Evaluation of total purchasing pilots in England and Scotland and implications for primary care groups in England: personal interviews and analysis of routine data

Objectives: To evaluate the reported achievements of the 52 first wave total purchasing pilot schemes in 1996-7 and the factors associated with these; and to consider the implications of these findings for the development of the proposed primary care groups.

Knowledge-based analysis of microarray gene expression data by using support vector machines

We introduce a method of functionally classifying genes by using gene expression data from DNA microarray hybridization experiments. The method is based on the theory of support vector machines (SVMs). SVMs are considered a supervised computer learning method because they exploit prior knowledge of gene function to identify unknown genes of similar function from expression data. SVMs avoid several problems associated with unsupervised clustering methods, such as hierarchical clustering and self-organizing maps. SVMs have many mathematical features that make them attractive for gene expression analysis, including their flexibility in choosing a similarity function, sparseness of solution when dealing with large data sets, the ability to handle large feature spaces, and the ability to identify outliers. We test several SVMs that use different similarity metrics, as well as some other supervised learning methods, and find that the SVMs best identify sets of genes with a common function using expression data. Finally, we use SVMs to predict functional roles for uncharacterized yeast ORFs based on their expression data.

Minisatellite marker analysis of Trypanosoma brucei: Reconciliation of clonal, panmictic, and epidemic population genetic structures

The African trypanosome, Trypanosoma brucei, has been shown to undergo genetic exchange in the laboratory, but controversy exists as to the role of genetic exchange in natural populations. Much of the analysis to date has been derived from isoenzyme or randomly amplified polymorphic DNA data with parasite material from a range of hosts and geographical locations. These markers fail to distinguish between the human infective (T. b. rhodesiense) and nonhuman infective (T. b. brucei) “subspecies” so that parasites derived from hosts other than humans potentially contain both subspecies. To overcome some of the inherent problems with the use of such markers and diverse populations, we have analyzed a well-defined population from a discrete geographical location (Busoga, Uganda) using three recently described minisatellite markers. The parasites were primarily isolated from humans and cattle with the latter isolates further characterized by their ability to resist lysis by human serum (equivalent to human infectivity). The minisatellite markers show high levels of polymorphism, and from the data obtained we conclude that T. b. rhodesiense is genetically isolated from T. b. brucei and can be unambiguously identified by its multilocus genotype. Analysis of the genotype frequencies in the separated T. b. brucei and T. b. rhodesiense populations shows the former has an epidemic population structure whereas the latter is clonal. This finding suggests that the strong linkage disequilibrium observed in previous analyses, where human and nonhuman infective trypanosomes were not distinguished, results from the treatment of two genetically isolated populations as a single population.

Analysis and interpretation of cost data in randomised controlled trials: review of published studies

Objective To review critically the statistical methods used for health economic evaluations in randomised controlled trials where an estimate of cost is available for each patient in the study.

Analysis of Cell Division and Elongation Underlying the Developmental Acceleration of Root Growth in Arabidopsis thaliana1

To investigate the relation between cell division and expansion in the regulation of organ growth rate, we used Arabidopsis thaliana primary roots grown vertically at 20°C with an elongation rate that increased steadily during the first 14 d after germination. We measured spatial profiles of longitudinal velocity and cell length and calculated parameters of cell expansion and division, including rates of local cell production (cells mm−1 h−1) and cell division (cells cell−1 h−1). Data were obtained for the root cortex and also for the two types of epidermal cell, trichoblasts and atrichoblasts. Accelerating root elongation was caused by an increasingly longer growth zone, while maximal strain rates remained unchanged. The enlargement of the growth zone and, hence, the accelerating root elongation rate, were accompanied by a nearly proportionally increased cell production. This increased production was caused by increasingly numerous dividing cells, whereas their rates of division remained approximately constant. Additionally, the spatial profile of cell division rate was essentially constant. The meristem was longer than generally assumed, extending well into the region where cells elongated rapidly. In the two epidermal cell types, meristem length and cell division rate were both very similar to that of cortical cells, and differences in cell length between the two epidermal cell types originated at the apex of the meristem. These results highlight the importance of controlling the number of dividing cells, both to generate tissues with different cell lengths and to regulate the rate of organ enlargement.

Statistical analysis of shape of objects based on landmark data.

Two objects with homologous landmarks are said to be of the same shape if the configurations of landmarks of one object can be exactly matched with that of the other by translation, rotation/reflection, and scaling. The observations on an object are coordinates of its landmarks with reference to a set of orthogonal coordinate axes in an appropriate dimensional space. The origin, choice of units, and orientation of the coordinate axes with respect to an object may be different from object to object. In such a case, how do we quantify the shape of an object, find the mean and variation of shape in a population of objects, compare the mean shapes in two or more different populations, and discriminate between objects belonging to two or more different shape distributions. We develop some methods that are invariant to translation, rotation, and scaling of the observations on each object and thereby provide generalizations of multivariate methods for shape analysis.