Mutations in the coding regions of the hepatocyte nuclear factor 4 alpha in Iranian families with maturity onset diabetes of the young

Hepatocyte nuclear factor 4α (HNF4α) is a nuclear receptor involved in glucose homeostasis and is required for normal β cell function. Mutations in the HNF4α gene are associated with maturity onset diabetes of the young type 1 (MODY1). The aim of the present study was to determine the prevalence and nature of mutations in HNF4α gene in Iranian patients with a clinical diagnosis of MODY and their family members. Twelve families including 30 patients with clinically MODY diagnosis and 21 members of their family were examined using PCR-RFLP method and in case of mutation confirmed by sequencing techniques. Fifty age and sex matched subjects with normal fasting blood sugar (FBS) and Glucose tolerance test (GTT) were constituted the control group and investigated in the similar pattern. Single mutation of V255M in the HNF4α gene was detected. This known mutation was found in 8 of 30 patients and 3 of 21 individuals in relatives. Fifty healthy control subjects did not show any mutation. Here, it is indicated that the prevalence of HNF4α mutation among Iranian patients with clinical MODY is considerable. This mutation was present in 26.6% of our patients, but nothing was found in control group. In the family members, 3 subjects with the age of ≤25 years old carried this mutation. Therefore, holding this mutation in this range of age could be a predisposing factor for developing diabetes in future

Classification and Analysis of Optimization Techniques for Integrated Energy Systems Utilizing Renewable Energy Sources: A Review for CHP and CCHP Systems

Energy generation and its utilization is bound to increase in the following years resulting in accelerating depletion of fossil fuels, and consequently, undeniable damages to our environment. Over the past decade, despite significant efforts in renewable energy realization and developments for electricity generation, carbon dioxide emissions have been increasing rapidly. This is due to the fact that there is a need to go beyond the power sector and target energy generation in an integrated manner. In this regard, energy systems integration is a concept that looks into how different energy systems, or forms, can connect together in order to provide value for consumers and producers. Cogeneration and trigeneration are the two most well established technologies that are capable of producing two or three different forms of energy simultaneously within a single system. Integrated energy systems make for a very strong proposition since it results in energy saving, fuel diversification, and supply of cleaner energy. Optimization of such systems can be carried out using several techniques with regards to different objective functions. In this study, a variety of optimization methods that provides the possibility of performance improvements, with or without presence of constraints, are demonstrated, pinpointing the characteristics of each method along with detailed statistical reports. In this context, optimization techniques are classified into two primary groups including unconstrained optimization and constrained optimization techniques. Further, the potential applications of evolutionary computing in optimization of Integrated Energy Systems (IESs), particularly Combined Heat and Power (CHP) and Combined Cooling, Heating, and Power (CCHP), utilizing renewable energy sources are grasped and reviewed thoroughly. It was illustrated that the employment of classical optimization methods is fading out, replacing with evolutionary computing techniques. Amongst modern heuristic algorithms, each method has contributed more to a certain application; while the Genetic Algorithm (GA) was favored for thermoeconomic optimization, Particle Swarm Optimization (PSO) was mostly applied for economic improvements. Given the mathematical nature and constraint satisfaction property of Mixed‐Integer Linear Programming (MILP), this method is gaining prominence for scheduling applications in energy systems

Differentiating benign and malignant thyroid nodules: A cross‐sectional study on the comparison of diagnostic value of ultrasound elastography and fine needle aspiration biopsy

Abstract Background and Aim This study examines the comparison of ultrasound elastography and fine needle aspiration (FNA) in diagnosing thyroid cancers and investigates the use of elastography as the initial diagnostic test of thyroid cancers to avoid the need for invasive diagnostic tests. Methods In this study, 28 patients with 48 thyroid nodules (TNs) who were candidates for FNA or surgery were examined within a period of 18 months. Cut‐off and subsequently sensitivity and specificity for elastography results, compared to pathology results as the gold standard, were calculated using the receiver operating characteristic curve (ROC). Results Based on ROC, the cut‐off point differentiating the tissue stiffness between benign and malignant TNs was 25.400 kilopascal (kPa) (sensitivity of 90.9% and specificity of 78.4%). It was observed that age affects the tissue stiffness; therefore, the cut‐off was defined as 65.625 kpa for age groups under 50 years old (sensitivity of 100% and specificity of 100%) and 25.400 kpa for the age group above 50 years old (sensitivity of 88.9% and specificity of 70.4%). Conclusion Based on the high sensitivity and specificity of shear wave elastography in the differentiation of benign and malignant TNs, it can be employed as a stand‐alone or in combination with other diagnostic techniques to reduce the need for inessential surgical operations. However, future studies or developments are needed on this promising diagnostic technique

Molecular interaction of fibrinogen with zeolite nanoparticles

International audienceFibrinogen is one of the key proteins that participate in the protein corona composition of many types of nanoparticles (NPs), and its conformational changes are crucial for activation of immune systems. Recently, we demonstrated that the fibrinogen highly contributed in the protein corona composition at the surface of zeolite nanoparticles. Therefore, understanding the interaction of fibrinogen with zeolite nanoparticles in more details could shed light of their safe applications in medicine. Thus, we probed the molecular interactions between fibrinogen and zeolite nanoparticles using both experimental and simulation approaches. The results indicated that fibrinogen has a strong and thermodynamically favorable interaction with zeolite nanoparticles in a non-cooperative manner. Additionally, fibrinogen experienced a substantial conformational change in the presence of zeolite nanoparticles through a concentration-dependent manner. Simulation results showed that both E- and D-domain of fibrinogen are bound to the EMT zeolite NPs via strong electrostatic interactions, and undergo structural changes leading to exposing normally buried sequences. D-domain has more contribution in this interaction and the C-terminus of γ chain (γ377–394), located in D-domain, showed the highest level of exposure compared to other sequences/residues