فهرست مطالب marzieh mohseni

 The study of Y-chromosomal variations provides valuable insights into male susceptibility in certain diseases like cardiovascular disease (CVD). In this study, we analyzed paternal lineage in different Iranian ethnic groups, not only to identify developing medical etiology, but also to pave the way for gender-specific targeted strategies and personalized medicine in medical genetic research studies.

 The diversity of eleven Iranian ethnic groups was studied using 27 Y-chromosomal short tandem repeat (Y-STR) haplotypes from Y-filer® Plus kit. Analysis of molecular variance (AMOVA) based on pair-wise RST along with multidimensional scaling (MDS) calculation and Network phylogenic analysis was employed to quantify the differences between 503 unrelated individuals from each ethnicity.

 Results from AMOVA calculation confirmed that Gilaks and Azeris showed the largest genetic distance (RST=0.35434); however, Sistanis and Lurs had the smallest considerable genetic distance (RST=0.00483) compared to other ethnicities. Although Azeris had a considerable distance from other ethnicities, they were still close to Turkmens. MDS analysis of ethnic groups gave the indication of lack of similarity between different ethnicities. Besides, network phylogenic analysis demonstrated insignificant clustering between samples.

 The AMOVA analysis results explain that the close distance of Azeris and Turkmens may be the effect of male-dominant expansions across Central Asia that contributed to historical and demographics of populations in the region. Insignificant differences in network analysis could be the consequence of high mutation events that happened in the Y-STR regions over the years. Considering the ethnic group affiliations in medical research, our results provided an understanding and characterization of Iranian male population for future medical and population genetics studies.

This study adopted the Shiono-Knight model (SKM) to estimate the lateral distribution of the depth-averaged velocity within rectangular and trapezoidal compound channels with emergent vegetation in floodplains. To implement the SKM, it was required to estimate the eddy viscosity coefficient, friction coefficient, and secondary flow coefficient. The present study estimated the friction coefficient using the Colebrook–White equation modified by Rameshwaran and Shiono for vegetated beds. An analysis of eddy viscosity models across compound channels indicated that the model was not sensitive to the eddy viscosity coefficient; thus, the eddy viscosity coefficient could be assumed constant across the channel. However, the negligence of the secondary flow in the model would lead to a significant error, and it was required to calibrate the secondary flow coefficient. Thus, this study used a genetic algorithm (GA) to develop equations for the secondary flow coefficient for different sections of the compound channel under two different approaches: (1) the approach of Abril and Knight (2004), who proposed constant values for the main channel and floodplains, and (2) the equations of Devi and Khatua (2017), which related the secondary flow coefficient to the relative depth and width ratio. It was found that the secondary flow coefficient was dependent on the relative depth and width ratio. As a result, the equation optimized based on the Devi-Khatua approach outperformed the Rameshwaran-Shiono technique in estimating the lateral distribution of the velocity, with a 10.2% lower error.

Genetic analysis of non-syndromic hearing loss (NSHL) has been challenged due to marked clinical and genetic heterogeneity. Today, advanced next-generation sequencing (NGS) technologies, such as exome sequencing (ES), have drastically increased the efficacy of gene identification in heterogeneous Mendelian disorders. Here, we present the utility of ES and re-evaluate the phenotypic data for identifying candidate causal variants for previously unexplained progressive moderate to severe NSHL in an extended Iranian family. Using this method, we identified a known heterozygous nonsense variant in exon 26 of the DIAPH1 gene (MIM: 602121), which led to “Deafness, autosomal dominant 1, with or without thrombocytopenia; DFNA1” (MIM: 124900) in this large family in the absence of GJB2 disease-causing variants and also OtoSCOPE-negative results. To the best of our knowledge, this nonsense variant (NM_001079812.3):c.3610C>T (p.Arg1204Ter) is the first report of the DIAPH1 gene variant for autosomal dominant non-syndromic hearing loss (ADNSHL) in Iran.

Groundwater resources are considered as the second largest fresh water resource of earth after glaciers. Water shortage and lack of proper management of groundwater resources result in droughts and consequent severe water crises around the world as well as Iran. Excessive withdrawal of groundwater from the Minab Aquifer caused that the inlet of the aquifer could not cope with the withdrawal and, as a result, the groundwater level was dropped. Prediction of groundwater flow behavior for optimal management of groundwater resources is one of the objectives of hydrological studies. Thus, the present study considered quantitative and qualitative modeling of the Minab aquifer by using GMS 7.1 which has a special importance in water management. Quantitative modeling of groundwater flow was carried out in MODFLOW code for steady state in October 2002 and for unsteady state during the year of 2002-2003. By calibrating the models, the RMSE and MAE values for determining groundwater levels were estimated as 0.268 and 0.25 meters, respectively. The average annual drop of groundwater level in Minab aquifer was estimated as 0.02 m during a year. The qualitative model of groundwater flow was run for a year period to determine TDS value by using MT3DMS code. After Model calibration, the RMSE and MAE values were estimated as 4.345 ppm and 2.357 ppm. It can be concluded that the current trend of groundwater flow will decrease the groundwater level and increase the aquifer pollution level.

Global real-time monitoring of SARS-CoV-2 variants is crucial to controlling the COVID-19 outbreak. The purpose of this study was to set up a Sanger-based platform for massive SARS-CoV-2 variant tracking in laboratories in low-resource settings.

We used nested RT-PCR assay, Sanger sequencing and lineage assignment for 930-bp of the SARS-CoV-2 spike gene, which harbors specific variants of concern (VOCs) mutations. We set up our platform by comparing its results with whole genome sequencing (WGS) data on 137 SARS-CoV-2 positive samples. Then, we applied it on 1028 samples from March-September 2021.

In total, 125 out of 137 samples showed 91.24% concordance in mutation detection. In lineage assignment, 123 out of 137 samples demonstrated 89.78% concordance, 65 of which were assigned as VOCs and showed 100% concordance. Of 1028 samples screened by our in-house method, 78 distinct mutations were detected. The most common mutations were: S:D614G (21.91%), S:P681R (12.19%), S:L452R (12.15%), S:T478K (12.15%), S:N501Y (8.91%), S:A570D (8.89%), S:P681H (8.89%), S:T716I (8.74%), S:L699I (3.50%) and S:S477N (0.28%). Of 1028 samples, 980 were attributed as VOCs, which include the Delta (B.1.617.2) and Alpha (B.1.1.7) variants.

Our proposed in-house Sanger-based assay for SARS-CoV-2 lineage assignment is an accessible strategy in countries with poor infrastructure facilities. It can be applied in the rapid tracking of SARS-CoV-2 VOCs in the SARS-CoV-2 pandemic.

Autosomal dominant polycystic kidney disease (ADPKD), one of the common inherited disorders in humans, is characterized by the development and enlargement of renal cysts, often leading to end-stage renal disease (ESRD). In this study, Iranian ADPKD families were subjected to high-throughput DNA sequencing to find potential causative variants facilitating the way toward risk assessment and targeted therapy.

Our protocol was based on the targeted next generation sequencing (NGS) panel previously developed in our center comprising 12 genes involved in PKD. This panel has been applied to investigate the genetic causes of 32 patients with a clinical suspicion of ADPKD.

We identified a total of 31 variants for 32 individuals, two of which were each detected in two individuals. Twenty-seven out of 31 detected variants were interpreted as pathogenic/likely pathogenic and the remaining 4 of uncertain significance with a molecular diagnostic success rate of 87.5%. Among these variants, 25 PKD1/2 pathogenic/likely pathogenic variants were detected in 32 index patients (78.1%), and variants of uncertain significance in four individuals (12.5% in PKD1/2). The majority of variants was identified in PKD1 (74.2%). Autosomal recessive PKD was identified in one patient, indicating the similarities between recessive and dominant PKD. In concordance with earlier studies, this biallelic PKD1 variant, p.Arg3277Cys, leads to rapidly progressive and severe disease with very early-onset ADPKD.

Our findings suggest that targeted gene panel sequencing is expected to be the method of choice to improve diagnostic and prognostic accuracy in PKD patients with heterogeneity in genetic background.

Complete SARS-CoV-2 genome sequencing in the early phase of the outbreak in Iran showed two independent viral entries. Subsequently, as part of a genome surveillance project, we aimed to characterize the genetic diversity of SARS-CoV-2 in Iran over one year after emerging.

We provided 319 SARS-CoV-2 whole-genome sequences used to monitor circulating lineages in March 2020-May 2021 time interval.

The temporal dynamics of major SARS-CoV-2 clades/lineages circulating in Iran is comparable to the global perspective and represent the 19A clade (B.4) dominating the first disease wave, followed by 20A (B.1.36), 20B (B.1.1.413), 20I (B.1.1.7), leading the second, third and fourth waves, respectively. We observed a mixture of circulating B.1.36, B.1.1.413, B.1.1.7 lineages in winter 2021, paralleled in a fading manner for B.1.36/B.1.1.413 and a growing rise for B.1.1.7, prompting the fourth outbreak. Entry of the Delta variant, leading to the fifth disease wave in summer 2021, was detected in April 2021. This study highlights three lineages as hallmarks of the SARS-CoV-2 outbreak in Iran; B4, dominating early periods of the epidemic, B.1.1.413 (B.1.1 with the combination of [D138Y-S477N-D614G] spike mutations) as a characterizing lineage in Iran, and the co-occurrence of [I100T-L699I] spike mutations in half of B.1.1.7 sequences mediating the fourth peak. It also designates the renowned combination of G and GR clades’ mutations as the top recurrent mutations.

In brief, we provided a real-time and comprehensive picture of the SARS-CoV-2 genetic diversity in Iran and shed light on the SARS-CoV-2 transmission and circulation on the regional scale.

The increasing demand of people and students for computer technology and the Internet has caused mental health problems and social communication in them. In this study, the relationship between Internet addiction and general health in students of Qom University of Medical Sciences has been investigated.

This descriptive-correlation study was performed on 321 students living in Qom dormitory of medical sciences through demographic, general health (GHQ) and Internet addiction questionnaires. Data analysis was performed using SPSS software in two parts: descriptive statistics, mean, frequency, frequency percentage and inferential statistics of Pearson correlation coefficient and univariate linear regression.

79.8% of students were regular users and 20.2% of students were addicted to the Internet and no severe Internet addiction was observed. According to the general health questionnaire, 13.1% of students had mild disorder, 66% had moderate disorder and 20.9% had severe disorder. Pearson correlation coefficient between scales and general health in general with Internet addiction showed a significant and positive relationship at a significant level of 0.05. In linear regression analysis, the only variable is the duration of internet connection under the same conditions in terms of other variables that predict the general health score.

There is a significant and positive relationship between public health and Internet addiction. Preventing the complications and dangers of Internet addiction is essential and requires educational, counseling, and behavioral planning among vulnerable students.

Natural rivers are commonly characterized by a main channel for primary flow conveyance and a floodplain to carry extra flow during floods. Floodplains are usually partially or completely covered with vegetation such as shrubs or trees. Vegetation affects the depth of flow, velocity distribution as well as sediment transport(Yang et al.,2007). Predicting the lateral velocity distribution in compound channels is important for determining the stage-discharge curve and supporting the management of fluvial processes in vegetation condition in river(Tong and Knight, 2009). Previous research in the area of vegetated floodplains has primarily focused on the adaptation of theory driven resistance equations. Since the 1990’s, several Lateral Distribution Models (LDM) have been developed for obtaining lateral velocity distribution in compound channels. Among the velocity lateral distribution models, the Shiono and Knight Model (SKM) is more popular with widespread applications(Unal et al, 2010). Three calibrating coefficients need to be estimated for applying the SKM, namely eddy viscosity coefficient (λ), friction factor (f) and secondary flow coefficient (k). Determining these coefficients in natural channels is not always feasible and requires some experiences (Knight et al. 2010). Utilizing soft computing (SC) methods to solve different problems is another progressing concept. One of the newest and most powerful SC methods is gene expression programming (GEP), which is an extension of GP and GA, and was first introduced by Ferreira(2001). The GEP method mitigates the majority of problems of principal SC methods related to the absence of equations for practical engineering by presenting explicit equations. The aim of this study was to use GEP modeling to predict the depth averaged velocity distribution in compound channels with vegetated floodplains. The results of the best GEP model are presented as an equation and compared with the result of SKM model.

In this study, by aid of nearly 508 depth-averaged velocity data reported in a study by Tavakoli(2019) and using gene expression programming (GEP), the depth-averaged velocity in compound channels with vegetated floodplains was modeled. 9 dimensionless input variables including, Relative flow depth 〖(D〗_r), Relative distance (χr), vegetation density (λ), shading factors , Dsa and Dsr, either aligned or randomly arranged, respectively, Dfp (the vegetation diameter over the width of the floodplain), y_n1,y_n2(the distance from the channel centerline to the measurement location in main channel and flooplain) and one output variable (depth averaged velocity) have been used in GEP. 70% of the experimental results are used for the training process and the remaining 30% for testing. After selecting the training set, the GEP learning environment should be defined. The five main steps in GEP training are as follows: First step: selecting fitness function. Second step: determining the function set(F) and terminal set (T) for chromosome generation. Third step: specifying the number of genes and the head length. Fourth step: defining the linking function for linking different sub-ETs. Fifth step: setting the values of different genetic operators, such as inversion, transposition and recombination(Fuladipanah, 2020). The values of these operators and other parameters used in GeneXpro program are presented in Table 2. Various statistical error analyses were performed to verify the reliability of the developed GEP model. An equation was derived from the best GEP model and its results were compared with the analytical method of Shiono and Knight. To obtain analytical solutions by SKM with an accepted accuracy, the drag coefficient, the shading factor, local friction factor, eddy viscosity and secondary flow term need to be determined, these parameters were discussed in the paper. Importance of the predictor variables for GEP models were also presented by using sensitivity analysis.

A number of expressions have been generated to predict depth averaged velocity distribution within a compound channel with vegetated floodplains using gene expression programming (GEP). For an initial attempt, the gene expression programming was run with all data in the non- dimensional form. The best produced formula was as given in Eq. 27. The amount of CC, RMSE, and MAE for GEP at the first scenario during training and testing phases were calculated as (0.919,0.13,0.093) and (0.874,0.156,0.096) respectively. This expression shows high positive correlation, however, this value may be misleading as correlation should only be used as a measure for normally distributed variables. Analysis of the Experimental data showed two distinct normalised distributions, for the lower velocities on the floodplain and the higher velocities on the main channel, respectively(Harris et al.,2003). So the data sets separated in to two data sets and the GeneXpro program was then applied to the two data sets separately, thus giving separate expressions for the two zones. Evaluation of model performance showed that the model presented for main channel, with CC of 0.902 and RMSE of 0.083 outperformed than the model presented for floodplain with CC of 0.843 and RMSE of 0.092. The velocity prediction on the main channel shows good correlation with R2=0.8536, see Fig. 2 but the floodplain results show a degree of scattering with R2=0.78 , this is due, in part, to data collection experimental error and the complexity of the flow around the vegetation. The sensitivity analysis results demonstrate that dimensionless shading factor of vegetation (Dsr), is the most influential parameter with regard to the depth averaged velocity distribution. As it is presented in Fig. 4. Dsr are the most important variable for GEP model, this conclusion is supported by the work of Naot et al. (1996). The results showed that the Shiono and Knight method (SKM) has shown satisfactory results for the prediction of depth-averaged velocity distribution in the lateral direction. The GEP model, with RMSE of 0.15, exhibits superior performance over the SKM model with RMSE of 0.24 for all data.

In this paper, two algorithms namely SKM and GEP have been applied to predict depth averaged velocity distribution in compound channels with vegetated floodplains. The results of these two mentioned algorithms were compared with experimental modeling. The paper highlights the advantages of using intelligent algorithm rather than the traditional approach to predict and extract the complicated and hidden relationship among dependent and independents variables.

Water level determination during a flood is always a challenging task for river engineers. During the flood, river channel becomes compound consisting of the main river channel which carries low flows and floodplains that carry overbank flows.  Flow velocity and structures are affected by vegetation, the degree to which depends on vegetation density, flexibility, type, and whether it is in a submerged or emergent condition. Water surface modeling help for the study of flood waves, water level calculation during flood, stage discharge relation, design of water work structures. This work develops a model which can be used to simulate water surface profile in compound channel with vegetated floodplains with various vegetation covers. To predict the water surface, experiments have been conducted in the laboratory for different hydraulic conditions. It can be seen from the results that the trend of stage-discharge relationships is found to be an exponential function giving a high value of R2. A multivariable regression model (MRM) has been developed to predict the water surface profile for such channels. The dependency of water surface profiles on four different non-dimensional parameters such as canopy arrangement, canopy density, relative depth and relative distance are analyzed. Using the relevant experimental data, non-linear regression has been performed. The results obtained from the present water surface profile model shows good agreement with the observed data.

Vegetation has traditionally been viewed as a nuisance and obstruction to channel flow by increasing flow resistance and water depth. However, in recent years, vegetation has become a major component of erosion control and stream restoration. Most of research efforts focus on describing vegetation roughness , determining drag coefficients and empirical formulas for resistance under various vegetation configurations. While the development of experimental solutions for vegetative resistance is important, it is also important to understand the detailed characteristics of flow through vegetation. Yang et al.(2007) conducted flume experiments with different types of vegetation, and found that, in the cases of non vegetated floodplains, all measured streamwise velocity distributions followed the logarithmic distribution, but for vegetated floodplains, they followed an S-shaped profile Nezu and Sanju(2008) have investigated turbulence structures and coherent motion in vegetated canopy open-channel flows. They divided the whole flow region into three sub-zones, i.e., the emergent zone, the mixing-layer zone and the log-law zone. In the present study, some experiments were undertaken herein under different conditions to elucidate the flow structure. The main focus is to examine how the vertical velocities, are affected by simulated vegetation arranged in emergent and submerged conditions. In addition, the effect of dowel density, configuration, and relative depth are examined.

The experiments were conducted in a fixed bed rectangular flume, 9 m long and 0.6 m high and 0.8 m wide. The slope of bed flume was 12 ×10-5. The main channel and floodplain had widths of 24 and 28 cm, respectively, and the main channel had a side slope, s, of 0. The bankfull height, h, was 6 cm. Vegetation were simulated by wooden dowels. The wooden dowels were 140 mm tall and 7 mm in diameter. The dowels were attached to a PVC sheet bolted to the bottom of the flood plain in linear and staggered arrangement. The spacing of the dowels varies from 2.5-10 cm in both lateral and streamwise directions forming stem density of 0.41, 1.64%, 6.04%. The flume was operated under a uniform flow condition, and measurements of discharge, point velocity and flow depth were taken. Flow depths were measured by means of a pointer gauge, discharges were measured by a digital flowmeter, installed upstream of the channel, and a micro propeller current meter were used to velocity measurements. Within the measurement cross section, located at 5.6 m, the authors arranged ten verticals, where the lateral values of y from the first vertical to the last were 0, 4, 8, 12, 12.2, 26 and 34 cm. When the vertical distance from the measurement point to the bed was less than 175 mm, the measurement interval was 10 mm and 5mm in the main channel and floodplain, respectively.

The experimental results are presented in three parts, flow through non-vegetated floodplain first, flow through emergent vegetation second, followed by the submerged case. The effects of density and dowel configuration are included in each of the sections. Each section ends with a discussion on the effects of rigid dowels on logarithmic profile. In the cases of nonvegetated floodplains, all measured streamwise velocity distributions followed the logarithmic distribution, but for vegetated floodplains, they followed an S-shaped profile. It is seen that after implanting the vegetation over the floodplain, the velocity over the floodplain decreases whereas it increases in the main channel. Also, as the vegetation density, λ, increases, velocity increases in the main channel and decreases in the floodplain. In the presence of emergent vegetation on floodplain, logarithmic profile does not exist even in the main channel, however it seems that the formation of the S-shaped profile in the main channel is under the bankfull height and above the bankfull height the vertical velocity profile takes on a logarithmic profile again. Under Submerged flow conditions, the velocity characteristics in all locations above the dowel array are well illustrated by the semi-logarithmic expression that has a slip velocity initially near the inflection point. On the basis of the present experimental results, the whole flow region is divided into the following three sub-zones: (1) Emergent zone (0 ≤ z ≤ hp), (2) Mixing-layer zone (hp < z ≤ hlog), (3) Log-law zone (hlog < z ≤ H). In the present study, hp was equal to 0.2 H and hlog was equal to 0.5 H. In the emergent zone (0 ≤ z ≤ hp) the velocity is almost constant due to strong wake effects of vegetation stems although it may behave slightly in a counter-gradient fashion. In the second zone (hp ≤ z ≤ hlog), the vertical velocity profile are similar in both submerged and emergent conditions, and the effect of bed roughness is completely eliminated and the velocity gradients are reduced and almost fixed. The velocity in the third zone (hlog < z ≤ H) is significantly higher than the velocity in the second zone. In the log-law zone (hlog < z ≤ H), the log-law of velocity distribution for rough beds is reasonably applied even to vegetated flows. Comparison the longitudinal velocity profiles for linear and staggered dowel arrangements indicates an increase in the resistance due to the linear arrangement compared to the staggered arrangement.

In the cases of non vegetated floodplains, all measured streamwise velocity distributions followed the logarithmic distribution, but for vegetated floodplains, they followed an S-shaped profile. However, in the main channel, higher than the bankfull height the velocity profile is logarithmic. The results shows that as the vegetation density, λ, increases, the velocity increases in the main channel and decreases in the floodplain. Linear arrangement resulted higher resistance compared to staggered vegetation arrangement. The velocity profile at all locations above the dowel array are very well represented by the following semi logarithmic expression. In fully submerged vegetation, the whole flow region was divided into three sub-zones, i.e., the emergent zone, (0≤z≤hp) the mixing-layer zone (hp < z≤hlog), and the log-law zone(hlog<z≤H). In the present study, hp was equal to 0.2 H and hlog was equal to 0.5 H.

Recently, we have reported mutations in LARP7 gene, leading to neurodevelopmental disorders (NDDs), the most frequent cause of disability in children with a broad phenotype spectrum and diverse genetic landscape.

Here, we present two Iranian patients from consanguineous families with syndromic intellectual disability, facial dysmorphism, and short stature.

Whole-exome sequencing (WES) revealed a novel homozygous stop-gain (c.C925T, p.R309X) variant and a previously known homozygous acceptor splice-site (c.1669-1_1671del) variant in LARP7 gene, indicating the diagnosis of Alazami syndrome.

These identified variants in patients with Alazami syndrome were consistent with previously reported loss of function variants in LARP7 and provide further evidence that loss of function of LARP7 is the disease mechanism.

Inherited peripheral neuropathies (IPNs) are a group of neuropathies affecting peripheral motor and sensory neurons. Charcot-Marie-Tooth (CMT) disease is the most common disease in this group. With recent advances in next-generation sequencing (NGS) technologies, more than 100 genes have been implicated for different types of CMT and other clinically and genetically inherited neuropathies. There are also a number of genes where neuropathy is a major feature of the disease such as spinocerebellar ataxia (SCA) and hereditary spastic paraplegia (HSP). We aimed to determine the genetic causes underlying IPNs in Iranian families.

We performed whole exome sequencing (WES) for 58 PMP22 deletion-/duplication-negative unrelated Iranian patients with a spectrum of phenotypes and with a preliminary diagnosis of hereditary neuropathies.

Twenty-seven (46.6%) of the cases were genetically diagnosed with pathogenic or likely pathogenic variants. In this study, we identified genetically strong variants within genes not previously linked to any established disease phenotype in five (8.6%) patients.

Our results highlight the advantage of using WES for genetic diagnosis in highly heterogeneous diseases such as IPNs. Moreover, functional analysis is required for novel and uncertain variants.

Ménière’s disease (MD) is a common inner ear disorder which is characterized by recurrent attacks of vertigo, fluctuating sensorineural hearing loss (SNHL), tinnitus, and a sense of fullness in the affected ear. MD is a complex disorder; although six genes have been linked to familial autosomal dominant form of the disease, in many cases, the exact genetic etiology remains elusive.

To elucidate the genetic causes of MD in an Iranian family, we performed exome sequencing on all members of the family: consanguineous parents and four children (two affected and two unaffected). Variant filtering was completed using a customized workflow keeping variants based on segregation with MD in autosomal recessive (AR) inheritance pattern, minor allele frequency (MAF), and in-silico prediction of pathogenicity.

Analysis revealed that in this family, 970 variants co-segregated with MD in AR pattern, out of which eight variants (one intergenic, four intronic, and three exonic) were extremely rare. The exonic variants included a synonymous substitution in USP3 gene, an in-frame deletion in ZBED2 gene, and a rare, highly conserved deleterious missense alteration in LSAMP gene.

The phenotype observed in the proband described here, i.e. vertigo, poor sense of smell, tinnitus, and borderline hearing ability, may originate from aberrant changes in the cerebellum and limbic system due to a deleterious mutation in the LSAMP gene; hence, LSAMP mutation is a possible candidate for the etiology of MD in this family.

Increasing attention to environmental issues in the management of rivers, causese the development of research in the field of hydraulic parameters and sediment transport in the rivers. Vegetation in many rivers, has a significant impact on the flow hydraulic, morphology and sediment transport processes. Understanding the hydraulics of flow in a compound channel with vegetated floodplains is very important for determining the stage-discharge curve and for supporting the management of fluvial processes. There are few models within CFD codes that conceptually or physically represent the hydrodynamic impact of a vegetation canopy on the velocity field and conveyance characteristics within an estuarine or riverine system. The present research investigates the numerical and experimental modelling aspects of flow in compound channels with vegetated floodplain, emphasis to the suspended sediment transport. This study, has proposed a method for predicting the depth-averaged velocity in compound channels with vegetated floodplains, based on an analytical solution to the depth-integrated Reynolds-Averaged Navier-Stokes equation (RANS) with a term included to account the effects of vegetation. Two dimensional advection-diffusion equation were used to calculate the dispersion coefficients and sedimentation rate, this equation were solved by using a finite volume method. The vegetation is modeled via an additional term in the momentum equation to account for the additional drag force. The method includes the effects of bed friction, drag force, lateral turbulence and secondary flows, via four coefficients f, CD, λ & Γ respectively. This model is able to estimate the velocity distribution in channels with different dimensions, different vegetation densities. This model is able to estimate the velocity distribution in channels with different dimensions, different vegetation densities. The wake interference model given by Nepf (1999) is used to estimate the bulk drag coefficient. Modified forms of the Colebrook–White equation can be used to calculate a local friction factor in compound channels with vegetated floodplains. Several eddy viscosity models have been used in the literature to predict transverse momentum exchange in the mixing layer. Once velocity profile is obtained, the dispersion coefficient is evaluated and the remarkable role of vegetation is shown. Both the velocity profile and the dispersion coefficient have been validated using our new experimental results. The model was applied in inverse mode to estimate the model parameters that quantified eddy viscosity coefficient, secondary flow, longitudinal dispersion, transverse dispersion and filtration in the experiments. In addition, the Elder’s and Neph’s relationships also calibrated to calculate the Longitudinal and transverse dispersion coefficients. A Levenberg-Marquardt algorithm was used to find the values of the model parameters that minimized the sum-of-squared differences between measured and modeled velocities and particle concentrations. Experiments performed in a flume of the Hydraulic laboratory. The experimental channel is employed in this investigation was 10 m long × 0.3 m wide and 0.6 m deep. The channel has a simple rectangular cross section; however, this was modified by using Plexiglas sheeting to produce an asymmetrical compound shape. The artificial stems were PVC rods of 5 mm outside diameter, arranged in staggered grid. The model substance used as suspended load was silica of mean particle diameter around 7µm and density 2143 kg/m3. Silica suspensions were injected to produce fully mixed inflow concentrations of about 6 g/l. In general, two series of experiments have been done in this study. In The first series of experiments the depth averaged velocity were measured, the second series have been conducted to estimate the rate of sedimentation. Depth averaged velocity measured by using micro-propeller and pitot tubes. Results showed that the use of constant coefficient of 0.0683 for eddy viscosity coefficient have not a significant impact on depth averaged velocity. The error about 1% have been observed between results of numerical modeling and experimental data, when the relationships 0.417δρgS0 HDr and 0.62δρgS0HDr have been used for secondary flow coefficients, to the main channel and floodplain, respectively. Results showed that dispersion coefficient in vegetated channels increased cross the main channel compared to no vegetated case, due to the gradient of velocity. Sedimentation rate coefficients calibrated by comparing the experimental and numerical sedimentation rate. The numerical model underestimates the experimental data about 8%. Experimental data of Zong(2011) were used to verification of numerical model, the results showed that the modified model overestimates the data with 22% difference. The results show that the quasi 2D model reproduces a reasonable simulation of the flow field and sediment transport in compound channels with vegetated floodplains.

Hearing loss (HL) is the most common sensory deficit in humans, and genetic factors contribute to about half of the cases. With 112 causative genes identified so far and a disproportionate share of the genes within different ethnic groups, HL has proven to be quite heterogeneous. Twenty Iranian families having at least 2 children with hereditary HL were initially verified to be GJB2-negative and were then subjected to whole exome sequencing (WES). Sanger sequencing was used to confirm segregation of the variant identified in each family. In 3 families, WES revealed 3 novel variants in KCNQ4, LHFPL5 and COCH genes. The KCNQ4 gene (DFNA2A) encodes a potassium channel (KV7.4) and the heterozygous variant identified (c.1647C>G, p.F549L) resulted in the substitution of Phe549 residing in the KV7.4 cytoplasmic region. The homozygous variant (c.34A>T, p.K12X) was identified in the LHFPL5 gene (DFNB67) which encodes a transmembrane protein, and another variant in a homozygous state (c.116T>A, p.L39X) was identified in the COCH gene which encodes a secretory protein. Pathogenic variants in the COCH gene are associated with late onset autosomal dominant hearing loss (DFNA9) but the affected individuals displayed early onset HL with a recessive mode of inheritance. The 16% contribution of GJB2 to HL in the Iranian population necessitates the discovery of the remaining causal factors. This study is the first to report KCNQ4 and COCH related HL in the Iranian population and the second study, globally, to report HL due to biallelic inactivation of the COCH gene.

Polymorphisms in α-actinin-3 (ACTN3) gene are considered to be important in the genetic predisposition to human athletic performance. Most of the activities in soccer such as jumping, striking the ball, and running are considered plyometric and explosive. Performance power during such activities depends on the strength of the muscles involved. Therefore, high muscle strength is considered crucial for soccer players. The primary objective of this study was to ascertain the association between ACTN3 R577X (rs1815739) polymorphism and sports athletism in Iranian elite male soccer players.
In total, 90 top-level professional Iranian male soccer players and 200 nonathletic Iranian men from the general population participated in this case–control study. Exon 16 of ACTN3 was genotyped throughout polymerase chain reaction (PCR) followed by Restriction Fragment Length Polymorphism (RFLP) using the restriction enzyme DdeI and direct sequencing. The genotypic and allelic frequencies of R577X polymorphism in athletes were compared to the frequencies in the general population (nonathletes).
According to the results, the percentage distributions of 577RR and 577RX genotypes (41% and 37%, respectively) were significantly higher and lower, respectively, than that of controls (25% and 57%, respectively) (P Our findings showed a significant association between ACTN3 genotypes and elite sport performance among Iranian male soccer players, which agrees with several previous studies.

A significant contribution to the causes of hereditary hearing impairment comes from genetic factors. More than 120 genes and 160 loci have been identified to be involved in hearing impairment. Given that consanguine populations are more vulnerable to most inherited diseases, such as hereditary hearing loss (HHL), the genetic picture of HHL among the Iranian population, which consists of at least eight ethnic subgroups with a high rate of intermarriage, is expected to be highly heterogeneous. Using an electronic literature review through various databases such as PubMed, MEDLINE, and Scopus, we review the current picture of HHL in Iran. In this review, we present more than 39 deafness genes reported to cause non-syndromic HHL in Iran, of which the most prevalent causative genes include GJB2, SLC26A4, MYO15A, and MYO7A. In addition, we highlight some of the more common genetic causes of syndromic HHL in Iran. These results are of importance for further investigation and elucidation of the molecular basis of HHL in Iran and also for developing a national diagnostic tool tailored to the Iranian context enabling early and efficient diagnosis of hereditary hearing impairment.

Cystic fibrosis (CF) is a common autosomal recessive disorder that affects many body systems and is produced by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. CF is also the most frequently inherited disorder in the West. The aim of this study was to detect the mutations in the CFTR gene in two Iranian families with CF.
After DNA extraction using the salting out method, a mutation panel consisting of 35 common mutations was tested by PCR, followed by reverse hybridization Strip Assay. To confirm the mutations, we have also performed Sanger sequencing for all 27 exons, intronic flanking regions, and 5' and 3' UTRs of the CFTR gene.
Carrier testing in a spouse revealed a novel nonsense mutation in the CFTR gene (c.2777 T>A (p.L926X)) in exon 17 for husband and a previously described heterozygous splice site pathogenic mutation (c.1393-1G>A) in his wife. The other novel compound heterozygous missense mutation (c.3119 T>A (p.L1040H)), which was previously reported as nonsense c.3484C>T (p.R1162X) mutation, was found in exon 19 in patient screening.
Two novel CFTR mutations in exons 17 and 19 are responsible for CF with severe phenotypes in two Iranian families. These two mutations supplement the mutation spectrum of CFTR and may contribute to a better understanding of CFTR protein function.

Non-syndromic autosomal recessive Retinitis Pigmentosa (arRP) is a highly heterogeneous genetic visual disorder with a large number of causative genes. We aimed to determine the power of Whole Exome Sequencing (WES) in the identification of the genes responsible for non-syndromic arRP among Iranian patients. We used WES, followed by the Sanger sequencing to identify the underlying gene mutations causing non-syndromic arRP. Our study revealed disease-causing mutations in known arRP genes for 10 of the 13 families studied (76.9%). These mutations included two-frameshift insertion/deletion in CRB1 and ABCA4, one splicing mutation in PDE6B, four missense mutations in RP1, CRB1, PANK2 and IFT140, as well as three stop codon mutations in RDH12, PRCD, and C2orf71. Three remaining families harbored no mutation in previously known RP genes. Of the 10 diseases causing mutations identified among the investigated Iranian patients with non-syndromic arRP, eight variants had not been reported previously. We confirmed segregation of all 10 mutations with disease phenotypes in our studied population. This study supports the genetic heterogeneity of non-syndromic arRP in Iranian patients, and provides an opportunity to show the effectiveness of WES in the identification of pathogenic mutations among patients with non-syndromic arRP born to consanguineous parents.

Cancer, with a high rate of mortalities worldwide, pose a major threat to human health. Although family history accounts for at least 5-10% of all cancers, it is conferred to be as a significant risk of developing cancer. Recently, application of high speed and low cost high-throughput nucleotide sequencing technologies has provided an opportunity to assess cancer risk in at risk healthy individuals. The present study has aimed to detect susceptible variants relevant to 69 known cancer genes on a 42-year-old Iranian healthy volunteer with familial history of cancer syndromes using Whole Exome Sequencing (WES). Exome enrichment and sequencing were applied using SureSelect V4 kit and Illumina Hiseq2000, respectively. Analysis of data was carried out by Insilico thoroughly methods. Some filtering criteria were considered to exclude the common (MAF>1%) and nonfunctional variants as well as any variants out of +- 2 bp exons boundaries according to RefSeq database. We focused on deleterious rare alternations. To further validation, data was compared to 300 Iranian normal controls and confirmed by Sanger sequencing method. As a result, 89 variants were identified totally which passed filtering process and eventually, the data emerging from Insilico analysis revealed a novel variant of WRN gene (c.953_954delTTA). Given the fact that cancer potentially could be predictable, genetic screening of hereditable deleterious variants in at risk individuals is crucial stage stag in terms of improving the quality of life allowing prevention and control. In this regards, WES, as cost-benefit diagnostic tool, effectively is capable of determining all susceptibility cancer genes variations predisposing to disease. The project as a first carrier detection is being emerged as a new insight to take a step to establish new genetic molecular approach in our country, as well as supporting the potential utilization of powerful WES in the field of early detection.

Heredity hearing loss (HL) is the most prevalent sensory disorder and most cases are non-syndromic. Eighty percent of non-syndromic sensorineural deaf patients show an autosomal recessive pattern of inheritance. To date، 47 genes and 98 loci have been reported for this mode of inheritance. Previous studies in our center showed the high prevalence of DFNB3 among Iranian deaf families. PJVK (DFNB59) is the first human gene implicated in non-syndromic deafness due to a neuronal defect. PJVK encodes Pejvakin، which is present in the auditory nerves and brainstem. Scientists believe Pejvakin can play an important role in transmission of nerve impulses that register sound. The aim of this study was to investigate the prevalence of DFNB59 mutations among 36 unrelated deaf Iranian families. We selected 36 consanguineous deaf families with two or more affected individuals who were negative for mutations in GJB2. At first، we conducted homozygosity mapping using four STR markers for DFNB59 and finally، for the families that showed autozygosity by descent، we performed Sanger Sequencing for all exons via intronic primers flanking the exons. One family showed autozygosity by descent at DFNB59 locus and Sanger Sequencing of the family revealed c: 499C>T transition، which produces a premature stop codon (R167X). So far، ten different types of mutations have been reported for Pejvakin gene. In 2007، R167X was first reported in a Turkish family. This study revealed the first case of R167X among Iranian population and it seems that the mutation in Pejvakin is more prevalent in Iran than other countries، because most cases have been reported among Iranian population.

About 50% of severe to profound intellectual disabilities (ID) are caused by genetic factors. In this study we decided to investigate the genetic causes of ID in 69 Bushehrian families to provide information for genetic counseling، carrier detection، and prenatal diagnosis. In this study we excluded known chromosomal abnormalities. The majority of families had more than two affected individuals. Karyotyping for each proband with physical malformations was performed. One affected member from each family was tested for FMR1 mutation and metabolic screening. Families with ID and primary microcephaly were checked for 7 known MCPH genes by linkage analysis. Chromosomal abnormality was not found in any of the families. One family had full mutation of CGG repeat of Fragile-X syndrome. Six out of 18 families with MCPH showed linkage to one of the MCPH loci. One family had a syndrome associated with microcephaly. Two families with microcephaly and one family with a non-syndromic form of mental retardation without microcephaly showed an autosomal dominant mode of inheritance. According to our results genetic causes of ID are very heterogeneous and autosomal recessive primary microcephaly has an extremely high prevalence (26. 09%) in Bushehr province of Iran.

Hereditary hearing loss (HHL) is a very common disorder. When inherited in an autosomal recessive manner, it typically presents as an isolated finding. Interestingly and unexpectedly, in spite of extreme heterogeneity, mutations in one gene, GJB2, are the most common cause of congenital severe-to-profound deafness in many different populations. In this study, we assessed the contributions made by GJB2 mutations and deletion in a portion of GJB6 to the autosomal recessive non-syndromic deafness genetic load in Iran. In this descriptive and cross – sectional study1605 probands from 1605 different nuclear families with autosomal recessive non-syndromic hearing loss were investigated. Hearing loss tests and clinical examination were done and 10 ml blood was drawn as DNA source. After study of 35delG mutation by ARMs PCR, negative or heterozygote individuals were sent to IOWA University for detection of other GJB2 mutations. GJB2-related deafness was found in 243 families (15.1%). Varient geographic pattern for GJB2-related deafness has considerable results in Iran in comparable with other study in Europe and our neighboring countries and deletion in GJB6. [∆ (GJB6-D13S1830)] hasnt been detected in our studied population.

Hereditary Hearing loss (HHL) affects one in 1000-2000 newborns and more than 50% of these cases, the loss has a genetic basis. About 70% of HHL is non-syndromic with autosomal recessive forms accounting for ~85% of the genetic load. To date, more than 100 locus estimated for this kind of deafness. Different genes have been reported to be involved, but mutations in the connexin 26 gene (Cx26) have been established as the basis of autosomal recessive non-syndromic hearing loss. The aim of this project is to study the prevalence of connexin 26 mutations. In this study from the population that referred to welfare center of Khoozestan province for genetic counseling, 50 individual have been selected and getting 5-10 ml blood then after DNA extraction we analyzed quality of DNA by spectrophotometry. Mutation screening began by using Amplification Refractory Mutation System (ARMS) – Polymerase Chain Reaction (PCR) for detection of 35delG and then we analyzed all samples excluding 35delG homozygote by Denaturation High Polymorphic liquid Chromatography (DHPLC) and Direct Sequencing. We screened 100 chromosomes (50 patients) for GJB2 mutations. Thirteen (13%) carry GJB2 mutations including 35delG, R184P, R32H, R127H, 300del2 (AT). Among them, 35delG has the highest frequency (61%). Polymorphism V153I was found in three chromosomes and also polymorphism V52V was found in family. According to our results, other loci and genes may be the major responsible for non-syndromic deafness in this population.