The seroprevalence of Mycoplasma pneumoniae IgM and IgG antibodies in patients with ischemic stroke

Background and Objectives: Association between Mycoplasma pneumoniae infection and increased risk for brain stroke has been well understood. Hence, the value of serologic tests for assessing causative relationship between this infection and brain stroke seems to be high. The present study aimed to determine serum level of anti-Mycoplasma pneumoniae antibodies in patients with brain stroke and to compare it with non-stroke patients. Materials and Methods: This cross-sectional study was performed on 97 consecutive ischemic stroke patients and 97 sex and age-matched non-stroke patients. Quantitative enzyme-linked immunosorbent assay (ELISA) was established to measure the levels of anti-Mycoplasma pneumoniae IgG and IgM antibodies. Results: Regarding the level of anti-Mycoplasma pneumoniae IgM, the titer of this marker was positive in 4.1 of patients with ischemic stroke, while none of the subjects in control group had positive titer for this antibody (OR = 1.043, 95CI: 1.001 � 1.087, p = 0.043). The rate of positivity for anti-Mycoplasma pneumoniae IgG in ischemic stroke patients was significantly higher than in the control group (28.5 versus 13.4, p = 0.031). Odds ratio for exposure to M. pneumoniae was 2.24 times of the control subjects. The level of anti-Mycoplasma pneumoniae IgM was independent to both sex and age variables in patients group (p = 0.77). The level of anti-Mycoplasma pneumoniae IgG did not depend on subjects� gender in control group, but was significantly higher in men compared with women in patients group. Conclusion: A high level of anti-Mycoplasma pneumoniae IgM and IgG antibodies indicate a significant association of M. pneumoniae infection and history of this infection with increased risk for ischemic stroke. © 2016, Tehran University of Medical Science. All rights reserved

Role of betahistine in glycemic control of obese subjects: a placebo- controlled clinical trial

Background: Poor glycemic control, insulin resistance and abnormal beta cell function are of the most important complications that associated with obesity, targeting of such complications with pharmacological agents depending on the already existing central mechanism may decrease the incidence of morbidity and mortality among obese subjects. Betahistine is an anti-vertigo drug, commonly prescribed to patients with balance disorders or to improve vertigo symptoms associated with Meniere's disease. The aim of this study was to investigate the effect of betahistine on glycemic status, insulin resistance and pancreatic function in obese subjects.Methods: A randomized, placebo controlled trial was carried out on 72 obese subjecta of both sexes with age range of 18-50 years who allocated into two groups: Group A: 48 patients treated with 144mg /day in three divided every eight hours for twelve weeks. Group B: 24 patients treated with placebo for twelve weeks to serve as control. For each group, demographic data, liver and renal function tests beside the studied parameters were investigated at baseline and after 12 weeks.Results: Administration of betahistine to obese subjects resulted in improvement in fasting blood glucose, glycosylated hemoglobin, insulin resistance and beta cell percent values after twelve weeks compared to baseline values and placebo treated group.Conclusions: Administration of betahistine in a dose of 144mg /day for twelve weeks to obese subjects effectively improve glycemic control, insulin resistance and beta cell functions in these subjects, indicating the beneficial effect of betahistine in slowing or reversing the long term progress of obesity complications without incidence of any serious adverse effects, indicating its efficacy and safety

Designing home-based physical activity programs for rural cancer survivors: A survey of technology access and preferences

BACKGROUND: While technology advances have increased the popularity of remote interventions in underserved and rural cancer communities, less is understood about technology access and preferences for home-based physical activity programs in this cancer survivor population. PURPOSE: To determine access, preferences, and needs, for a home-based physical activity program in rural cancer survivors. METHODS: A Qualtrics Research Panel was recruited to survey adults with cancer across the United States. Participants self-reported demographics, cancer characteristics, technology access and usage, and preferences for a home-based physical activity program. The Godin Leisure Time Exercise Questionnaire (GLTEQ) assessed current levels of physical activity. Descriptive statistics included means and standard deviations for continuous variables, and frequencies for categorical variables. Independent samples t-tests explored differences between rural and non-rural participants. RESULTS: Participants (N=298; mean age=55.2 ± 16.5) had a history of cancer (mean age at diagnosis=46.5), with the most commonly reported cancer type being breast (25.5%), followed by prostate (16.1%). 74.2% resided in rural hometowns. 95% of participants reported accessing the internet daily. On a scale of 0-100, computer/laptop (M=63.4) and mobile phone (M=54.6) were the most preferred delivery modes for a home-based physical activity intervention, and most participants preferred balance/flexibility (72.2%) and aerobic (53.9%) exercises. Desired intervention elements included a frequency of 2-3 times a week (53.5%) for at least 20 minutes (75.7%). While there were notable rural disparities present (e.g., older age at diagnosis, lower levels of education; CONCLUSION: These findings provide insights into the preferred physical activity intervention (e.g., computer delivery, balance/flexibility exercises) in rural cancer survivors, while highlighting the need for personalization. Future efforts should consider these preferences when designing and delivering home-based interventions in this population

Using quantitative systems pharmacology modeling to optimize combination therapy of anti-PD-L1 checkpoint inhibitor and T cell engager

Although immune checkpoint blockade therapies have shown evidence of clinical effectiveness in many types of cancer, the outcome of clinical trials shows that very few patients with colorectal cancer benefit from treatments with checkpoint inhibitors. Bispecific T cell engagers (TCEs) are gaining popularity because they can improve patients’ immunological responses by promoting T cell activation. The possibility of combining TCEs with checkpoint inhibitors to increase tumor response and patient survival has been highlighted by preclinical and clinical outcomes. However, identifying predictive biomarkers and optimal dose regimens for individual patients to benefit from combination therapy remains one of the main challenges. In this article, we describe a modular quantitative systems pharmacology (QSP) platform for immuno-oncology that includes specific processes of immune-cancer cell interactions and was created based on published data on colorectal cancer. We generated a virtual patient cohort with the model to conduct in silico virtual clinical trials for combination therapy of a PD-L1 checkpoint inhibitor (atezolizumab) and a bispecific T cell engager (cibisatamab). Using the model calibrated against the clinical trials, we conducted several virtual clinical trials to compare various doses and schedules of administration for two drugs with the goal of therapy optimization. Moreover, we quantified the score of drug synergy for these two drugs to further study the role of the combination therapy

Combination of Growth Model and Earned Schedule to Forecast Project Cost at Completion

To improve the accuracy of early forecasting the final cost at completion of an ongoing construction project, a new regression-based nonlinear cost estimate at completion (CEAC) methodology is proposed that integrates a growth model with earned schedule (ES) concepts. The methodology provides CEAC computations for project early-stage and middle-stage completion. To this end, this paper establishes three primary objectives, as follows: (1) develop a new formula based on integration of the ES method and four candidate growth models (logistic, Gompertz, Bass, andWeibull), (2) validate the new methodology through its application to nine past projects, and (3) select the equation with the best-performing growth model through testing their statistical validity and comparing the accuracy of their CEAC estimates. Based on statistical validity analysis of the four growth models and comparison of CEAC errors, the CEAC formula based on the Gompertz model is better-fitting and generates more accurate final-cost estimates than those computed by using the other three models and the index-based method. The proposed methodology is a theoretical contribution towards the combination of earned-value metrics with regression-based studies. It also brings practical implications associated with usage of a viable and accurate forecasting technique that considers the schedule impact as a determinant factor of cost behavio

Complete fuzzy scheduling and fuzzy earned value management in construction projects

Complete fuzzy scheduling and fuzzy earned value management in construction projects Por: Luis Ponz-Tienda, Jose; Pellicer, Eugenio; Yepes, Victor JOURNAL OF ZHEJIANG UNIVERSITY-SCIENCE A Volumen: 13 Número: 1 Páginas: 56-68 Fecha de publicación: JAN 2012 Search For Full Text Cerrar abstractCerrar abstract This paper aims to present a comprehensive proposal for project scheduling and control by applying fuzzy earned value. It goes a step further than the existing literature: in the formulation of the fuzzy earned value we consider not only its duration, but also cost and production, and alternatives in the scheduling between the earliest and latest times. The mathematical model is implemented in a prototypical construction project with all the estimated values taken as fuzzy numbers. Our findings suggest that different possible schedules and the fuzzy arithmetic provide more objective results in uncertain environments than the traditional methodology. The proposed model allows for controlling the vagueness of the environment through the adjustment of the alpha-cut, adapting it to the specific circumstances of the project. © Zhejiang University and Springer-Verlag Berlin Heidelberg 2012.The authors want to thank Ms. Doria GIL-SENABRE, Universitat Politecnica de Valencia, Spain, for the support provided.Ponz Tienda, JL.; Pellicer Armiñana, E.; Yepes Piqueras, V. (2012). Complete fuzzy scheduling and fuzzy earned value management in construction projects. Journal of Zhejiang University Science A. 13(1):56-68. https://doi.org/10.1631/jzus.A1100160S566813

Global, regional, and national incidence, prevalence, and mortality of HIV, 1980–2017, and forecasts to 2030, for 195 countries and territories: a systematic analysis for the Global Burden of Diseases, Injuries, and Risk Factors Study 2017

Background Understanding the patterns of HIV/AIDS epidemics is crucial to tracking and monitoring the progress of prevention and control efforts in countries. We provide a comprehensive assessment of the levels and trends of HIV/AIDS incidence, prevalence, mortality, and coverage of antiretroviral therapy (ART) for 1980–2017 and forecast these estimates to 2030 for 195 countries and territories. Methods We determined a modelling strategy for each country on the basis of the availability and quality of data. For countries and territories with data from population-based seroprevalence surveys or antenatal care clinics, we estimated prevalence and incidence using an open-source version of the Estimation and Projection Package—a natural history model originally developed by the UNAIDS Reference Group on Estimates, Modelling, and Projections. For countries with cause-specific vital registration data, we corrected data for garbage coding (ie, deaths coded to an intermediate, immediate, or poorly defined cause) and HIV misclassification. We developed a process of cohort incidence bias adjustment to use information on survival and deaths recorded in vital registration to back-calculate HIV incidence. For countries without any representative data on HIV, we produced incidence estimates by pulling information from observed bias in the geographical region. We used a re-coded version of the Spectrum model (a cohort component model that uses rates of disease progression and HIV mortality on and off ART) to produce age-sex-specific incidence, prevalence, and mortality, and treatment coverage results for all countries, and forecast these measures to 2030 using Spectrum with inputs that were extended on the basis of past trends in treatment scale-up and new infections. Findings Global HIV mortality peaked in 2006 with 1·95 million deaths (95% uncertainty interval 1·87–2·04) and has since decreased to 0·95 million deaths (0·91–1·01) in 2017. New cases of HIV globally peaked in 1999 (3·16 million, 2·79–3·67) and since then have gradually decreased to 1·94 million (1·63–2·29) in 2017. These trends, along with ART scale-up, have globally resulted in increased prevalence, with 36·8 million (34·8–39·2) people living with HIV in 2017. Prevalence of HIV was highest in southern sub-Saharan Africa in 2017, and countries in the region had ART coverage ranging from 65·7% in Lesotho to 85·7% in eSwatini. Our forecasts showed that 54 countries will meet the UNAIDS target of 81% ART coverage by 2020 and 12 countries are on track to meet 90% ART coverage by 2030. Forecasted results estimate that few countries will meet the UNAIDS 2020 and 2030 mortality and incidence targets. Interpretation Despite progress in reducing HIV-related mortality over the past decade, slow decreases in incidence, combined with the current context of stagnated funding for related interventions, mean that many countries are not on track to reach the 2020 and 2030 global targets for reduction in incidence and mortality. With a growing population of people living with HIV, it will continue to be a major threat to public health for years to come. The pace of progress needs to be hastened by continuing to expand access to ART and increasing investments in proven HIV prevention initiatives that can be scaled up to have population-level impact

Mapping 123 million neonatal, infant and child deaths between 2000 and 2017

Since 2000, many countries have achieved considerable success in improving child survival, but localized progress remains unclear. To inform efforts towards United Nations Sustainable Development Goal 3.2—to end preventable child deaths by 2030—we need consistently estimated data at the subnational level regarding child mortality rates and trends. Here we quantified, for the period 2000–2017, the subnational variation in mortality rates and number of deaths of neonates, infants and children under 5 years of age within 99 low- and middle-income countries using a geostatistical survival model. We estimated that 32% of children under 5 in these countries lived in districts that had attained rates of 25 or fewer child deaths per 1,000 live births by 2017, and that 58% of child deaths between 2000 and 2017 in these countries could have been averted in the absence of geographical inequality. This study enables the identification of high-mortality clusters, patterns of progress and geographical inequalities to inform appropriate investments and implementations that will help to improve the health of all populations