55 research outputs found
Antibiotic resistance pattern of staphylococcus strains isolated from orange and apple juices in Shahre-Kord, Iran
Get PDFObjective: One of the main routes of transmission of antibiotic resistance in bacteria is through food production. The antibiotics that are used to control diseases are transferred to human through food stuff such as meat, milk, fruit, fruit juices, water and lead to the spread of antibiotic resistant bacteria to human populations. The aim of this study was to determine the pattern of antibiotic resistance of staphylococcus strains isolated from orange and apple juices in Shahre-Kord, Iran. Methodology: This descriptive-sectional study was carried out on a total of 32 bacterial isolates of staphylococci (4 Staphylococcus aureus strains and 28 Staphylococcus epidermidis strains) isolated from 360 fruit juice samples tested in Shahre-kord. Antibiotic susceptibility test was performed using disc diffusion method and data were analyzed using fishers Z test. Results: Staphylococcus aureus showed 25 resistance to five antibiotics which included tetracycline, co-trimoxazole, amoxicillin, erythromycin and methicillin. Staphylococcus epidermidis was the most resistant bacteria to erythromycin. Twenty five percent of the Staphylococcus aureus strains and 64.28 of the Staphylococcus epidermidis strains were resistant to two or more than two of the antibiotics used in this study. Conclusions: The results showed that the vast majority of the bacterial isolates were resistant to one or more than one of the antibiotics studied. It is possible for bacterial resistance to result from food products like fruit juices. Therefore it is necessary to restrict the use of antibiotics and control the production, transportation of fruit juices
Estimation of spatial and seasonal variability of soil erosion in a cold arid river basin in hindu kush mountainous region using remote sensing
Get PDFAn approach is proposed in the present study to estimate the soil erosion in data-scarce Kokcha subbasin in Afghanistan. The Revised Universal Soil Loss Equation (RUSLE) model is used to estimate soil erosion. The satellite-based data are used to obtain the RUSLE factors. The results show that the slight (71.34%) and moderate (25.46%) erosion are dominated in the basin. In contrast, the high erosion (0.01%) is insignificant in the study area. The highest amount of erosion is observed in Rangeland (52.2%) followed by rainfed agriculture (15.1%) and barren land (9.8%) while a little or no erosion is found in areas with fruit trees, forest and shrubs, and irrigated agriculture land. The highest soil erosion was observed in summer (June–August) due to snow melting from high mountains. The spatial distribution of soil erosion revealed higher risk in foothills and degraded lands. It is expected that the methodology presented in this study for estimation of spatial and seasonal variability soil erosion in a remote mountainous river basin can be replicated in other similar regions for management of soil, agriculture, and water resources
Direct foam writing in microgravity
Get PDFHerein we report 2D printing in microgravity of aqueous-based foams containing metal oxide nanoparticles. Such hierarchical foams have potential space applications, for example for in situ habitat repair work, or for UV shielding. Foam line patterns of a TiO2-containing foam have been printed onto glass substrates via Direct Foam Writing (DFW) under microgravity conditions through a parabolic aircraft flight. Initial characterization of the foam properties (printed foam line width, bubble size, etc.) are presented. It has been found that gravity plays a significant role in the process of direct foam writing. The foam spread less over the substrate when deposited in microgravity as compared to Earth gravity. This had a direct impact on the cross-sectional area and surface roughness of the printed lines. Additionally, the contact angle of deionized water on a film exposed to microgravity was higher than that of a film not exposed to microgravity, due to the increased surface roughness of films exposed to microgravity
The Effects of Probiotic Honey Consumption on Metabolic Status in Patients with Diabetic Nephropathy: a Randomized, Double-Blind, Controlled Trial
Get PDFTo the best of our knowledge, this study is the first evaluating the effects of probiotic honey intake on glycemic control, lipid profiles, biomarkers of inflammation, and oxidative stress in patients with diabetic nephropathy (DN). This investigation was conducted to evaluate the effects of probiotic honey intake on metabolic status in patients with DN. This randomized, double-blind, controlled clinical trial was performed among 60 patients with DN. Patients were randomly allocated into two groups to receive either 25 g/day probiotic honey containing a viable and heat-resistant probiotic Bacillus coagulans T11 (IBRC-M10791) (10 8  CFU/g) or 25 g/day control honey (n = 30 each group) for 12 weeks. Fasting blood samples were taken at baseline and 12 weeks after supplementation to quantify glycemic status, lipid concentrations, biomarkers of inflammation, and oxidative stress. After 12 weeks of intervention, patients who received probiotic honey compared with the control honey had significantly decreased serum insulin levels (� 1.2 ± 1.8 vs. � 0.1 ± 1.3 μIU/mL, P = 0.004) and homeostasis model of assessment-estimated insulin resistance (� 0.5 ± 0.6 vs. 0.003 ± 0.4, P = 0.002) and significantly improved quantitative insulin sensitivity check index (+ 0.005 ± 0.009 vs. � 0.0007 ± 0.005, P = 0.004). Additionally, compared with the control honey, probiotic honey intake has resulted in a significant reduction in total-/HDL-cholesterol (� 0.2 ± 0.5 vs. + 0.1 ± 0.1, P = 0.04). Probiotic honey intake significantly reduced serum high-sensitivity C-reactive protein (hs-CRP) (� 1.9 ± 2.4 vs. � 0.2 ± 2.7 mg/L, P = 0.01) and plasma malondialdehyde (MDA) levels (� 0.1 ± 0.6 vs. + 0.6 ± 1.0 μmol/L, P = 0.002) compared with the control honey. Probiotic honey intake had no significant effects on other metabolic profiles compared with the control honey. Overall, findings from the current study demonstrated that probiotic honey consumption for 12 weeks among DN patients had beneficial effects on insulin metabolism, total-/HDL-cholesterol, serum hs-CRP, and plasma MDA levels, but did not affect other metabolic profiles. http://www.irct.ir: IRCT201705035623N115. © 2018, Springer Science+Business Media, LLC, part of Springer Nature
Natural environments, ancestral diets, and microbial ecology: is there a modern “paleo-deficit disorder”? Part II
Get PDFA novel framework for selecting general circulation models based on the spatial patterns of climate
No full textGeneral circulation models (GCMs), used for climate change projections, should be able to simulate both the temporal variability and spatial patterns of the observed climate. However, the selection of GCMs in most previous studies was either based on temporal variability or mean spatial pattern of past climate. In this study, a framework is proposed for the selection of GCMs based on their ability to reproduce the spatial patterns for different climate variables. The Kling-Gupta efficiency (KGE) was used to assess GCMs ability to simulate the annual spatial patterns of maximum and minimum temperatures (Tmx and Tmn, respectively) and rainfall depth. The mean and standard deviation of KGEs were used as performance indicators to present the GCMs' overall skill. Finally, the global performance indicator was used as a multi-criteria decision-making approach to integrate the results of different climate variables and seasons in order to rank the GCMs. Egypt was considered as a case study. The results revealed the better performance, in order, of the MRI-CGCM3, followed by FGOALS-g2, GFDL-ESM2G, GFDL-CM3 and lastly MPI-ESM-MR over Egypt. The final set of GCMs showed a similar spatial pattern for the projected change in temperature over Egypt. For different scenarios, Tmx was projected to increase in the range of 1.63–4.2°C while the increase in Tmn ranged between 1.28 and 4.43°C. A projected increase in temperature in winter is likely greater than in summer. The selected models also projected a 62% decrease in rainfall depth over the northern coastline where rain is currently most abundant while an increase in the dry southern zones. The rise in temperature and decrease in rainfall depth could have severe implications for a country with dwindling water resources
Use of Tarragon (Artemisia dracunculus) essential oil as a natural preservative in beef burger
Get PDFNowdays, adding natural food preservatives is one of the methods for increasing shelf-life. The aim of this study was evaluation of antioxidant activity and antibacterial effects Tarragon (Artemisia dracunculus) essential oil (TEO) in beef burger product. In this experimental study, essential oil of the Tarragon was isolated by hydrodistillation. Then, TEO was analyzed by gas chromatography-flame ionization detector (GC-FID) and gas chromatography/ mass spectrometry (GC-MS). The effect of different concentrations of Tarragon essential oil (0.00, 0.062, 0.125, and 0.25) in 4° ±1°C temperature and storage time up to 12 days was evaluated on lipid oxidation, anti Staphylococcus aureus activity and organoleptic effects in beef burger. The monoterpenes hydrocarbons constitute the major fraction of the TEO (95.91) and the sesquiterpene hydrocarbons were the minor fraction (0.46). No significant differences were observed after adding of different concentrations of essential oil on lipid oxidation value in raw beef burger (P>0.05). The Tarragon essential oil 0.25 in storage temperature (4±1°C) decreased growth rate of S. aureus in beef burger (p<0.05). Also overall acceptance rate in beef burger containing Tarragon essential oil 0.125 created a better sense in product (p<0.05). Therefore, this essential oil might be used as an antibacterial agent and flavor enhancer in meat products such as beef burger
A novel framework for selecting general circulation models based on the spatial patterns of climate
No full textEXTRACTION OF PROBABILITY DISTRIBUTION OF STABILITY SAFETY FACTOR USING LHS AND GLUE METHODS (CASE STUDY: PARSIAN DAM
No full textStability analysis is an important issue during designing and operation of earthfill dam. Importance of this issue is related to failure possibility and other risks for people who are living in downstream. The various sources of uncertainties exist in stability analysis of earthfill dam body, such as random parameters (Parameter Uncertainty) and randomness characteristic of stability model (Model Uncertainty). Therefore, the estimated stability safety factor is more accurate by considering the mentioned sources of uncertainty. There are many new methods of slope stability analysis that use statistical approach to the consideration and quantification of uncertainties. In this study, LHS and GLUE were used as sampling methods for extraction probability distribution of
stability safety factor. In this respect, stability safety factor of Parsian rockfill dam was estimated by considering the uncertainty of random variables in semi-static analysis with full reservoir. In addition, ``limit equilibrium general'' theory and ``method of components'' were used for estimating stability analysis of Parsian dam. In this respect, the randomness characteristic of the resistance parameters of different dam sections was quantified by considering the different probability distributions. The obtain result showed that, the uncertainty and variability of horizontal drain and filter geomechanical parameters has no main effect on safety factor variability. In addition, the comparison between derived probability distribution of safety factor using LHS and GLUE approach shows that, the LHS method is more conservative compared to GLUE approach in evaluating dam failure. The reliability indexes (\beta) of GLUE and LHS were computed. The magnitudes of (\beta) for GLUE and LHS are 1.36 and 0.93, respectively. So, according to obtain result, the estimated stability safety factor by GLUE approach is more reliable compared to LHS method. In addition, the average of safety factor in both LHS and GLUE methods is equal to 1.12 that is very close to allowable stability safety factor of Parsian dam
Satellite-based prediction of surface dust mass concentration in southeastern Iran using an intelligent approach
No full textThe southeastern section of Iran, especially the province of Khuzestan, experience severe air pollution levels, such as high values of surface dust mass concentration (SDMC). The province lacks accurate and well-placed ground observational stations, therefore the only viable approach for evaluating SDMC is via remote sensing. In this study, meteorological, hydrological and geological data on 11 input variables from Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2), global precipitation measurement (GPM) and Global Land Data Assimilation System (GLDAS) for the year 2018 are used for prediction of the SDMC values, also obtained from another MERRA-2 mission. For real-time prediction, Pearson’s correlation coefficient (PCC) analysis shows that wind-related variables—surface wind speed, surface aerodynamic conductance and surface pressure—are those with the highest correlation with SDMC. Using the gradient boosting regression (GBR) algorithm, these three variables can simulate SDMC with good accuracy (R2=0.76,NSE=0.76,N-RMSE=0.48andN-MAE=0.34) . Furthermore, near-future SDMC forecasting down to 8 days prior of SMDC occurrence is also carried out. A sequential forward feature selection of the input variables, based on PCC, is used for four lead times and results show that surface pressure and heat flux govern near-future predictions. With R= 0.46 and N- RMSE= 0.74 , GBR shows good potential for forecasting SDMC 8 days in advance. Real-time and near-future simulation results generally show that robust SDMC prediction can be obtained using exclusively remote sensing data, without ground-based observations
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