·4 million). Annualised rates of change (ARC) for incidence, prevalence, and death became negative after 2000. Tuberculosis in HIV-negative individuals disproportionately occurs in men and boys (versus women and girls); 64·0% of cases (63·6 to 64·3) and 64·7% of deaths (60·8 to 70·3). Globally, malaria cases and deaths grew rapidly from 1990 reaching a peak of 232 million cases (143 million to 387 million) in 2003 and 1·2 million deaths (1·1 million to 1·4 million) in 2004. Since 2004, child deaths from malaria in sub-Saharan Africa have decreased by 31·5% (15·7 to 44·1). Outside of Africa, malaria mortality has been steadily decreasing since 1990. INTERPRETATION: Our estimates of the number of people living with HIV are 18·7% smaller than UNAIDS's estimates in 2012. The number of people living with malaria is larger than estimated by WHO. The number of people living with HIV, tuberculosis, or malaria have all decreased since 2000. At the global level, upward trends for malaria and HIV deaths have been reversed and declines in tuberculosis deaths have accelerated. 101 countries (74 of which are developing) still have increasing HIV incidence. Substantial progress since the Millennium Declaration is an encouraging sign of the effect of global action. FUNDING: Bill & Melinda Gates Foundation