A multiple-outgroup approach to resolving division-level phylogenetic relationships using 16S rDNA data

The 16S rRNA gene (16S rDNA) is currently the most widely used gene for estimating the evolutionary history of prokaryotes, To date, there are more than 30 000 16S rDNA sequences available from the core databases, GenBank, EMBL and DDBJ, This great number may cause a dilemma when composing datasets for phylogenetic analysis, since the choice and number of reference organisms are known to affect the resulting tree topology. A group of sequences appearing monophyletic in one dataset may not be so in another. This can be especially problematic when establishing the relationships of distantly related sequences at the division (phylum) level. In this study, a multiple-outgroup approach to resolving division-level phylogenetic relationships is suggested using 16S rDNA data. The approach is illustrated by two case studies concerning the monophyly of two recently proposed bacterial divisions, OP9 and OP10.

A new approach for detecting and mapping sewage impacts

Increased nitrogen loading has been implicated in eutrophication occurrences worldwide. Much of this loading is attributable to the growing human population along the world's coastlines. A significant component of this nitrogen input is from sewage effluent, and delineation of the distribution and biological impact of sewage-derived nitrogen is becoming increasingly important. Here, we show a technique that identifies the source, extent and fate of biologically available sewage nitrogen in coastal marine ecosystem. This method is based on the uptake of sewage nitrogen by marine plants and subsequent analysis of the sewage signature (elevated delta N-15) in plant tissues. Spatial analysis is used to create maps of delta N-15 and establish coefficient of variation estimates of the mapped values. We show elevated delta N-15 levels in marine plants near sewage outfalls in Moreton Bay, Australia, a semi-enclosed bay receiving multiple sewage inputs. These maps of sewage nitrogen distribution are being used to direct nutrient reduction strategies in the region and will assist in monitoring the effectiveness of environmental protection measures. (C) 2001 Elsevier Science Ltd. All rights reserved.

A comparison of the lateral and posterior retroperitoneoscopic approach for complete and partial nephroureterectomy in children

Objective To report the comparative results of a selective posterior or lateral retroperitoneoscopic approach (RPA) for nephroureterectomy in children. Patients and methods Following an established experience with RPA, 36 complete and 19 partial nephrouretectomies were prospectively randomized to a posterior and lateral retroperitoneoscopic approach. The patients were aged 4 months to 14 years, with a body weight at operation of 5.7-82 kg. For posterior RPA the child is positioned prone, with three access ports. The operating space was created with balloon dissection and maintained with CO2 insufflation. The child was then rotated 30 degrees with the kidney in the dependent position, and the operator and assistant standing on the affected side. In the lateral approach the child is in the lateral decubitus position with the operator and assistant facing the dorsal aspect of the patient. Results There was no significant difference in operative duration between the lateral and posterior approaches for nephrectomy (65 and 47 min) or partial nephrectomy (85 and 75 min). Two lateral nephrectomies required open conversion (one upper pole and one lower pole). Conclusion The posterior approach gives easy and quick access to the renal pedicle. It is preferable for complete nephrectomy alone and partial or polar excision. In children under 5 years old a near complete ureterectomy can be achieved. The lateral approach creates more inferomedial space, gives better access to ectopic kidneys and allows complete ureterectomy in all cases, Access to the pedicle in the normal position requires more frequent positioning of the kidney. Care must be taken as peritoneal tears are more common.

Audit and comprehensive health assessment programme in the primary healthcare of adults with intellectual disability: a pilot study

International research has demonstrated significant shortcomings in the health of adults with intellectual disability (ID). Because general practitioners (GPs) are the main providers of primary healthcare for this population, strategies to improve general practice care are an important aspect of rectifying these shortcomings. The present pilot study aimed to determine the effect of various interventions on health maintenance activities and to assess their acceptability to GPs, with a view to informing larger scale studies. The GPs were recruited through an earlier questionnaire-based postal survey. The GPs identified all their adult patients with ID, then obtained consent for participation from three patients randomly selected by the investigators. The GPs completed two self-evaluation forms and case note audits 12 months apart, read a synopsis of the relevant literature provided by the researchers, and completed a comprehensive health assessment (CHA) of their three patients. Forty-five GPs agreed to participate in the CHA programme (CHAP), and 15 completed the project. Thirty-eight patients completed the project. The number of patient-GP dyads who completed the project was too small to demonstrate statistically significant changes in health issues over time. The GPs found that the synopsis of the literature was the best intervention for increasing knowledge and was also the most practical to use in general practice. The CHAP was the intervention that prompted the most action from the GP which would not have been undertaken otherwise. The CHAP appeared to provide a superior review process compared to the other interventions used in the present study. The numbers of health maintenance activities found to be overdue and the number of health issues detected as a result of the process were considerable. The CHAP served as a communication tool and an educative instrument, providing a basis for future studies and strategies to improve the general practice care of adults with ID.

Compact clinical MRI magnet design using a multilayer current density approach

In this work, a new method of optimization is successfully applied to the theoretical design of compact, actively shielded, clinical MRI magnets. The problem is formulated as a two-step process in which the desired current densities on multiple, cc-axial surface layers are first calculated by solving Fredholm equations of the first kind. Non-linear optimization methods with inequality constraints are then invoked to fit practical magnet coils to the desired current densities. The current density approach allows rapid prototyping of unusual magnet designs. The emphasis of this work is on the optimal design of short, actively-shielded MRI magnets for whole-body imaging. Details of the hybrid numerical model are presented, and the model is used to investigate compact, symmetric, and asymmetric MRI magnets. Magnet designs are presented for actively-shielded, symmetric magnets of coil length 1.0 m, which is considerably shorter than currently available designs of comparable dsv size. Novel, actively-shielded, asymmetric magnet designs are also presented in which the beginning of a 50-cm dsv is positioned just 11 cm from the end of the coil structure, allowing much improved access to the patient and reduced patient claustrophobia. Magn Reson Med 45:331540, 2001. (C) 2001 Wiley-Liss, Inc.

Increasing profits and reducing risks in crop production using participatory systems simulation approaches

The development of cropping systems simulation capabilities world-wide combined with easy access to powerful computing has resulted in a plethora of agricultural models and consequently, model applications. Nonetheless, the scientific credibility of such applications and their relevance to farming practice is still being questioned. Our objective in this paper is to highlight some of the model applications from which benefits for farmers were or could be obtained via changed agricultural practice or policy. Changed on-farm practice due to the direct contribution of modelling, while keenly sought after, may in some cases be less achievable than a contribution via agricultural policies. This paper is intended to give some guidance for future model applications. It is not a comprehensive review of model applications, nor is it intended to discuss modelling in the context of social science or extension policy. Rather, we take snapshots around the globe to 'take stock' and to demonstrate that well-defined financial and environmental benefits can be obtained on-farm from the use of models. We highlight the importance of 'relevance' and hence the importance of true partnerships between all stakeholders (farmer, scientists, advisers) for the successful development and adoption of simulation approaches. Specifically, we address some key points that are essential for successful model applications such as: (1) issues to be addressed must be neither trivial nor obvious; (2) a modelling approach must reduce complexity rather than proliferate choices in order to aid the decision-making process (3) the cropping systems must be sufficiently flexible to allow management interventions based on insights gained from models. The pro and cons of normative approaches (e.g. decision support software that can reach a wide audience quickly but are often poorly contextualized for any individual client) versus model applications within the context of an individual client's situation will also be discussed. We suggest that a tandem approach is necessary whereby the latter is used in the early stages of model application for confidence building amongst client groups. This paper focuses on five specific regions that differ fundamentally in terms of environment and socio-economic structure and hence in their requirements for successful model applications. Specifically, we will give examples from Australia and South America (high climatic variability, large areas, low input, technologically advanced); Africa (high climatic variability, small areas, low input, subsistence agriculture); India (high climatic variability, small areas, medium level inputs, technologically progressing; and Europe (relatively low climatic variability, small areas, high input, technologically advanced). The contrast between Australia and Europe will further demonstrate how successful model applications are strongly influenced by the policy framework within which producers operate. We suggest that this might eventually lead to better adoption of fully integrated systems approaches and result in the development of resilient farming systems that are in tune with current climatic conditions and are adaptable to biophysical and socioeconomic variability and change. (C) 2001 Elsevier Science Ltd. All rights reserved.

A mixture model-based approach to the clustering of microarray expression data

Motivation: This paper introduces the software EMMIX-GENE that has been developed for the specific purpose of a model-based approach to the clustering of microarray expression data, in particular, of tissue samples on a very large number of genes. The latter is a nonstandard problem in parametric cluster analysis because the dimension of the feature space (the number of genes) is typically much greater than the number of tissues. A feasible approach is provided by first selecting a subset of the genes relevant for the clustering of the tissue samples by fitting mixtures of t distributions to rank the genes in order of increasing size of the likelihood ratio statistic for the test of one versus two components in the mixture model. The imposition of a threshold on the likelihood ratio statistic used in conjunction with a threshold on the size of a cluster allows the selection of a relevant set of genes. However, even this reduced set of genes will usually be too large for a normal mixture model to be fitted directly to the tissues, and so the use of mixtures of factor analyzers is exploited to reduce effectively the dimension of the feature space of genes. Results: The usefulness of the EMMIX-GENE approach for the clustering of tissue samples is demonstrated on two well-known data sets on colon and leukaemia tissues. For both data sets, relevant subsets of the genes are able to be selected that reveal interesting clusterings of the tissues that are either consistent with the external classification of the tissues or with background and biological knowledge of these sets.