A GIS-index integration approach to groundwater suitability zoning for irrigation purposes

In recent decades, the high population growth has increased the demand for agricultural lands and products. Groundwater offers reliability and flexibility in access to water for irrigation purposes, especially in arid and semi-arid areas, such as Amol-Babol Plain, Iran. However, the quality and quantity of groundwater may not be suitable for irrigation purposes in all areas due to urbanizations, and intensive agricultural and industrial activities. Groundwater suitability zoning for irrigation purposes could be useful to improve water resources and land use planning, mostly in areas with water scarcity. Therefore, a GIS-based indices method is proposed to assess suitable zones for agricultural activities, integrating the irrigation water quality (IWQ) index and hydrogeological factors. IWQ index was utilized to assess groundwater quality based on salinity hazard, infiltration hazard, specific ions, and trace elements hazards, and miscellaneous effects such as pH, bicarbonate, and nitrate. The potential of the aquifer for irrigation water abstraction was investigated using hydrogeological surveys such as slope angle of the plain, hydraulic conductivity, and aquifer thickness. The groundwater suitability index classified most of the study area (more than 90 %) as “excellent” or “good” suitability zones for irrigation purposes. A limited area of around 5.6 % of the total area has moderate suitability for irrigation purposes due to the Caspian Seawater intrusion and the presence of fossil saline water. The proposed methodology provides useful information in order to allow irrigation management to prevent water and soil deterioration

The first experience of ex-vivo lung perfusion (EVLP) in Iran: An effective method to increase suitable lung for transplantation

Background: Although lung transplantation is a well-accepted treatment for end-stage lung diseases patients, only 15-20 of the brain-dead donors' lungs are usable for transplantation. This results in high mortality of candidates on waiting lists. Ex-vivo lung perfusion (EVLP) is a novel method for better evaluation of a potential lung for transplantation. Objective: To report the first experience of EVLP in Iran. Methods: The study included a pig in Vienna Medical University, Vienna, Austria, and 4 humans in Masih Daneshvari Hospital, Tehran, Iran. All brain-dead donors from 2013 to 2015 in Tehran were evaluated for EVLP. Donors without signs of severe chest trauma or pneumonia, with poor oxygenation were included. Results: An increasing trend in difference between the pulmonary arterial pO2 and left atrial pO2, an increasing pattern in dynamic lung compliance, and a decreasing trend in the pulmonary vascular resistance, were observed. Conclusion: The initial experience of EVLP in Iran was successful in terms of important/critical parameters. The results emphasize on some important considerations such as precisely following standard lung harvesting and monitoring temperature and pressure. EVLP technique may not be a cost-effective option for low-income countries at first glance. However, because this is the only therapeutic treatment for end-stage lung disease, it is advisable to continue working on this method to find alternatives with lesser costs

The first experience of ex-vivo lung perfusion (EVLP) in Iran: An effective method to increase suitable lung for transplantation

Background: Although lung transplantation is a well-accepted treatment for end-stage lung diseases patients, only 15-20 of the brain-dead donors' lungs are usable for transplantation. This results in high mortality of candidates on waiting lists. Ex-vivo lung perfusion (EVLP) is a novel method for better evaluation of a potential lung for transplantation. Objective: To report the first experience of EVLP in Iran. Methods: The study included a pig in Vienna Medical University, Vienna, Austria, and 4 humans in Masih Daneshvari Hospital, Tehran, Iran. All brain-dead donors from 2013 to 2015 in Tehran were evaluated for EVLP. Donors without signs of severe chest trauma or pneumonia, with poor oxygenation were included. Results: An increasing trend in difference between the pulmonary arterial pO2 and left atrial pO2, an increasing pattern in dynamic lung compliance, and a decreasing trend in the pulmonary vascular resistance, were observed. Conclusion: The initial experience of EVLP in Iran was successful in terms of important/critical parameters. The results emphasize on some important considerations such as precisely following standard lung harvesting and monitoring temperature and pressure. EVLP technique may not be a cost-effective option for low-income countries at first glance. However, because this is the only therapeutic treatment for end-stage lung disease, it is advisable to continue working on this method to find alternatives with lesser costs

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

A predictive assessment of genetic correlations between traits in chickens using markers

International audienceAbstractBackgroundGenomic selection has been successfully implemented in plant and animal breeding programs to shorten generation intervals and accelerate genetic progress per unit of time. In practice, genomic selection can be used to improve several correlated traits simultaneously via multiple-trait prediction, which exploits correlations between traits. However, few studies have explored multiple-trait genomic selection. Our aim was to infer genetic correlations between three traits measured in broiler chickens by exploring kinship matrices based on a linear combination of measures of pedigree and marker-based relatedness. A predictive assessment was used to gauge genetic correlations.MethodsA multivariate genomic best linear unbiased prediction model was designed to combine information from pedigree and genome-wide markers in order to assess genetic correlations between three complex traits in chickens, i.e. body weight at 35 days of age (BW), ultrasound area of breast meat (BM) and hen-house egg production (HHP). A dataset with 1351 birds that were genotyped with the 600 K Affymetrix platform was used. A kinship kernel (K) was constructed as K = λG + (1 − λ)A, where A is the numerator relationship matrix, measuring pedigree-based relatedness, and G is a genomic relationship matrix. The weight (λ) assigned to each source of information varied over the grid λ = (0, 0.2, 0.4, 0.6, 0.8, 1). Maximum likelihood estimates of heritability and genetic correlations were obtained at each λ, and the “optimum” λ was determined using cross-validation.ResultsEstimates of genetic correlations were affected by the weight placed on the source of information used to build K. For example, the genetic correlation between BW–HHP and BM–HHP changed markedly when λ varied from 0 (only A used for measuring relatedness) to 1 (only genomic information used). As λ increased, predictive correlations (correlation between observed phenotypes and predicted breeding values) increased and mean-squared predictive error decreased. However, the improvement in predictive ability was not monotonic, with an optimum found at some 0 < λ < 1, i.e., when both sources of information were used together.ConclusionsOur findings indicate that multiple-trait prediction may benefit from combining pedigree and marker information. Also, it appeared that expected correlated responses to selection computed from standard theory may differ from realized responses. The predictive assessment provided a metric for performance evaluation as well as a means for expressing uncertainty of outcomes of multiple-trait selection

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