Antioxidative and anti-inflammatory impact of valsartan against renal ischemia-reperfusion injury; role of nitric oxide signaling pathway

Introduction: Renal ischemia reperfusion injury is one of the main causes of acute renal failure, which is associated with high mortality. Tissue damage caused by ischemia-reperfusion occurs due to the release of oxygen free radicals. Type I angiotensin receptor antagonists such as valsartan can be useful in the treatment of chronic kidney disease and hypertension. Objectives: We aimed to evaluate the protective effect of valsartan against renal ischemia reperfusion via antioxidant property and nitric oxide (NO) signaling pathway. Materials and Methods: Fifty male Wistar rats (220 +/- 10 g) were randomly divided into five groups as follows: Group 1; healthy rats without ischemia-reperfusion (control group). Group 2; rats with ischemia reperfusion (IR) (IR control group). Group 3; rats with IR which received 30 mg/kg valsartan orally. Group 4; rats with IR which received 30 mg/kg valsartan together with 40 mg/kg L-NAME. Group 5; rats with IR which received 30 mg/kg valsartan together with 40 mg/kg L-arginine. To induce ischemia-reperfusion, rats were anesthetized with thiopental and underwent surgery. Then, we induced ischemia with blocking blood vessels for 45 minutes by clamping. Biochemical parameters including urea and creatinine were measured using commercial kits. Oxidative stress and inflammatory parameters were measured by ELISA method. Renal tissues were stained with hematoxylin and eosin. Finally, the Kolmogorov-Smirnov test was used to determine the normal distribution of data. Results: The findings of this study indicated that treatment with valsartan and valsartan plus L-arginine leads to significant decrease in the serum levels of creatinine, urea, and albumin/creatinine, malondialdehyde (MDA), interleukin-6 (IL-6) and tumor necrosis factor-alpha (TNF-alpha) in contrast to IR control group which has increased level of these parameters. On the other hand, treatment with valsartan and valsartan plus L-arginine lead to increase in the serum levels of glutathione peroxidase (GPX), in contrast to ischemia reperfusion control group. Conclusion: Our data revealed that valsartan as a type I angiotensin receptor antagonist could decrease oxidative stress and inflammation due to renal ischemia reperfusion injury. Hence, valsartan could propose as a therapeutic agent for kidney diseases such as renal ischemia-reperfusion injury regarded to these renoprotective effects. Keywords Author Keywords:Valsartan; Renal ischemia reperfusion; Antioxidant property; Kidney; Acute renal failure; Reactive oxygen species KeyWords Plus:KIDNEY-DISEASE; HYPERTENSIO

Geographical and socioeconomic inequalities in female breast cancer incidence and mortality in Iran: A Bayesian spatial analysis of registry data

Background In Iran, trends in breast cancer incidence and mortality have generally been monitored at national level. The purpose of this study is to examine province-level disparities in age-standardised breast cancer incidence versus mortality from 2000 to 2010 and their association with socioeconomic status. Methods In this study, data from Iran’s national cancer and death registry systems, and covariates from census and household expenditure surveys were used. We estimated the age-standardised incidence and mortality rates in women aged more than 30 years for all 31 provinces in the consecutive time intervals 2000–2003, 2004–2007 and 2008–2010 using a Bayesian spatial model. Results Mean age-standardised breast cancer incidence across provinces increased over time from 15.0 per 100,000 people (95% credible interval 12.0,18.3) in 2000–2003 to 39.6 (34.5,45.1) in 2008–2010. The mean breast cancer mortality rate declined from 10.9 (8.3,13.8) to 9.9 (7.5,12.5) deaths per 100,000 people in the same period. When grouped by wealth index quintiles, provinces in the highest quintile had higher levels of incidence and mortality. In the wealthiest quintile, reductions in mortality over time were larger than those observed among provinces in the poorest quintile. Relative breast cancer mortality decreased by 16.7% in the highest quintile compared to 10.8% in the lowest quintile. Conclusions Breast cancer incidence has increased over time, with lower incidence in the poorest provinces likely driven by underdiagnoses or late-stage diagnosis. Although the reported mortality rate is still higher in wealthier provinces, the larger decline over time in these provinces indicates a possible future reversal, with the most deprived provinces having higher mortality rates. Ongoing analysis of incidence and mortality at sub-national level is crucial in addressing inequalities in healthcare systems and public health both in Iran and elsewhere

Rising rural body-mass index is the main driver of the global obesity epidemic in adults

Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

Supply chain optimization of forest-based biomass for gasification considering uncertainties

Producing energy from forest-based biomass could aid the transitions in energy and forest sectors to replace fossil fuels; reduce emissions and wastes; and diversify product portfolios and revenue streams. Optimizing the economic and environmental performance of biomass supply chains can help realize these benefits. Besides optimizing the supply chain, investigating other factors, e.g., government incentives and carbon and energy pricing, which contribute to success or failure of forest-based biomass projects, is beneficial. The supply chain of forest-based biomass includes different activities that are cost- and emission-intensive and involve uncertainties. Unlike the majority of studies on forest-based biomass supply chain planning that focused on long-term and deterministic optimization, this dissertation aims to optimize the supply chain of syngas production at tactical level considering uncertainties. Thus, a multi-period bi-objective robust optimization model is developed and applied to the case of a British Columbia Kraft pulp mill that would produce syngas to fuel their lime kiln. The objectives are to minimize costs and emissions while optimizing the monthly biomass procurement, storage, and preprocessing decisions. Robust optimization with an adjustable budget of uncertainty is used to model the uncertainties in biomass supply and cost. Robust Pareto-optimal solutions are obtained that demonstrate a trade-off between objectives. The cost and emissions of robust solutions are on average 68% and 41% higher than those of the deterministic solutions. However, unlike the robust solution, the deterministic solution becomes infeasible in 98% of simulated future scenarios. Besides logistics costs, other factors (e.g., capital investment, government funding, fuel prices, and carbon tax) determine the financial viability of biomass projects. A previous techno-economic feasibility study for the same case revealed that despite a short payback period and positive net present value, the syngas price and carbon tax would result in negative annual cashflows halfway through project’s lifespan. Thus, the pulp mill would be reluctant to invest in this project despite all its potential, especially emission savings. To improve the financial attractiveness of this project for the pulp mill, an optimization model is developed that shows an optimal syngas price of 27 $/GJ, increasing by 0.49¢ annually, would make all cashflows positive.Forestry, Faculty ofGraduat

An efficient method for kidney allocation problem: a credibility-based fuzzy common weights data envelopment analysis approach

Abstract Giventheperennialimbalanceandchronicscarcity betweenthedemandforandsupplyofavailableorgans,organ allocation is one of the most critical decisions in the managementoforgan transplantationnetworks. Organ allocationsystems undergo rapid revisions for the sake of improved outcomes in terms of both equity and medical efficiency. This paper presents a Data Envelopment Analysis (DEA)-based model to evaluate the efficiency of possible patient-organ pairs for kidney allocation in order to enhance the fitness of organ allocation under inherent uncertainty in such problem. Eligible patient-kidney pairs are regarded as decision making units(DMUs)inaCredibility-based FuzzyCommonWeights DEA (CFCWDEA) approach and are ranked based on efficiency scores. Using a common set of weights for all DMUs ensures a high degree of fairness in the assessment and ranking of DMUs. The proposed model is also the first allocation methodcapableofcopingwiththevagueandintervallicmedical and nonmedical allocation factors by the aid of fuzzy programming. Verification and validation of the proposed approachareperformedintwostepsusingarealcasestudyfrom the Iranian kidney allocation system. First, the superiority of theproposeddeterministicmodelinenhancingallocationoutcomesisdemonstratedandanalyzed.Second,theapplicability of the proposed fuzzy DEA method is demonstrated using a series of data realizations for different credibility levels.Keywords Dataenvelopmentanalysis .Credibilitymeasure . Organtransplantation .Organallocation .Kidneyallocatio

A Novel Low-Cost Method for Fabrication of 2D Multi-Electrode Array (MEA) to Evaluate Functionality of Neuronal Cells

In this paper, a fabrication method for two-dimensional multi-electrode arrays (MEAs) using inexpensive material and method is proposed. The focus in this work is on the design and fabrication of 2D Microelectrode arrays using metallic electrodes on a silica substrate. Titanium/gold multi-electrode arrays containing 60 electrodes with optimized metal thicknesses and 30 μm diameter, covered with thin modified SU-8 insulator layer as biocompatible material have been designed and manufactured using the standard photolithography-based microfabrication method. The utilization of affordable and more accessible materials and simpler techniques can be mentioned as the distinct point of the proposed fabrication method. Using these multi-electrode arrays, it is possible to either record or stimulate cells by accessing multiple sites of cell tissues and collect signals from the sources around each electrode simultaneously. Precisely adjusting the size, distance, and number of microelectrodes causes high measurement selectivity and reliability which has been taken into account in the design of the microelectrodes. In this study, we manufactured a preliminary representative MEA and the bio-compatibility of the manufactured MEA is going to be evaluated by neural cells, obtained from rat cortices. The main aim of this study is to compare our inexpensive strategy with other approaches

Predominance of Leishmania major and rare occurrence of Leishmania tropica with haplotype variability at the center of Iran

ABSTRACT Background Leishmania major is a causative agent of zoonotic cutaneous leishmaniasis in the center of Iran, Abarkouh district. Molecular characterization and precise incrimination of Leishmania species was carried out to perform controlling measurements and to design treatment programs for zoonotic cutaneous leishmaniasis. Methods All smears isolated from ulcers of suspected patients were examined under a light microscope and graded for amastigotes frequency. Extraction of DNA, PCR, RFLP and sequencing of ITS-rDNA genotype were done to increase the efficacy of Leishmania parasites identification at their species-specific level and to detect any Leishmania infections within. Results Humans were found to be infected with L. major with high infection frequency and also Leishmania tropica was identified with low occurrence for the first time as non-native species using molecular analyses. The rates of infections was considerable with microscopic observation (n= 65, 73%) out of 89 smears prepared from suspected patients. Molecular analyses showed that the density of L. major was significantly higher (n= 48, 53.93%) than L. tropica (n= 4, 4.49%) (Mann-Whitney U test: p< 0.05) and two samples (2.25%) remained ambiguous after several sequencing. L. major did not have diversity with two common haplotypes but L. tropica were found to exhibit high diversity with three novel haplotypes. Conclusion L. major was considered the causative agent of leishmaniasis in the region, but the identification of a non-native L. tropica revealed the importance of further isolation of Leishmania parasites following molecular analyses and confirmation, and also revealed the importance of further isolation of Leishmania parasites from patients of the field areas who do not have easily access to health care centers for specialized treatment strategies

SARS-CoV-2 vaccination modelling for safe surgery to save lives: data from an international prospective cohort study

Background: Preoperative SARS-CoV-2 vaccination could support safer elective surgery. Vaccine numbers are limited so this study aimed to inform their prioritization by modelling. Methods: The primary outcome was the number needed to vaccinate (NNV) to prevent one COVID-19-related death in 1 year. NNVs were based on postoperative SARS-CoV-2 rates and mortality in an international cohort study (surgical patients), and community SARS-CoV-2 incidence and case fatality data (general population). NNV estimates were stratified by age (18-49, 50-69, 70 or more years) and type of surgery. Best- and worst-case scenarios were used to describe uncertainty. Results: NNVs were more favourable in surgical patients than the general population. The most favourable NNVs were in patients aged 70 years or more needing cancer surgery (351; best case 196, worst case 816) or non-cancer surgery (733; best case 407, worst case 1664). Both exceeded the NNV in the general population (1840; best case 1196, worst case 3066). NNVs for surgical patients remained favourable at a range of SARS-CoV-2 incidence rates in sensitivity analysis modelling. Globally, prioritizing preoperative vaccination of patients needing elective surgery ahead of the general population could prevent an additional 58 687 (best case 115 007, worst case 20 177) COVID-19-related deaths in 1 year. Conclusion: As global roll out of SARS-CoV-2 vaccination proceeds, patients needing elective surgery should be prioritized ahead of the general population