Issues in the provision of nursing care to people undergoing cardiac surgery who also have type 2 diabetes

There has been little investigation of the issues associated with caring for patients presenting for cardiac surgery with a comorbid diagnosis of diabetes although there is some evidence that the diabetes management is suboptimal. This study aimed to identify issues that patients and cardiac specialist nurses experience with the provision of inpatient services for people undergoing cardiac surgery who also have type 2 diabetes. A qualitative interpretive design, using individual interviews with patients and nurses, provided data about some of these issues. The study found that nurses had high levels of confidence in their cardiac care but little confidence in diabetes management. Patients described concerns about their diabetes care and treatment regimens. A 'typical journey' for a person with diabetes undergoing cardiac surgery was identified. The findings support the need to build increased capacity in specialist nurses to support diabetes care as a secondary diagnosis.

Evidence for a common role for the serine-type Plasmodium falciparum serine repeat antigen proteases : implications for vaccine and drug design

Serine repeat antigens (SERAs) are a family of secreted “cysteine-like” proteases of Plasmodium parasites. Several SERAs possess an atypical active-site serine residue in place of the canonical cysteine. The human malaria parasite Plasmodium falciparum possesses six “serine-type” (SERA1 to SERA5 and SERA9) and three “cysteine-type” (SERA6 to SERA8) SERAs. Here, we investigate the importance of the serine-type SERAs to blood-stage parasite development and examine the extent of functional redundancy among this group. We attempted to knock out the four P. falciparum serine-type SERA genes that have not been disrupted previously. SERA1, SERA4, and SERA9 knockout lines were generated, while only SERA5, the most strongly expressed member of the SERA family, remained refractory to genetic deletion. Interestingly, we discovered that while SERA4-null parasites completed the blood-stage cycle normally, they exhibited a twofold increase in the level of SERA5 mRNA. The inability to disrupt SERA5 and the apparent compensatory increase in SERA5 expression in response to the deletion of SERA4 provides evidence for an important blood-stage function for the serine-type SERAs and supports the notion of functional redundancy among this group. Such redundancy is consistent with our phylogenetic analysis, which reveals a monophyletic grouping of the serine-type SERAs across the genus Plasmodium and a predominance of postspeciation expansion. While SERA5 is to some extent further validated as a target for vaccine and drug development, our data suggest that the expression level of other serine-type SERAs is the only barrier to escape from anti-SERA5-specific interventions.

CIDB: Chlamydia Interactive Database for cross-querying genomics, transcriptomics and proteomics data

Chlamydiae are important pathogens of humans, birds and a wide range of animals. They are a unique group of bacteria, characterized by their developmental cycle. Chlamydia has been difficult to study because of their obligate intracellular growth habit and lack of a genetic transformation system. However, the past 5 years has seen the full genome sequencing of seven strains of Chlamydia and a rapid expansion of genomic, transcriptomic (RT-PCR, microarray) and proteomic analysis of these pathogens. The Chlamydia Interactive Database (CIDB) described here is the first database of its type that holds genomic, RT-PCR, microarray and proteomics data sets that can be cross-queried by researchers for patterns in the data. Combining the data of many research groups into a single database and cross-querying from different perspectives should enhance our understanding of the complex cell biology of these pathogens. The database is available at: http://www3.it.deakin.edu.au:8080/CIDB/.

Purification and membrane reconstitution of catalytically active Menkes copper-transporting P-type ATPase (MNK; ATP7A)

The MNK (Menkes disease protein; ATP7A) is a major copper- transporting P-type ATPase involved in the delivery of copper to cuproenzymes in the secretory pathway and the efflux of excess copper from extrahepatic tissues. Mutations in the MNK (ATP7A) gene result in Menkes disease, a fatal neurodegenerative copper deficiency disorder. Currently, detailed biochemical and biophysical analyses of MNK to better understand its mechanisms of copper transport are not possible due to the lack of purified MNK in an active form. To address this issue, we expressed human MNK with an N-terminal Glu-Glu tag in Sf9 [Spodoptera frugiperda (fall armyworm) 9] insect cells and purified it by antibody affinity chromatography followed by size-exclusion chromatography in the presence of the non-ionic detergent DDM (n-dodecyl b-D-maltopyranoside). Formation of the classical vanadate-sensitive phosphoenzyme by purified MNK was activated by Cu(I) [EC50=0.7 µM; h (Hill coefficient) was 4.6]. Furthermore, we report the first measurement of Cu(I)-dependent ATPase activity of MNK (K0.5=0.6 µM; h=5.0). The purified MNK demonstrated active ATP-dependent vectorial 64Cu transport when reconstituted into soya-bean asolectin liposomes. Together, these data demonstrated that Cu(I) interacts with MNK in a co-operative manner and with high affinity in the sub-micromolar range. The present study provides the first biochemical characterization of a purified full-length mammalian copper-transporting P-type ATPase associated with a human disease.

Novel data management algorithms in peer-to-peer content distribution networks

The peer-to-peer content distribution network (PCDN) is a hot topic recently, and it has a huge potential for massive data intensive applications on the Internet. One of the challenges in PCDN is routing for data sources and data deliveries. In this paper, we studied a type of network model which is formed by dynamic autonomy area, structured source servers and proxy servers. Based on this network model, we proposed a number of algorithms to address the routing and data delivery issues. According to the highly dynamics of the autonomy area, we established dynamic tree structure proliferation system routing, proxy routing and resource searching algorithms. The simulations results showed that the performance of the proposed network model and the algorithms are stable.

Disease fingerprinting with cDNA microarrays reveals distinct gene expression profiles in lethal type 1 and type 2 cytokine-mediated inflammatory reactions

Development of polarized immune responses controls resistance and susceptibility to many microorganisms. However, studies of several infectious, allergic, and autoimmune diseases have shown that chronic type-1 and type-2 cytokine responses can also cause significant morbidity and mortality if left unchecked. We used mouse cDNA microarrays to molecularly phenotype the gene expression patterns that characterize two disparate but equally lethal forms of liver pathology that develop in Schistosoma mansoni infected mice polarized for type-1 and type-2 cytokine responses. Hierarchical clustering analysis identified at least three groups of genes associated with a polarized type-2 response and two linked with an extreme type-1 cytokine phenotype. Predictions about liver fibrosis,  apoptosis, and granulocyte recruitment and activation generated by the microarray studies were confirmed later by traditional biological assays. The data show that cDNA microarrays are useful not only for determining  coordinated gene expression profiles but are also highly effective for molecularly “fingerprinting” diseased tissues. Moreover, they illustrate the potential of genome-wide approaches for generating comprehensive views on the molecular and biochemical mechanisms regulating infectious  disease pathogenesis.

An agent-based framework for petroleum information services from distributed heterogeneous data resources

For making good decisions in the area of petroleum production, it is becoming a big problem how to timely gather sufficient and correct information, which may be stored in databases, data files, or on the World Wide Web. In this paper, Gaia methodology and Open Agent Architecture were employed to contribute a framework to solve above problem. The framework consists of three levels, namely, role mode, agent type, and agent instance. The model with five roles is analyzed. Four agent types are designed Six agent instances are developed for constructing the system of petroleum information services. The experimental results show that all agents in the system can work cooperatively to organize and retrieve relevant petroleum information. The successful implementation of the framework shows that agent-based technology can significantly facilitate the construction of complex systems in distributed heterogeneous data resource environment.

Bayesian classification of catchments using spatial data: a first step to improved modelling of catchment effects on stream ecological condition

A major challenge facing freshwater ecologists and managers is the development of models that link stream ecological condition to catchment scale effects, such as land use. Previous attempts to make such models have followed two general approaches. The bottom-up approach employs mechanistic models, which can quickly become too complex to be useful. The top-down approach employs empirical models derived from large data sets, and has often suffered from large amounts of unexplained variation in stream condition.

We believe that the lack of success of both modelling approaches may be at least partly explained by scientists considering too wide a breadth of catchment type. Thus, we believe that by stratifying large sets of catchments into groups of similar types prior to modelling, both types of models may be improved. This paper describes preliminary work using a Bayesian classification software package, ‘Autoclass’ (Cheeseman and Stutz 1996) to create classes of catchments within the Murray Darling Basin based on physiographic data.

Autoclass uses a model-based classification method that employs finite mixture modelling and trades off model fit versus complexity, leading to a parsimonious solution. The software provides information on the posterior probability that the classification is ‘correct’ and also probabilities for alternative classifications. The importance of each attribute in defining the individual classes is calculated and presented, assisting description of the classes. Each case is ‘assigned’ to a class based on membership probability, but the probability of membership of other classes is also provided. This feature deals very well with cases that do not fit neatly into a larger class. Lastly, Autoclass requires the user to specify the measurement error of continuous variables.

Catchments were derived from the Australian digital elevation model. Physiographic data werederived from national spatial data sets. There was very little information on measurement errors for the spatial data, and so a conservative error of 5% of data range was adopted for all continuous attributes. The incorporation of uncertainty into spatial data sets remains a research challenge.

The results of the classification were very encouraging. The software found nine classes of catchments in the Murray Darling Basin. The classes grouped together geographically, and followed altitude and latitude gradients, despite the fact that these variables were not included in the classification. Descriptions of the classes reveal very different physiographic environments, ranging from dry and flat catchments (i.e. lowlands), through to wet and hilly catchments (i.e. mountainous areas). Rainfall and slope were two important discriminators between classes. These two attributes, in particular, will affect the ways in which the stream interacts with the catchment, and can thus be expected to modify the effects of land use change on ecological condition. Thus, realistic models of the effects of land use change on streams would differ between the different types of catchments, and sound management practices will differ.

A small number of catchments were assigned to their primary class with relatively low probability. These catchments lie on the boundaries of groups of catchments, with the second most likely class being an adjacent group. The locations of these ‘uncertain’ catchments show that the Bayesian classification dealt well with cases that do not fit neatly into larger classes.

Although the results are intuitive, we cannot yet assess whether the classifications described in this paper would assist the modelling of catchment scale effects on stream ecological condition. It is most likely that catchment classification and modelling will be an iterative process, where the needs of the model are used to guide classification, and the results of classifications used to suggest further refinements to models.

Interpolatory type construction of general aggregation operators

In this chapter we examine a number of methods to construct aggregation operators of interpolatory type for specific applications. The construction is based on the desired values of the aggregation operator at certain prototypical points, and on other desired properties, such as, conjuctive, disjunctive or averaging behaviour, symmetry and marginals.

The mother-daughter guilt dynamic : effects of type 1 diabetes during life transitions

Aim. The aim of the study was to explore and describe the strategies young women with type 1 diabetes used to manage life transitions. The paper describes one aspect of how guilt dynamic often operates between mothers and daughters and how the women managed the guilt dynamic to create stability in their lives.
Background. When a child is diagnosed with diabetes, major transitional changes occur in the relationships between the mother and her child. The changes affect the psychological and social aspects of their lives and have a major impact on how young women manage their diabetes. A guilt dynamic between mothers and young women with diabetes emerged as a major theme in a larger study that investigated how young women with diabetes managed life transitions. Although the literature indicates that mothers of chronically ill children experience guilt feelings towards their children, little research was identified that addressed the emotional dynamics between mothers and daughters with diabetes.
Design. Using grounded theory method, interviews were conducted with 20 women with type 1 diabetes and five mothers during 2002 and 2003. Constant comparative analysis was used to analyse the data and develop an in-depth understanding of the experience of living with diabetes during life transitions.
Findings. The findings revealed that guilt feelings created a two-way dependency between mothers and their daughters with diabetes. The two-way dependency involved feelings of being a burden to each other, difficulty balancing responsibilities for diabetes management, difficulty relinquishing emotional and social dependency especially during life transitions. In addition, these issues were rarely discussed openly with each other or with health professionals. The findings provide additional information about the human experience of the mother–daughter relationship and the effect on coping with diabetes in the context of life transitions.
Conclusions. Understanding the impact diabetes has on the emotional and social well being of both women with type 1 diabetes and their mothers is critical in planning appropriate support for both groups. Most importantly, it is critical to understand the guilt dynamic that operates during young women with diabetes' life transitions when the daughters' dependency on their mother's control and responsibility for diabetes management undergo changes resulting in emotional responses, especially guilt feelings.
Relevance to clinical practice. Health professionals need to understand the emotional and social impact of the guilt dynamics between young women with type 1 diabetes and their mothers. Adequate and appropriate support can minimize the guilt feelings and enhance stability and quality of life for both mothers and their daughters, especially during major life transitions, such as motherhood.

Predictors of timely doctoral student completions by type of attendance: the utility of a pragmatic approach

Federal government changes to the funding of doctoral students have focused the attention of university management on their completion rates. The aims of this paper are to inform the allocation of institutional resources in a manner that improves the likelihood of timely doctoral completions and to highlight a process that can also be used for analyses of other key indicators of progression and attrition. The analyses and model development used national data readily available to all universities, which are collected in a standard approach through the Graduate Destinations Survey (GDS). The findings show that the most important variable for timely completion was attendance (full-time compared with part-time), whereby in terms of full-time equivalent (FTE) years of study, part-time students were far more likely to complete quickly than full-time students. For the full-time students, the key predictors of timely completion were residency, field of study and English-speaking background (ESB). The timeliness of part-time students was predicted by field of study and ESB. This study confirms that there is considerable variation by discipline for timely doctoral completions. The pragmatic application and prospective test of the derived models present a variety of opportunities for research student administrators. For example, those full-time students scoring highly represented a concentration of timely graduates more than 7.5 times higher than the lowest-scoring group - almost an order of magnitude of difference. In short, university management could gain tremendous value from more widely using the data available.

Predicting spatio-temporal distribution for eastern Australian birds using birds Australia's atlas data : survey method, habitat and seasonal effects

Faunal atlases are landscape-level survey collections that can be used for describing spatial and temporal patterns of distribution and densities. They can also serve as a basis for quantitative analysis of factors that may influence the distributions of species. We used a subset of Birds Australia’s Atlas of Australian Birds data (January 1998 to December 2002) to examine the spatio-temporal distribution patterns of 280 selected species in eastern Australia (17–37°S and 136–152°E). Using geographical information systems, this dataset was converted into point coverage and overlaid with a vegetation polygon layer and a half-degree grid. The exploratory data analysis involved calculating species-specific reporting rates spatially, per grid and per vegetation unit, and also temporally, by month and year. We found high spatio-temporal variability in the sampling effort. Using generalised linear models on unaggregated point data, the influences of four factors – survey method and month, geographical location and habitat type – were analysed for each species. When counts of point data were attributed to grid-cells, the total number of species correlated with the total number of surveys, while the number of records per species was highly variable. Surveys had high interannual location fidelity. The predictive values of each of the four factors were species-dependent. Location and habitat were correlated and highly predictive for species with restricted distribution and strong habitat preference. Month was only of importance for migratory species. The proportion of incidental sightings was important for extremely common or extremely rare species. In conclusion, behaviour of species differed sufficiently to require building a customized model for each species to predict distribution. Simple models were effective for habitat specialists with restricted ranges, but for generalists with wide distributions even complex models gave poor predictions.

Productivity growth and efficiency change in Malaysian manufacturing : recent evidence from disaggregated data

This paper estimates productivity growth in Malaysian manufacturing over the period 1983-1999. Malmquist productivity Indices (MPIs) have been computed using non parametric Data Envelopment Analysis (DEA) type linear programming, which show productivity growth sourced from efficiency change and growth in technology. Unlike previous studies, this study identifies the Malaysian manufacturing industries at the five digit breakdown of Malaysian Standard Industrial Classification (MSIC) thereby revealing more industry specific efficiency and technical growth patterns. Results indicate that two third of the industries (76 out of total 114 categories) experienced average annual
productivity improvement ranging from 0.1% to 7.8% over the sampled period. Average annual technical progress was recorded by 95 industry categories while technical efficiency improvement was achieved by 53 industries. Overall yearly average indicated relatively low productivity growth from the mid 1990’s onwards caused by either efficiency decline or technical regress. Summary results for industries reveal that some of the high rates of productivity growth have been recorded in glass and glass products (7.3%), Petroleum and coal (7.2%), industrial chemicals (4.9%) contributed from both efficiency improvement and technical progress ranging from 0.8% to 5.4% and from 1.7% to 4.1%, respectively. These results are expected to have some implications for ongoing and future strategic policy reform in Malaysian manufacturing generating a more sustainable growth for specific industry categories.

Cost-efficacy of surgically induced weight loss for the management of type 2 diabetes : a randomized controlled trial

OBJECTIVE -- To determine the within-trial cost-efficacy of surgical therapy relative to conventional therapy for achieving remission of recently diagnosed type 2 diabetes in class I and II obese patients.

RESEARCH DESIGN AND METHODS -- Efficacy results were derived from a 2-year randomized controlled trial. A health sector perspective was adopted, and within-trial intervention costs included gastric banding surgery, mitigation of complications, outpatient medical consultations, medical investigations, pathology, weight loss therapies, and medication. Resource use was measured based on data drawn from a trial database and patient medical records and valued based on private hospital costs and government schedules in 2006 Australian dollars (AUD). An incremental cost-effectiveness analysis was undertaken.

RESULTS -- Mean 2-year intervention costs per patient were 13,400 AUD for surgical therapy and 3,400 AUD for conventional therapy, with laparoscopic adjustable gastric band (LAGB) surgery accounting for 85% of the difference. Outpatient medical consultation costs were three times higher for surgical patients, whereas medication costs were 1.5 times higher for conventional patients. The cost differences were primarily in the first 6 months of the trial. Relative to conventional therapy, the incremental cost-effectiveness ratio for surgical therapy was 16,600 AUD per case of diabetes remitted (currency exchange: 1 AUD = 0.74 USD).

CONCLUSIONS -- Surgical therapy appears to be a cost-effective option for managing type 2 diabetes in class I and II obese patients.

Specific risk assessment based on victim type in children sexual offenders

Actuarial instruments for assessing sex offender recidivism have limited utility for specific risk assessment questions, such as the risk posed to particular types of victim. In order to obtain variables that discriminate between offenders with different classes of victim, data were coded from 324 files of child sexual offenders from a community-based sexual offender treatment program. Offenders with single or multiple victims were compared, as were offenders who did or did not offend against victims of both genders, and offenders with only intra-familial or extra-familial victims versus offenders with victims in both relationship categories. Variables that discriminated single-victim and multiple-victim offenders were similar to those identified in actuarial risk assessment scales, with the exception of history of childhood sexual abuse. With the exception of physical abuse history, the same variables discriminated specific offender groups according to victim gender and victim relationship, although in different combinations. There was limited support for the notion of specific risk variables.