Association of Zinc, Copper and Magnesium with bone mineral density in Iranian postmenopausal women - a case control study

Background: The risk of inadequate nutrition such as trace elements and vitamin deficiencies is considerable in postmenopausal women. The aim of this study was to compare trace elements (Zinc, Copper and Magnesium) concentration in nail, urine and serum among osteoporotic postmenopausal women with control group in Iran.Methods: Forty eight postmenopausal women aged 36-60 years, were recruited, consisting 30 osteoporotic patients and 18 healthy controls. Blood, nail and urine concentration of Zinc (Zn), copper (Cu) and magnesium (Mg) were determined using Inductively Coupled Plasma -Atomic Emission Spectrometry (ICP-AES) method. Their Bone Mineral Density was measured by Dual X-ray Absorption (DEXA) method.Results: The urine level of trace elements had significant difference between osteoporotic groups and controls (p < 0.001). Moreover Mg level significantly differed in serum between two groups (p < 0.04). There was no statistically significant difference in trace minerals in nail beyond groups.Conclusion: Our findings indicate that Urine Zn level could be considerable an appropriate marker for bone absorption, usage of Zn supplements in postmenopausal women may result a beneficial reduction in osteoporotic risk. © 2014 Razmandeh et al.; licensee BioMed Central Ltd

Molecular detection of prostate specific antigen in patients with prostate cancer or benign prostate hyperplasia the first investigation from Iran

Prostate cancer is the second common form of cancer in men. Detection of circulating Prostate Specific Antigen (PSA) transcripts has effectively been used for early diagnosis of prostate cancer cells. This investigation employed a reverse transcriptase polymerase chain reaction (RT-PCR) technique to distinguish the patients with either localized or metastatic prostate cancer (CaP) vs. Benign Prostate Hyperplasia (BPH) and control subjects, as compared with clinical and pathological records. With reservation of ethical issues, blood samples were collected from 60 cases. Based on pathological and clinical findings, 25 patients (20 with localized cancer, 5 with metastatic), 22 with BPH, and 13 healthy (including 3 females) subjects as negative controls, were selected from Shariati, Mehrad, Sina,, Khatam and Atie Hospitals in Tehran, Iran. RT-PCR for a 260 bp PSA transcript was then performed. Clinical and pathological records were used for the assessment and comparison of PSA RT-PCR results. None of the control subjects and BPH (with 7 exceptions) were found positive by RT-PCR (Relative specificity= 72.7). In patients with prostate cancer, 21 out of 25 were found PSA positive (Relative sensitivity= 83.4) and the remaining 3 have been shown to be PSA negative (Positive predictive value= 83.4). All of 5 metastatic patients (100) revealed PSA positive results. Our data reflects the clinical relevance and significance of RT-PCR results as assessed with clinical and pathological examinations. PSA RT-PCR might be used as a powerful means for diagnosis, even when either pathological or clinical findings are negative, and could be employed for further molecular epidemiology surveys

Targeting Acanthamoeba proteins interaction with flavonoids of Propolis extract by in vitro and in silico studies for promising therapeutic effects

Background: Propolis is a natural resinous mixture produced by bees. It provides beneficial effects on human health in the treatment/management of many diseases. The present study was performed to demonstrate the anti-Acanthamoeba activity of ethanolic extracts of Propolis samples from Iran. The interactions of the compounds and essential proteins of Acanthamoeba were also visualized through docking simulation. Methods: The minimal inhibitory concentrations (MICs) of Propolis extract against Acanthamoeba trophozoites and cysts was determined in vitro. In addition, two-fold dilutions of each of agents were tested for encystment, excystment and adhesion inhibitions. Three major compounds of Propolis extract such as chrysin, tectochrysin and pinocembrin have been selected in molecular docking approach to predict the compounds that might be responsible for encystment, excystment and adhesion inhibitions of A. castellanii. Furthermore, to confirm the docking results, molecular dynamics (MD) simulations were also carried out for the most promising two ligand-pocket complexes from docking studies. Results: The minimal inhibitory concentrations (MICs) 62.5 and 125 µg/mL of the most active Propolis extract were assessed in trophozoites stage of Acanthamoeba castellanii ATCC30010 and ATCC50739, respectively. At concentrations lower than their MICs values (1/16 MIC), Propolis extract revealed inhibition of encystation. However, at 1/2 MIC, it showed a potential inhibition of excystation and anti-adhesion. The molecular docking and dynamic simulation revealed the potential capability of Pinocembrin to form hydrogen bonds with A. castellanii Sir2 family protein (AcSir2), an encystation protein of high relevance for this process in Acanthamoeba. Conclusions: The results provided a candidate for the development of therapeutic drugs against Acanthamoeba infection. In vivo experiments and clinical trials are necessary to support this claim

Prioritization of Erosion Prone Sub-Watersheds using MCDM Methods in Roudzard Watershed, Khuzestan Province

Soil erosion has been one of the most important problems of watersheds in the world and is considered one of the main obstacles to achieving sustainable development in agriculture and natural resources. Identifying and prioritizing regions sensitive to soil erosion is essential for water and soil conservation and natural resource management in watersheds. The present research was performed in 2021 year to prioritize the soil erosion susceptibility in 12 sub-watersheds of the Roudzard watershed in Khouzestan province using morphometric analysis and multiple criteria decision-making (MCDM) methods. In this regard, 11 morphometric parameters including shape parameters such as compactness constant (Cc), circularity ratio (Rc), form factor (Rf), elongation ratio (Re), linear parameters such as drainage density (Dd), stream frequency (Fs), drainage texture (Dt), bifurcation ratio (Rb), Basin length (L), Length of overland flow (Lg), and topographic parameter including Ruggedness number (Rn) were extracted and their relative weights were calculated using Analytic Hierarchy Process (AHP). The prioritization sub-watershed to soil erosion was performed using TOPSIS, VIKOR, and SAW methods, and the results were combined using rank mean, Copeland, and Borda methods. The final prioritization was compared with the amount of specific erosion in the MPSIAC model by determining Spearman's correlation coefficient. The result of the evaluation of morphometric parameters by using the AHP model showed that drainage density (0.161), drainage texture (0.158), and stream frequency (0.146) had the greatest effect on the erodability of the sub-watersheds. In contrast, the form factor (0.049), Elongation Ratio (0.036), and shape factor (0.026) had the least effects on erodability of the study area. In this research, the Spearman correlation coefficient between the final result of prioritizing the sub-watershed and the MPSIAC model was obtained as 0.8 in p-value<0.01. The results of prioritization of the sub-watersheds in terms of their sensitivity to soil erosion showed that sub-watersheds 11, 12, and 10 with an area of 191.83 km2 are categorized as very sensitive to soil erosion due to high value of linear parameters, low value of shape parameters, sensitive geology formation, and poor vegetation cover and located in rank 1 to 3, respectively. According to the results sub-watersheds 11, 12, and 10 have the highest amount of specific erosion equal to 16.03, 12.48, and 11.6 tons per hectare per year, respectively. Therefore, these sub-watersheds are a priority for watershed management operations. The results of the present study showed that MCDM methods and morphometric analysis are suitable tools for identifying areas sensitive to soil erosion and using the combined methods of the results and it is possible to take advantage of each of the different multi-criteria decision-making methods

Prediction of superoxide quenching activity of fullerene (C 60) derivatives by genetic algorithm-support vector machine

In this study, the quantitative structure-activity relationship (QSAR) models for the superoxide quenching activity of fullerene derivatives were developed. The dataset was divided into a training set and test set, based on hierarchical clustering technique. Three variables were selected by the genetic algorithm (GA) variable subset selection procedure. Multiple linear regressions (MLR) and support vector machine (SVM) were used as linear and nonlinear methods. Both the linear and nonlinear models could give very satisfactory prediction results: The square correlation coefficient of R2 for the training and test sets were 0.826 and 0.981, by MLR and 0.957 and 0.965, by SVM methods, respectively. The prediction result of the SVM model was better than that obtained by MLR method, which proved SVM was a useful tool in the prediction of the superoxide quenching activity of fullerene derivatives. The results suggested that the minimum atomic partial charge, minimum valence of hydrogen atom, and minimum atomic state energy of oxygen atom, are the main independent factors contributing to the superoxide quenching activity of fullerene derivatives. © 2015 Taylor and Francis Group, LLC

A review of machine learning methods to predict the solubility of overexpressed recombinant proteins in Escherichia coli

BACKGROUND: Over the last 20 years in biotechnology, the production of recombinant proteins has been a crucial bioprocess in both biopharmaceutical and research arena in terms of human health, scientific impact and economic volume. Although logical strategies of genetic engineering have been established, protein overexpression is still an art. In particular, heterologous expression is often hindered by low level of production and frequent fail due to opaque reasons. The problem is accentuated because there is no generic solution available to enhance heterologous overexpression. For a given protein, the extent of its solubility can indicate the quality of its function. Over 30% of synthesized proteins are not soluble. In certain experimental circumstances, including temperature, expression host, etc., protein solubility is a feature eventually defined by its sequence. Until now, numerous methods based on machine learning are proposed to predict the solubility of protein merely from its amino acid sequence. In spite of the 20 years of research on the matter, no comprehensive review is available on the published methods. RESULTS: This paper presents an extensive review of the existing models to predict protein solubility in Escherichia coli recombinant protein overexpression system. The models are investigated and compared regarding the datasets used, features, feature selection methods, machine learning techniques and accuracy of prediction. A discussion on the models is provided at the end. CONCLUSIONS: This study aims to investigate extensively the machine learning based methods to predict recombinant protein solubility, so as to offer a general as well as a detailed understanding for researches in the field. Some of the models present acceptable prediction performances and convenient user interfaces. These models can be considered as valuable tools to predict recombinant protein overexpression results before performing real laboratory experiments, thus saving labour, time and cost

QSAR study of mGlu5 inhibitors by genetic algorithm-multiple linear regressions

In this study, the quantitative structure-Activity relationship (QSAR) model for some pyrazole/imidazole amide derivatives as mGlu5 inhibitors was developed. The data set was split into the training and test subsets, randomly. The most relevant variables were selected using the genetic algorithm (GA) variable selection method. Multiple linear regression (MLR) method was used as a linear model to predict the activity of mGlu5 inhibitors based on compounds in training set. The external set of nine compounds selected out of 47 compounds, and used to evaluate the predictive ability of QSAR model. The built model could give high statistical quantities (R train 2 = 0.837, Q 2 = 0.759, R test 2 = 0.919) in which proved that the GA-MLR model was a useful tool to predict the inhibitory activity of pyrazole/imidazole amide derivatives. The results suggested that the atomic masses, atomic van der Waals volumes, atomic electronegativities, and the number of imines (aromatic) are the most important independent factors that contribute to the mGlu5 inhibition activity of pyrazole/imidazole amides derivatives. © 2013 Springer Science+Business Media New York

Mapping of Soil Saturated Hydraulic Conductivity in Navroud-Assalem Watershed in Guilan Province

Introduction: With increasing awareness of human beings towards the environment, researchers pay more attention to process and redistribution of water flow and solute transport in the soil and groundwater. Moreover, determination of soil hydraulic conductivity is necessary to determine the runoff from basins. Water movement within the unsaturated zone is often described by the formulae proposed by Richards. To solve this equation, initial and boundary conditions of the hydraulic conductivity and the soil water pressure should be determined as functions of soil water content. Beerkan method was developed to identify retention and hydraulic conductivity curves. In this method, van Gunechten with Burdine condition and Brooks and Corey equations were used to describe water retention and hydraulic conductivity curves. Recognition of the spatial pattern of studied parameter using semivariogram and then preparing zoning map with interpolation methods such as IDW and kriging can help us in relevant watershed management. The aim of this study was to spatial analyze of saturated hydraulic conductivity from 50 infiltration tests at watershed scale using Beerkan method and then preparing zoning map for the Navroud watershed. Materials and Methods: Navroud-Assalem watershed with an area of about 307 km2 is located in the west part of Guilan province, within the city of Talesh. Of the total watershed area of Navroud, about 41 km2 is plains and the rest of it is about 266 km2, corresponding to the mountainous area. The study area includes an area with a height above 130 m. In order to complete the database of the studied watershed the present study was designed to assess soil saturated hydraulic conductivity. In this study, a 2×2 km network was designed in Navroud watershed with a surface area of 307 km2, and then infiltration tests were carried out in each node using single ring of Beerkan. Beerkan method derives shape parameters from particle-size distribution and normalization parameters from infiltration test with a near zero pressure head. Evaluation of spatial variation was done using GS+ and zoning map was prepared with ArcGIS software. Statistical evaluation of recorded data was done using SPSS software package. Results and Discussion: Results showed that the soil bulk density was of 1.07 gr cm-3 in average. Furthermore, the results showed that the average of saturated hydraulic conductivity (Ks) in the watershed was of 3.96 cm hr-1 with a coefficient of variation of 151%. The watershed Ks is classified in the moderate class. Regarding the high value of Ks variation coefficient, using geostatistics is necessary to analyze Ks spatial variation. The results indicate the absence of the anisotropy. Using GS+ software, exponential model was fit on the empirical variation (r2=0.953 and RSS=0.0057 cm hr-1). The effective range was of 2280 m. The difference between the amounts reported by other studies and this study was because of the effect of the difference in the study area (307 km, in this study), scale (the field or watershed) and the distance between measured points. Two usual methods of interpolation including inverse distance weighting and ordinal kriging were verified. The results showed that ordinal kriging performed better than inverse distance weighting method (RMSEs for ordinal kriging and inverse distance weighting were 8.97 and 9.75, respectively). Zoning map of Ks was prepared according to the results of GS+ software using ArcGIS software. The correlation coefficients between Ks and sand, silt and clay percents were -0.04, 0.01 and 0.07, which demonstrate a weak effect of soil texture on the Ks as compared with soil structure. The correlation coefficient of the soil bulk density with Ks was of -0.45 which demonstrate a stronger effect as compared with the soil texture. Conclusions: The results of this study can be used to proper management of watersheds. One of the main information needed to manage a watershed is Ks. Determining the spatial variability of soil saturated hydraulic conductivity at watershed scale in spite of its difficulty is one of the main prerequisite parameters to provide detailed maps of a watershed. The aim of this study was to analyze the spatial variability of Ks in Navroud-Assalem watershed, Guilan province. After analyzing spatial data, using ordinary kriging interpolation method, zoning map of Ks was prepared. This map can be used to find the optimal management of watershed, such as determining the amount of basin runoff and groundwater recharge