Mortality and disability-adjusted life years in North Africa and Middle East attributed to kidney dysfunction : a systematic analysis for the Global Burden of Disease Study 2019

The authors would like to thank the hard work of the staff of the Institute for Health Metrics and Evaluation (IHME) for providing the best possible epidemiologic estimation of diseases in almost all regions and countries of the world, trying to reduce and eliminate poverty of knowledge and information about the diseases globally. Also, the core team authors sincerely thank all the collaborators of the GBD 2019 study who contributed to this study by providing data or a precise review of the manuscript. Publisher Copyright: © The Author(s) 2023. Published by Oxford University Press on behalf of the ERA. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Peer reviewe

The global burden of cancer attributable to risk factors, 2010-19 : a systematic analysis for the Global Burden of Disease Study 2019

Background Understanding the magnitude of cancer burden attributable to potentially modifiable risk factors is crucial for development of effective prevention and mitigation strategies. We analysed results from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 to inform cancer control planning efforts globally. Methods The GBD 2019 comparative risk assessment framework was used to estimate cancer burden attributable to behavioural, environmental and occupational, and metabolic risk factors. A total of 82 risk-outcome pairs were included on the basis of the World Cancer Research Fund criteria. Estimated cancer deaths and disability-adjusted life-years (DALYs) in 2019 and change in these measures between 2010 and 2019 are presented. Findings Globally, in 2019, the risk factors included in this analysis accounted for 4.45 million (95% uncertainty interval 4.01-4.94) deaths and 105 million (95.0-116) DALYs for both sexes combined, representing 44.4% (41.3-48.4) of all cancer deaths and 42.0% (39.1-45.6) of all DALYs. There were 2.88 million (2.60-3.18) risk-attributable cancer deaths in males (50.6% [47.8-54.1] of all male cancer deaths) and 1.58 million (1.36-1.84) risk-attributable cancer deaths in females (36.3% [32.5-41.3] of all female cancer deaths). The leading risk factors at the most detailed level globally for risk-attributable cancer deaths and DALYs in 2019 for both sexes combined were smoking, followed by alcohol use and high BMI. Risk-attributable cancer burden varied by world region and Socio-demographic Index (SDI), with smoking, unsafe sex, and alcohol use being the three leading risk factors for risk-attributable cancer DALYs in low SDI locations in 2019, whereas DALYs in high SDI locations mirrored the top three global risk factor rankings. From 2010 to 2019, global risk-attributable cancer deaths increased by 20.4% (12.6-28.4) and DALYs by 16.8% (8.8-25.0), with the greatest percentage increase in metabolic risks (34.7% [27.9-42.8] and 33.3% [25.8-42.0]). Interpretation The leading risk factors contributing to global cancer burden in 2019 were behavioural, whereas metabolic risk factors saw the largest increases between 2010 and 2019. Reducing exposure to these modifiable risk factors would decrease cancer mortality and DALY rates worldwide, and policies should be tailored appropriately to local cancer risk factor burden. Copyright (C) 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 license.Peer reviewe

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

On the complexity of the colorful directed paths in vertex coloring of digraphs

The colorful paths and rainbow paths have been considered by severalauthors.A colorful directed path in a digraph $G$ is a directed path with $chi(G)$ vertices whose colors are different. A $v$-colorful directed path is such a directed path, starting from $v$. We prove that for a given $3$-regular triangle-free digraph $G$ determining whether there is a proper $chi(G)$-coloring of $G$such that for every $v in V (G)$, there exists a $v$-colorful directed path is $mathbf{NP}$-complete

Synthesis, Antimicrobial Activity and Molecular Docking Study of Novel N,2-Diphenylquinazolin-4-amine Derivatives: Synthesis, Docking and Antimicrobial Activities of Some Quinazoline Derivatives

A new series of derivatives of N, 2-diphenylquinazolin-4-amine (3a-g) was synthesized through nucleophilic substitution. The structures of compounds were characterized by FTIR, 1H-NMR, and 13C-NMR spectroscopy. All synthesized compounds were evaluated for their antimicrobial activities against Gram-positive (Staphylococcus aureus, Bacillus subtilis, Lactobacillus rhamnosus) and Gram-negative (Escherichia coli, Pseudomonas aeruginosa) bacteria and also for antifungal activities, against Candida albicans, using broth microdilution method to determine their minimum inhibitory concentrations (MIC). Most of the compounds have shown moderate to good antibacterial activities, significantly compound 3g at 0.0625 mg/mL concentration had the highest activity against P. aeruginosa. Also, the MIC of compound 3f was 0.0078 mg/mL against S. aureus. Furthermore, the tested compounds exhibited remarkable antifungal activities against C. albicans, significantly compounds 3c and 3g showed the least MIC (equal to 0.0625 mg/mL). Also, a docking study into DNA gyrase has been made for these compounds. The synthesized compounds showed dock score values between -3.05 and -6.13kcal/mol. The highest dock score among them was -6.13 kcal/mol, found for compound 3c

The Alpha-Beta Skew Generalized t Distribution: Properties and Applications

n this paper, we propose a new distribution, namely alpha-beta-skew generalized tdistribution. The proposed distribution is really flxible and includes as special models some important distributions like Normal, t-student, Cauchy and etc as its marginal component distributions. It features a probability density function with up to three modes. The moment generating function as well as the main moments are provided. Inference is based on a usual maximum-likelihood estimation approach and a small Monte Carlo simulation is conducted for studying the asymptotic properties of the maximum-likelihood estimate. The usefulness of the new model is illustrated in a real dat

Application of Pb–Fe spinel-activated carbon for phenol removal from aqueous solutions: fixed-bed adsorption studies

Fixed-bed studies for phenol uptake from water were carried out using a novel Pb–Fe spinel-activated carbon adsorbent. A characterization phase including TGA, FTIR, SEM, and BET analyses was performed for the developed active carbon. In column studies, the influence of initial phenol concentration, column bed height, and the solution flow rate was investigated at natural pH. Adsorption of phenol onto Pb–Fe spinel-activated carbon composite and pristine activated carbon was analyzed in the form of breakthrough curves. Under optimum conditions, the maximum adsorption capacities for the magnetic active carbon composite and pristine activated carbon were found to be 113.95 and 102.61 mg/g, respectively. Results indicated that the adsorption capacity of adsorbent for all examined conditions was higher than that obtained for unmodified activated carbon because the composite contains additional metal hydroxides compared with the pristine activated carbon. The Yoon and Nelson, Thomas, and instantaneous local equilibrium (ILE) models were used to explain column data collected under different operating conditions. Finally, the results of the continuous adsorption process were explained successfully using the Yoon–Nelson and Thomas models. Thus, the phenol adsorption on Pb-Fe@MAC was a feasible operation to be performed in fixed-bed mode

Toward a mechanistic understanding of adsorption behavior of phenol onto a novel activated carbon composite

In this research, the solid–liquid adsorption systems for MSAC (PbFe2O4 spinel-activated carbon)-phenol and pristine activated carbon-phenol were scrutinized from the thermodynamics and statistical physics (sta-phy) viewpoints. Experimental results indicated that MSAC composite outperformed pristine AC for the uptake of phenol from waste streams. By increasing the process temperature, the amount of phenol adsorbed onto both adsorbents, MSAC composite and pristine AC, decreased. Thermodynamic evaluations for MSAC demonstrated the spontaneous and exothermic characteristics of the adsorption process, while positive values of ΔG for pristine AC indicated a non-spontaneous process of phenol adsorption in all temperatures. In a mechanistic investigation, statistical physics modeling was applied to explore the responsible mechanism for phenol adsorption onto the MSAC composite and pristine AC. The single-layer model with one energy was the best model to describe the experimental data for both adsorbents. The adsorption energies of phenol onto both adsorbents were relatively smaller than 20 kJ/mol, indicating physical interactions. By increasing temperature from 298 to 358 K, the value of the absorbed amount of phenol onto the MSAC composite and pristine AC at saturation (Qsat) decreased from 158.94 and 138.91 to 115.23 and 112.34 mg/g, respectively. Mechanistic studies confirm the significant role of metallic hydroxides in MSAC to facilitate the removal of phenol through a strong interaction with phenol molecules, as compared with pristine activated carbon

Smart distribution grid management during a worst-case scenario of renewable energy outage

Nowadays, due to the high penetration of renewable energy sources such as wind generation and PV in the distribution network and the possibility of their outage, the optimal operation of the distribution grid has faced challenges. In this paper, a bi-level model based on mixed integer quadratic programming (MIQP) is proposed for the optimal operation of smart distribution networks under the worst case of the outage of renewable energy resources. At the upper-level problem, minimization of the energy losses, energy purchase, and load shedding in the demand side management program is formulated, and at the lower-level problem, the maximization of output and curtailment of renewable energy resources is modeled. At the lower level, the worst-case realization of the renewable outage is derived and at the upper level, optimal operation of the distribution network is done under the worst-case realization of renewable resources. The reformulation method based on Karush–Kuhn–Tucker (KKT) conditions is considered to solve the proposed bi-level model, which is faster and less complicated than similar algorithms. The IEEE 33-bus distribution grid is considered for the analysis of the proposed model and method, which proves the accuracy and optimal performance of the proposed model and method. The findings indicate that, with the implementation of the suggested model, the smart distribution network successfully avoided load-shedding even when various renewable resources were disconnected. Also, the proposed model in operation under normal conditions has caused a 56% reduction in losses and a 53% reduction in energy purchases compared to the outage of 6 renewable units in the distribution network

Factors affecting nursing student acceptance of online learning under the COVID-19 pandemic

Introduction: The advantages of online learning are enhancing independence and incentive of students for learning, improving the connection between individuals and making flexibility in time and place for doing the activity. This study endeavored to determine factors affecting nursing students’ acceptance of online learning during the COVID-19 pandemic Methods: This cross-sectional descriptive-analytical study that was done with a sample of students on Islamic Azad University of Gorgan and Neishaboor's. Convenience sampling was done and 368 of 500 students participated in the study. The questionnaire consisted of demographic questions, educational information and translated questionnaires that included student perceptions of an online course, University student engagement inventory and acceptance of online learning. Descriptive statistics were employed to assess demographic characteristics simple and multiple linear regression models were used to analyze the predictor variables of students' acceptance of online learning. Pvalue<0.05 was considered for all tests. Results: The effective factors on student's acceptance for online learning was widespread high-speed Internet access at home, increasing the quality of connection to Internet and increasing the quality of laptop, tablet or mobile phone. On the other hand, multiple linear regression results showed only the remaining variables in the model were increasing the score of the course content (β=0.18, P0.001). It is of note that this model had an explanatory power of 46%. Conclusion: According to the results of the study, if teachers strengthen the content of the course and create the creativity in interaction and use of all the features of the online learning system, we can hope that the rate of online learning acceptance among students will increase