siRNA nanotherapeutics: a promising strategy for anti‐HBV therapy

Chronic hepatitis B (CHB) is the most common cause of hepatocellular carcinoma (HCC) and liver cirrhosis worldwide. In spite of the numerous advances in the treatment of CHB, drugs and vaccines have failed because of many factors like complexity, resistance, toxicity, and heavy cost. New RNA interference (RNAi)‐based technologies have developed innovative strategies to target Achilles'' heel of the several hazardous diseases involving cancer, some genetic disease, autoimmune illnesses, and viral disorders particularly hepatitis B virus (HBV) infections. Naked siRNA delivery has serious challenges including failure to cross the cell membrane, susceptibility to the enzymatic digestion, and excretion by renal filtration, which ideally can be addressed by nanoparticle‐mediated delivery systems. cccDNA formation is a significant problem in obtaining HBV infections complete cure because of strength, durability, and lack of proper immune response. Nano‐siRNA drugs have a great potential to address this problem by silencing specific genes which are involved in cccDNA formation. In this article, the authors describe siRNA nanocarrier‐mediated delivery systems as a promising new strategy for HBV infections therapy. Simultaneously, the authors completely represent the clinical trials which use these strategies for treatment of the HBV infections.Inspec keywords: tumours, drugs, genetics, cellular biophysics, RNA, nanomedicine, diseases, molecular biophysics, microorganisms, cancer, liver, nanoparticles, patient treatmentOther keywords: siRNA nanotherapeutics, anti‐HBV therapy, chronic hepatitis B, CHB, HCC, hazardous diseases, cancer, genetic disease, autoimmune illnesses, viral disorders, hepatitis B virus infections, naked siRNA delivery, cell membrane, enzymatic digestion, renal filtration, nanoparticle‐mediated delivery systems, cccDNA formation, HBV infections complete cure, nanosiRNA drugs, siRNA nanocarrier‐mediated delivery systems, HBV infections therapy, liver cirrhosis, RNA interference, immune response, hepatocellular carcinoma     

Mathematical-Thermodynamic Prediction and Kinetics of Eta Phase Formation in Fe–Ni-Based Superalloys

Time–temperature–precipitation diagram of eta phase formation was established for an Fe–Ni based superalloy by means of mathematical-thermodynamic analysis, kinetic investigation, and microstructural observation. The eta phase started to precipitate at the expense of the γ′ phase after prolonged aging. On the basis of thermodynamic prediction, the interaction between Gibbs free energy of eta phase formation and activation energy for diffusion of elements, especially titanium, was considered. The tip of TTP diagram was obtained at 817 °C, on the basis of mathematical-thermodynamic prediction, and 825–840 and 840 °C, on the basis of microstructural evolution and kinetic analysis, respectively. Kinetic investigations predicted that the eta transformation started with diffusion of Ti into Ni. This indicated that, with the progress of transformation, as n in Avrami’s equation predicts, other eta formation mechanisms such as γ′ to eta transformation, instant nucleation from the matrix, coincidence of eta lamellas, etc. increased n and activation energy.     

Thermodynamics of Aluminium in Molten Zinc with the use of Electrochemical Sensors

In the present study the thermodynamics of aluminium in molten Zn‐Al was determined at the temperatures 470, 490 and 520°C with the use of electrochemical sensors. Cell and sensor techniques were used. The following concentration cell was used: Al (pure reference) |Al³⁺ (in fused salt) | [Al]_{in zinc}. It was found that the activity of aluminium shows positive deviation from Raoult's law. The partial heat of solution of aluminium at temperatures between 470 and 520°C for X_Al = 0.004 was determined as = 21882 J. The dilute solution of aluminium in zinc in the range of 0≤X_Al≤0.044 obeys Henry's law. The Wagner's first order interaction coefficient e^Al_Al was determined.     

Evaluation of driver drowsiness using respiration analysis by thermal imaging on a driving simulator

In this paper, a new non-intrusive driver drowsiness detection method is introduced based on respiration analysis using facial thermal imaging. Drowsiness is the cause of many driving accidents all over the world. Drivers’ respiration system undergoes significant changes from wakefulness to drowsiness and can be used to detect drowsiness. Current respiration measurement methods are intrusive and uncomfortable making respiration the least measured vital sign during driving. In this paper, a new method is presented based on facial thermal imaging to analyze drivers’ respiration signal non-intrusively. Thirty subjects are tested in a car simulator. They are fully awake at the beginning and experience drowsiness during the tests. The mean and the standard deviation of the respiration rate and the inspiration-to-expiration time ratio are extracted from the subjects’ respiration signal. To detect drowsiness, the Support Vector Machine (SVM) and the K-Nearest Neighbor (KNN) classifiers are used. The Observer Rating of Drowsiness method is used for scoring the drowsiness level and validating the proposed method. The performance and the results of both methods are presented and compared. The results indicate that drowsiness can be detected with the accuracy of 90%, sensitivity of 92%, specificity of 85%, and precision of 91%.

     

Tracking Structural Phase Transitions in Lead‐Halide Perovskites by Means of Thermal Expansion

The extraordinary properties of lead‐halide perovskite materials have spurred intense research, as they have a realistic perspective to play an important role in future photovoltaic devices. It is known that these materials undergo a number of structural phase transitions as a function of temperature that markedly alter their optical and electronic properties. The precise phase transition temperature and exact crystal structure in each phase, however, are controversially discussed in the literature. The linear thermal expansion of single crystals of APbX₃ (A = methylammonium (MA), formamidinium (FA); X = I, Br) below room temperature is measured using a high‐resolution capacitive dilatometer to determine the phase transition temperatures. For δ‐FAPbI₃, two wide regions of negative thermal expansion below 173 and 54 K, and a cascade of sharp transitions for FAPbBr₃ that have not previously been reported are uncovered. Their respective crystal phases are identified via powder X‐ray diffraction. Moreover, it is demonstrated that transport under steady‐state illumination is considerably altered at the structural phase transition in the MA compounds. The results provide advanced insights into the evolution of the crystal structure with decreasing temperature that are essential to interpret the growing interest in investigating the electronic, optical, and photonic properties of lead‐halide perovskite materials.     

Fabrication and characterization of gold nanoparticle-doped electrospun PCL/chitosan nanofibrous scaffolds for nerve tissue engineering

In the field of nerve tissue engineering, nanofibrous scaffolds could be a promising candidate when they are incorporated with electrical cues. Unique physico-chemical properties of gold nanoparticles (AuNPs) make them an appropriate component for increasing the conductivity of scaffolds to enhance the electrical signal transfer between neural cells. The aim of this study was fabrication of AuNPs-doped nanofibrous scaffolds for peripheral nerve tissue engineering. Polycaprolactone (PCL)/chitosan mixtures with different concentrations of chitosan (0.5, 1 and 1.5) were electrospun to obtain nanofibrous scaffolds. AuNPs were synthesized by the reduction of HAuCl₄ using chitosan as a reducing/stabilizing agent. A uniform distribution of AuNPs with spherical shape was achieved throughout the PCL/chitosan matrix. The UV–Vis spectrum revealed that the amount of gold ions absorbed by nanofibrous scaffolds is in direct relationship with their chitosan content. Evaluation of electrical property showed that inclusion of AuNPs significantly enhanced the conductivity of scaffolds. Finally, after 5 days of culture, biological response of Schwann cells on the AuNPs-doped scaffolds was superior to that on as-prepared scaffolds in terms of improved cell attachment and higher proliferation. It can be concluded that the prepared AuNPs-doped scaffolds can be used to promote peripheral nerve regeneration.

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Multi-criteria evolutionary optimization of a traffic light using genetics algorithm and teaching-learning based optimization

Today, the development of urbanization and increasing the number of vehicles has resulted in displeased consequences like traffic congestion and vehicle queuing. The vast majority of countries in the world encounter the challenge of the explosive rise in traffic demand. In this regard, it is necessary to meet traffic demand in transport networks, especially in metropolitans. In traffic management and shortening the trip duration, traffic lights on the signalized intersections play an essential role in urban pathways. This work provides a multi-criteria decision-making method for optimum traffic light control in an isolated corner. The main idea involves establishing a set of sub-optimal solutions for traffic light timing and selecting the best one among the diverse solutions. We have mathematically modelled the problem as an optimization problem to achieve an optimal solution with less waiting time for vehicles in intersections and the lowest cost. Genetic algorithm (GA) and Teaching-Learning-based Optimization (TLBO) are utilized for each phase to create a set of suitable timing scenarios. The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method is used to identify the best scenario, considering both waiting vehicles and traffic capacity as decision criteria. Its efficiency has been demonstrated over three different traffic volumes. Also, in a real-world implementation, its practical capability has been approved at a crossroads in Mashhad, Iran. The simulations indicate the improvement in the number of vehicles waiting behind the crossroad and the traffic capacity by 10% and 6.76% compared to the existing signal timing of the studied intersection, respectively.     

Two Efficient Dual-Band and Wide-Band Low-Power DCO Designs Using Current Starving Gates,DCV and Reconfigurable Schmitt Triggers in 180 nm

Digitally controlled oscillators are the main cores in all-digital phase-locked loops (ADPLL), which are important for determining the range of frequency and power consumption in ADPLLs. In the conventional digitally controlled oscillator (DCO) designs, one single band of operation is assigned to the DCO. The following paper presents a new approach in the design of DCOs, which works in dual-band and wide-band modes with a control unit. In dual-band mode, the DCO works in two different ranges of frequencies simultaneously via digital control bits. The wide-band DCO (WBDCO) works in one wider range of frequencies consecutively. It seems that in the wide-band DCO, the gap width for the dual-band DCO (DBDCO) is zero. The previously mentioned designs allow the designer to have standard frequencies with the help of direct or multiplied frequencies. So, we can have a trade-off between power and performance. This means that we can have low power consumption in low-frequency applications and vice versa. The proposed designs are based on using digitally controlled capacitors, current starving gates and Schmitt triggers in critical points of the DCO loop, while preserving coarse and fine tunings. The non-delay linearity factors are clearly investigated and resolved with the use of a new combined control unit. The simulations of the proposed designs are performed in Hspice with a voltage of \(\mathrm{VDD}=1.8\) v in 180 nm CMOS technology for 64- and 128-bit input coarse codes. Our simulation and evaluation results showed that in the dual-band DCO, a 14.8 ps jitter was calculated at 134 MHz with 1.2131 mW power consumption, while in the wide band with overlap mode, a 68.7 ps jitter was measured at 184.61 MHz with 1.604 mW power consumption. Our designs are proper for reconfigurable and multi-standard ADPLL designs.     

Automatic segmentation of thalamus from brain MRI integrating fuzzy clustering and dynamic contours

Thalamus is an important neuro-anatomic structure in the brain. In this paper, an automated method is presented to segment thalamus from magnetic resonance images (MRI). The method is based on a discrete dynamic contour model that consists of vertices and edges connecting adjacent vertices. The model starts from an initial contour and deforms by external and internal forces. Internal forces are calculated from local geometry of the model and external forces are estimated from desired image features such as edges. However, thalamus has low contrast and discontinues edges on MRI, making external force estimation a challenge. The problem is solved using a new algorithm based on fuzzy C-means (FCM) unsupervised clustering, Prewitt edge-finding filter, and morphological operators. In addition, manual definition of the initial contour for the model makes the final segmentation operator-dependent. To eliminate this dependency, new methods are developed for generating the initial contour automatically. The proposed approaches are evaluated and validated by comparing automatic and radiologist's segmentation results and illustrating their agreement.     

The impact of home freezing on the sensory characteristics of ready-to-use leafy vegetables

BACKGROUND: Owing to the increasing trend of consumption of ready‐to‐use leafy vegetables, the necessity of determining the best conditions for their frozen storage and the considerable impact of freezing on their sensory attributes, research was carried out to determine the best freezing temperature and storage time for a mixture of Allium ampeloprasum, Lepidium sativum and Stureia hortensis. RESULTS: The results for freezing temperature at three different storage times showed that colour and overall acceptability at ? 18 °C were always ranked first (P < 0.05), while taste at ? 18 °C was ranked first on days 120 and 150. The results for frozen storage time at three different temperatures indicated that colour, taste and acceptability were not significantly different. CONCLUSION: Overall, the results of this research indicated that the sensory attributes of leafy vegetables during 180 days of frozen storage were affected mainly by freezing temperature rather than frozen storage time. Copyright © 2010 Society of Chemical Industry