Global, regional, and national cancer incidence, mortality, years of life lost, years lived with disability, and disability-Adjusted life-years for 29 cancer groups, 1990 to 2017 : A systematic analysis for the global burden of disease study

Importance: Cancer and other noncommunicable diseases (NCDs) are now widely recognized as a threat to global development. The latest United Nations high-level meeting on NCDs reaffirmed this observation and also highlighted the slow progress in meeting the 2011 Political Declaration on the Prevention and Control of Noncommunicable Diseases and the third Sustainable Development Goal. Lack of situational analyses, priority setting, and budgeting have been identified as major obstacles in achieving these goals. All of these have in common that they require information on the local cancer epidemiology. The Global Burden of Disease (GBD) study is uniquely poised to provide these crucial data. Objective: To describe cancer burden for 29 cancer groups in 195 countries from 1990 through 2017 to provide data needed for cancer control planning. Evidence Review: We used the GBD study estimation methods to describe cancer incidence, mortality, years lived with disability, years of life lost, and disability-Adjusted life-years (DALYs). Results are presented at the national level as well as by Socio-demographic Index (SDI), a composite indicator of income, educational attainment, and total fertility rate. We also analyzed the influence of the epidemiological vs the demographic transition on cancer incidence. Findings: In 2017, there were 24.5 million incident cancer cases worldwide (16.8 million without nonmelanoma skin cancer [NMSC]) and 9.6 million cancer deaths. The majority of cancer DALYs came from years of life lost (97%), and only 3% came from years lived with disability. The odds of developing cancer were the lowest in the low SDI quintile (1 in 7) and the highest in the high SDI quintile (1 in 2) for both sexes. In 2017, the most common incident cancers in men were NMSC (4.3 million incident cases); tracheal, bronchus, and lung (TBL) cancer (1.5 million incident cases); and prostate cancer (1.3 million incident cases). The most common causes of cancer deaths and DALYs for men were TBL cancer (1.3 million deaths and 28.4 million DALYs), liver cancer (572000 deaths and 15.2 million DALYs), and stomach cancer (542000 deaths and 12.2 million DALYs). For women in 2017, the most common incident cancers were NMSC (3.3 million incident cases), breast cancer (1.9 million incident cases), and colorectal cancer (819000 incident cases). The leading causes of cancer deaths and DALYs for women were breast cancer (601000 deaths and 17.4 million DALYs), TBL cancer (596000 deaths and 12.6 million DALYs), and colorectal cancer (414000 deaths and 8.3 million DALYs). Conclusions and Relevance: The national epidemiological profiles of cancer burden in the GBD study show large heterogeneities, which are a reflection of different exposures to risk factors, economic settings, lifestyles, and access to care and screening. The GBD study can be used by policy makers and other stakeholders to develop and improve national and local cancer control in order to achieve the global targets and improve equity in cancer care. © 2019 American Medical Association. All rights reserved.Peer reviewe

Prediction of Ethanol Concentration in Biofuel Production Using Artificial Neural Networks

Abstract Environmentally friendly and important enhancements in biofuel production technology are necessary in order to cut back production prices and create it as a competitive resource material. This study performed a costeffective bioprocess to provide bio-ethanol from sugarcane molasses by chosen strains of the yeast S. cerevisiae, through experiments at laboratory, pilot and industrial scales. Artificial neural networks are shown to be powerful tools for system modeling. The objective of this study was to develop a straightforward, accurate and time saving prognosticative model for alcohol production. Results recommend that artificial neural networks provide a good means of effective recognizing patterns in data and accurately predicting ethanol concentration based on investigating inputs. The ethanol concentration evaluated in experiments of industrial biofuel production and this research develops a simple, accurate, nondestructive and time saving artificial neural networks model for estimation of ethanol concentration in batch ethanol fermentation from molasses based on live and dead yeast cells, sugar concentration

Comparison of partial least squares-discriminant analysis and soft independent modeling of class analogy methods for classification of Saccharomyces cerevisiae cells based on mid-infrared spectroscopy

Saccharomyces cerevisiae is a widely studied and highly utilized eukaryotic organism, ideally suited to high throughput metabolic analysis, being a powerful model for understanding basic cell biology. This study compares the models developed by two supervised methods, such as the partial least squares-discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA), using mid-infrared (MIR) spectra registered during the growth of S. cerevisiae in bioreactor. The spectra were analyzed using the principal component analysis (PCA), with resolution in five different classes, which were well defined in terms of their biochemical parameters. The SIMCA model showed a significant fitting, 99%, validation, 98%, and prediction parameters, 97%, comparatively with PLS-DA model. Regarding accuracy, sensitivity, and specificity parameters, a value between 83% and 100% was achieved for both methods, but the SIMCA method showed significant specificity and sensitivity values, 98%-100%, representing a suitable classification tool of yeast cells. According to these results, the MIR spectra associated with chemometric tools can be considered a valued strategy for a classification and detailed analysis for an accurate control, allowing to predict the evolution of the corrected process in advance, avoiding losses of time and costs associated with new fermentations, identifying a significant number of samples in any biotechnological process.info:eu-repo/semantics/publishedVersio

The Iranian blood pressure measurement campaign, 2019: study protocol and preliminary results

Purpose Hypertension is one of the most important risk factors for premature mortality and morbidity in Iran. The objective of the Iranian blood pressure (BP) measurement campaign was to identify individuals with raised blood pressure and providing appropriate care and increase the awareness among the public and policymakers of the importance of tackling hypertension. Methods The campaign was conducted in two phases. The first (communication) phase started on May 17th (International Hypertension Day). The second phase started on June 8th, 2019, and lasted up to July 7th during which, blood pressures were measured. The target population was Iranians aged >= 30 years. Participants voluntarily referred to health houses in rural and health posts and comprehensive health centers in urban areas in the setting of the Primary Health Care network. Additionally, over 13,700 temporary stations were set up in highly visited places in urban areas. Volunteer healthcare staff interviewed the participants, measured their BP, and provided them with lifestyle advice and knowledge of the risks and consequences of high blood pressure. They referred participants to physicians in case their BP was high. Participants immediately received a text message containing the relevant advice based on their measured BP and their past history. Results Blood pressure was measured for a total of 26,678,394 participants in the campaign. A total of 13,722,148 participants (51.4) were female. The mean age was 46 +/- 14.1 years. Among total participants, 15,012,693 adults (56.3) with no past history of hypertension had normal BP, 7,959,288 participants had BP in the prehypertension range (29.8), and finally, 3,706,413 participants (13.9) had either past medical history of hypertension, used medications, or had high BP measured in the campaign. Conclusion The campaign was feasible with the objective to increase the awareness among the public and policymakers of the importance of tackling hypertension in Iran