Pharmacophore Synergism in Diverse Scaffold Clinches in Aurora Kinase B

Aurora kinase B (AKB) is a crucial signaling kinase with an important role in cell division. Therefore, inhibition of AKB is an attractive approach to the treatment of cancer. In the present work, extensive quantitative structure–activity relationships (QSAR) analysis has been performed using a set of 561 structurally diverse aurora kinase B inhibitors. The Organization for Economic Cooperation and Development (OECD) guidelines were used to develop a QSAR model that has high statistical performance (R²_tr = 0.815, Q²_LMO = 0.808, R²_ex = 0.814, CCC_ex = 0.899). The seven-variable-based newly developed QSAR model has an excellent balance of external predictive ability (Predictive QSAR) and mechanistic interpretation (Mechanistic QSAR). The QSAR analysis successfully identifies not only the visible pharmacophoric features but also the hidden features. The analysis indicates that the lipophilic and polar groups—especially the H-bond capable groups—must be present at a specific distance from each other. Moreover, the ring nitrogen and ring carbon atoms play important roles in determining the inhibitory activity for AKB. The analysis effectively captures reported as well as unreported pharmacophoric features. The results of the present analysis are also supported by the reported crystal structures of inhibitors bound to AKB.     

Metal ion sensing and light activated antimicrobial activity of aloe-vera derived carbon dots

Carbon dots (CDs) have emerged out as a potential material amongst the carbon family for a wide range of applications including chemical/biological sensing, photocatalysis, bioimaging, etc. The green synthesis of these CDs from natural sources is gaining the significant interest of peer community for their wide utility. Herein, we present a facile one-step pyrolysis method for CDs synthesis from Aloe-Vera extract, which show bright blue luminescence under UV light with a quantum yield of 12.3%. Further, ex-situ morphological, structural and optical characterizations reveal their high quality and excitation independent emission behavior with the presence of carboxyl, hydroxyl functional groups. Furthermore, these CDs were studied for Fe(III) sensing in water without any surface modifications and assessed for their light activated antibacterial activity against E.Coli and Staphylococcus aureus.     

Large-scale compressed hydrogen storage as part of renewable electricity storage systems

Storing energy in the form of hydrogen is a promising green alternative. Thus, there is a high interest to analyze the status quo of the different storage options. This paper focuses on the large-scale compressed hydrogen storage options with respect to three categories: storage vessels, geological storage, and other underground storage alternatives. In this study, we investigated a wide variety of compressed hydrogen storage technologies, discussing in fair detail their theory of operation, potential, and challenges. The analysis confirms that a techno-economic chain analysis is required to evaluate the viability of one storage option over another for a case by case. Some of the discussed technologies are immature; however, this does not rule out these technologies; rather, it portrays the research opportunities in the field and the foreseen potential of these technologies. Furthermore, we see that hydrogen would have a significant role in balancing intermittent renewable electricity production.     

Fast and stable bayesian image expansion using sparse edge priors.

Smoothness assumptions in traditional image expansion cause blurring of edges and other high-frequency content that can be perceptually disturbing. Previous edge-preserving approaches are either ad hoc, statistically untenable, or computationally unattractive. We propose a new edge-driven stochastic prior image model and obtain the maximum a posteriori (MAP) estimate under this model. The MAP estimate is computationally challenging since it involves the inversion of very large matrices. An efficient algorithm is presented for expansion by dyadic factors. The technique exploits diagonalization of convolutional operators under the Fourier transform, and the sparsity of our edge prior, to speed up processing. Visual and quantitative comparison of our technique with other popular methods demonstrates its potential and promise.     

Simultaneous area and delay minimum K-LUT mapping for K-exact networks

We address the technology mapping problem for lookup table FPGAs. The area minimization problem, for mapping K-bounded networks, consisting of nodes with at most K inputs, using K-input lookup tables, is known to be NP-complete for K 5. The complexity was unknown for K = 2, 3, and 4. The corresponding delay minimization problem (under the constant delay model) was solved in polynomial time by the flow-map algorithm, for arbitrary values of K. We study the class of K-bounded networks, where all nodes have exactly K inputs. We call such networks K-exact. We give a characterization of mapping solutions for such networks. This leads to a polynomial time algorithm for computing the simultaneous area and delay minimum mapping for such networks using K-input lookup tables. We also show that the flow-map algorithm computes the same mapping solution as our algorithm. We then show that for K = 2 the mapping solution for a 2-bounded network, minimizing the area and delay simultaneously, can be easily obtained from that of a 2-exact network derived from it by eliminating single input nodes. Thus the area minimization problem for 2-input lookup tables can be solved in polynomial time, resolving an open problem.     

Do the diminishing efficacy and increasing toxicity of sodium stibogluconate in the treatment of visceral leishmaniasis in Bihar, India, justify its continued use as a first-line drug? An observational study of 80 cases

The results of recent investigations of the analgesic and the nonanalgesic effects of opioid glucuronides are relevant to the research on drug abuse in forensic toxicology. As has been shown for heroin, knowledge of the state of distribution and elimination of active and inactive metabolites and glucuronides offers new possibilities in forensic interpretation of analytic results. Because of similar metabolic degradation, calculation of the time-dependent ratio of the concentration of morphine and its glucuronide metabolites in blood or serum allows a rough estimation of increased dosage and of time elapsed since the last application. Drug effects can be examined with respect to individual case histories, including overdose and survival time if the patient died. However, different methods of administration and the strong influence of different volumes or compartments of distribution of parent compounds and metabolites on concentrations in human body tissues require careful use of glucuronide concentration data. In Germany, dihydrocodeine (DHC) is prescribed as a heroin substitute, and relative overdoses are needed to be effective. DHC metabolism was studied in three patients who died from overdoses. All metabolites (dihydrocodeine-6-glucuronide [DHC6], nor-DHC [NDHC], dihydromorphine [DHM], nor-DHM [NDHM], and DHM-3- and 6-glucuronide [DHM3G, DHM6G]) were determined using HPLC and fluorescence detection. Concentrations of DHM (0.16 mg/L to 0.22 mg/L serum) were found. The DHM glucuronide ratios were similar to those of morphine. Receptor binding studies showed that the binding affinity of DHM to porcine mu-receptor was higher than that of morphine, and DHM6G's binding affinity was as high as that of morphine-6-glucuronide (M6G). Metabolites may play an important role in the effectiveness of DHC in substitution and toxicity. Because of enzyme polymorphism, the formation of DHC poses a risk for proper dosage in patients who are either poor or extensive metabolizers. The distribution of opioid glucuronides in cerebral spinal fluid in relation to transcellular transport in central nervous tissue is discussed with respect to the receptor binding of opiates and drug effect.