Effect of Marginal-Quality Irrigation on Accumulation of some Heavy Metals (Mn, Pb, and Zn) in TypicTorripsamment Soils and Food Crops

Lack of active sorption sites in sandy soils renders metals added by irrigation water more labile and increases their soil-to-plant transfer. Thus, this study investigated the long-term impacts of irrigation using sewage effluents and contaminated groundwater on metal accumulations in TypicTorripsamment soils, and edible parts of food crops. Nine sites in El-Gabal El-Asfar farm, south-eastern to the Nile Delta of Egypt, were selected. At each site, irrigation water, soil (0-30 cm), and the crop's edible part were sampled in triplicates and analyzed for Mn, Pb, and Zn. Results revealed significant (p < 0.05) differences in metal concentrations among water sources. Thus, constant irrigation caused significant spatial variations in total and available metal contents in soils. Total contents of Pb (in four sites) and Zn (in all sites) exceed the lithosphere range, while the available contents of the three metals exceeded the safe limits in all soils. The index of geo-accumulation indicated no Mn pollution but showed elevated pollution risks for Pb and Zn. The three metals showed high availability ratios, proving the effect of light soil texture. The multivariate statistical analysis indicated that Mn and Zn had similar geochemical behaviors in soils. Metal contents in all crop's edible parts surpassed the safe limits. The bioaccumulation factor (BAF) was less than 1.0 for Mn and Zn but higher than 1.0 for Pb. The highest BAFs occurred in cabbage leaves, indicating the phytoextraction potential of this species. Sufficient water treatment and proper remediation techniques are recommended to alleviate metal accumulation in food crops and their transfer via the food chain

Modeling and assessing potential soil erosion hazards using usle and wind erosion models in integration with GIS techniques: Dakhla oasis, Egypt

Soil erosion modeling is becoming more significant in the development and implementation of soil management and conservation policies. For a better understanding of the geographical distribution of soil erosion, spatial-based models of soil erosion are required. The current study proposed a spatial-based model that integrated geographic information systems (GIS) techniques with both the universal soil loss equation (USLE) model and the Index of Land Susceptibility to Wind Erosion (ILSWE). The proposed Spatial Soil Loss Model (SSLM) was designed to generate the potential soil erosion maps based on water erosion and wind erosion by integrating factors of the USLE and ILSWE models into the GIS environment. Hence, the main objective of this study is to predict, quantify, and assess the soil erosion hazards using the SSLM in the Dakhla Oasis as a case study. The water soil loss values were computed by overlaying the values of five factors: the rainfall factor (R-Factor), soil erodibility (K-Factor), topography (LS-Factor), crop types (C-Factor), and conservation practice (P-Factor). The severity of wind-driven soil loss was calculated by overlaying the values of five factors: climatic erosivity (CE-Factor), soil erodibility (E-Factor), soil crust (SC-Factor), vegetation cover (VC-Factor), and surface roughness (SR-Factor). The proposed model was statistically validated by comparing its outputs to the results of USLE and ILSWE models. Soil loss values based on USLE and SSLM varied from 0.26 to 3.51 t ha−1 yr−1 with an average of 1.30 t ha−1 yr−1 and from 0.26 to 3.09 t ha−1 yr−1 with a mean of 1.33 t ha−1 yr−1, respectively. As a result, and according to the assessment of both the USLE and the SSLM, one soil erosion class, the very low class (<6.7 t ha−1 yr−1 ), has been reported to be the prevalent erosion class in the study area. These findings indicate that the Dakhla Oasis is slightly eroded and more tolerable against water erosion factors under current management conditions. Furthermore, the study area was classified into four classes of wind erosion severity: very slight, slight, moderate, and high, representing 1.0%, 25.2%, 41.5%, and 32.3% of the total study area, respectively, based on the ILSWE model and 0.9%, 25.4%, 43.9%, and 29.9%, respectively, according to the SSLM. Consequently, the Dakhla Oasis is qualified as a promising area for sustainable agriculture when appropriate management is applied. The USLE and ILSWE model rates had a strong positive correlation (r = 0.97 and 0.98, respectively), with the SSLM rates, as well as a strong relationship based on the average linear regression (R2 = 0.94 and 0.97, respectively). The present study is an attempt to adopt a spatial-based model to compute and map the potential soil erosion. It also pointed out that designing soil erosion spatial models using available data sources and the integration of USLE and ILSWE with GIS techniques is a viable option for calculating soil loss rates. Therefore, the proposed soil erosion spatial model is fit for calculating and assessing soil loss rates under this study and is valid for use in other studies under arid regions with the same condition

Production of insulin producing cells from cord blood mesenchymal stem cells and their potential in cell therapy

Introduction: Mesenchymal stem cells (MSCs) were described as adherent cells with a fibroblast-like appearance, have a great capacity for self-renewal while maintaining their multipotency and differentiation into multiple tissues in vivo and in vitro. Methods: MSCs were isolated from cord blood of Sudanese donors using Ficoll-Hypaque gradient density protocol, and differentiate into β- like cells using 3-step protocol. STZ induced diabetic rats were injected intraperitoneally with the differentiated islet β- like cells and blood glucose levels were monitored for seven days. Results: The adherent cell appeared round and sphere after one-week of incubation, and the fibroblast-like colony was strongly attached after three weeks of seeding. The phenotyping of cells showed positivity for CD13, and negativity for CD34, CD45 and HLADR. MSCs were induced into islet-like cells using a 3-step (15-days) protocol. The differentiated cells showed positive diathizone stain and positive imuno-reactivity to anti-human insulin antibody. Secretion of insulin by insulin-producing cells showed positive result with &gt;3.4 u/ml scale reading in high glucose concentration medium. After one-week of transplantation the level of blood glucose was reduced from 410 to 225 mg/dl in the experimental rat. Conclusion: Human UCB-MSCs can be differentiated into insulin-secreting cells invitro, and are able to produce and secrete insulin in response to high glucose concentration in vivo and in vitro. Keywords: Cord blood, Mesenchymal stem cell, islets β-like cell

Y Chromosome Lineage- and Village-Specific Genes on Chromosomes 1p22 and 6q27 Control Visceral Leishmaniasis in Sudan

Familial clustering and ethnic differences suggest that visceral leishmaniasis caused by Leishmania donovani is under genetic control. A recent genome scan provided evidence for a major susceptibility gene on Chromosome 22q12 in the Aringa ethnic group in Sudan. We now report a genome-wide scan using 69 families with 173 affected relatives from two villages occupied by the related Masalit ethnic group. A primary ten-centimorgan scan followed by refined mapping provided evidence for major loci at 1p22 (LOD score 5.65; nominal p = 1.72 × 10(−7); empirical p < 1 × 10(−5); λ(S) = 5.1) and 6q27 (LOD score 3.74; nominal p = 1.68 × 10(−5); empirical p < 1 × 10(−4); λ(S) = 2.3) that were Y chromosome–lineage and village-specific. Neither village supported a visceral leishmaniasis susceptibility gene on 22q12. The results suggest strong lineage-specific genes due to founder effect and consanguinity in these recently immigrant populations. These chance events in ethnically uniform African populations provide a powerful resource in the search for genes and mechanisms that regulate this complex disease

Collagen extract obtained from Nile tilapia (Oreochromis niloticus L.) skin accelerates wound healing in rat model via up regulating VEGF, bFGF, and α-SMA genes expression

Background Collagen is the most abundant structural protein in the mammalian connective tissue and represents approximately 30% of animal protein. The current study evaluated the potential capacity of collagen extract derived from Nile tilapia skin in improving the cutaneous wound healing in rats and investigated the underlying possible mechanisms. A rat model was used, and the experimental design included a control group (CG) and the tilapia collagen treated group (TCG). Full-thickness wounds were conducted on the back of all the rats under general anesthesia, then the tilapia collagen extract was applied topically on the wound area of TCG. Wound areas of the two experimental groups were measured on days 0, 3, 6, 9, 12, and 15 post-wounding. The stages of the wound granulation tissues were detected by histopathologic examination and the expression of vascular endothelial growth factor (VEGF), and transforming growth factor (TGF-ß1) were investigated using immunohistochemistry. Moreover, relative gene expression analysis of transforming growth factor-beta (TGF-ß1), basic fibroblast growth factor (bFGF), and alpha-smooth muscle actin (α-SMA) were quantified by real-time qPCR. Results The histopathological assessment showed noticeable signs of skin healing in TCG compared to CG. Immunohistochemistry results revealed remarkable enhancement in the expression levels of VEGF and TGF-β1 in TCG. Furthermore, TCG exhibited marked upregulation in the VEGF, bFGF, and α-SMA genes expression. These findings suggested that the topical application of Nile tilapia collagen extract can promote the cutaneous wound healing process in rats, which could be attributed to its stimulating effect on recruiting and activating macrophages to produce chemotactic growth factors, fibroblast proliferation, and angiogenesis. Conclusions The collagen extract could, therefore, be a potential biomaterial for cutaneous wound healing therapeutics. Backgroun

Cause of Death and Predictors of All-Cause Mortality in Anticoagulated Patients With Nonvalvular Atrial Fibrillation : Data From ROCKET AF

M. Kaste on työryhmän ROCKET AF Steering Comm jäsen.Background-Atrial fibrillation is associated with higher mortality. Identification of causes of death and contemporary risk factors for all-cause mortality may guide interventions. Methods and Results-In the Rivaroxaban Once Daily Oral Direct Factor Xa Inhibition Compared with Vitamin K Antagonism for Prevention of Stroke and Embolism Trial in Atrial Fibrillation (ROCKET AF) study, patients with nonvalvular atrial fibrillation were randomized to rivaroxaban or dose-adjusted warfarin. Cox proportional hazards regression with backward elimination identified factors at randomization that were independently associated with all-cause mortality in the 14 171 participants in the intention-to-treat population. The median age was 73 years, and the mean CHADS(2) score was 3.5. Over 1.9 years of median follow-up, 1214 (8.6%) patients died. Kaplan-Meier mortality rates were 4.2% at 1 year and 8.9% at 2 years. The majority of classified deaths (1081) were cardiovascular (72%), whereas only 6% were nonhemorrhagic stroke or systemic embolism. No significant difference in all-cause mortality was observed between the rivaroxaban and warfarin arms (P=0.15). Heart failure (hazard ratio 1.51, 95% CI 1.33-1.70, P= 75 years (hazard ratio 1.69, 95% CI 1.51-1.90, P Conclusions-In a large population of patients anticoagulated for nonvalvular atrial fibrillation, approximate to 7 in 10 deaths were cardiovascular, whereasPeer reviewe

Soil Salinity Assessing and Mapping Using Several Statistical and Distribution Techniques in Arid and Semi-Arid Ecosystems, Egypt

Oasis lands in Egypt are commonly described as salty soils; therefore, waterlogging and higher soil salinity are major obstacles to sustainable agricultural development. This study aims to map and assess soil salinization at El-Farafra Oasis in the Egypt Western Desert based on salinity indices, Imaging Spectroscopy (IS), and statistical techniques. The regression model was developed to test the relationship between the electrical conductivity (ECe) of 70 surface soil samples and seven salinity indices (SI 1, SI 2, SI 5, SI 6, SI 7, SI 8, and SI 9) to produce soil salinity maps depending on Landsat-8 (OLI) images. The investigations of soil salinization and salinity indices were validated in a studied area based on 30 soil samples; the obtained results represented that all salinity indices have shown satisfactory correlations between ECe values for each soil sample site and salinity indices, except for the SI 5 index that present non-significant correlations with R2 value of 0.2688. The SI 8 index shows a higher negative significant correlation with ECe and an R2 value of 0.6356. There is a significant positive correlation at the (p &lt; 0.01) level between SI 9 and ECe (r = 0.514), a non-significant correlation at the (p &lt; 0.05) level between soil ECe and SI 1 index (r = 0.495), and the best-verified salinity index was for SI 7 that has a low estimated RMSE error of 8.58. Finally, the highest standard error (R2) was represented as ECe (dS m&minus;1) with an R2 of 0.881, and the lowest one was SI 9 with an R2 of 0.428, according to Tukey&rsquo;s test analysis. Therefore, observing and investigating soil salinity are essential requirements for appropriate natural resource management plans in the future

Land Degradation Vulnerability Mapping in a Newly-Reclaimed Desert Oasis in a Hyper-Arid Agro-Ecosystem Using AHP and Geospatial Techniques

Modelling land degradation vulnerability (LDV) in the newly-reclaimed desert oases is a key factor for sustainable agricultural production. In the present work, a trial for using remote sensing data, GIS tools, and Analytic Hierarchy Process (AHP) was conducted for modeling and evaluating LDV. The model was then applied within 144,566 ha in Farafra, an inland hyper-arid Western Desert Oases in Egypt. Data collected from climate conditions, geological maps, remote sensing imageries, field observations, and laboratory analyses were conducted and subjected to AHP to develop six indices. They included geology index (GI), topographic quality index (TQI), physical soil quality index (PSQI), chemical soil quality index (CSQI), wind erosion quality index (WEQI), and vegetation quality index (VQI). Weights derived from the AHP showed that the effective drivers of LDV in the studied area were as follows: CSQI (0.30) &gt; PSQI (0.29) &gt; VQI (0.17) &gt; TQI (0.12) &gt; GI (0.07) &gt; WEQI (0.05). The LDV map indicated that nearly 85% of the total area was prone to moderate degradation risks, 11% was prone to high risks, while less than 1% was prone to low risks. The consistency ratio (CR) for all studied parameters and indices were less than 0.1, demonstrating the high accuracy of the AHP. The results of the cross-validation demonstrated that the performance of ordinary kriging models (spherical, exponential, and Gaussian) was suitable and reliable for predicting and mapping soil properties. Integrated use of remote sensing data, GIS, and AHP would provide an effective methodology for predicting LDV in desert oases, by which proper management strategies could be adopted to achieve sustainable food security

Evaluation of Desertification Severity in El-Farafra Oasis, Western Desert of Egypt: Application of Modified MEDALUS Approach Using Wind Erosion Index and Factor Analysis

Desertification is a serious threat to human survival and to ecosystems, especially to inland desert oases. An assessment of desertification severity is essential to ensure national sustainable development for agricultural and land expansion processes in this region. In this study, Index of Land Susceptibility to Wind Erosion (ILSWE) was integrated with a Modified Mediterranean Desertification and Land Use (MEDALUS) method and factor analysis (FA) to develop a GIS-based model for mapping desertification severity. The model was then applied to 987.77 km2 in the El-Farafra Oasis, located in the Western Desert of Egypt, as a case study. Climate and field survey data together with remote sensing images were used to generate five quality indices (soil, climate, vegetation, land management and wind erosion). Based on the FA, a weighted value was assigned to each index. Five thematic layers representing the indices were created within the GIS environment and overlaid using the weighted sum model. The developed model showed that 59% of the total area was identified as high-critical and 38% as medium-critical. The results of an environmentally sensitive area index suggested by the original MEDALUS model indicated similar results: 18.37% of the total area was classified as high-critical and 78.73% as medium-critical. However, the sensitivity analysis indicated that weights derived from FA resulted in better performance of the developed spatial model than that derived from the original MEDALUS method. The proposed model would be a suitable tool for monitoring vulnerable zones, and could be a starting point for sustainable agricultural development in inland oases

Evaluation of Desertification Severity in El-Farafra Oasis, Western Desert of Egypt: Application of Modified MEDALUS Approach Using Wind Erosion Index and Factor Analysis

Desertification is a serious threat to human survival and to ecosystems, especially to inland desert oases. An assessment of desertification severity is essential to ensure national sustainable development for agricultural and land expansion processes in this region. In this study, Index of Land Susceptibility to Wind Erosion (ILSWE) was integrated with a Modified Mediterranean Desertification and Land Use (MEDALUS) method and factor analysis (FA) to develop a GIS-based model for mapping desertification severity. The model was then applied to 987.77 km2 in the El-Farafra Oasis, located in the Western Desert of Egypt, as a case study. Climate and field survey data together with remote sensing images were used to generate five quality indices (soil, climate, vegetation, land management and wind erosion). Based on the FA, a weighted value was assigned to each index. Five thematic layers representing the indices were created within the GIS environment and overlaid using the weighted sum model. The developed model showed that 59% of the total area was identified as high-critical and 38% as medium-critical. The results of an environmentally sensitive area index suggested by the original MEDALUS model indicated similar results: 18.37% of the total area was classified as high-critical and 78.73% as medium-critical. However, the sensitivity analysis indicated that weights derived from FA resulted in better performance of the developed spatial model than that derived from the original MEDALUS method. The proposed model would be a suitable tool for monitoring vulnerable zones, and could be a starting point for sustainable agricultural development in inland oases