Numerical modelling of the groundwater inflow to an advancing open pit mine: Kolahdarvazeh pit, Central Iran

The groundwater inflow into a mine during its life and after ceasing operations is one of the most important concerns of the mining industry. This paper presents a hydrogeological assessment of the Irankuh Zn-Pb mine at 20 km south of Esfahan and 1 km northeast of Abnil in west-Central Iran. During mine excavation, the upper impervious bed of a confined aquifer was broken and water at high-pressure flowed into an open pit mine associated with the Kolahdarvazeh deposit. The inflow rates were 6.7 and 1.4 m3/s at the maximum and minimum quantities, respectively. Permeability, storage coefficient, thickness and initial head of the fully saturated confined aquifer were 3.5 x 10−4 m/s, 0.2, 30 m and 60 m, respectively. The hydraulic heads as a function of time were monitored at four observation wells in the vicinity of the pit over 19 weeks and at an observation well near a test well over 21 h. In addition, by measuring the rate of pumping out from the pit sump, at a constant head (usually equal to height of the pit floor), the real inflow rates to the pit were monitored. The main innovations of this work were to make comparison between numerical modelling using a finite element software called SEEP/W and actual data related to inflow and extend the applicability of the numerical model. This model was further used to estimate the hydraulic heads at the observation wells around the pit over 19 weeks during mining operations. Data from a pump-out test and observation wells were used for model calibration and verification. In order to evaluate the model efficiency, the modelling results of inflow quantity and hydraulic heads were compared to those from analytical solutions, as well as the field data. The mean percent error in relation to field data for the inflow quantity was 0.108. It varied between 1.16 and 1.46 for hydraulic head predictions, which are much lower values than the mean percent errors resulted from the analytical solutions (from 1.8 to 5.3 for inflow and from 2.16 to 3.5 for hydraulic head predictions). The analytical solutions underestimated the inflow compared to the numerical model for the time period of 2-19 weeks. The results presented in this paper can be used for developing an effective dewatering program

Implications on the Therapeutic Potential of Statins via Modulation of Autophagy

Statins, which are functionally known as 3-hydroxy-3-methyl-glutaryl-CoA (HMG-CoA) inhibitors, are lipid-lowering compounds widely prescribed in patients with cardiovascular diseases (CVD). Several biological and therapeutic functions have been attributed to statins, including neuroprotection, antioxidation, anti-inflammation, and anticancer effects. Pharmacological characteristics of statins have been attributed to their involvement in the modulation of several cellular signaling pathways. Over the past few years, the therapeutic role of statins has partially been attributed to the induction of autophagy, which is critical in maintaining cellular homeostasis and accounts for the removal of unfavorable cells or specific organelles within cells. Dysregulated mechanisms of the autophagy pathway have been attributed to the etiopathogenesis of various disorders, including neurodegenerative disorders, malignancies, infections, and even aging. Autophagy functions as a double-edged sword during tumor metastasis. On the one hand, it plays a role in inhibiting metastasis through restricting necrosis of tumor cells, suppressing the infiltration of the inflammatory cell to the tumor niche, and generating the release of mediators that induce potent immune responses against tumor cells. On the other hand, autophagy has also been associated with promoting tumor metastasis. Several anticancer medications which are aimed at inducing autophagy in the tumor cells are related to statins. This review article discusses the implications of statins in the induction of autophagy and, hence, the treatment of various disorders

Evaluation of the association between KIR polymorphisms and systemic sclerosis : a meta-analysis

Background: The results of investigations on the association between killer cell immunoglobulin-like receptor (KIR) gene polymorphisms and the risk of systemic sclerosis (SSc) are inconsistent. To comprehensively evaluate the influence of KIR polymorphisms on the risk of SSc, this meta-analysis was performed. Methods: A systematic literature search was performed in electronic databases including Scopus and PubMed/ MEDLINE to find all available studies involving KIR gene family polymorphisms and SSc risk prior to July 2019. Pooled odds ratios (ORs) and their corresponding 95% confidence intervals (CIs) were measured to detect associations between KIR gene family polymorphisms and SSc risk. Results: Five articles, comprising 571 patients and 796 healthy participants, evaluating the KIR gene family polymorphisms were included in the final meta-analysis according to the inclusion and exclusion criteria, and 16 KIR genes were assessed. None of the KIR genes were significantly associated with the risk of SSc. Conclusions: The current meta-analysis provides evidence that KIR genes might not be potential risk factors for SSc risk

Graves' disease: introducing new genetic and epigenetic contributors

Autoimmune thyroid disease (AITD) accounts for 90% of all thyroid diseases and affects 2-5% of the population with remarkable familial clustering. Among AITDs, Graves' disease (GD) is a complex disease affecting thyroid function. Over the l ast two decades, casecontrol studies using cutting-edge gene sequencing techniques have detected various susceptible loci that may predispose individuals to GD. It has been presumed that all likely associated genes, variants, and polymorphisms might be responsible for 75-80% of the heritability of GD. As a result, there are implications concerning the potential contribution of environmental and epigenetic factors in the pathogenesis of GD, including its initiation, progression, and development. Numerous review studies have summarized the contribution of genetic factors in GD until now, but there are still some key questions and notions that have not been discussed concerning the interplay of genetic, epigenetic, and immunological factors. With this in mind, this review discusses some newly-identified loci and their potential roles in the pathogenicity of GD. This may lead to the identification of new, promising therapeutic targets. Here, we emphasized principles, listed all the reported disease-associated genes and polymorphisms, and also summarized the current understanding of the epigenetic basis of GD

Genome-Wide Linkage Analysis of Hemodynamic Parameters Under Mental and Physical Stress in Extended Omani Arab Pedigrees:The Oman Family Study

Background: We performed a genome-wide scan in a homogeneous Arab population to identify genomic regions linked to blood pressure (BP) and its intermediate phenotypes during mental and physical stress tests. Methods: The Oman Family Study subjects (N = 1277) were recruited from five extended families of similar to 10 generations. Hemodynamic phenotypes were computed from beat-to-beat BP, electrocardiography and impedance cardiography. Multi-point linkage was performed for resting, mental (word conflict test, WCT) and cold pressor (CPT) stress and their reactivity scores (Delta), using variance components decomposition-based methods implemented in SOLAR. Results: Genome-wide scans for BP phenotypes identified quantitative trait loci (QTLs) with significant evidence of linkage on chromosomes 1 and 12 for WCT-linked cardiac output (LOD = 3.1) and systolic BP (LOD = 3.5). Evidence for suggestive linkage for WCT was found on chromosomes 3, 17 and 1 for heart rate (LOD = 2.3), DBP (LOD = 2.4) and left ventricular ejection time (LVET), respectively. For Delta WCT, suggestive QTLs were detected for CO on chr11 (LOD = 2.5), LVET on chr3 (LOD = 2.0) and EDI on chr9 (LOD = 2.1). For CPT, suggestive QTLs for HR and LVET shared the same region on chr22 (LOD 2.3 and 2.8, respectively) and on chr9 (LOD = 2.3) for SBP, chr7 (LOD = 2.4) for SV and chr19 (LOD = 2.6) for CO. For Delta CPT, CO and TPR top signals were detected on chr15 and 10 (LOD; 2.40, 2.08) respectively. Conclusion: Mental stress revealed the largest number of significant and suggestive loci for normal BP reported to date. The study of BP and its intermediate phenotypes under mental and physical stress may help reveal the genes involved in the pathogenesis of essential hypertension

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BACKGROUND Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. METHODS The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model-a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates-with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality-which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. FINDINGS The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2-100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1-290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1-211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4-48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3-37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7-9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. INTERPRETATION Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere. FUNDING Bill & Melinda Gates Foundation

Global burden of 288 causes of death and life expectancy decomposition in 204 countries and territories and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background Regular, detailed reporting on population health by underlying cause of death is fundamental for public health decision making. Cause-specific estimates of mortality and the subsequent effects on life expectancy worldwide are valuable metrics to gauge progress in reducing mortality rates. These estimates are particularly important following large-scale mortality spikes, such as the COVID-19 pandemic. When systematically analysed, mortality rates and life expectancy allow comparisons of the consequences of causes of death globally and over time, providing a nuanced understanding of the effect of these causes on global populations. Methods The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 cause-of-death analysis estimated mortality and years of life lost (YLLs) from 288 causes of death by age-sex-location-year in 204 countries and territories and 811 subnational locations for each year from 1990 until 2021. The analysis used 56 604 data sources, including data from vital registration and verbal autopsy as well as surveys, censuses, surveillance systems, and cancer registries, among others. As with previous GBD rounds, cause-specific death rates for most causes were estimated using the Cause of Death Ensemble model—a modelling tool developed for GBD to assess the out-of-sample predictive validity of different statistical models and covariate permutations and combine those results to produce cause-specific mortality estimates—with alternative strategies adapted to model causes with insufficient data, substantial changes in reporting over the study period, or unusual epidemiology. YLLs were computed as the product of the number of deaths for each cause-age-sex-location-year and the standard life expectancy at each age. As part of the modelling process, uncertainty intervals (UIs) were generated using the 2·5th and 97·5th percentiles from a 1000-draw distribution for each metric. We decomposed life expectancy by cause of death, location, and year to show cause-specific effects on life expectancy from 1990 to 2021. We also used the coefficient of variation and the fraction of population affected by 90% of deaths to highlight concentrations of mortality. Findings are reported in counts and age-standardised rates. Methodological improvements for cause-of-death estimates in GBD 2021 include the expansion of under-5-years age group to include four new age groups, enhanced methods to account for stochastic variation of sparse data, and the inclusion of COVID-19 and other pandemic-related mortality—which includes excess mortality associated with the pandemic, excluding COVID-19, lower respiratory infections, measles, malaria, and pertussis. For this analysis, 199 new country-years of vital registration cause-of-death data, 5 country-years of surveillance data, 21 country-years of verbal autopsy data, and 94 country-years of other data types were added to those used in previous GBD rounds. Findings The leading causes of age-standardised deaths globally were the same in 2019 as they were in 1990; in descending order, these were, ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and lower respiratory infections. In 2021, however, COVID-19 replaced stroke as the second-leading age-standardised cause of death, with 94·0 deaths (95% UI 89·2–100·0) per 100 000 population. The COVID-19 pandemic shifted the rankings of the leading five causes, lowering stroke to the third-leading and chronic obstructive pulmonary disease to the fourth-leading position. In 2021, the highest age-standardised death rates from COVID-19 occurred in sub-Saharan Africa (271·0 deaths [250·1–290·7] per 100 000 population) and Latin America and the Caribbean (195·4 deaths [182·1–211·4] per 100 000 population). The lowest age-standardised death rates from COVID-19 were in the high-income super-region (48·1 deaths [47·4–48·8] per 100 000 population) and southeast Asia, east Asia, and Oceania (23·2 deaths [16·3–37·2] per 100 000 population). Globally, life expectancy steadily improved between 1990 and 2019 for 18 of the 22 investigated causes. Decomposition of global and regional life expectancy showed the positive effect that reductions in deaths from enteric infections, lower respiratory infections, stroke, and neonatal deaths, among others have contributed to improved survival over the study period. However, a net reduction of 1·6 years occurred in global life expectancy between 2019 and 2021, primarily due to increased death rates from COVID-19 and other pandemic-related mortality. Life expectancy was highly variable between super-regions over the study period, with southeast Asia, east Asia, and Oceania gaining 8·3 years (6·7–9·9) overall, while having the smallest reduction in life expectancy due to COVID-19 (0·4 years). The largest reduction in life expectancy due to COVID-19 occurred in Latin America and the Caribbean (3·6 years). Additionally, 53 of the 288 causes of death were highly concentrated in locations with less than 50% of the global population as of 2021, and these causes of death became progressively more concentrated since 1990, when only 44 causes showed this pattern. The concentration phenomenon is discussed heuristically with respect to enteric and lower respiratory infections, malaria, HIV/AIDS, neonatal disorders, tuberculosis, and measles. Interpretation Long-standing gains in life expectancy and reductions in many of the leading causes of death have been disrupted by the COVID-19 pandemic, the adverse effects of which were spread unevenly among populations. Despite the pandemic, there has been continued progress in combatting several notable causes of death, leading to improved global life expectancy over the study period. Each of the seven GBD super-regions showed an overall improvement from 1990 and 2021, obscuring the negative effect in the years of the pandemic. Additionally, our findings regarding regional variation in causes of death driving increases in life expectancy hold clear policy utility. Analyses of shifting mortality trends reveal that several causes, once widespread globally, are now increasingly concentrated geographically. These changes in mortality concentration, alongside further investigation of changing risks, interventions, and relevant policy, present an important opportunity to deepen our understanding of mortality-reduction strategies. Examining patterns in mortality concentration might reveal areas where successful public health interventions have been implemented. Translating these successes to locations where certain causes of death remain entrenched can inform policies that work to improve life expectancy for people everywhere

Competitive Interaction of Canola (Brassica napus) against Wild Mustard (Sinapis arvensis) using Replacement Series Method

Introduction: Increasing costs of herbicide inputs in intensive crop production systems and the incidence of herbicide resistance in weeds have renewed interest in exploiting crop competitiveness to reduced herbicide use. Two factors contribute to crop competitiveness against weeds: ability to withstand competition (AWC), or the ability to maintain high yields in the presence of weeds, and weed suppressive ability (WSA), the ability of the crop to reduce weed biomass and seed production. Wild mustard is a dominant weed in rapeseed fields of Iran bringing about major yield losses. A strongly persistent seedbank, competitive growth habit, and high fecundity all contribute to its weedy nature ensuring that it will be a continuing problem. In addition to yield losses in rapeseed, wild mustard can reduce crop quality even at its low densities. The main objective of the current paper is to investigate the competitive ability of the canola against wild mustard, and evaluating of empirical yield loss model in predicting the effect of different densities of wild mustard on canola yield. Materials and Methods: The experiment was performed in a randomized complete blocks design with four replications using replacement series in which wild mustard and rapeseed were planted in different ratios of 8:0, 6:2, 4:4, 2:6 and 0:8 plants per pot in 2014. Wild mustard and rapeseed seeds were planted in 35 cm diameter plastic pots filled with a sandy clay loam soil and 1 and 2 cm deep, respectively. Plants were harvested from the soil surface at maturity and were oven dried at 75 ͦ C for 48h, while total shoot biomass for each species being determined. Measurements included shoot and root dry weight, plant height, number of branches per plant, number of pod per plant, number seed per pod and plant seed yield in rapeseed. Relative Yield (RY), Relative Yield Total (RYT) and Relative Crowding Coefficient (RCC) were calculated. Relative yield (RY) is a measure of the relative competitive ability of the two species. RY was calculated using the equation: where Ymix and Ymon are yields in mixture and monoculture. Relative Yield Total (RYT) describes how the species pair utilizes resources. RYT was calculated using the equation: RYT= Relative Crowding Coefficient (RCC) is a measure of competitiveness between the two species. The RCC was calculated using the equation: RCC= Where YAmix and YBmix are average yield per plant of A and of B grown in mixture, respectively, YAmon and YBmon are average yield per plant of A and B grown in monoculture, respectively. Means were compared using Duncans, Multiple Range Test (P 0.05) (SAS, 2002). Results and Discussion: Results showed that the relative yield of rapeseed decreased in the density ratio of 25 and 50 percent compared to same densities of wild mustard. In comparison, rapeseed in a lower or even equal density was more sensitive to competition than wild mustard and hence it faced to sharp yield decrease. However, in the higher planting densities of 75 percent the relative yield of rapeseed increased and the value reached to 0.497. Regarding the higher values of wild mustard compared to rapeseed’s relative yield in higher density ratios of 50 and 75 percent it can be concluded that wild mustard possesses a higher competitive strength, as a consequence, was able to better use nutrition resources. Grain yield influenced markedly by density ratios (

China's Political Economy and the Rapid Increase of its Foreign Aid to Africa

Along with the profound structural changes in China's political economy, its foreign assistance has rapidly increased to a wide range of countries, especially African societies, in the early years of the new century. This phenomenon, as well as many other phenomena associated with the "emergence of China," has sparked a lot of controversy about the motives and consequences of this transformation, which has not yet been addressed in our country. In this regard, the present paper, regardless of the implications of this evolution, examines its causes and context by referring to Beijing's motivations as donors and the needs of African societies as recipients in the context of the core question of the article. The hypothesis that the article examines by descriptive-analytic method is that the rapid increase of Chinese foreign aid to African countries in recent years is primarily due to the international requirements for responding to structural changes in China's domestic political economy and the alignment of the needs of African with Beijing foreign assistance. So, it can be predicted that the presence of China in the Africa will continue to increase in the coming years, and foreign aid will continue to be considered by Beijing officials as one of the main means for establishing this wider presence