676 research outputs found

    From regional pulse vaccination to global disease eradication: insights from a mathematical model of Poliomyelitis

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    Mass-vaccination campaigns are an important strategy in the global fight against poliomyelitis and measles. The large-scale logistics required for these mass immunisation campaigns magnifies the need for research into the effectiveness and optimal deployment of pulse vaccination. In order to better understand this control strategy, we propose a mathematical model accounting for the disease dynamics in connected regions, incorporating seasonality, environmental reservoirs and independent periodic pulse vaccination schedules in each region. The effective reproduction number, ReR_e, is defined and proved to be a global threshold for persistence of the disease. Analytical and numerical calculations show the importance of synchronising the pulse vaccinations in connected regions and the timing of the pulses with respect to the pathogen circulation seasonality. Our results indicate that it may be crucial for mass-vaccination programs, such as national immunisation days, to be synchronised across different regions. In addition, simulations show that a migration imbalance can increase ReR_e and alter how pulse vaccination should be optimally distributed among the patches, similar to results found with constant-rate vaccination. Furthermore, contrary to the case of constant-rate vaccination, the fraction of environmental transmission affects the value of ReR_e when pulse vaccination is present.Comment: Added section 6.1, made other revisions, changed titl

    Characterization of heterogeneity and spatial distribution of phases in complex solid dispersions by thermal analysis by structural characterization and X-ray micro computed tomography

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    Purpose: This study investigated the effect of drug-excipient miscibility on the heterogeneity and spatial distribution of phase separation in pharmaceutical solid dispersions at a micron-scale using two novel and complementary characterization techniques, thermal analysis by structural characterization (TASC) and X-ray micro-computed tomography (XCT) in conjunction with conventional characterization methods. Method: Complex dispersions containing felodipine, TPGS, PEG and PEO were prepared using hot melt extrusion-injection moulding. The phase separation behavior of the samples was characterized using TASC and XCT in conjunction with conventional thermal, microscopic and spectroscopic techniques. The in vitro drug release study was performed to demonstrate the impact of phase separation on dissolution of the dispersions. Results: The conventional characterization results indicated the phase separating nature of the carrier materials in the patches and the presence of crystalline drug in the patches with the highest drug loading (30% w/w). TASC and XCT where used to provide insight into the spatial configuration of the separate phases. TASC enabled assessment of the increased heterogeneity of the dispersions with increasing the drug loading. XCT allowed the visualization of the accumulation of phase separated (crystalline) drug clusters at the interface of air pockets in the patches with highest drug loading which led to poor dissolution performance. Semi-quantitative assessment of the phase separated drug clusters in the patches were attempted using XCT. Conclusion: TASC and XμCT can provide unique information regarding the phase separation behavior of solid dispersions which can be closely associated with important product quality indicators such as heterogeneity and microstructure

    Seasonal variations of EPG levels in gastro-intestinal parasitic infection in a southeast asian controlled locale:a statistical analysis

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    We present a data based statistical study on the effects of seasonal variations in the growth rates of the gastro-intestinal (GI) parasitic infection in livestock. The alluded growth rate is estimated through the variation in the number of eggs per gram (EPG) of faeces in animals. In accordance with earlier studies, our analysis too shows that rainfall is the dominant variable in determining EPG infection rates compared to other macro-parameters like temperature and humidity. Our statistical analysis clearly indicates an oscillatory dependence of EPG levels on rainfall fluctuations. Monsoon recorded the highest infection with a comparative increase of at least 2.5 times compared to the next most infected period (summer). A least square fit of the EPG versus rainfall data indicates an approach towards a super diffusive (i. e. root mean square displacement growing faster than the square root of the elapsed time as obtained for simple diffusion) infection growth pattern regime for low rainfall regimes (technically defined as zeroth level dependence) that gets remarkably augmented for large rainfall zones. Our analysis further indicates that for low fluctuations in temperature (true on the bulk data), EPG level saturates beyond a critical value of the rainfall, a threshold that is expected to indicate the onset of the nonlinear regime. The probability density functions (PDFs) of the EPG data show oscillatory behavior in the large rainfall regime (greater than 500 mm), the frequency of oscillation, once again, being determined by the ambient wetness (rainfall, and humidity). Data recorded over three pilot projects spanning three measures of rainfall and humidity bear testimony to the universality of this statistical argument. © 2013 Chattopadhyay and Bandyopadhyay

    Clinical characteristics and outcomes of patients with acute myelogenous leukemia admitted to intensive care: a case-control study

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    <p>Abstract</p> <p>Background</p> <p>There is limited epidemiologic data on patients with acute myelogenous (myeloid) leukemia (AML) requiring life-sustaining therapies in the intensive care unit (ICU). Our objectives were to describe the clinical characteristics and outcomes in critically ill AML patients.</p> <p>Methods</p> <p>This was a retrospective case-control study. Cases were defined as adult patients with a primary diagnosis of AML admitted to ICU at the University of Alberta Hospital between January 1<sup>st </sup>2002 and June 30<sup>th </sup>2008. Each case was matched by age, sex, and illness severity (ICU only) to two control groups: hospitalized AML controls, and non-AML ICU controls. Data were extracted on demographics, course of hospitalization, and clinical outcomes.</p> <p>Results</p> <p>In total, 45 AML patients with available data were admitted to ICU. Mean (SD) age was 54.8 (13.1) years and 28.9% were female. Primary diagnoses were sepsis (32.6%) and respiratory failure (37.3%). Mean (SD) APACHE II score was 30.3 (10.3), SOFA score 12.6 (4.0) with 62.2% receiving mechanical ventilation, 55.6% vasoactive therapy, and 26.7% renal replacement therapy. Crude in-hospital, 90-day and 1-year mortality was 44.4%, 51.1% and 71.1%, respectively. AML cases had significantly higher adjusted-hazards of death (HR 2.23; 95% CI, 1.38-3.60, p = 0.001) compared to both non-AML ICU controls (HR 1.69; 95% CI, 1.11-2.58, p = 0.02) and hospitalized AML controls (OR 1.0, reference variable). Factors associated with ICU mortality by univariate analysis included older age, AML subtype, higher baseline SOFA score, no change or an increase in early SOFA score, shock, vasoactive therapy and mechanical ventilation. Active chemotherapy in ICU was associated with lower mortality.</p> <p>Conclusions</p> <p>AML patients may represent a minority of all critically ill admissions; however, are not uncommonly supported in ICU. These AML patients are characterized by high illness severity, multi-organ dysfunction, and high treatment intensity and have a higher risk of death when compared with matched hospitalized AML or non-AML ICU controls. The absence of early improvement in organ failure may be a useful predictor for mortality for AML patients admitted to ICU.</p

    Estimation of Ligament Loading and Anterior Tibial Translation in Healthy and ACL-Deficient Knees During Gait and the Influence of Increasing Tibial Slope Using EMG-Driven Approach

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    The purpose of this study was to develop a biomechanical model to estimate anterior tibial translation (ATT), anterior shear forces, and ligament loading in the healthy and anterior cruciate ligament (ACL)-deficient knee joint during gait. This model used electromyography (EMG), joint position, and force plate data as inputs to calculate ligament loading during stance phase. First, an EMG-driven model was used to calculate forces for the major muscles crossing the knee joint. The calculated muscle forces were used as inputs to a knee model that incorporated a knee–ligament model in order to solve for ATT and ligament forces. The model took advantage of using EMGs as inputs, and could account for the abnormal muscle activation patterns of ACL-deficient gait. We validated our model by comparing the calculated results with previous in vitro, in vivo, and numerical studies of healthy and ACL-deficient knees, and this gave us confidence on the accuracy of our model calculations. Our model predicted that ATT increased throughout stance phase for the ACL-deficient knee compared with the healthy knee. The medial collateral ligament functioned as the main passive restraint to anterior shear force in the ACL-deficient knee. Although strong co-contraction of knee flexors was found to help restrain ATT in the ACL-deficient knee, it did not counteract the effect of ACL rupture. Posterior inclination angle of the tibial plateau was found to be a crucial parameter in determining knee mechanics, and increasing the tibial slope inclination in our model would increase the resulting ATT and ligament forces in both healthy and ACL-deficient knees
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