Caregiving experience and its influencing factors : rural versus urban adult-child caregivers caring for parents with dementia in China

Background: It is predicted that China will have the largest number of cases of dementia in the world by 2025 (Ferri et al., 2005). Research has demonstrated that caring for family members with dementia can be a long-term, burdensome activity resulting in physical and emotional distress and impairment (Pinquart & Sorensen, 2003b). The establishment of family caregiver supportive services in China can be considered urgent; and the knowledge of the caregiving experience and related influencing factors is necessary to inform such services. Nevertheless, in the context of rapid demographic and socioeconomic change, the impact of caregiving for rural and urban Chinese adult-child caregivers may be different, and different needs in supportive services may therefore be expected. Objectives: The aims of this research were 1) to examine the potential differences existing in the caregiving experience between rural and urban adult-child caregivers caring for parents with dementia in China; and 2) to examine the potential differences existing in the influencing factors of the caregiving experience for rural as compared with urban adult-child caregivers caring for parents with dementia in China. Based on the literature review and Kramer.s (1997) caregiver adaptation model, six concepts and their relationships of caregiving experience were studied: severity of the care receivers. dementia, caregivers. appraisal of role strain and role gain, negative and positive well-being outcomes, and health related quality of life. Furthermore, four influencing factors (i.e., filial piety, social support, resilience, and personal mastery) were studied respectively. Methods: A cross-sectional, comparative design was used to achieve the aims of the study. A questionnaire, which was designed based on the literature review and on Kramer.s (1997) caregiver adaptation model, was completed by 401 adult-child caregivers caring for their parents with dementia from the mental health outpatient departments in five hospitals in the Yunnan province, P.R. China. Structural equation modelling (SEM) was employed as the main statistical technique for data analyses. Other statistical techniques (e.g., t-tests and Chi-Square tests) were also conducted to compare the demographic characteristics and the measured variables between rural and urban groups. Results: For the first research aim, the results indicated that urban adult-child caregivers in China experienced significantly greater strain and negative well-being outcomes than their rural peers; whereas, the difference on the appraisal of role gain and positive outcomes was nonsignificant between the two groups. The results also indicated that the amounts of severity of care receivers. dementia and caregivers. health related quality of life do not have the same meanings between the two groups. Thus, the levels of these two concepts were not comparable between the rural and urban groups in this study. Moreover, the results also demonstrated that the negative direct effect of gain on negative outcomes in urban caregivers was stronger than that in rural caregivers, suggesting that the urban caregivers tended to use appraisal of role gain to protect themselves from negative well-being outcomes to a greater extent. In addition, the unexplained variance in strain in the urban group was significantly more than that in the rural group, suggesting that there were other unmeasured variables besides the severity of care receivers. dementia which would predict strain in urban caregivers compared with their rural peers. For the second research aim, the results demonstrated that rural adult-child caregivers reported a significantly higher level of filial piety and more social support than their urban counterparts, although the two groups did not significantly differ on the levels of their resilience and personal mastery. Furthermore, although the mediation effects of these four influencing factors on both positive and negative aspects remained constant across rural and urban adult-child caregivers, urban caregivers tended to be more effective in using personal mastery to protect themselves from role strain than rural caregivers, which in turn protects them more from the negative well-being outcomes than was the case with their rural peers. Conclusions: The study extends the application of Kramer.s caregiving adaptation process model (Kramer, 1997) to a sample of adult-child caregivers in China by demonstrating that both positive and negative aspects of caregiving may impact on the caregiver.s health related quality of life, suggesting that both aspects should be targeted in supportive interventions for Chinese family caregivers. Moreover, by demonstrating partial mediation effects, the study provides four influencing factors (i.e., filial piety, social support, resilience, and personal mastery) as specific targets for clinical interventions. Furthermore, the study found evidence that urban adult-child caregivers had more negative but similar positive experience compared to their rural peers, suggesting that the establishment of supportive services for urban caregivers may be more urgent at present stage in China. Additionally, since urban caregivers tended to use appraisal of role gain and personal mastery to protect themselves from negative well-being outcomes than rural caregivers to a greater extend, interventions targeting utility of gain or/and personal mastery to decrease negative outcomes might be more effective in urban caregivers than in rural caregivers. On the other hand, as cultural expectations and expression of filial piety tend to be more traditional in rural areas, interventions targeting filial piety could be more effective among rural caregivers. Last but not least, as rural adult-child caregivers have more existing natural social support than their urban counterparts, mobilising existing natural social support resources may be more beneficial for rural caregivers, whereas, formal supports (e.g., counselling services, support groups and adult day care centres) should be enhanced for urban caregivers.

The molecular structure of the multianion mineral hidalgoite PbAl3(AsO4)(SO4)(OH)6 : implications for arsenic removal from soils

The objective of this research is to determine the molecular structure of the mineral hidalgoite PbAl3(AsO4)(SO4)(OH)6 using vibrational spectroscopy. The mineral is found in old mine sites. Observed bands are assigned to the stretching and bending vibrations of (SO4)2- and (AsO4)3- units, stretching and bending vibrations of hydrogen bonded (OH)- ions and Al3+-(O,OH) units. The approximate range of O-H...O hydrogen bond lengths is inferred from the Raman and infrared spectra. Values of 2.6989 Å, 2.7682 Å, 2.8659 Å were obtained. The formation of hidalgoite may offer a mechanism for the removal of arsenic from the environment.

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

An evaluation of the pattern and structure mathematics awareness program in the early school years

This paper reports a 2-year longitudinal study on the effectiveness of the Pattern and Structure Mathematical Awareness Program (PASMAP) on students’ mathematical development. The study involved 316 Kindergarten students in 17 classes from four schools in Sydney and Brisbane. The development of the PASA assessment interview and scale are presented. The intervention program provided explicit instruction in mathematical pattern and structure that enhanced the development of students’ spatial structuring, multiplicative reasoning, and emergent generalisations. This paper presents the initial findings of the impact of the PASMAP and illustrates students’ structural development.

Developing the Pattern and Structure Assessment (PASA) interview to inform early mathematics learning

The Pattern and Structure Mathematical Awareness Program(PASMAP) stems from a 2-year longitudinal study on students’ early mathematical development. The paper outlines the interview assessment the Pattern and Structure Assessment(PASA) designed to describe students’ awareness of mathematical pattern and structure across a range of concepts. An overview of students’ performance across items and descriptions of their structural development are described.

The motivation and structure of corrupt police networks : theorising the dark side of the ‘thin blue line’

In recent times considerable research attention has been directed to understanding dark networks, especially criminal and terrorist networks. Dark networks are those in which member motivations are self rather than public interested, achievements come at the cost of other individuals, groups or societies and, in addition, their activities are both ‘covert and illegal’ (Raab & Milward, 2003: 415). This ‘darkness’ has implications for the way in which these networks are structured, the strategies adopted and their recruitment methods. Such entities exhibit distinctive operating characteristics including most notably the tension between creating an efficient network structure while retaining the ability to hide from public view while avoiding catastrophic collapse should one member cooperate with authorities (Bouchard 2007). While theoretical emphasis has been on criminal and terrorist networks, recent work has demonstrated that corrupt police networks exhibit some distinctive characteristics. In particular, these entities operate within the shadows of a host organisation - the Police Force and distort the functioning of the ‘Thin Blue Line’ as the interface between the law abiding citizenry and the criminal society. Drawing on data derived from the Queensland Fitzgerald Commission of Enquiry into Police Misconduct and related documents, this paper examines the motivations, structural properties and operational practices of corrupt police networks and compares and contrasts these with other dark networks with ‘bright’ public service networks. The paper confirms the structural differences between dark corrupt police networks and bright networks and suggests. However, structural embeddedness alone is found to be an insufficient theoretical explanation for member involvement in networks and that a set of elements combine to impact decision-making. Although offering important insights into network participation, the paper’s findings are especially pertinent in identifying additional points of intervention for police corruption networks.

Complexity, evolution, and the structure of demand

This chapter argues that evolutionary economics should be founded upon complex systems theory rather than neo-Darwinian analogies concerning natural selection, which focus on supply side considerations and competition amongst firms and technologies. It suggests that conceptions such as production and consumption functions should be replaced by network representations, in which the preferences or, more correctly, the aspirations of consumers are fundamental and, as such, the primary drivers of economic growth. Technological innovation is viewed as a process that is intermediate between these aspirational networks, and the organizational networks in which goods and services are produced. Consumer knowledge becomes at least as important as producer knowledge in determining how economic value is generated. It becomes clear that the stability afforded by connective systems of rules is essential for economic flexibility to exist, but that too many rules result in inert and structurally unstable states. In contrast, too few rules result in a more stable state, but at a low level of ordered complexity. Economic evolution from this perspective is explored using random and scale free network representations of complex systems.

Interactive axial shortening of columns and walls in high rise buildings

Concrete is commonly used as a primary construction material for tall building construction. Load bearing components such as columns and walls in concrete buildings are subjected to instantaneous and long term axial shortening caused by the time dependent effects of "shrinkage", "creep" and "elastic" deformations. Reinforcing steel content, variable concrete modulus, volume to surface area ratio of the elements and environmental conditions govern axial shortening. The impact of differential axial shortening among columns and core shear walls escalate with increasing building height. Differential axial shortening of gravity loaded elements in geometrically complex and irregular buildings result in permanent distortion and deflection of the structural frame which have a significant impact on building envelopes, building services, secondary systems and the life time serviceability and performance of a building. Existing numerical methods commonly used in design to quantify axial shortening are mainly based on elastic analytical techniques and therefore unable to capture the complexity of non-linear time dependent effect. Ambient measurements of axial shortening using vibrating wire, external mechanical strain, and electronic strain gauges are methods that are available to verify pre-estimated values from the design stage. Installing these gauges permanently embedded in or on the surface of concrete components for continuous measurements during and after construction with adequate protection is uneconomical, inconvenient and unreliable. Therefore such methods are rarely if ever used in actual practice of building construction. This research project has developed a rigorous numerical procedure that encompasses linear and non-linear time dependent phenomena for prediction of axial shortening of reinforced concrete structural components at design stage. This procedure takes into consideration (i) construction sequence, (ii) time varying values of Young's Modulus of reinforced concrete and (iii) creep and shrinkage models that account for variability resulting from environmental effects. The capabilities of the procedure are illustrated through examples. In order to update previous predictions of axial shortening during the construction and service stages of the building, this research has also developed a vibration based procedure using ambient measurements. This procedure takes into consideration the changes in vibration characteristic of structure during and after construction. The application of this procedure is illustrated through numerical examples which also highlight the features. The vibration based procedure can also be used as a tool to assess structural health/performance of key structural components in the building during construction and service life.

Flexible high voltage pulsed power supply for plasma applications

Demands for delivering high instantaneous power in a compressed form (pulse shape) have widely increased during recent decades. The flexible shapes with variable pulse specifications offered by pulsed power have made it a practical and effective supply method for an extensive range of applications. In particular, the release of basic subatomic particles (i.e. electron, proton and neutron) in an atom (ionization process) and the synthesizing of molecules to form ions or other molecules are among those reactions that necessitate large amount of instantaneous power. In addition to the decomposition process, there have recently been requests for pulsed power in other areas such as in the combination of molecules (i.e. fusion, material joining), gessoes radiations (i.e. electron beams, laser, and radar), explosions (i.e. concrete recycling), wastewater, exhausted gas, and material surface treatments. These pulses are widely employed in the silent discharge process in all types of materials (including gas, fluid and solid); in some cases, to form the plasma and consequently accelerate the associated process. Due to this fast growing demand for pulsed power in industrial and environmental applications, the exigency of having more efficient and flexible pulse modulators is now receiving greater consideration. Sensitive applications, such as plasma fusion and laser guns also require more precisely produced repetitive pulses with a higher quality. Many research studies are being conducted in different areas that need a flexible pulse modulator to vary pulse features to investigate the influence of these variations on the application. In addition, there is the need to prevent the waste of a considerable amount of energy caused by the arc phenomena that frequently occur after the plasma process. The control over power flow during the supply process is a critical skill that enables the pulse supply to halt the supply process at any stage. Different pulse modulators which utilise different accumulation techniques including Marx Generators (MG), Magnetic Pulse Compressors (MPC), Pulse Forming Networks (PFN) and Multistage Blumlein Lines (MBL) are currently employed to supply a wide range of applications. Gas/Magnetic switching technologies (such as spark gap and hydrogen thyratron) have conventionally been used as switching devices in pulse modulator structures because of their high voltage ratings and considerably low rising times. However, they also suffer from serious drawbacks such as, their low efficiency, reliability and repetition rate, and also their short life span. Being bulky, heavy and expensive are the other disadvantages associated with these devices. Recently developed solid-state switching technology is an appropriate substitution for these switching devices due to the benefits they bring to the pulse supplies. Besides being compact, efficient, reasonable and reliable, and having a long life span, their high frequency switching skill allows repetitive operation of pulsed power supply. The main concerns in using solid-state transistors are the voltage rating and the rising time of available switches that, in some cases, cannot satisfy the application’s requirements. However, there are several power electronics configurations and techniques that make solid-state utilisation feasible for high voltage pulse generation. Therefore, the design and development of novel methods and topologies with higher efficiency and flexibility for pulsed power generators have been considered as the main scope of this research work. This aim is pursued through several innovative proposals that can be classified under the following two principal objectives. • To innovate and develop novel solid-state based topologies for pulsed power generation • To improve available technologies that have the potential to accommodate solid-state technology by revising, reconfiguring and adjusting their structure and control algorithms. The quest to distinguish novel topologies for a proper pulsed power production was begun with a deep and through review of conventional pulse generators and useful power electronics topologies. As a result of this study, it appears that efficiency and flexibility are the most significant demands of plasma applications that have not been met by state-of-the-art methods. Many solid-state based configurations were considered and simulated in order to evaluate their potential to be utilised in the pulsed power area. Parts of this literature review are documented in Chapter 1 of this thesis. Current source topologies demonstrate valuable advantages in supplying the loads with capacitive characteristics such as plasma applications. To investigate the influence of switching transients associated with solid-state devices on rise time of pulses, simulation based studies have been undertaken. A variable current source is considered to pump different current levels to a capacitive load, and it was evident that dissimilar dv/dts are produced at the output. Thereby, transient effects on pulse rising time are denied regarding the evidence acquired from this examination. A detailed report of this study is given in Chapter 6 of this thesis. This study inspired the design of a solid-state based topology that take advantage of both current and voltage sources. A series of switch-resistor-capacitor units at the output splits the produced voltage to lower levels, so it can be shared by the switches. A smart but complicated switching strategy is also designed to discharge the residual energy after each supply cycle. To prevent reverse power flow and to reduce the complexity of the control algorithm in this system, the resistors in common paths of units are substituted with diode rectifiers (switch-diode-capacitor). This modification not only gives the feasibility of stopping the load supply process to the supplier at any stage (and consequently saving energy), but also enables the converter to operate in a two-stroke mode with asymmetrical capacitors. The components’ determination and exchanging energy calculations are accomplished with respect to application specifications and demands. Both topologies were simply modelled and simulation studies have been carried out with the simplified models. Experimental assessments were also executed on implemented hardware and the approaches verified the initial analysis. Reports on details of both converters are thoroughly discussed in Chapters 2 and 3 of the thesis. Conventional MGs have been recently modified to use solid-state transistors (i.e. Insulated gate bipolar transistors) instead of magnetic/gas switching devices. Resistive insulators previously used in their structures are substituted by diode rectifiers to adjust MGs for a proper voltage sharing. However, despite utilizing solid-state technology in MGs configurations, further design and control amendments can still be made to achieve an improved performance with fewer components. Considering a number of charging techniques, resonant phenomenon is adopted in a proposal to charge the capacitors. In addition to charging the capacitors at twice the input voltage, triggering switches at the moment at which the conducted current through switches is zero significantly reduces the switching losses. Another configuration is also introduced in this research for Marx topology based on commutation circuits that use a current source to charge the capacitors. According to this design, diode-capacitor units, each including two Marx stages, are connected in cascade through solid-state devices and aggregate the voltages across the capacitors to produce a high voltage pulse. The polarity of voltage across one capacitor in each unit is reversed in an intermediate mode by connecting the commutation circuit to the capacitor. The insulation of input side from load side is provided in this topology by disconnecting the load from the current source during the supply process. Furthermore, the number of required fast switching devices in both designs is reduced to half of the number used in a conventional MG; they are replaced with slower switches (such as Thyristors) that need simpler driving modules. In addition, the contributing switches in discharging paths are decreased to half; this decrease leads to a reduction in conduction losses. Associated models are simulated, and hardware tests are performed to verify the validity of proposed topologies. Chapters 4, 5 and 7 of the thesis present all relevant analysis and approaches according to these topologies.

Graph rigidity for near-coplanar structure from motion

Recent algorithms for monocular motion capture (MoCap) estimate weak-perspective camera matrices between images using a small subset of approximately-rigid points on the human body (i.e. the torso and hip). A problem with this approach, however, is that these points are often close to coplanar, causing canonical linear factorisation algorithms for rigid structure from motion (SFM) to become extremely sensitive to noise. In this paper, we propose an alternative solution to weak-perspective SFM based on a convex relaxation of graph rigidity. We demonstrate the success of our algorithm on both synthetic and real world data, allowing for much improved solutions to marker less MoCap problems on human bodies. Finally, we propose an approach to solve the two-fold ambiguity over bone direction using a k-nearest neighbour kernel density estimator.

A two-stage decision model for information filtering

Information mismatch and overload are two fundamental issues influencing the effectiveness of information filtering systems. Even though both term-based and pattern-based approaches have been proposed to address the issues, neither of these approaches alone can provide a satisfactory decision for determining the relevant information. This paper presents a novel two-stage decision model for solving the issues. The first stage is a novel rough analysis model to address the overload problem. The second stage is a pattern taxonomy mining model to address the mismatch problem. The experimental results on RCV1 and TREC filtering topics show that the proposed model significantly outperforms the state-of-the-art filtering systems.

Enriching XML documents clustering by using concise structure and content

With the growing number of XML documents on theWeb it becomes essential to effectively organise these XML documents in order to retrieve useful information from them. A possible solution is to apply clustering on the XML documents to discover knowledge that promotes effective data management, information retrieval and query processing. However, many issues arise in discovering knowledge from these types of semi-structured documents due to their heterogeneity and structural irregularity. Most of the existing research on clustering techniques focuses only on one feature of the XML documents, this being either their structure or their content due to scalability and complexity problems. The knowledge gained in the form of clusters based on the structure or the content is not suitable for reallife datasets. It therefore becomes essential to include both the structure and content of XML documents in order to improve the accuracy and meaning of the clustering solution. However, the inclusion of both these kinds of information in the clustering process results in a huge overhead for the underlying clustering algorithm because of the high dimensionality of the data. The overall objective of this thesis is to address these issues by: (1) proposing methods to utilise frequent pattern mining techniques to reduce the dimension; (2) developing models to effectively combine the structure and content of XML documents; and (3) utilising the proposed models in clustering. This research first determines the structural similarity in the form of frequent subtrees and then uses these frequent subtrees to represent the constrained content of the XML documents in order to determine the content similarity. A clustering framework with two types of models, implicit and explicit, is developed. The implicit model uses a Vector Space Model (VSM) to combine the structure and the content information. The explicit model uses a higher order model, namely a 3- order Tensor Space Model (TSM), to explicitly combine the structure and the content information. This thesis also proposes a novel incremental technique to decompose largesized tensor models to utilise the decomposed solution for clustering the XML documents. The proposed framework and its components were extensively evaluated on several real-life datasets exhibiting extreme characteristics to understand the usefulness of the proposed framework in real-life situations. Additionally, this research evaluates the outcome of the clustering process on the collection selection problem in the information retrieval on the Wikipedia dataset. The experimental results demonstrate that the proposed frequent pattern mining and clustering methods outperform the related state-of-the-art approaches. In particular, the proposed framework of utilising frequent structures for constraining the content shows an improvement in accuracy over content-only and structure-only clustering results. The scalability evaluation experiments conducted on large scaled datasets clearly show the strengths of the proposed methods over state-of-the-art methods. In particular, this thesis work contributes to effectively combining the structure and the content of XML documents for clustering, in order to improve the accuracy of the clustering solution. In addition, it also contributes by addressing the research gaps in frequent pattern mining to generate efficient and concise frequent subtrees with various node relationships that could be used in clustering.

Identification of early-stage colorectal cancer patients at risk of relapse post-resection by immunobead reverse transcription-PCR analysis of peritoneal lavage fluid for malignant cells

Purpose: Colorectal cancer patients diagnosed with stage I or II disease are not routinely offered adjuvant chemotherapy following resection of the primary tumor. However, up to 10% of stage I and 30% of stage II patients relapse within 5 years of surgery from recurrent or metastatic disease. The aim of this study was to determine if tumor-associated markers could detect disseminated malignant cells and so identify a subgroup of patients with early-stage colorectal cancer that were at risk of relapse. Experimental Design: We recruited consecutive patients undergoing curative resection for early-stage colorectal cancer. Immunobead reverse transcription-PCR of five tumor-associated markers (carcinoembryonic antigen, laminin γ2, ephrin B4, matrilysin, and cytokeratin 20) was used to detect the presence of colon tumor cells in peripheral blood and within the peritoneal cavity of colon cancer patients perioperatively. Clinicopathologic variables were tested for their effect on survival outcomes in univariate analyses using the Kaplan-Meier method. A multivariate Cox proportional hazards regression analysis was done to determine whether detection of tumor cells was an independent prognostic marker for disease relapse. Results: Overall, 41 of 125 (32.8%) early-stage patients were positive for disseminated tumor cells. Patients who were marker positive for disseminated cells in post-resection lavage samples showed a significantly poorer prognosis (hazard ratio, 6.2; 95% confidence interval, 1.9-19.6; P = 0.002), and this was independent of other risk factors. Conclusion: The markers used in this study identified a subgroup of early-stage patients at increased risk of relapse post-resection for primary colorectal cancer. This method may be considered as a new diagnostic tool to improve the staging and management of colorectal cancer. © 2006 American Association for Cancer Research.

Reduced variance in monozygous twins for multiple MR parameters : implications for disease studies and the genetic basis of brain structure

Twin studies offer the opportunity to determine the relative contribution of genes versus environment in traits of interest. Here, we investigate the extent to which variance in brain structure is reduced in monozygous twins with identical genetic make-up. We investigate whether using twins as compared to a control population reduces variability in a number of common magnetic resonance (MR) structural measures, and we investigate the location of areas under major genetic influences. This is fundamental to understanding the benefit of using twins in studies where structure is the phenotype of interest. Twenty-three pairs of healthy MZ twins were compared to matched control pairs. Volume, T2 and diffusion MR imaging were performed as well as spectroscopy (MRS). Images were compared using (i) global measures of standard deviation and effect size, (ii) voxel-based analysis of similarity and (iii) intra-pair correlation. Global measures indicated a consistent increase in structural similarity in twins. The voxel-based and correlation analyses indicated a widespread pattern of increased similarity in twin pairs, particularly in frontal and temporal regions. The areas of increased similarity were most widespread for the diffusion trace and least widespread for T2. MRS showed consistent reduction in metabolite variation that was significant in the temporal lobe N-acetylaspartate (NAA). This study has shown the distribution and magnitude of reduced variability in brain volume, diffusion, T2 and metabolites in twins. The data suggest that evaluation of twins discordant for disease is indeed a valid way to attribute genetic or environmental influences to observed abnormalities in patients since evidence is provided for the underlying assumption of decreased variability in twins.