HNF1A Mutations and Beta Cell Dysfunction in Diabetes

Understanding the genetic factors of diabetes is essential for addressing the global increase in type 2 diabetes. HNF1A mutations cause a monogenic form of diabetes called maturity-onset diabetes of the young (MODY), and HNF1A single-nucleotide polymorphisms are associated with the development of type 2 diabetes. Numerous studies have been conducted, mainly using genetically modified mice, to explore the molecular basis for the development of diabetes caused by HNF1A mutations, and to reveal the roles of HNF1A in multiple organs, including insulin secretion from pancreatic beta cells, lipid metabolism and protein synthesis in the liver, and urinary glucose reabsorption in the kidneys. Recent studies using human stem cells that mimic MODY have provided new insights into beta cell dysfunction. In this article, we discuss the involvement of HNF1A in beta cell dysfunction by reviewing previous studies using genetically modified mice and recent findings in human stem cell-derived beta cells.     

Factors Associated with Platelet Activation-Recent Pharmaceutical Approaches

Platelets are at the forefront of human health and disease following the advances in their research presented in past decades. Platelet activation, their most crucial function, although beneficial in the case of vascular injury, may represent the initial step for thrombotic complications characterizing various pathologic states, primarily atherosclerotic cardiovascular diseases. In this review, we initially summarize the structural and functional characteristics of platelets. Next, we focus on the process of platelet activation and its associated factors, indicating the potential molecular mechanisms involving inflammation, endothelial dysfunction, and miRs. Finally, an overview of the available antiplatelet agents is being portrayed, together with agents possessing off-set platelet-inhibitory actions, while an extensive presentation of drugs under investigation is being given.     

Patent information visualization: the use of social media for its selective dissemination and to leverage innovation

Universal Access in the Information Society - This work describes the development and implementation of a theoretical support model for the creation of an information system that will allow the...     

An innovative method to perform maskless plain waterjet milling for pocket generation: a case study in Ti-based superalloys

This paper presents an innovative methodology/jet path on which plain waterjet (PWJ) can generate pockets of good dimensional/geometrical definition (minimised under/over-erosion) while the proposed method leads to the avoidance of grit embedment on the target workpiece and the elimination of extra cost and time related to the use of mask.The novelty of the paper relies on the proposal of jet-path strategy that minimises the variations in jet dwell time by providing “continuous” relative movement during the jet-part interaction (through minimisation of accelerations/decelerations of the machine head) and by removing a controlled amount of material in a series of layers using special techniques. The proposed method is powerful in its approach from which it ensures (quasi)equal exposure time for each zone of material over which the jet passes, so that the jet path is “totally contained” within the form to be generated; hence, no masking is necessary to define the contour/shape.This approach has been employed for generating pockets on two Ti-based superalloys commonly used in aerospace industries, followed by dimensional, geometrical and surface quality analysis. The results proved that this approach can produce milled surfaces of straightness of the pocket bottom (<200 μm), tolerance on depth of cut per layer (<20 μm), tolerance on the radii at the bottom of the pockets (<100 μm), surface roughness (Ra=4–14 μm) and waviness (Wa=10–13 μm) characteristics in conditions of high surface integrity (no cracks, contaminations, etc.).     

Growth and characterization of Ca5(BO3)3F fiber crystals, a new nonlinear optical material for UV light generation

For the first time, Ca₅(BO₃)₃F (CBF) fiber crystals were grown by the micro-pulling down technique from LiF-based flux. Regular and transparent fibers were obtained with good optical quality. Characterization by Raman spectroscopy and EDX microprobe showed fibers compositionally homogeneous. The specific heat capacity of the fibers was measured indicating a laser damage threshold slightly lower, at room temperature, than for crystals belonging to the related rare earth calcium oxoborate family.     

On the asymptotic behaviour of shells of revolution in free vibration

We consider the free vibration problem of thin shells of revolution of constant type of geometry, focusing on the asymptotic behaviour of the lowest eigenfrequency, as the thickness tends to zero. Numerical experiments are computed using two discretization methods, collocation and finite elements, each corresponding to a different shell model. Our results are in agreement with theoretical results obtained using interpolation theory and cited in literature.     

Anticoagulant, Antioxidant and Antitumor Activities of Heterofucans from the Seaweed Dictyopteris delicatula

In the present study, six families of sulfated polysaccharides were obtained from seaweed Dictyopteris delicatula by proteolytic digestion, followed by acetone fractionation and molecular sieving on Sephadex G-100. Chemical analyses demonstrated that all polysaccharides contain heterofucans composed mainly of fucose, xylose, glucose, galactose, uronic acid, and sulfate. The fucans F0.5v and F0.7v at 1.0 mg/mL showed high ferric chelating activity (～45%), whereas fucans F1.3v (0.5 mg/mL) showed considerable reducing power, about 53.2% of the activity of vitamin C. The fucan F1.5v presented the most prominent anticoagulant activity. The best antiproliferative activity was found with fucans F1.3v and F0.7v. However, F1.3v activity was much higher than F0.7v inhibiting almost 100% of HeLa cell proliferation. These fucans have been selected for further studies on structural characterization as well as in vivo experiments, which are already in progress.     

Study on the real-time size distribution of smoke particles for each fire stage by using a steady-state tube furnace method

For the analysis of the adverse effects of smoke on health, it is essential to determine the amount and location of smoke particles deposited in the respiratory tract. However, the deposition characteristics of the particles are influenced by their morphology and size distribution. Moreover, the real-time particle size distribution during inhalation is important for determining smoke particle deposition in the lungs. Smoke particles generated under different fire conditions differ in their physical and chemical characteristics. Thus, there is a need to adopt international standard methods for characterizing the particles generated in fire. In the present study, the size distributions together with morphology of smoke particles were measured for each fire stage by using the steady-state tube furnace method given in ISO/TS 19700. The size distributions of smoke particles from wood and polypropylene (PP) were measured in real time by using an electric low-pressure impactor (ELPI⁺), and their morphologies were analyzed using transmission electron microscopy (TEM).     

Using backward elimination with a new model order reduction algorithm to select best double mixture model for document clustering

Probabilistic latent semantic analysis (PLSA) is a double structure mixture model which has got a wide application in text and web mining. This method is capable of establishing hidden semantic relations among the observed features, using a number of latent variables. In this approach, the selection of the correct number of latent variables is critical. In the most of the previous researches, the number of latent topics was selected based on the number of invoked classes. This paper presents a method, based on backward elimination approach, which is capable of unsupervised order selection in PLSA. This method starts with a model having a number of components more than the needed value, and then prunes the mixtures to reach their optimum size. During the elimination process, proper selection of some latent variables which must be deleted is the most essential problem, and its relation to the final performance of the pruned model is straightforward. To treat this problem, we introduce a new combined pruning method which selects the best options for removal, while keeping a low computational cost, at all. We conducted some experiments on two datasets from Reuters-21578 corpus. The obtained results show that this algorithm leads to an optimized number of latent variables and in turn achieves better clustering performance compared to the conventional model selection methods. It also shows superiority over the case in which a PLSA model with a fixed number of latent variables, equal to the real number of clusters, is exploited.     

Knowledge-based system for safety control of damaged ship

The maritime casualties cause serious consequences such as loss of life, property and maritime pollution. Therefore, the large-scaled casualties will be derived from loss of structural strength and stability due to the progressive flooding and enlargement of damage by the effect of wave and wind. The improvement of damage survivability is very important in maritime safety. In this paper, the knowledge-based system which could improve the safety level of stability and longitudinal strength through posture control of a damaged ship is studied. The system has been incorporated to interface with user to develop an ‘operationally practical’ action list based on ballasting to improve the ship's structural safety and stability status.