Global, regional, and national burden of colorectal cancer and its risk factors, 1990–2019: a systematic analysis for the Global Burden of Disease Study 2019

Funding: F Carvalho and E Fernandes acknowledge support from Fundação para a Ciência e a Tecnologia, I.P. (FCT), in the scope of the project UIDP/04378/2020 and UIDB/04378/2020 of the Research Unit on Applied Molecular Biosciences UCIBIO and the project LA/P/0140/2020 of the Associate Laboratory Institute for Health and Bioeconomy i4HB; FCT/MCTES through the project UIDB/50006/2020. J Conde acknowledges the European Research Council Starting Grant (ERC-StG-2019-848325). V M Costa acknowledges the grant SFRH/BHD/110001/2015, received by Portuguese national funds through Fundação para a Ciência e Tecnologia (FCT), IP, under the Norma Transitória DL57/2016/CP1334/CT0006.proofepub_ahead_of_prin

Evolutionary Optimization for the Number and Capacity of Surge Tanks and Pipeline Diameters in a Transmission Line

Controlling the unsteady effects of fluid flow (water hammer) is one of the most important monitoring factors for structural protection of transmission pipelines. These effects are controlled by surge tanks, air chambers, pressure relief valves, and check valves. Generally, the critical points are detected by simulating the unsteady flow of the fluid, and accordingly, optimum positioning of the control devices is decided. Among the search methods, Genetic Algorithm (GA) is an effective and robust method to solve highly complex optimization problems. Here, for the first time, GA coupled with an unsteady flow simulator is used to optimize the number and capacity of surge tanks in a pipeline system. In addition, the pipeline diameters are optimized for their best performance

Estimating Penetration Resistance in Agricultural Soils of Ardabil Plain Using Artificial Neural Network and Regression Methods

Introduction: Penetration resistance is one of the criteria for evaluating soil compaction. It correlates with several soil properties such as vehicle trafficability, resistance to root penetration, seedling emergence, and soil compaction by farm machinery. Direct measurement of penetration resistance is time consuming and difficult because of high temporal and spatial variability. Therefore, many different regressions and artificial neural network pedotransfer functions have been proposed to estimate penetration resistance from readily available soil variables such as particle size distribution, bulk density (Db) and gravimetric water content (θm). The lands of Ardabil Province are one of the main production regions of potato in Iran, thus, obtaining the soil penetration resistance in these regions help with the management of potato production. The objective of this research was to derive pedotransfer functions by using regression and artificial neural network to predict penetration resistance from some soil variations in the agricultural soils of Ardabil plain and to compare the performance of artificial neural network with regression models. Materials and methods: Disturbed and undisturbed soil samples (n= 105) were systematically taken from 0-10 cm soil depth with nearly 3000 m distance in the agricultural lands of the Ardabil plain ((lat 38°15' to 38°40' N, long 48°16' to 48°61' E). The contents of sand, silt and clay (hydrometer method), CaCO3 (titration method), bulk density (cylinder method), particle density (Dp) (pychnometer method), organic carbon (wet oxidation method), total porosity(calculating from Db and Dp), saturated (θs) and field soil water (θf) using the gravimetric method were measured in the laboratory. Mean geometric diameter (dg) and standard deviation (σg) of soil particles were computed using the percentages of sand, silt and clay. Penetration resistance was measured in situ using cone penetrometer (analog model) at 10 replicates. The data were divided into two series as 78 data for training and 27 data for testing. The SPSS 18 with stepwise method and MATLAB software were used to derive the regression and artificial neural network, respectively. A feed forward three-layer (8, 11 and 15 neurons in the hidden layer) perceptron network and the tangent sigmoid transfer function were used for the artificial neural network modeling. In estimating penetration resistance, The accuracy of artificial neural network and regression pedotransfer functions were evaluated by coefficient of determination (R2), root mean square error (RMSE), mean error (ME) and Akaike information criterion (AIC) statistics. Results and discussion: The textural classes of study soils were loamy sand (n= 8), sandy loam (n= 70), loam (n= 6) and silt loam (n= 21). The values of sand (26.26 to 87.43 %), clay (3.99 to 17.34 %), organic carbon (0.3 to 2.41 %), field moisture (4.56 to 33.18 mass percent), Db (1.02 to 1.63 g cm-3) and penetration resistance (1.1 to 6.6 MPa) showed a large variations of study soils. There were found significant correlations between penetration resistance and sand (r= - 0.505**), silt (r= 0.447**), clay (r= 0.330**), organic carbon (r= - 0.465**), Db (r= 0.655**), θf (r= -0.63**), CaCO3 (r= 0.290**), total porosity (r= - 0.589**) and Dp (r= 0.266*). Generally, 15 regression and artificial neural network pedotransfer functions were constructed to predict penetration resistance from measured readily available soil variables. The results of regression and artificial neural network pedotransfer functions showed that the most suitable variables to estimate penetration resistance were θf, Db and particles size distribution. The input variables were n and θf for the best regression pedotransfer function and also Db, silt, θf and σg for the best artificial neural network pedotransfer function. The values of R2, RMSE, ME and AIC were obtained equal to 0.55, 0.89 MPa, 0.05 MPa and -14.67 and 0.91, 0.37 MPa, - 0.0026 MPa and -146.64 for the best regression and artificial neural network pedotransfer functions, respectively. The former researchers also reported that there is a positive correlation between penetration resistance with Db and a negative correlation between penetration resistance with θf and organic carbon. Conclusion: The results showed that silt, standard deviation of soil particles (σg), bulk density (Db), total porosity and field water content (θf) are the most suitable readily available soil variables to predict penetration resistance in the studied area. According to the RMSE and AIC criteria, the accuracy of artificial neural network in estimating soil penetration resistance was more than regression pedotransfer functions in this research

Formulation of Herbal Gel of Antirrhinum majus Extract and Evaluation of its Anti- Propionibacterium acne Effects

Background: Antirrhinum majus contains aurone with excellent antibacterial and antifungal activities. In addition, visible light activates the endogenous porphyrins of Propionibacterium acne, which results in bacterial death. Therefore, considering the above-mentioned facts, the aim of the present study was to prepare a topical herbal gel of A. majus hydroalcoholic extract and to evaluate its antiacne effects with or without blue light combination as an activator of the porphyrins. Materials and Methods: Antibacterial activity of the shoot or petal extracts was evaluated by disc diffusion method and the minimum inhibitory concentration (MIC) was calculated. Various gel formulations were developed by the Experimental Design software. The obtained gel formulations were prepared and tested for pharmaceutical parameters including organoleptic features, pH, viscosity, drug content, and release studies. Finally, the antibacterial activity was evaluated against (P. acnes) with or without blue light. Results: The MIC of the extracts showed to be 0.25 μg/ml. Evaluation of the gel formulation showed acceptable properties of the best formulation in comparison to a gel in the market. Pharmaceutical parameters were also in accordance with the standard parameters of the marketed gel. Furthermore, statistical analyses showed significant antibacterial effect for gel when compared to negative control. However, combination of blue light with gel did not show any significant difference on the observed antibacterial effect. Conclusion: Because of the statistically significant in vitro antiacne effects of the formulated gel, further clinical studies for evaluation of the healing effects of the prepared gel formulation on acne lesions must be performed

Comparison of the accuracy of NovApex apex locator and radiographic method: in vivo/ex vivo study

INTRODUCTION: Determination of the canal working length with radiographs has many drawbacks. Electronic apex locators have been developed to overcome some of these problems. Recently, a newly designed apex locator called NovApex has been introduced. All the studies conducted to determine the accuracy of NovApex have been carried out in-vitro on extracted teeth. The aim of this in vivo study was to evaluate the accuracy of NovApex compared with traditional radiographic method. MATERIALS & METHODS: Twenty-five patients whose lower molars that were candidates for extraction were selected. The teeth were accessed, and the radiographic working length was determined by measuring the length of the initial file 0.5mm short of the radiographic apex. Then, NovApex apex locator was used to measure the electronic working length. Subsequently, the tooth was extracted, and the actual working length was measured by introducing a size #15 K-file into each canal until the file tip was visible at the apex, then 1.5mm was subtracted to attain the working length. Cohen's Kappa was computed for each of the methods versus actual working length as a measure of reliability. The accuracies were compared using Chi-square test. RESULTS: The accuracy of NovApex apex locator and radiographic method in detecting the apical end point within ±0.5mm was 74.7% and 68%, respectively; this was not significantly different (P<0.001). CONCLUSION: The NovApex apex locator is useful in detecting the apical end point with the accuracy similar to radiographic method. However, neither technique is fully reliable in detecting the apical end point of the canal. KEYWORDS: Electronic apex locator, NovApex, Radiographic Image Interpretation.

Evaluation of the educational environments of undergraduate medicine and pharmacy programmes at the University of Zambia

Background:A Based on the World Health Organization’s reporting, over 1.25 million people die annually in traffic accidents worldwide. Traffic accidents are the ninth main cause of death worldwide, with an average age range of victims of 15 to 29. Broadly speaking, 90% of traffic accidents happen in the lowand middle-income countries that comprise 82% of the global population, and these countries account for half of the world’s vehicles. One of the goals of the National Road Traffic Knowledge Development Trustee is to plan and implement training courses (content design, design and implementation and evaluation) for target groups. To achieve this goal and due to the lack of academic programs on traffic safety in Iran, a single-credit course, “Safety and Traffic,” was developed to be run as a compulsory academic course in all universities across the country. Methods: This course was administered as a national pilot study in four phases and in 17 medical universities across the country. All experts and national authorities in the Ministry of Science and the Ministry of Health and Medical Education were requested to provide feedback. Afterwards, the results and comments were forwarded to the Supreme Council of Cultural Revolution for further investigation. Upon approval of the Council, the course will be implemented in all universities across the country. Results: Results from the pre-test showed that the level of students’ knowledge was low before attending the training courses. Surveys also revealed that the two items of “pedestrian safety” and “first aids in RTCs” were the most useful and applicable subjects. The percentage of wrong answers ranged from 61 to 98%. Conclusion: Considering the importance of traffic accidents and people’s role in traffic-related issues, it seems that it is necessary to provide university courses for traffic safety education

Injury burden in individuals aged 50 years or older in the Eastern Mediterranean region, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019

Background: Injury poses a major threat to health and longevity in adults aged 50 years or older. The increased life expectancy in the Eastern Mediterranean region warrants a further understanding of the ageing population's inevitable changing health demands and challenges. We aimed to examine injury-related morbidity and mortality among adults aged 50 years or older in 22 Eastern Mediterranean countries. Methods: Drawing on data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019, we categorised the population into adults aged 50–69 years and adults aged 70 years and older. We examined estimates for transport injuries, self-harm injuries, and unintentional injuries for both age groups, with sex differences reported, and analysed the percentage changes from 1990 to 2019. We reported injury-related mortality rates and disability-adjusted life-years (DALYs). The Socio-demographic Index (SDI) and the Healthcare Access and Quality (HAQ) Index were used to better understand the association of socioeconomic factors and health-care system performance, respectively, with injuries and health status in older people. Healthy life expectancy (HALE) was compared with injury-related deaths and DALYs and to the SDI and HAQ Index to understand the effect of injuries on healthy ageing. Finally, risk factors for injury deaths between 1990 and 2019 were assessed. 95% uncertainty intervals (UIs) are given for all estimates. Findings: Estimated injury mortality rates in the Eastern Mediterranean region exceeded the global rates in 2019, with higher injury mortality rates in males than in females for both age groups. Transport injuries were the leading cause of deaths in adults aged 50–69 years (43·0 [95% UI 31·0–51·8] per 100 000 population) and in adults aged 70 years or older (66·2 [52·5–75·5] per 100 000 population), closely followed by conflict and terrorism for both age groups (10·2 [9·3–11·3] deaths per 100 000 population for 50–69 years and 45·7 [41·5–50·3] deaths per 100 000 population for ≥70 years). The highest annual percentage change in mortality rates due to injury was observed in Afghanistan among people aged 70 years or older (400·4% increase; mortality rate 1109·7 [1017·7–1214·7] per 100 000 population). The leading cause of DALYs was transport injuries for people aged 50–69 years (1798·8 [1394·1–2116·0] per 100 000 population) and unintentional injuries for those aged 70 years or older (2013·2 [1682·2–2408·7] per 100 000 population). The estimates for HALE at 50 years and at 70 years in the Eastern Mediterranean region were lower than global estimates. Eastern Mediterranean countries with the lowest SDIs and HAQ Index values had high prevalence of injury DALYs and ranked the lowest for HALE at 50 years of age and HALE at 70 years. The leading injury mortality risk factors were occupational exposure in people aged 50–69 years and low bone mineral density in those aged 70 years or older. Interpretation: Injuries still pose a real threat to people aged 50 years or older living in the Eastern Mediterranean region, mainly due to transport and violence-related injuries. Dedicated efforts should be implemented to devise injury prevention strategies that are appropriate for older adults and cost-effective injury programmes tailored to the needs and resources of local health-care systems, and to curtail injury-associated risk and promote healthy ageing. Funding: Bill & Melinda Gates Foundation