Patient perspectives of the impact and long-term management of lymphoedema

Lymphoedema following cancer treatment is characterized by swelling, and adversely influences mobility, function and quality of life. There is no cure, but without treatment lymphedema may progress. Since lymphedema treatment options are costly and time consuming, understanding the influence of these, and other potential barriers, on treatment adherence is vital in reducing the public health burden of lymphedema. Complex physical therapy and compression are supported by scientific evidence and patients also perceive these treatments as effective for improving symptoms and function. Multiple treatments may be required to treat all aspects of the condition. Patients and health professionals should consider effect and costs when identifying optimal treatment strategies.

MT1-MMP-dependent and -independent regulation of gelatinase A activation in long-term, ascorbate-treated fibroblast cultures: Regulation by fibrillar collagen

Human skin fibroblasts were cultured long-term in the presence of ascorbic acid to allow formation of a three-dimensional collagen matrix, and the effects of this on activation of secreted matrix metalloproteinase-2 (MMP-2) were examined. Accumulation of collagen over time correlated with increased levels of both mature MMP-2 and cell-associated membrane type 1-MMP (MT1-MMP), and subsequently increased mRNA levels for MT1-MMP, providing temporal resolution of the "nontranscriptional" and "transcriptional" effects of collagen on MT-1MMP functionality. MMP-2 activation by these cultures was blocked by inhibitors of prolyl-4-hydroxylase, or when fibroblasts derived from the collagen α1(I) gene-deficient Mov-13 mouse were used. MMP-2 activation by the Mov-13 fibroblasts was rescued by transfection of a full-length α1(I) collagen cDNA, and to our surprise, also by transfection with an α1(I) collagen cDNA carrying a mutation at the C-proteinase cleavage, which almost abrogated fibrillogenesis. Although studies with ascorbate-cultured MT1-MMP-/- fibroblasts showed that MT1-MMP played a significant role in the collagen-induced MMP-2 activation, a residual MT1-MMP-independent activation of MMP-2 was seen which resembled the level of MMP-2 activation persisting when wild-type fibroblasts were cultured in the presence of both ascorbic acid and MMP inhibitors. We were also unable to block this residual activation with inhibitors specific for serinyl, aspartyl, or cysteinyl enzymes.

Predicting positive and negative impacts of cancer among long-term endometrial cancer survivors

OBJECTIVE Although the survival outcomes among women diagnosed with endometrial cancer are very favorable, little is known about the long-term impact of their cancer experience. This study identifies the extent of positive and negative impacts of cancer and factors associated with this, amongst long-term survivors of endometrial cancer. METHODS Australian women diagnosed with endometrial cancer (N=632) were sent questionnaires at the time of diagnosis and 3-5 years later. Hierarchical multiple regression models were used to examine whether a range of variables at diagnosis/treatment predicted subsequent scores on the Impact of Cancer Scale, which examines positive (e.g. health awareness) and negative (e.g. appearance concerns) impacts amongst cancer survivors. RESULTS Overall, women had a higher mean score for the positive than negative impact scales (M=3.5 versus M=2.5, respectively). An intermediate grade of endometrial cancer, a prior diagnosis of cancer and lower levels of education were significant, but weak, predictors of higher scores on the positive impact scale. Higher scores on the negative impact scale were predicted by a higher grade of cancer, poor physical and mental health, a younger age, being single or having lower levels of education. CONCLUSIONS The study demonstrates that factors that predict positive impact in cancer survivors differ to those that predict negative impact, suggesting that interventions to optimize cancer survivors' quality of life will need to be multi-dimensional, and this supports the need for tailored intervention.

Calculate excess mortality during heatwaves using Hilbert-Huang transform algorithm

Background Heatwaves could cause the population excess death numbers to be ranged from tens to thousands within a couple of weeks in a local area. An excess mortality due to a special event (e.g., a heatwave or an epidemic outbreak) is estimated by subtracting the mortality figure under ‘normal’ conditions from the historical daily mortality records. The calculation of the excess mortality is a scientific challenge because of the stochastic temporal pattern of the daily mortality data which is characterised by (a) the long-term changing mean levels (i.e., non-stationarity); (b) the non-linear temperature-mortality association. The Hilbert-Huang Transform (HHT) algorithm is a novel method originally developed for analysing the non-linear and non-stationary time series data in the field of signal processing, however, it has not been applied in public health research. This paper aimed to demonstrate the applicability and strength of the HHT algorithm in analysing health data. Methods Special R functions were developed to implement the HHT algorithm to decompose the daily mortality time series into trend and non-trend components in terms of the underlying physical mechanism. The excess mortality is calculated directly from the resulting non-trend component series. Results The Brisbane (Queensland, Australia) and the Chicago (United States) daily mortality time series data were utilized for calculating the excess mortality associated with heatwaves. The HHT algorithm estimated 62 excess deaths related to the February 2004 Brisbane heatwave. To calculate the excess mortality associated with the July 1995 Chicago heatwave, the HHT algorithm needed to handle the mode mixing issue. The HHT algorithm estimated 510 excess deaths for the 1995 Chicago heatwave event. To exemplify potential applications, the HHT decomposition results were used as the input data for a subsequent regression analysis, using the Brisbane data, to investigate the association between excess mortality and different risk factors. Conclusions The HHT algorithm is a novel and powerful analytical tool in time series data analysis. It has a real potential to have a wide range of applications in public health research because of its ability to decompose a nonlinear and non-stationary time series into trend and non-trend components consistently and efficiently.

Combined analysis of categorical and numerical descriptors of Australian groundnut accessions using nonlinear principal component analysis

For users of germplasm collections, the purpose of measuring characterization and evaluation descriptors, and subsequently using statistical methodology to summarize the data, is not only to interpret the relationships between the descriptors, but also to characterize the differences and similarities between accessions in relation to their phenotypic variability for each of the measured descriptors. The set of descriptors for the accessions of most germplasm collections consists of both numerical and categorical descriptors. This poses problems for a combined analysis of all descriptors because few statistical techniques deal with mixtures of measurement types. In this article, nonlinear principal component analysis was used to analyze the descriptors of the accessions in the Australian groundnut collection. It was demonstrated that the nonlinear variant of ordinary principal component analysis is an appropriate analytical tool because subspecies and botanical varieties could be identified on the basis of the analysis and characterized in terms of all descriptors. Moreover, outlying accessions could be easily spotted and their characteristics established. The statistical results and their interpretations provide users with a more efficient way to identify accessions of potential relevance for their plant improvement programs and encourage and improve the usefulness and utilization of germplasm collections.

Dynamic modelling of long-term care decisions

This paper describes and analyzes research on the dynamics of long-term care and the policy relevance of identifying the sources of persistence in caregiving arrangements (including the effect of dynamics on parameter estimates, implications for family welfare, parent welfare, child welfare, and cost of government programs). We discuss sources and causes of observed persistence in caregiving arrangements including inertia/state dependence (confounded by unobserved heterogeneity) and costs of changing caregivers. We comment on causes of dynamics including learning/human capital accumulation; burnout; and game-playing. We suggest how to deal with endogenous geography; dynamics in discrete and continuous choices; and equilibrium issues (multiple equilibria, dynamic equilibria). We also present an overview of commonly used longitudinal data sets and evaluate their relative advantages/disadvantages. We also discuss other data issues related to noisy measures of wealth and family structure. Finally, we suggest some methods to handle econometric problems such as endogeneous geography. © 2014 Springer Science+Business Media New York.

Strategic play among family members when making long-term care decisions

This paper describes a strategic model of bargaining within a family to determine how to care for an elderly parent. We estimate the parameters of the model using data from the National Long-term Care Survey. We find that the parameter estimates generally make sense and that the model is consistent with the data. The results have strong implications for using less structural empirical models for policy analysis.

Long-term care and family bargaining

We present a structural model of how families decide who should care for elderly parents. We use data from the National Long-Term Care Survey to estimate and test the parameters of the model. Then we use the parameter estimates to simulate the effects of the existing long-term trends in terms of the common but untested explanations for them. Finally, we simulate the effects of alternative family bargaining rules on individual utility to measure the sensitivity of our results to the family decision-making assumptions we make.

Measuring child work and residence adjustments to parents' long-term care needs

This article estimates the effects of various parent and child characteristics on the choice of care arrangement of the parent, taking into account the potential endogeneity of some of the child characteristics. Three equations are estimated: a care choice equation, a child location equation, and a child work equation. Results suggest a hierarchy of family decision making; child locations affect the care decision, which affects child work decisions. The results also question previous research attempting to explain causes of secular trends in long-term care.

Gene electrotransfer into murine skeletal muscle: A systematic analysis of parameters for long-term gene expression

Skeletal muscle is an attractive target tissue for delivery of therapeutic genes, since it is well vascularized, easily accessible, and has a high capacity for protein synthesis. For efficient transfection in skeletal muscle, several protocols have been described, including delivery of low voltage electric pulses and a combination of high and low voltage electric pulses. The aim of this study was to determine the influence of different parameters of electrotransfection on short-term and long-term transfection efficiency in murine skeletal muscle, and to evaluate histological changes in the treated tissue. Different parameters of electric pulses, different time lags between plasmid DNA injection and application of electric pulses, and different doses of plasmid DNA were tested for electrotransfection of tibialis cranialis muscle of C57BI/6 mice using DNA plasmid encoding green fluorescent protein (GFP). Transfection efficiency was assessed on frozen tissue sections one week after electrotransfection using a fluorescence microscope and also noninvasively, followed by an in vivo imaging system using a fluorescence stereo microscope over a period of several months. Histological changes in muscle were evaluated immediately or several months after electrotransfection by determining infiltration of inflammatory mononuclear cells and presence of necrotic muscle fibers. The most efficient electrotransfection into skeletal muscle of C57BI/6 mice in our experiments was achieved when one high voltage (HV) and four low voltage (LV) electric pulses were applied 5 seconds after the injection of 30 μg of plasmid DNA. This protocol resulted in the highest short-term as well as long-term transfection. The fluorescence intensity of the transfected area declined after 2-3 weeks, but GFP fluorescence was still detectable 18 months after electrotransfection. Extensive inflammatory mononuclear cell infiltration was observed immediately after the electrotransfection procedure using the described parameters, but no necrosis or late tissue damage was observed. This study showed that electric pulse parameters, time lag between the injection of DNA and application of electric pulses, and dose of plasmid DNA affected the duration of transgene expression in murine skeletal muscle. Therefore, transgene expression in muscle can be controlled by appropriate selection of electrotransfection protocol.

Demonstration of nonlinear absorption in Au semi-continuous film by electrical measurement

We have demonstrated the nonlinear absorption at 532 nm wavelength in an Au semi-continuous film (SF) resulting from smearing of the Fermi distribution and diffusion of conduction electrons into the substrate. The Au SF was irradiated by a pulsed laser with 8 ns pulse width at 532 nm in near resonance with the interband transition of the Au. We determined the temperature increase in the SF for different intensities by electrical measurement. We calculated the temperature increase by using a 1D heat transport equation; comparing the results of the calculation with measured values for the temperature increase, revealed the nonlinear absorption in the Au SF. We employed this deviation from linear behaviour to determine the nonlinear absorption coefficient.

Arterial short-term travel time prediction using Bluetooth data

This project recognized lack of data analysis and travel time prediction on arterials as the main gap in the current literature. For this purpose it first investigated reliability of data gathered by Bluetooth technology as a new cost effective method for data collection on arterial roads. Then by considering the similarity among varieties of daily travel time on different arterial routes, created a SARIMA model to predict future travel time values. Based on this research outcome, the created model can be applied for online short term travel time prediction in future.

Nonlinear ion-acoustic surface waves on a dusty plasma

A nonlinear theory for ion-acoustic surface waves propagating at the interface between a dusty plasma and a dielectric is presented. The nonlinear effects are associated with density modulations caused by surface-wave induced anomalous ionization. The negative charge of the massive dust grains is assumed to be constant. It is shown that the effect of the ionization nonlinearity arising from the ion-acoustic surface waves can result in the formation of surface envelope solitons. The wave phase shifts and the widths of the solitons are estimated for typical gas discharge plasmas.

Nonlinear effects of ionization on surface waves on a plasma-metal interface

Nonlinear effects associated with density modulation caused by wave-induced ionization in magnetized plasmas were studied. The ionizing surface waves propagate at the interface between the plasma and a metallic surface. It is shown that the ionization nonlinearity can be important for typical experimental conditions.

Nonlinear geometric and material computational technique : higher-order element with refined plastic hinge approach

This paper addresses of the advanced computational technique of steel structures for both simulation capacities simultaneously; specifically, they are the higher-order element formulation with element load effect (geometric nonlinearities) as well as the refined plastic hinge method (material nonlinearities). This advanced computational technique can capture the real behaviour of a whole second-order inelastic structure, which in turn ensures the structural safety and adequacy of the structure. Therefore, the emphasis of this paper is to advocate that the advanced computational technique can replace the traditional empirical design approach. In the meantime, the practitioner should be educated how to make use of the advanced computational technique on the second-order inelastic design of a structure, as this approach is the future structural engineering design. It means the future engineer should understand the computational technique clearly; realize the behaviour of a structure with respect to the numerical analysis thoroughly; justify the numerical result correctly; especially the fool-proof ultimate finite element is yet to come, of which is competent in modelling behaviour, user-friendly in numerical modelling and versatile for all structural forms and various materials. Hence the high-quality engineer is required, who can confidently manipulate the advanced computational technique for the design of a complex structure but not vice versa.