Design of Trehalose-Based Amide/Sulfonamide C-type Lectin Receptor Signaling Compounds

Mincle agonists have been shown to induce inflammatory cytokine production, such as tumor necrosis factor-alpha (TNF) and promote the development of a Th1/Th17 immune response that might be crucial to development of effective vaccination against pathogens such as Mycobacterium tuberculosis. As an expansion of our previous work, a library of 6,6′-amide and sulfonamide α,α-d -trehalose compounds with various substituents on the aromatic ring was synthesized efficiently in good to excellent yields. These compounds were evaluated for their ability to activate the human C-type lectin receptor Mincle by the induction of cytokines from human peripheral blood mononuclear cells. A preliminary structure–activity relationship (SAR) of these novel trehalose diamides and sulfonamides revealed that aryl amide-linked trehalose compounds demonstrated improved activity and relatively high potency cytokine production compared to the Mincle ligand trehalose dibehenate adjuvant (TDB) and the natural ligand trehalose dimycolate (TDM) inducing dose-dependent and human-Mincle-specific stimulation in a HEK reporter cell line.     

In vitro evaluation and in vivo performance of lyophilized gliclazide

Enhancement of the dissolution rate of the poorly water-soluble hypoglycemic agent, gliclazide, by the aid of lyophilization was investigated. Mannitol, sodium lauryl sulfate (SLS) and polyvinyl pyrrolidone (PVP-k-30) were employed in different weight ratios (43%, 56% and 64% w/w, respectively) as water-soluble excipients in the formulation. Lyophilized systems were found to exhibit extremely higher in vitro dissolution rate compared to the unprocessed drug powder. Solid state characterization of the lyophilized systems using X-ray powder diffraction, Fourier transform infrared spectroscopy and differential scanning calorimetry techniques revealed that dissolution enhancement was attributable to transformation of gliclazide from the crystalline to an amorphous state in the solid dispersion formed during the lyophilization process. The gastrointestinal absorption and hypoglycemic effect of the lyophilized gliclazide/SLS system were investigated following oral administration to Albino rabbits. C_max and area under the plasma concentration–time curve of gliclazide (AUC_0–12) after administration of the lyophilized formulations were significantly higher than those obtained after administration of the unprocessed gliclazide.     

Zooplankton population in the river tigris: Effects of samarra impoundment

The influences of the Samarra impoundment on the ecology of the downstream sector of the river Tigris are investigated. Zooplankton were collected monthly from July 1987 to July 1988. It was found that zooplankton were most abundant during high river discharges in March. During the month of low river discharge, September, the zooplankton population was greatly reduced immediately below the barrage and remained so to the last downstream station. Several factors seem to explain such differences. The high discharge from the impoundment was found to be the dominating factor and may flush the small backwaters in which zooplankton were abundant, thus increasing the population in the river. Zooplankton species vary in their ability to sustain populations in the river, variations which are due mainly to species-specific characteristics.     

A hybrid model for spelling error detection and correction for Urdu language

Neural Computing and Applications - Detecting and correcting misspelled words in a written text are of great importance in many natural language processing applications. Errors can be broadly...     

The Complex and Critical Role of Glycine 12 (G12) in Beta-Connexins of Human Skin

Glycine is an amino acid with unique properties because its side chain is composed of a single hydrogen atom. It confers conformational flexibility to proteins and conserved glycines are often indicative of protein domains involving tight turns or bends. All six beta-type connexins expressed in human epidermis (Cx26, Cx30, Cx30.3, Cx31, Cx31.1 and Cx32) contain a glycine at position 12 (G12). G12 is located about halfway through the cytoplasmic amino terminus and substitutions alter connexin function in a variety of ways, in some cases altering protein interactions and leading to cell death. There is also evidence that alteration of G12 changes the structure of the amino terminus in connexin- and amino acid- specific ways. This review integrates structural, functional and physiological information about the role of G12 in connexins, focusing on beta-connexins expressed in human epidermis. The importance of G12 substitutions in these beta-connexins is revealed in two hereditary skin disorders, keratitis ichthyosis and erythrokeratodermia variabilis, both of which result from missense mutations affecting G12.     

The Role of Deep Learning in Parking Space Identification andPredictionSystems

In today’s smart city transportation, traffic congestion is a vexing issue, and vehicles seeking parking spaces have been identified as one of the causes leading to approximately 40% of traffic congestion. Identifying parking spaces alone is insufficient because an identified available parking space may have been taken by another vehicle when it arrives, resulting in the driver’s frustration and aggravating traffic jams while searching for another parking space. This explains the need to predict the availability of parking spaces. Recently, deep learning (DL) has been shown to facilitate drivers to find parking spaces efficiently, leading to a promising performance enhancement in parking identification and prediction systems. However, no work reviews DL approaches applied to solve parking identification and prediction problems. Inspired by this gap, the purpose of this work is to investigate, highlight, and report on recent advances in DL approaches applied to predict and identify the availability of parking spaces. A taxonomy of DL-based parking identification and prediction systems is established as a methodology by classifying and categorizing existing literature, and by doing so, the salient and supportive features of different DL techniques for providing parking solutions are presented. Moreover, several open research challenges are outlined. This work identifies that there are various DL architectures, datasets, and performance measures used to address parking identification and prediction problems. Moreover, there are some open-source implementations available that can be used directly either to extend existing works or explore a new domain. This is the first short survey article that focuses on the use of DL-based techniques in parking identification and prediction systems for smart cities. This study concludes that although the deployment of DL in parking identification and prediction systems provides various benefits, the convergence of these two types of systems and DL brings about new issues that must be resolved in the near future.     

A model to measure QoE for virtual personal assistant

Until now the virtual assistants (like Siri, Google Now and Cortana) have primarily been confined to voice input and output only. Is there a justification for voice only confinement or can we enhance the user experience by adding a visual output? We hypothesized that providing a higher level of visual/auditory immersion would enhance the quality of user experience. In order to test this hypothesis, we first developed 4 variants of virtual assistant, each with a different audio/visual level of immersion. Developed virtual assistant systems were the following; audio only, audio and 2D visual display, audio and 3D visual display and audio and immersive 3D visual display. We developed a plan for usability testing of all 4 variants. The usability testing was conducted with 30 subjects against eight (8) dependent variables included presence, involvement, attention, reliability, dependency, easiness, satisfaction and expectations. Each subject rated these dependent variables based on a scale of 1–5, 5 being the highest value. The raw data collected from usability testing was then analyzed through several tools in order to determine the factors contributing towards the quality of experience for each of the 4 variants. The significant factors were then used develop a model that measures the quality of user experience. It was found that each variant had a different set of significant variables. Hence, in order to rate each system there is a need to develop a scale that is dependent upon the unique set of variables for the respective variant. Furthermore, it was found that variant 4 scored the highest rate for Quality of Experience (QoE). Lastly several other qualitative conclusions were also drawn from this research that will guide future work in the field of virtual assistants.