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.     

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.     

Increased expression of peripheral benzodiazepine receptors in the facial nucleus following motor neuron axotomy

Peripheral benzodiazepine receptors (PBRs) are expressed in a variety of tissues but are normally found at low levels in the brain. Following various types of nerve injury, a reactive gliosis results that exhibits a high expression of this receptor. To further characterize the expression of PBRs following neuronal injury, we evaluated PBR expression in the facial nucleus following facial nerve axotomy (FNA). Injury to a peripheral nerve results in a complex series of metabolic and morphological changes around the injured neuron. Transections of the facial nerve results in a rapid activation of both astrocytes and microglia around axotomized motor neurons. FNA resulted in an increase in the staining for both astrocytes (glial fibrillary acidic protein) and activated microglia (OX42). There was also a reduction in synaptic contacts with the motor nucleus as evidenced by reduced staining for the synaptic marker, synaptophysin. In sections labeled with [3H]-PK11195, the subsequent autoradiograms displayed marked increases in the labeling for PBRs. This increase was observed at 5, 7 and 10 days after nerve transection. The increase was primarily in the level of expression (Bmax), with no change in the affinity of the ligand (Kd). The increase in PBR expression after FNA supports the hypothesis that PBRs can be used as a sensitive marker for CNS injury.     

Aesthetic outcome of breast implant removal in 85 consecutive patients

As we began to see increasing numbers of women concerned about their gel-filled breast implants, we became aware that we could not advise them with any degree of confidence what they might expect in terms of aesthetic result after implant removal. We decided to review the records and outcomes over a 2-year period of a number of patients who underwent implant removal. Eighty-five consecutive patients were reviewed, 69 of whom had undergone cosmetic augmentation and 16 of whom had breast reconstruction with silicone gel implant(s). Thirty-nine of the 69 cosmetic augmentation patients had removal of implants alone, and 27 had removal accompanied by mastopexy. Three had reaugmentation with saline-filled implants; one had replacement with saline-filled implants. Fifteen of the 16 reconstruction patients underwent autogenous tissue transfer. Preoperative and postoperative photographs of all patients were mixed randomly and rated by two independent raters in four aesthetic categories on a five-point scoring system. Repeatability was measured several weeks later, when each rater scored randomly selected photographs from this patient pool. The patients also performed their own outcome evaluations by means of questionnaire. We discovered that cosmetic augmentation patients who undergo implant removal only often suffer adverse aesthetic results. The postremoval appearance of many cosmetic augmentation patients actually will be improved over their preoperative appearance when mastopexy is performed in conjunction with implant removal. The study demonstrated that patients with certain body types could expect a particular outcome; i.e., women with asthenic builds and older patients with lax, striated breast skin generally had unsatisfactory aesthetic outcomes with implant removal only. Patients selected for autogenous breast reconstruction had favorable results, with extended latissimus dorsi and TRAM flaps yielding equally good outcomes. The study allows us to offer patients an optimistic view of postoperative results following breast implant removal. We have begun to advise selected patients that implant removal accompanied by mastopexy provides a more pleasing aesthetic outcome than implant removal alone.     

Running programs backwards: The logical inversion of imperative computation

Imperative programs can be inverted directly from their forward-directed program code with the use of logical inference. The relational semantics of imperative computations treats programs as logical relations over the observable state of the environment, which is taken to be the state of the variables in memory. Program relations denote both forward and backward computations, and the direction of the computation depends upon the instantiation pattern of arguments in the relation. This view of inversion has practical applications when the relational semantics is treated as a logic program. Depending on the logic programming inference scheme used, execution of this relational program can compute the inverse of the imperative program. A number of nontrivial imperative computations can be inverted with minimal logic programming tools.