Quantitative pharmacophore models with inductive logic programming

Three-dimensional models, or pharmacophores, describing Euclidean constraints on the location on small molecules of functional groups (like hydrophobic groups, hydrogen acceptors and donors, etc.), are often used in drug design to describe the medicinal activity of potential drugs (or ‘ligands’). This medicinal activity is produced by interaction of the functional groups on the ligand with a binding site on a target protein. In identifying structure-activity relations of this kind there are three principal issues: (1) It is often difficult to “align” the ligands in order to identify common structural properties that may be responsible for activity; (2) Ligands in solution can adopt different shapes (or `conformations’) arising from torsional rotations about bonds. The 3-D molecular substructure is typically sought on one or more low-energy conformers; and (3) Pharmacophore models must, ideally, predict medicinal activity on some quantitative scale. It has been shown that the logical representation adopted by Inductive Logic Programming (ILP) naturally resolves many of the difficulties associated with the alignment and multi-conformation issues. However, the predictions of models constructed by ILP have hitherto only been nominal, predicting medicinal activity to be present or absent. In this paper, we investigate the construction of two kinds of quantitative pharmacophoric models with ILP: (a) Models that predict the probability that a ligand is “active”; and (b) Models that predict the actual medicinal activity of a ligand. Quantitative predictions are obtained by the utilising the following statistical procedures as background knowledge: logistic regression and naive Bayes, for probability prediction; linear and kernel regression, for activity prediction. The multi-conformation issue and, more generally, the relational representation used by ILP results in some special difficulties in the use of any statistical procedure. We present the principal issues and some solutions. Specifically, using data on the inhibition of the protease Thermolysin, we demonstrate that it is possible for an ILP program to construct good quantitative structure-activity models. We also comment on the relationship of this work to other recent developments in statistical relational learning. Editors: Tamás Horváth and Akihiro Yamamoto     

MANAGING DISTRIBUTED COMPUTING Five Practices for Success

Management of distributed environments requires corporate IS managers to shift from being operators of a central utility to facilitators who can recognize the synergy among loosely related groups of users. Success depends on the development of new ways of visualizing and measuring the service delivery process.     

Kinetic analysis of papaya proteinase omega

Papaya proteinase omega (pp omega) has been purified from dried latex both by immunoaffinity and traditional methods. Kinetic analysis revealed that (1), the pp omega-catalysed hydrolysis of N-benzoyl-L-arginine p-nitroanilide (BApNA) has a lower specificity (kcat/Km) than the same reaction catalysed by papain; (2), the pp omega-catalysed hydrolysis of a tripeptide substrate having phenylalanine at the second position (S2-site) showed a more similar specificity to that catalysed by papain; (3), the significant difference between the two enzymes is that steady state kinetics with both L-BApNA and a tripeptide enables the identification in pp omega of other ionizations affecting binding. The active sites of papain and pp omega can therefore be distinguished by pH-dependence of kcat/Km.     

Simulation of magnetic component models in electric circuitsincluding dynamic thermal effects

It is essential in the simulation of power electronics applications to model magnetic components accurately. In addition to modeling the nonlinear hysteresis behavior, eddy currents and winding losses must be included to provide a realistic model. In practice the losses in magnetic components give rise to significant temperature increases which can lead to major changes in the component behavior. In this paper a model of magnetic components is presented which integrates a nonlinear model of hysteresis, electro-magnetic windings and thermal behavior in a single model for use in circuit simulation of power electronics systems. Measurements and simulations are presented which demonstrate the accuracy of the approach for the electrical, magnetic and thermal domains across a variety of operating conditions, including static thermal conditions and dynamic self heating     

What We Mean by Future-Proofing

Perhaps the most powerful claim that advocates of fiber can make,on top of the massive bandwidthfiber makes possible today, is that fiber is future-proof. That is, the fiber that is laid today can be upgraded so that the same strands of glass can carry massively more bandwidth in the future.     

Renal length in sickle cell disease: observations from a cohort study

Renal length has been measured by ultrasound in 237 subjects with homozygous sickle cell (SS) disease, 147 with sickle cell-hemoglobin C (SC) disease, and in 78 age-matched controls with a normal hemoglobin (AA) genotype. As expected, renal length increased with age in all genotypes but mean length was significantly greater in SS disease compared with SC disease (mean difference 4.3 mm after adjustment for height) and significantly greater in both genotypes than in AA controls (SS/AA difference 9.2 mm, SC/AA difference 5.0 mm after adjustment for height). Examination of relationships between renal length and some hematological indices (hemoglobin, fetal hemoglobin, reticulocyte counts, alpha thalassemia status) in SS or SC disease showed only a significant negative correlation with hemoglobin and positive correlation with reticulocyte count in SS disease. Further analysis suggested that the stronger relationship was between renal length and high reticulocyte count. The mechanism of renal enlargement is unknown although glomerular hypertrophy and increased renal blood volume are likely contributors.     

Value of transcranial Doppler indices in predicting raised ICP in infantile hydrocephalus. A study with review of the literature

Cerebral hemodynamic changes in infants with progressive hydrocephalus have been studied with the transcranial Doppler (TCD) technique. Several authors have referred to the correlation between the hemodynamic changes and increased intracranial pressure (ICP). Despite conflicting conclusions on the value of pulsatility index (PI) and resistance index (RI) measurements for monitoring infantile hydrocephalus, these pulsatility indices are the most commonly used for this purpose. Although clinical signs of raised ICP are highly variable and unreliable in infants, assumptions have been made in most of the studies about the presence of elevated ICP on the basis of the patient's clinical state. Few studies have reported on actual ICP values, however, and a direct relationship between ICP and TCD changes has never been adequately demonstrated. In the present study, this relationship was investigated in long-term simultaneous TCD/ICP measurements, in an attempt to develop a noninvasive method of monitoring the effect of ICP on intracranial hemodynamics. Two groups of data sets were established. Group I consisted of pre- and postoperative (shunt implantation) TCD/ICP measurements. Group II were long-term simultaneous TCD/ICP recordings showing significant ICP variations. In most of the postoperative measurements there was a decrease in the average PI and RI values. The correlation between PI or RI and ICP in the long-term simultaneous recordings, however, was generally poor. The risk of obtaining false positive or false negative PI or RI values in short-term measurements was also demonstrated. It can be concluded from our results, besides the wide range of reference values for the Doppler indices and extracranial influences upon them, that the present Doppler indices are inadequate for monitoring the complex intracranial dynamic responses in patients with raised ICP.     

Proceedings of the Joint US/EU Workshop: urinary biomarkers to detect significant effects of environmental and occupational exposure to nephrotoxins

Tear cytokines and growth factors are likely to modulate the wound healing process following corneal epithelial injury. Hepatocyte growth factor (HGF) is a paracrine mediator of epithelial proliferation, motility, and differentiation that is produced by keratocytes and the lacrimal gland. Tear samples were collected preoperatively and one, two, and seven days postoperatively in eyes undergoing excimer laser surface ablation [photorefractive keratoplasty (PRK) or phototherapeutic keratoplasty (PTK)]. Tear HGF concentration was measured with a sensitive ELISA assay. Tear HGF production was calculated using the tear flow rate in the collection capillary and HGF concentration. Although the instantaneous concentration of HGF in tears decreased significantly in the days following PRK, a large increase in tear flow resulted in a marked increase in HGF bioavailability. The heparin-binding characteristics of HGF would result in increased binding to glycosaminoglycans and other heparin-like matrix components and, therefore, increased growth factor availability to the cognate recptor. This is the first report documenting changes in tear film HGF production. HGF may have an important function in maintenance and wound healing of the ocular surface epithelium since HGF is present in the normal tear film and the HGF secretion rate increases markedly in parallel with aqueous tear production following corneal surgical injury.