PREDICTION OF NETILMICIN DISPOSITION IN NEONATES

Multiple regression analyses of data from 33 neonates who received netilmicin therapy showed that concurrent treatment with other drugs (Drg), creatinine clearance (CL(cr)), gestational age (GA), and an apgar score of less than 6 at 1 min (Agl') were significant determinants of netilmicin clearance. Apparent volume of distribution was significantly affected by postnatal age (PNA), gender, the presence of ascites and/or oedema (A/O), and whether or not the neonate was small for gestational age (SGA). The following formulae were obtained: CL (ml min-1 kg-1) = -0.108 - 0.210 (Drg) + 0.152(CL(cr)) + 0.019(GA) -0.128(Agl') (multiple R = 0.725, p

Low pressure carbon dioxide solubility in pure electrolyte solvents for lithium-ion batteries as a function of temperature. Measurement and prediction

Experimental values for the carbon dioxide solubility in eight pure electrolyte solvents for lithium ion batteries – such as ethylene carbonate (EC), propylene carbonate (PC), dimethyl carbonate (DMC), ethyl methyl carbonate (EMC), diethyl carbonate (DEC), ?-butyrolactone (?BL), ethyl acetate (EA) and methyl propionate (MP) – are reported as a function of temperature from (283 to 353) K and atmospheric pressure. Based on experimental solubility data, the Henry’s law constant of the carbon dioxide in these solvents was then deduced and compared with reported values from the literature, as well as with those predicted by using COSMO-RS methodology within COSMOthermX software and those calculated by the Peng–Robinson equation of state implemented into Aspen plus. From this work, it appears that the CO2 solubility is higher in linear carbonates (such as DMC, EMC, DEC) than in cyclic ones (EC, PC, ?BL). Furthermore, the highest CO2 solubility was obtained in MP and EA solvents, which are comparable to the solubility values reported in classical ionicliquids. The precision and accuracy of the experimental values, considered as the per cent of the relative average absolute deviations of the Henry’s law constants from appropriate smoothing equations and from literature values, are close to (1% and 15%), respectively. From the variation of the Henry’s law constants with temperature, the partial molar thermodynamic functions of dissolution such as the standard Gibbs free energy, the enthalpy, and the entropy are calculated, as well as the mixing enthalpy of the solvent with CO2 in its hypothetical liquid state.

Serum eosinophilic cationic protein and blood eosinophil counts for the prediction of the presence of airways inflammation in children with wheezing

Background Serum eosinophilic cationic protein (ECP) concentrations may be useful noninvasive markers of airways inflammation in atopic asthma. However, the usefulness of serum ECP measurement for the prediction of airways inflammation in children with a history of wheezing is unknown.

Behavior-Based branch prediction by dynamically clustering branch instructions

Conditional branches frequently exhibit similar behavior (bias, time-varying behavior,...), a property that can be used to improve branch prediction accuracy. Branch clustering constructs groups or clusters of branches with similar behavior and applies different branch prediction techniques to each branch cluster. We revisit the topic of branch clustering with the aim of generalizing branch clustering. We investigate several methods to measure cluster information, with the most effective the storage of information in the branch target buffer. Also, we investigate alternative methods of using the branch cluster identification in the branch predictor. By these improvements we arrive at a branch clustering technique that obtains higher accuracy than previous approaches presented in the literature for the gshare predictor. Furthermore, we evaluate our branch clustering technique in a wide range of predictors to show the general applicability of the method. Branch clustering improves the accuracy of the local history (PAg) predictor, the path-based perceptron and the PPM-like predictor, one of the 2004 CBP finalists.

Fast-track construction with slag cement concrete: Adiabatic strength development and strength prediction

The early-age strength development of concrete containing slag cement has been investigated to give guidance for its use in fast-track construction. Measurements of temperature rise under adiabatic conditions have shown that high levels of slag cement-for example, 70% of the total binder-are required to obtain a significant reduction in the peak temperature rise. Despite these temperature rises being lower than those for portland cement mixtures, however the early-age strength under adiabatic conditions of slag cement concrete can be as high as 250% of the strength of companion cubes cured at 20 degrees C (68 degrees F). The maturity and, hence, strength development were calculated from the adiabatic temperature histories based on several Maturity functions available in the literature. The predicted strength development with age was compared with the experimental results. Maturity functions that take into account the lower ultimate strengths obtained at elevated curing temperatures were found to be better at predicting the strength development.

Stiffness prediction for bolted moment-connections between cold-formed steel members

The authors have recently described a cold-formed steel portal framing system in which simple bolted moment-connections, formed through brackets, were used for the eaves and apex joints. Such connections, however, cannot be considered as rigid because of localised in-plane elongation of the bolt-holes caused by bearing against the bolt-shanks. To therefore predict the initial stiffness of such connections, it is necessary to know the initial bolt-hole elongation stiffness k(b). In this paper, a finite element-solid idealisation of a bolted lap joint in shear will be described that can be used to determine k(b); the results obtained are validated against experimental data. A beam idealisation of a cold-formed steel bolted moment-connection is then described, in which spring elements are used to idealise the rotational flexibility of the bolt-groups resulting from bolt-hole elongation: Using the value of k(b) in the beam idealisation, the deflections predicted are shown to be similar to those measured experimentally in laboratory tests conducted on the apex joint of a cold-formed steel portal frame. (C) 2003 Elsevier Ltd. All rights reserved.

High confidence prediction of essential genes in burkholderia cenocepacia

Essential genes are absolutely required for the survival of an organism. The identification of essential genes, besides being one of the most fundamental questions in biology, is also of interest for the emerging science of synthetic biology and for the development of novel antimicrobials. New antimicrobial therapies are desperately needed to treat multidrug-resistant pathogens, such as members of the Burkholderia cepacia complex.

P2Y(1) antagonists: Combining receptor-based modeling and QSAR for a quantitative prediction of the biological activity based on consensus scoring

P2Y(1) is an ADP-activated G protein-coupled receptor (GPCR). Its antagonists impede platelet aggregation in vivo and are potential antithrombotic agents. Combining ligand and structure-based modeling we generated a consensus model (LIST-CM) correlating antagonist structures with their potencies. We docked 45 antagonists into our rhodopsin-based human P2Y(1) homology model and calculated docking scores and free binding energies with the Linear Interaction Energy (LIE) method in continuum-solvent. The resulting alignment was also used to build QSAR based on CoMFA, CoMSIA, and molecular descriptors. To benefit from the strength of each technique and compensate for their limitations, we generated our LIST-CM with a PLS regression based on the predictions of each methodology. A test set featuring untested substituents was synthesized and assayed in inhibition of 2-MeSADP-stimulated PLC activity and in radioligand binding. LIST-CM outperformed internal and external predictivity of any individual model to predict accurately the potency of 75% of the test set.