Global features of upper-tropospheric zonal wind and thermal fields during anomalous monsoon situations

Global analyses of mean monthly zonal wind component and temperature at 200, 150 and 100 mb levels have been made for the region between 60°N and 60°S, for the months May through September during two poor monsoon years (1972 and 1979) and a good monsoon year (1975). Prominent and consistent contrasting features of the zonal wind and thermal fields have been identified, with reference to the monsoon performance over India. It has been noticed that the areal spreading of easterlies over the tropics and extratropics is significantly more during a good monsoon year. Shifting of the axis of the tropical easterly jet stream to a higher level and generally stronger easterlies also characterize good monsoon activity. The upper troposphere has been found to be considerably cooler during poor monsoon years

Dealing with missing standard deviation and mean values in meta-analysis of continuous outcomes: a systematic review

Background: Rigorous, informative meta-analyses rely on availability of appropriate summary statistics or individual participant data. For continuous outcomes, especially those with naturally skewed distributions, summary information on the mean or variability often goes unreported. While full reporting of original trial data is the ideal, we sought to identify methods for handling unreported mean or variability summary statistics in meta-analysis. Methods: We undertook two systematic literature reviews to identify methodological approaches used to deal with missing mean or variability summary statistics. Five electronic databases were searched, in addition to the Cochrane Colloquium abstract books and the Cochrane Statistics Methods Group mailing list archive. We also conducted cited reference searching and emailed topic experts to identify recent methodological developments. Details recorded included the description of the method, the information required to implement the method, any underlying assumptions and whether the method could be readily applied in standard statistical software. We provided a summary description of the methods identified, illustrating selected methods in example meta-analysis scenarios. Results: For missing standard deviations (SDs), following screening of 503 articles, fifteen methods were identified in addition to those reported in a previous review. These included Bayesian hierarchical modelling at the meta-analysis level; summary statistic level imputation based on observed SD values from other trials in the meta-analysis; a practical approximation based on the range; and algebraic estimation of the SD based on other summary statistics. Following screening of 1124 articles for methods estimating the mean, one approximate Bayesian computation approach and three papers based on alternative summary statistics were identified. Illustrative meta-analyses showed that when replacing a missing SD the approximation using the range minimised loss of precision and generally performed better than omitting trials. When estimating missing means, a formula using the median, lower quartile and upper quartile performed best in preserving the precision of the meta-analysis findings, although in some scenarios, omitting trials gave superior results. Conclusions: Methods based on summary statistics (minimum, maximum, lower quartile, upper quartile, median) reported in the literature facilitate more comprehensive inclusion of randomised controlled trials with missing mean or variability summary statistics within meta-analyses

Generating Dashboards Using Fine-Grained Components: A Case Study for a PhD Programme

Developing dashboards is a complex domain, especially when several stakeholders are involved; while some users could demand certain indicators, other users could demand specific visualizations or design features. Creating individual dashboards for each potential need would consume several resources and time, being an unfeasible approach. Also, user requirements must be thoroughly analyzed to understand their goals regarding the data to be explored, and other characteristics that could affect their user experience. All these necessities ask for a paradigm to foster reusability not only at development level but also at knowledge level. Some methodologies, like the Software Product Line paradigm, leverage domain knowledge and apply it to create a series of assets that can be composed, parameterized, or combined to obtain fully functional systems. This work presents an application of the SPL paradigm to the domain of information dashboards, with the goal of reducing their development time and increasing their effectiveness and user experience. Different dashboard configurations have been suggested to test the proposed approach in the context of the Education in the Knowledge Society PhD programme of the University of Salamanca

Natural computation meta-heuristics for the in silico optimization of microbial strains

<p>Abstract</p> <p>Background</p> <p>One of the greatest challenges in Metabolic Engineering is to develop quantitative models and algorithms to identify a set of genetic manipulations that will result in a microbial strain with a desirable metabolic phenotype which typically means having a high yield/productivity. This challenge is not only due to the inherent complexity of the metabolic and regulatory networks, but also to the lack of appropriate modelling and optimization tools. To this end, Evolutionary Algorithms (EAs) have been proposed for <it>in silico </it>metabolic engineering, for example, to identify sets of gene deletions towards maximization of a desired physiological objective function. In this approach, each mutant strain is evaluated by resorting to the simulation of its phenotype using the Flux-Balance Analysis (FBA) approach, together with the premise that microorganisms have maximized their growth along natural evolution.</p> <p>Results</p> <p>This work reports on improved EAs, as well as novel Simulated Annealing (SA) algorithms to address the task of <it>in silico </it>metabolic engineering. Both approaches use a variable size set-based representation, thereby allowing the automatic finding of the best number of gene deletions necessary for achieving a given productivity goal. The work presents extensive computational experiments, involving four case studies that consider the production of succinic and lactic acid as the targets, by using <it>S. cerevisiae </it>and <it>E. coli </it>as model organisms. The proposed algorithms are able to reach optimal/near-optimal solutions regarding the production of the desired compounds and presenting low variability among the several runs.</p> <p>Conclusion</p> <p>The results show that the proposed SA and EA both perform well in the optimization task. A comparison between them is favourable to the SA in terms of consistency in obtaining optimal solutions and faster convergence. In both cases, the use of variable size representations allows the automatic discovery of the approximate number of gene deletions, without compromising the optimality of the solutions.</p

A statistical framework for genetic association studies of power curves in bird flight

How the power required for bird flight varies as a function of forward speed can be used to predict the flight style and behavioral strategy of a bird for feeding and migration. A U-shaped curve was observed between the power and flight velocity in many birds, which is consistent to the theoretical prediction by aerodynamic models. In this article, we present a general genetic model for fine mapping of quantitative trait loci (QTL) responsible for power curves in a sample of birds drawn from a natural population. This model is developed within the maximum likelihood context, implemented with the EM algorithm for estimating the population genetic parameters of QTL and the simplex algorithm for estimating the QTL genotype-specific parameters of power curves. Using Monte Carlo simulation derived from empirical observations of power curves in the European starling (Sturnus vulgaris), we demonstrate how the underlying QTL for power curves can be detected from molecular markers and how the QTL detected affect the most appropriate flight speeds used to design an optimal migration strategy. The results from our model can be directly integrated into a conceptual framework for understanding flight origin and evolution

Continuous low-dose cyclophosphamide and methotrexate combined with celecoxib for patients with advanced cancer

BACKGROUND: Combined therapy of metronomic cyclophosphamide, methotrexate and high-dose celecoxib targeting angiogenesis was used in a phase II trial. METHODS: Patients with advanced cancer received oral cyclophosphamide 50 mg o.d., celecoxib 400 mg b.d. and methotrexate 2.5 mg b.d. for two consecutive days each week. Response was determined every 8 weeks; toxicity was evaluated according to CTC version 2.0. Plasma markers of inflammation, coagulation and angiogenesis were measured. RESULTS: Sixty-seven of 69 patients were evaluable for response. Twenty-three patients had stable disease (SD) after 8 weeks, but there were no objective responses to therapy. Median time to progression was 57 days. There was a low incidence of toxicities. Among plasma markers, levels of tissue factor were higher in the SD group of patients at baseline, and levels of both angiopoietin-1 and matrix metalloproteinase-9 increased in the progressive disease group only. There were no changes in other plasma markers. CONCLUSION: This metronomic approach has negligible activity in advanced cancer albeit with minimal toxicity. Analysis of plasma markers indicates minimal effects on endothelium in this trial. These data for this particular regimen do not support basic tenets of metronomic chemotherapy, such as the ability to overcome resistant tumours by targeting the endothelium

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

In vitro and in vivo characterization of highly purified Human Mesothelioma derived cells

<p>Abstract</p> <p>Background</p> <p>Malignant pleural mesothelioma is a rare disease known to be resistant to conventional therapies. A better understanding of mesothelioma biology may provide the rationale for new therapeutic strategies. In this regard, tumor cell lines development has been an important tool to study the biological properties of many tumors. However all the cell lines established so far were grown in medium containing at least 10% serum, and it has been shown that primary cell lines cultured under these conditions lose their ability to differentiate, acquire gene expression profiles that differ from that of tissue specific stem cells or the primary tumor they derive from, and in some cases are neither clonogenic nor tumorigenic. Our work was aimed to establish from fresh human pleural mesothelioma samples cell cultures maintaining tumorigenic properties.</p> <p>Methods</p> <p>The primary cell cultures, obtained from four human pleural mesotheliomas, were expanded in vitro in a low serum proliferation-permissive medium and the expression of different markers as well as the tumorigenicity in immunodeficient mice was evaluated.</p> <p>Results</p> <p>The established mesothelioma cell cultures are able to engraft, after pseudo orthotopic intraperitoneal transplantation, in immunodeficient mouse and maintain this ability to after serial transplantation. Our cell cultures were strongly positive for CD46, CD47, CD56 and CD63 and were also strongly positive for some markers never described before in mesothelioma cell lines, including CD55, CD90 and CD99. By real time PCR we found that our cell lines expressed high mRNA levels of typical mesothelioma markers as mesothelin (MSLN) and calretinin (CALB2), and of BMI-1, a stemness marker, and DKK1, a potent Wingless [WNT] inhibitor.</p> <p>Conclusions</p> <p>These cell cultures may provide a valuable in vitro and in vivo model to investigate mesothelioma biology. The identification of new mesothelioma markers may be useful for diagnosis and/or prognosis of this neoplasia as well as for isolation of mesothelioma tumor initiating cells.</p