Termination of second trimester pregnancy with laminaria and intramuscular 16 phenoxy-ω-17,18,19,20 tetranor PGE2 methylsuldonylamide (sulprostone) — A randomised study

16 phenoxy-ω-17,18,19,20 tetranor PGE₂ methylsulfonylamide (Sulprostone) was used for termination of second trimester pregnancy in four groups of 30 patients. The drug was administered in intramuscular doses of either 0.5 mg four hourly or 1.0 mg 8 hourly. In two groups of 30 patients a medium size sterile laminaria was inserted into the cervical canal eight hours before the start of prostaglandin treatment. In the group treated with 1.0 mg sulprostone eight hourly, 96.7% of those with laminaria and 86.7% without laminaria aborted in respective mean times of 11.2 hrs and 17.5 hrs. All 30 patients (100%) in the laminaria group treated with 0.5 mg sulprostone four hourly aborted within 30 hours in a mean time of 10.4 hours compared with 26 patients (86.7%) in a mean time of 16.7 hours in the group without laminaria.One patient receiving 0.5 mg sulprostone four hourly (no laminaria) sustained a cervical tear requiring repair. The incidence of nausea, vomiting, diarrhoea, cold and shivering was low and similar in the four groups.     

A bioassay for mefloquine.

A bioassay method that allows for the estimation of serum concentrations of mefloquine is presented. Concentrations obtained by bioassay and high performance liquid chromatography showed a good correlation. This bioassay should be helpful in assessing prophylactic/treatment failures to mefloquine under field conditions.     

Maximum entropy modeling of short sequence motifs with applications to RNA splicing signals.

We propose a framework for modeling sequence motifs based on the maximum entropy principle (MEP). We recommend approximating short sequence motif distributions with the maximum entropy distribution (MED) consistent with low-order marginal constraints estimated from available data, which may include dependencies between nonadjacent as well as adjacent positions. Many maximum entropy models (MEMs) are specified by simply changing the set of constraints. Such models can be utilized to discriminate between signals and decoys. Classification performance using different MEMs gives insight into the relative importance of dependencies between different positions. We apply our framework to large datasets of RNA splicing signals. Our best models out-perform previous probabilistic models in the discrimination of human 5' (donor) and 3' (acceptor) splice sites from decoys. Finally, we discuss mechanistically motivated ways of comparing models.     

Potential Interaction of Plasmodium falciparum Hsp60 and Calpain

After invasion of red blood cells, malaria matures within the cell by degrading hemoglobin avidly. For enormous protein breakdown in trophozoite stage, many efficient and ordered proteolysis networks have been postulated and exploited. In this study, a potential interaction of a 60-kDa Plasmodium falciparum (Pf)-heat shock protein (Hsp60) and Pf-calpain, a cysteine protease, was explored. Pf-infected RBC was isolated and the endogenous Pf-Hsp60 and Pf-calpain were determined by western blot analysis and similar antigenicity of GroEL and Pf-Hsp60 was determined with anti-Pf-Hsp60. Potential interaction of Pf-calpain and Pf-Hsp60 was determined by immunoprecipitation and immunofluorescence assay. Mizoribine, a well-known inhibitor of Hsp60, attenuated both Pf-calpain enzyme activity as well as P. falciparum growth. The presented data suggest that the Pf-Hsp60 may function on Pf-calpain in a part of networks during malaria growth.     

An Analytical Planning Model to Estimate the Optimal Density of Charging Stations for Electric Vehicles

The charging infrastructure location problem is becoming more significant due to the extensive adoption of electric vehicles. Efficient charging station planning can solve deeply rooted problems, such as driving-range anxiety and the stagnation of new electric vehicle consumers. In the initial stage of introducing electric vehicles, the allocation of charging stations is difficult to determine due to the uncertainty of candidate sites and unidentified charging demands, which are determined by diverse variables. This paper introduces the Estimating the Required Density of EV Charging (ERDEC) stations model, which is an analytical approach to estimating the optimal density of charging stations for certain urban areas, which are subsequently aggregated to city level planning. The optimal charging station’s density is derived to minimize the total cost. A numerical study is conducted to obtain the correlations among the various parameters in the proposed model, such as regional parameters, technological parameters and coefficient factors. To investigate the effect of technological advances, the corresponding changes in the optimal density and total cost are also examined by various combinations of technological parameters. Daejeon city in South Korea is selected for the case study to examine the applicability of the model to real-world problems. With real taxi trajectory data, the optimal density map of charging stations is generated. These results can provide the optimal number of chargers for driving without driving-range anxiety. In the initial planning phase of installing charging infrastructure, the proposed model can be applied to a relatively extensive area to encourage the usage of electric vehicles, especially areas that lack information, such as exact candidate sites for charging stations and other data related with electric vehicles. The methods and results of this paper can serve as a planning guideline to facilitate the extensive adoption of electric vehicles.