Molecular crowding effects of linear polymers in protein solutions

Measurement of protein-polymer second virial coefficients (B-AP) by sedimentation equilibrium studies of carbonic anhydrase and cytochrome c in the presence of dextrans (T10-T80) has revealed an inverse dependence of B-AP upon dextran molecular mass that conforms well with the behaviour predicted for the excluded-volume interaction between a spherical protein solute A and a random-flight representation of the polymeric cosolute P. That model of the protein-polymer interaction is also shown to provide a reasonable description of published gel chromatographic and equilibrium dialysis data on the effect of polymer molecular mass on BAP for human serum albumin in the presence of polyethylene glycols, a contrary finding from analysis of albumin solubility measurements being rejected on theoretical grounds. Inverse dependence upon polymer chainlength is also the predicted excluded-volume effect on the strength of several types of macromolecular equilibria-protein isomerization, protein dimerization, and 1 : 1 complex formation between dissimilar protein reactants. It is therefore concluded that published experimental observations of the reverse dependence, preferential reaction enhancement within DNA replication complexes by larger polyethylene glycols, must reflect the consequences of cosolute chemical interactions that outweigh those of thermodynamic nonideality arising from excluded-volume effects. (c) 2005 Elsevier B.V. All rights reserved.

Optimal crossover designs for logistic regression models in pharmacodynamics

Pharmacodynamics (PD) is the study of the biochemical and physiological effects of drugs. The construction of optimal designs for dose-ranging trials with multiple periods is considered in this paper, where the outcome of the trial (the effect of the drug) is considered to be a binary response: the success or failure of a drug to bring about a particular change in the subject after a given amount of time. The carryover effect of each dose from one period to the next is assumed to be proportional to the direct effect. It is shown for a logistic regression model that the efficiency of optimal parallel (single-period) or crossover (two-period) design is substantially greater than a balanced design. The optimal designs are also shown to be robust to misspecification of the value of the parameters. Finally, the parallel and crossover designs are combined to provide the experimenter with greater flexibility.

Introducing uncertainty into pattern discovery in temporal event sequences

Pattern discovery in temporal event sequences is of great importance in many application domains, such as telecommunication network fault analysis. In reality, not every type of event has an accurate timestamp. Some of them, defined as inaccurate events may only have an interval as possible time of occurrence. The existence of inaccurate events may cause uncertainty in event ordering. The traditional support model cannot deal with this uncertainty, which would cause some interesting patterns to be missing. A new concept, precise support, is introduced to evaluate the probability of a pattern contained in a sequence. Based on this new metric, we define the uncertainty model and present an algorithm to discover interesting patterns in the sequence database that has one type of inaccurate event. In our model, the number of types of inaccurate events can be extended to k readily, however, at a cost of increasing computational complexity.