Assessment of cadmium and lead in the water and trout fish (Salmo trutta) of Zayandehroud River, a case study of Zarinshahr rice farms, Isfahan

This study aimed to investigate the concentrations of two heavy metals, lead and cadmium, in the water of Zayandehroud River which is surrounded by Zarinshahr rice farms. Water was sampled from a depth of 30 cm during June, July and August 2015, i.e. during the process of planting, growing and after harvesting, in three stations. Water was collected from three points; 20m before the farms, beside the farms and 100m after the farms. Three water samples and one trout fish (Salmo trutta) sample were collected each month and the concentrations of lead and cadmium were measured in the kidney, liver and gills of trout fish. The results showed that the amounts of lead and cadmium in the water were less and more than standard levels for these metals, respectively. The average concentrations of cadmium in the water were 15.81, 11.25, 8.92 μg/L during June, July and August, respectively. It is evident that the amount of cadmium in water was significantly higher in June during the planting phase and use of fertilizers and pesticides was more than the other months (p≤0.01). There was a correlation in cadmium and lead concentrations between water and fish organs (kidney, liver and gill)

Assimilative capacity and flow dilution for water quality protection in rivers

Industrial and urban development is a common cause of increased pollution. Pollutants are in many instances discharged untreated to rivers due to lack of adequate treatment facilities and high treatment cost. In many cases, the detriment of pollution discharge to a river exceeds its self-purification capacity, and it may cause irreparable damages to the riverine environment. In this regard, water flow in a river is an effective characteristic behind its assimilative capacity that can be used to decrease pollution damages. Determining a river's assimilation capacity and the flow necessary for dilution of pollutants are important tasks. In this paper, pollution damage to a riverine environment is a function of the pollutant's concentration and the contact duration with river water. Pollutant transport in a river is simulated based on mathematical equations of pollutant advection-dispersion. The optimum values of a river's assimilation capacity and the dilution flow required in a river to mitigate pollution are determined using a nonlinear programming (NLP) method and the nondominated sorting genetic algorithms II (NSGA-II). The optimum assimilation capacity of a river was calculated in an application example for different reservoir releases. The results show that the magnitude of river flow can improve the total riverine assimilation capacity by up to 80%. Optimal Pareto boundaries were obtained for pollutant concentration and the duration of pollutant contact by means of river flow adjustment

Investigating the Relationship between the Structure of Educational Program and Research Outputs in Top Iranian and international Architectural Schools

Academic educational programs such as architectural programs are all influenced by the quality of education and Premier academic staff. They also consist of theoretical, practical and experimental units. One of the criteria for evaluating such international educational programs is the rate of their research outputs in an international ranking called QS. The lack of knowledge about the relationship between the structure of educational programs and the rate of their research outputs in an international scale causes the inconsistency between educational programs and research outputs. This matter consequently leads to a lower international ranking of universities. Thus, the current article aimed at addressing this issue for the first time. To collect data, the thirteen and three top international and Iranian architectural faculties with higher impact factors in the global rankings were selected. Then, the meaningful relationship between the research outputs and their educational systems upstream and downstream levels, including the relationship between the quality of education, educational programs, faculty members and allotted hours to theoretical, practical and experimental units and the research outputs were investigated. The results revealed that there is no relationship between having top academic staff and allotted hours to theoretical, practical and experimental units and the research outputs in all top international faculties. In addition, the results showed that there is no relationship between the hours allotted to research units and the research outputs of top three Iranian architectural faculties

Nutritional value of freshwater mesozooplankton assemblages from Hanna Dam Lake, Iran, during a one-year study

Nutritional value of freshwater mesozooplankton, fatty acid (FA) and amino acid (AA) compositions were determined in the middle of each season for a one-year period from May 2009 to February 2010 in Hanna Dam Lake, Isfahan, Iran. FA and AA composition significantly (P<0.05) varied in relation to the seasonal changes of water quality, phytoplankton and zooplankton community. The content of saturated fatty acids (SAFA), mono unsaturated fatty acids (MUFA) and polyunsaturated fatty acids (PUFA) ranged from 22.4-29.0%, 30.9-40.4%, 11.8-20.9% of dry weight (DW), respectively. The major SAFA were 16:0 (13.7-17.0 % DW) and 18:0 (4.9-7.0 % DW), whereas contents of MUFA were mainly 18:1n-9 (13.8-16.2 % DW), 16:1n-7 (6.9-13.6% DW), and 18:1n-7 (5.7-10.6% DW). The major PUFA were 18:2n-6 (2.6-11.7 % DW), 18:3n-3 (2.4-3.1% DW), 20:5n-3 (3.9-4.8% DW), 22:6n-3 (0.73-0.99% DW), and 20:4n-6 (0.56-0.73% DW). As for the ratios of n-3:n-6, the values were 0.70:1, 2.54:1, 2.10:1, and 1.73:1 in spring, summer, autumn and winter respectively. The mean essential amino acid (EAA) and non-essential amino acid (NEAA) were 28.7 and 71.3 %; 31.0 and 69.0 %; 31.63 and 68.4 %; 34.5 and 67.0 % of total amino acid in spring, summer, autumn and winter, respectively. The amount of tyrosin, isolucine, lucine, arginine, cysteine, aspartic acid, glycine and proline were higher in mesozooplankton population at summer and autumn compared to winter and spring

Cross-species meta-analysis of transcriptomic data in combination with supervised machine learning models identifies the common gene signature of lactation process

Lactation, a physiologically complex process, takes place in mammary gland after parturition. The expression profile of the effective genes in lactation has not comprehensively been elucidated. Herein, meta-analysis, using publicly available microarray data, was conducted identify the differentially expressed genes (DEGs) between pre- and post-peak milk production. Three microarray datasets of Rat, Bos Taurus, and Tammar wallaby were used. Samples related to pre-peak (n = 85) and post-peak (n = 24) milk production were selected. Meta-analysis revealed 31 DEGs across the studied species. Interestingly, 10 genes, including MRPS18B, SF1, UQCRC1, NUCB1, RNF126, ADSL, TNNC1, FIS1, HES5 and THTPA, were not detected in original studies that highlights meta-analysis power in biosignature discovery. Common target and regulator analysis highlighted the high connectivity of CTNNB1, CDD4 and LPL as gene network hubs. As data originally came from three different species, to check the effects of heterogeneous data sources on DEGs, 10 attribute weighting (machine learning) algorithms were applied. Attribute weighting results showed that the type of organism had no or little effect on the selected gene list. Systems biology analysis suggested that these DEGs affect the milk production by improving the immune system performance and mammary cell growth. This is the first study employing both meta-analysis and machine learning approaches for comparative analysis of gene expression pattern of mammary glands in two important time points of lactation process. The finding may pave the way to use of publically available to elucidate the underlying molecular mechanisms of physiologically complex traits such as lactation in mammals.Mohammad Farhadian, Seyed A. Rafat, Karim Hasanpur, Mansour Ebrahimi and Esmaeil Ebrahimi

Investigating the effect of vocational education and training on rural women’s empowerment

peer reviewedThis research is an attempt to identify the most important dimensions of vocational education and training (VET) on empowering rural women, a topic that has received less attention. The present study is a quantitative, non-experimental, applied, survey research, whose statistical population includes rural women and girls who participated in VET classes. The research tool was a researcher-designed questionnaire. The reliability and validity of the research tool using a pilot test and calculating Cronbach’s alpha, AVE, and CR coefficients were shown to indicate the high capability of the research tool to collect data. The results showed that among the four dimensions of VET, the role of content and educator was more than other dimensions and these dimensions of training had improved the economic empowerment of rural women, which was often at the lowest level. The conceptual framework presented can be used as a guide to achieving sustainable development goals of the millennium; and should be considered at the national and international levels. The paper makes an impact on the growing body of knowledge by emphasizing on more important dimensions of education; which can be effective for the empowerment of women, especially in the economic dimension. In the existing studies on empowering rural women, none of them examined the effect of all different components of education on women’s overall empowerment, which are among the innovations of the present study and should be considered in future planning

Insights into the molecular interaction between sucrose and α-chymotrypsin

© 2018 Elsevier B.V. One of the most important purposes of enzyme engineering is to increase the thermal and kinetic stability of enzymes, which is an important factor for using enzymes in industry. The purpose of the present study is to achieve a higher thermal stability of α-chymotrypsin (α-Chy) by modification of the solvent environment. The influence of sucrose was investigated using thermal denaturation analysis, fluorescence spectroscopy, circular dichroism, molecular docking and molecular dynamics (MD) simulations. The results point to the effect of sucrose in enhancing the α-Chy stability. Fluorescence spectroscopy revealed one binding site that is dominated by static quenching. Molecular docking and MD simulation results indicate that hydrogen bonding and van der Waals forces play a major role in stabilizing the complex. Tm of this complex was enhanced due to the higher H-bond formation and the lower surface hydrophobicity after sucrose modification. The results show the ability of sucrose in protecting the native structural conformation of α-Chy. Sucrose was preferentially excluded from the surface of α-Chy which is explained by the higher tendency of water toward favorable interactions with the functional groups of α-Chy than with sucrose

An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources

A unique maternal and placental galectin signature upon SARS-CoV-2 infection suggests galectin-1 as a key alarmin at the maternal–fetal interface

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic imposed a risk of infection and disease in pregnant women and neonates. Successful pregnancy requires a fine-tuned regulation of the maternal immune system to accommodate the growing fetus and to protect the mother from infection. Galectins, a family of β-galactoside–binding proteins, modulate immune and inflammatory processes and have been recognized as critical factors in reproductive orchestration, including maternal immune adaptation in pregnancy. Pregnancy-specific glycoprotein 1 (PSG1) is a recently identified gal-1 ligand at the maternal–fetal interface, which may facilitate a successful pregnancy. Several studies suggest that galectins are involved in the immune response in SARS-CoV-2–infected patients. However, the galectins and PSG1 signature upon SARS-CoV-2 infection and vaccination during pregnancy remain unclear. In the present study, we examined the maternal circulating levels of galectins (gal-1, gal-3, gal-7, and gal-9) and PSG1 in pregnant women infected with SARS-CoV-2 before vaccination or uninfected women who were vaccinated against SARS-CoV-2 and correlated their expression with different pregnancy parameters. SARS-CoV-2 infection or vaccination during pregnancy provoked an increase in maternal gal-1 circulating levels. On the other hand, levels of PSG1 were only augmented upon SARS-CoV-2 infection. A healthy pregnancy is associated with a positive correlation between gal-1 concentrations and gal-3 or gal-9; however, no correlation was observed between these lectins during SARS-CoV-2 infection. Transcriptome analysis of the placenta showed that gal-1, gal-3, and several PSG and glycoenzymes responsible for the synthesis of gal-1-binding glycotopes (such as linkage-specific N-acetyl-glucosaminyltransferases (MGATs)) are upregulated in pregnant women infected with SARS-CoV-2. Collectively, our findings identify a dynamically regulated “galectin-specific signature” that accompanies the SARS-CoV-2 infection and vaccination in pregnancy, and they highlight a potentially significant role for gal-1 as a key pregnancy protective alarmin during virus infection