Formulation design,in vitro characterizations and anti-malarial investigations of artemether and lumefantrine-entrapped solid lipid microparticles

Context: Poor aqueous solubility of artemether and lumefantrine makes it important to seek better ways of enhancing their oral delivery and bioavailability.

Objective: To formulate and carry out in vitro and anti-malarial pharmacodynamic evaluations of solidified reverse micellar solutions (SRMS)-based solid lipid microparticles (SLMs) of artemether and lumefantrine for oral delivery and improved bioavailability.

Materials and methods: Rational blends of Softisan^®154 and Phospholipon^®90H lipid matrices, and different concentrations of artemether and lumefantrine were used to formulate several batches of SLMs. Drug-free SLMs were also formulated. Morphology, particle size, encapsulation efficiency (EE%) and pH studies were performed. In vitro release studies were performed in alcoholic buffer, simulated gastric fluid (SGF) and simulated intestinal fluid (SIF) without enzymes. Anti-malarial pharmacodynamic studies were conducted in mice.

Results: Stable, smooth and spherical particles with sizes ranging from 4.2?±?0.02 to 9.3?±?0.8?µm were formed. EE% of 92.2–97.3% and 30.2–84.7% and pH of 3.0?±?0.02 to 4.9?±?0.12 and 3.0?±?0.02 to 5.8?±?0.05 were obtained for artemether and lumefantrine SLMs, respectively. Release of 100, 88.28 and 75.49%, as well as 63.26, 34.31 and 56.17% were recorded for artemether and lumefantrine in alcoholic buffer, SGF and SIF, respectively. Pharmacodynamic studies indicated very significant (p?Conclusion: Oral delivery and bioavailability of artemether and lumefantrine could be improved using SRMS-based SLMs.     

Polyphosphoinositide synthesis in human neutrophils. Effects of a low metabolic energy state

Phosphatidylinositol (PtdIns) synthesis and polyphosphoinositide (PPI) formation were measured as the incorporation of [32P]orthophosphate ([32P]Pi) or [3H]inositol into non-stimulated intact human neutrophil membrane phospholipids. The rate of PtdIns "de novo" synthesis appeared to be a slow mechanism when compared to the rapid incorporation of [32P]Pi into PPIs. Of the "de novo" synthesized [3H]PtdIns, 70% was further phosphorylated to PPI. Nevertheless, this PPI pool represented less than 0.01% of the total nmols of PPIs formed evaluated as [32P]Pi labeling, indicating that PPI formation mainly involves a no "de novo" synthesized phosphatidylinositol pool. When evaluated at short incubation times, oscillations in the formation of PPIs were detected. A rapid phase was characterized after 30 s of incubation with [32P]Pi Phosphorylation levels returned to an equilibrium state within a minute, and the second phase peaked at 5 min., returning to equilibrium at 15 min. The fluctuant kinetics though not the equilibrium level of PPI formation, could be abolished by neomycin. On the other hand, a selective inhibition of the rapid phase of PPI synthesis occurred in the presence of the tyrosine kinase inhibitor genistein. When the incorporations of [gamma-32P]-adenosine triphosphate (ATP) or [32P]Pi into human neutrophil particulate fraction membranes were evaluated, PPIs synthesis showed fluctuations independently of the precursor used. Noticeably, [32P]from [32P]Pi was incorporated more efficiently into PPIs than that from [gamma-32P]ATP, when evaluated in parallel using equal specific activities for both radiolabeled precursors and under non-ATP synthesizing conditions. Moreover, the incorporation of [32P]Pi into particulate fraction PPIs was not abolished by high concentrations of non-radiolabeled ATP, and metabolically inhibited PMNs showed high rates of PPI synthesis. These data suggest that PPI formation is not necessarily a futile cycle in PMNs.     

Age differences in identifying words in synthetic speech

OBJECTIVES: We investigated whether context or different speech rates could improve older adult performance on identification of synthetically generated words. BACKGROUND: Synthetic speech systems can potentially improve the daily functioning of older adults. However, research must determine whether older adults can effectively implement current text-to-speech technologies, which few studies have examined. Older adults' sensory and cognitive declines may cause difficulties in identifying words in synthetic speech. METHODS: Ninety-six participants (young, middle-aged, and older adults) identified auditory monosyllabic words (half natural, half synthetic) presented in isolation or at the ends of sentences. Participants heard speech at either normal or slower rates. RESULTS: We found an interaction of age, context, and voice type and that slower speech rates worsened performance for all groups. Contrasts revealed that context reduced age differences, though only for natural speech. Hearing acuity was highly correlated with age and fully accounts for the interaction. CONCLUSIONS: Context improves performance for everyone in natural speech. However, whereas context improves performance for synthetic speech, it does not differentially reduce the age impairment for older adults. Slower speed generally impairs everyone's performance compared with the normal rate. APPLICATIONS: Systems using synthetic speech should avoid presenting words in isolation, and rich contextual support should be consistently adopted. Synthetic speech fidelity must be improved significantly before becoming truly useful for older adult populations.     

A nucleolus-associated coiled body

One or two healthy structures frequently have been observed attached to nucleoli in facial motor neurons of the golden hamster. These round-to-oval structures, called "coiled bodies", were seen at 15, 19, and 24 days postnatal and in the adult, both in normal neurons and in chromatolytic neurons which had been axotomized 4 days previously. With one exception, the coiled bodies were seen to be attached via fibrillar material to the nucleolar periphery. Although the numbers of coiled bodies may be altered during neuronal maturation and as a result of axon section, the bodies revealed no structural alterations that could be attributed to developmental age or to experimental trauma.     

Symbolic connectionism in natural language disambiguation

Natural language understanding involves the simultaneous consideration of a large number of different sources of information. Traditional methods employed in language analysis have focused on developing powerful formalisms to represent syntactic or semantic structures along with rules for transforming language into these formalisms. However, they make use of only small subsets of knowledge. This article describes how to use the whole range of information through a neurosymbolic architecture which is a hybridization of a symbolic network and subsymbol vectors generated from a connectionist network. Besides initializing the symbolic network with prior knowledge, the subsymbol vectors are used to enhance the system's capability in disambiguation and provide flexibility in sentence understanding. The model captures a diversity of information including word associations, syntactic restrictions, case-role expectations, semantic rules and context. It attains highly interactive processing by representing knowledge in an associative network on which actual semantic inferences are performed. An integrated use of previously analyzed sentences in understanding is another important feature of our model. The model dynamically selects one hypothesis among multiple hypotheses. This notion is supported by three simulations which show the degree of disambiguation relies both on the amount of linguistic rules and the semantic-associative information available to support the inference processes in natural language understanding. Unlike many similar systems, our hybrid system is more sophisticated in tackling language disambiguation problems by using linguistic clues from disparate sources as well as modeling context effects into the sentence analysis. It is potentially more powerful than any systems relying on one processing paradigm     

A general compiler framework for speculative multithreaded processors

Speculative multithreading (SpMT) promises to be an effective mechanism for parallelizing nonnumeric programs, which tend to have irregular and pointer-intensive data structures and complex flows of control. Proper thread formation is crucial for obtaining good speedup in an SpMT system. This paper presents a compiler framework for partitioning a sequential program into multiple threads for parallel execution in an SpMT system. This framework is very general and supports speculative threads, nonspeculative threads, loop-centric threads, and out-of-order thread spawning. It is therefore useful for compiling for a wide variety of SpMT architectures. For effective partitioning of programs, the compiler uses profiling, interprocedural pointer analysis, data dependence information, and control dependence information. The compiler is implemented on the SUIF-MachSUIF platform. A simulation-based evaluation of the generated threads shows that the use of nonspeculative threads and nonloop speculative threads provides a significant increase in speedup for nonnumeric programs.     

The performance characteristics of a novel multi-electrode electromagnetic flowmeter

The design of a novel multi-electrode electromagnetic flowmeter, which provides nine conventional electromagnetic flowmeters housed in a single body, has been used in adverse flow conditions immediately downstream from a header tank. The results show that careful initial calibration, in accord with the pipeline conditions recommended in international standards, enables errors of under 1% to be achieved. The results show that the two electrode planes closest to the header provide results with the greatest errors. The performance with the electrodes mounted in the vertical plane is generally better than that achieved with the electrodes mounted in the horizontal plane. Pressure measurements together with laser Doppler anemometry (LDA) and particle image velocimetry (PIV) techniques have been used to provide details of the magnitude of the disturbance caused to the flow field by the header and outflow combination.     

Propagation of Data Error and Parametric Sensitivity in Computable General Equilibrium Models

While computable general equilibrium (CGE) models are a well-established tool in economic analyses, it is often difficult to disentangle the effects of policies of interest from that of the assumptions made regarding the underlying calibration data and model parameters. To characterize the behavior of a CGE model of carbon output with respect to two of these assumptions, we perform a large-scale Monte Carlo experiment to examine its sensitivity to base year calibration data and elasticity of substitution parameters in the absence of a policy change. By examining a variety of output variables at different levels of economic and geographic aggregation, we assess how these forms of uncertainty impact the conclusions that can be drawn from the model simulations. We find greater sensitivity to uncertainty in the elasticity of substitution parameters than to uncertainty in the base-year data as the projection period increases. While many model simulations were conducted to generate large output samples, we find that few are required to capture the mean model response of the variables tested. However, characterizing standard errors and empirical probability distribution functions is not possible without a large number of simulations.