Sharif Digital Repository

The present study investigated the biological treatment of produced water in a microbial electrochemical cell (MXC). The main objectives were to develop a novel spiral microbial electrochemical cell (SMXC) and test its performance for produced water treatment under highly saline conditions (salinity > 200000 ppm). The bioelectrochemical performance of the system was also evaluated in terms of power and hydrogen production over time. The comparatively inexpensive material and ease of application increased the feasibility of the SMXC configuration for produced water treatment. Optimal SMXC performance as a microbial fuel cell was achieved at a maximum open circuit potential of 330 mV, maximum... 

The discrete fracture network (DFN) and Multiple-Continua concept are among the most widely used methods to model naturally fractured reservoirs. Each faces specific limitations. The recently introduced recovery curve method (RCM) is believed to be a compromise between these two current methods. In this method the recovery curves are used to determine the amount of mass exchanges between the matrix and fracture mediums. Two recovery curves are assigned for each simulation cell, one curve for gas displacement in the presence of the gravity drainage mechanism, and another for water displacement in the case of the occurrence of the imbibition mechanism. These curves describe matrix-fracture... 

Protein fibrillation process (e.g., from amyloid beta (Aβ) and α-synuclein) is the main cause of several catastrophic neurodegenerative diseases such as Alzheimer's and Parkinson diseases. During the past few decades, nanoparticles (NPs) were recognized as one of the most promising tools for inhibiting the progress of the disease by controlling the fibrillation kinetic process; for instance, gold NPs have a strong capability to inhibit Aβ fibrillations. It is now well understood that a layer of biomolecules would cover the surface of NPs (so called "protein corona") upon the interaction of NPs with protein sources. Due to the fact that the biological species (e.g., cells and amyloidal... 

The potential for using Thermophotovoltaic (1TPV) generators as an alternative for recovering energy losses in steel production industry is assessed. A mathematical model for the assessment of the performance of TPV application in the iron and steel industry has been developed. In order to support the mathematical model, a sample TPV apparatus in laboratory scale based on an IR emitter has been designed and assembled. The key modeling parameters of TPV generator include: the open circuit voltage, the short circuit current density and fill factor of the TPV cell. These parameters have been considered in the model as functions of several variables such as: the emitter (hot steel slab)... 

In this study, a multi-scale model is proposed to assess softening kinetics and microstructural changes during isothermal annealing within an aluminum alloy. In the first stage, an elastic-plastic finite element analysis is performed for computing the distributions of effective plastic strain and stress while the stored energy after cold rolling is defined based on the predicted data and then utilized for generation of the initial conditions in the microstructural analysis. In the next stage, an algorithm based on cellular automata coupled with a first order rate equation is used to determine the progress of softening behavior at elevated temperatures while both recrystallization and... 

A new method of spatial filtering in high-order finite volume methods is presented and assessed. The base of this method is to filter face-averaged variables (fluxes) and then the recovery of cell-averaged ones. Two kinds of filtering method are proposed. The first kind is highly dissipative and appropriate for the numerical regions that need high dissipation, e.g. sponge zones. The second kind, on the other hand, is a precise method and hence is suitable for applying the high-order finite difference filters to the finite volume methods. Applying high-order finite difference filters directly to the high-order finite volume methods without using the proposed method causes stability problems... 

Since physiological and pathological processes occur at nano-environments, nanotechnology has considered as an efficient tool for designing of next generation specific biomolecules with enhanced pharmacodynamic and pharmacodynamic properties. In the current investigation, by control of the size and hydrodynamic volume at the nanoscale, for the first time, physicochemical and pharmacokinetic properties of an anti-VEGFA nanobody was remarkably improved by attachment of a Proline-Alanine-Serine (PAS) rich sequence. The results elucidated unexpected impressive effects of PAS sequence on physicochemical properties especially on size, hydrodynamics radius, and even solubility of nanobody. CD... 

Motif discovery is a challenging problem in molecular biology and has been attracting researcher's attention for years. Different kind of data and computational methods have been used to unravel this problem, but there is still room for improvement. In this study, our goal was to develop a method with the ability to identify all the TFBS signals, including known and unknown, inside the input set of sequences. We developed a clustering method specialized as part of our algorithm which outperforms other existing clustering methods such as DNACLUST and CD-HIT-EST in clustering short sequences. A scoring system was needed to determine how much a cluster is close to being a real motif. Multiple... 

Many problems in applied machine learning deal with graphs (also called networks), including social networks, security, web data mining, protein function prediction, and genome informatics. The kernel paradigm beautifully decouples the learning algorithm from the underlying geometric space, which renders graph kernels important for the aforementioned applications. In this paper, we give a new graph kernel which we call graph traversal edit distance (GTED). We introduce the GTED problem and give the first polynomial time algorithm for it. Informally, the graph traversal edit distance is the minimum edit distance between two strings formed by the edge labels of respective Eulerian traversals... 

Optical tweezers are proven indispensable single-cell micro-manipulation and mechanical phenotyping tools. In this study, we have used optical tweezers for measuring the viscoelastic properties of human red blood cells (RBCs). Comparison of the viscoelastic features of the healthy fresh and atorvastatin treated cells revealed that the drug softens the cells. Using a simple modeling approach, we proposed a molecular model that explains the drug-induced softening of the RBC membrane. Our results suggest that direct interactions between the drug and cytoskeletal components underlie the drug-induced softening of the cells. © 2018 Optical Society of America  

Biological cell studies have many applications in biology, cell manipulation, and diagnosis of diseases such as cancer and malaria. In this study, Inverse Finite Element Method (IFEM) combined with Levenberg-Marquardt optimization algorithm has been used to extract and characterize material properties of mouse oocyte and embryo cells at large deformations. Then, the simulation results have been validated using data from experimental works. In this study, it is assumed that cell material is hyperelastic, isotropic, homogenous, and axisymmetric. For inverse analysis, FEM model of cell injection experiment implemented in Abaqus software has been coupled with Levenberg-Marquardt optimization... 

In this study, a folic acid-functionalized niosome was formulated and loaded with letrozole and curcumin as a promising drug carrier system for chemotherapy of the breast cancer cells. The formulation process was optimized by varying the type of Span 80 and total lipid to drug ratio, where Span 80 and lipid to drug molar ratio of 10 resulted in the niosomes with maximum encapsulation of both drugs but minimum size. The developed niosomal formulation showed a great storage stability up to one month with the small changes in drug encapsulation efficiency and size during the storage. In addition, they showed a pH-dependent release behaviour with slow drug release at physiological pH (7.4) while... 

Upon incubation of nanoparticles in biological fluids, a new layer called the protein corona is formed on their surface affecting the interactions between nanoparticles and targeted cells during the endocytosis process. In the present study, a mathematical model based on the diffusion of membrane mobile receptors is proposed. Opposing the endocytosis proceeding, membrane bending and tension energies are named as resistant energy. Also, the binding energy and free-energy associated with the configurational entropy are collectively termed promoter energy. Utilizing this model, endocytosis of gold nanoparticle (GNP) is simulated to explore the biological media effect. The results reveal that... 

With large amounts of experimental data, modern molecular biology needs appropriate methods to deal with biological sequences. In this work, we apply a statistical method (Pearson's chi-square test) to recognize the signals appear in the whole genome of the Escherichia coli. To show the effectiveness of the method, we compare the Pearson's chi-square test with linguistic complexity on the complete genome of E. coli. The results suggest that Pearson's chi-square test is an efficient method for distinguishing genes (coding regions) form pseudogenes (noncoding regions). On the other hand, the performance of the linguistic complexity is much lower than the chi-square test method. We also use the... 

Upon incorporation of nanoparticles (NPs) into the body, they are exposed to biological fluids, and their interaction with the dissolved biomolecules leads to the formation of the so-called protein corona on the surface of the NPs. The composition of the corona plays a crucial role in the biological fate of the NPs. While the effects of various physicochemical parameters on the composition of the corona have been explored in depth, the role of temperature upon its formation has received much less attention. In this work, we have probed the effect of temperature on the protein composition on the surface of a set of NPs with various surface chemistries and electric charges. Our results... 

It remains unclear whether causal, rather than merely correlational, relationships in molecular networks can be inferred in complex biological settings. Here we describe the HPN-DREAM network inference challenge, which focused on learning causal influences in signaling networks. We used phosphoprotein data from cancer cell lines as well as in silico data from a nonlinear dynamical model. using the phosphoprotein data, we scored more than 2,000 networks submitted by challenge participants. The networks spanned 32 biological contexts and were scored in terms of causal validity with respect to unseen interventional data. A number of approaches were effective, and incorporating known biology was... 

Haplotype information has become increasingly important in analyzing fine-scale molecular genetics data, Due to the mutated form in human genome; SNPs (Single Nucleotide Polymorphism) are responsible for some genetic diseases. As a consequence, obtaining all SNPs from human populations is one of the primary goals of studies in human genomics. In this paper, a data fusion method based on multiple parallel classifiers for reconstruction of haplotypes from a given sample Single Nucleotide Polymorphism (SNP) is proposed. First, we design a single greedy algorithm for solving haplotype reconstructions. [2] is used as an efficient approach to be combined with first classification method. The... 

Intracellular production of recombinant proteins in prokaryotes necessitates subsequent disruption of cells for protein recovery. Since the cell disruption and subsequent purification steps largely contribute to the total production cost, scalable tools for protein release into the extracellular space is of utmost importance. Although there are several ways for enhancing protein release, changing culture conditions is rather a simple and scalable approach compared to, for example, molecular cell design. This contribution aimed at quantitatively studying process technological means to boost protein release of a periplasmatic recombinant protein (alkaline phosphatase) from E. coli.... 

This review aims to propose the integrative implementation of microfluidic devices, biomaterials, and computational methods that can lead to a significant progress in tissue engineering and regenerative medicine researches. Simultaneous implementation of multiple techniques can be very helpful in addressing biological processes. Providing controllable biochemical and biomechanical cues within artificial extracellular matrix similar to in vivo conditions is crucial in tissue engineering and regenerative medicine researches. Microfluidic devices provide precise spatial and temporal control over cell microenvironment. Moreover, generation of accurate and controllable spatial and temporal... 

Developments of sensitive, rapid, and cheap systems for identification of a wide range of biomolecules have been recognized as a critical need in the biology field. Here, we introduce a simple colorimetric sensor array for detection of biological thiols, based on aggregation of three types of surface engineered gold nanoparticles (AuNPs). The low-molecular-weight biological thiols show high affinity to the surface of AuNPs; this causes replacement of AuNPs' shells with thiol containing target molecules leading to the aggregation of the AuNPs through intermolecular electrostatic interaction or hydrogen-bonding. As a result of the predetermined aggregation, color and UV-vis spectra of AuNPs...