A quasi-likelihood method for fractal-dimension estimation

We propose a simple method of constructing quasi-likelihood functions for dependent data based on conditional-mean-variance relationships, and apply the method to estimating the fractal dimension from box-counting data. Simulation studies were carried out to compare this method with the traditional methods. We also applied this technique to real data from fishing grounds in the Gulf of Carpentaria, Australia

Robust estimation using the Huber function with a data-dependent tuning constant

Robust estimation often relies on a dispersion function that is more slowly varying at large values than the square function. However, the choice of tuning constant in dispersion functions may impact the estimation efficiency to a great extent. For a given family of dispersion functions such as the Huber family, we suggest obtaining the "best" tuning constant from the data so that the asymptotic efficiency is maximized. This data-driven approach can automatically adjust the value of the tuning constant to provide the necessary resistance against outliers. Simulation studies show that substantial efficiency can be gained by this data-dependent approach compared with the traditional approach in which the tuning constant is fixed. We briefly illustrate the proposed method using two datasets.

Unbiased estimating equations from working correlation models for irregularly timed repeated measures

The method of generalized estimating equation-, (GEEs) has been criticized recently for a failure to protect against misspecification of working correlation models, which in some cases leads to loss of efficiency or infeasibility of solutions. However, the feasibility and efficiency of GEE methods can be enhanced considerably by using flexible families of working correlation models. We propose two ways of constructing unbiased estimating equations from general correlation models for irregularly timed repeated measures to supplement and enhance GEE. The supplementary estimating equations are obtained by differentiation of the Cholesky decomposition of the working correlation, or as score equations for decoupled Gaussian pseudolikelihood. The estimating equations are solved with computational effort equivalent to that required for a first-order GEE. Full details and analytic expressions are developed for a generalized Markovian model that was evaluated through simulation. Large-sample ".sandwich" standard errors for working correlation parameter estimates are derived and shown to have good performance. The proposed estimating functions are further illustrated in an analysis of repeated measures of pulmonary function in children.

Kallikrein-related peptidases in prostate cancer: From molecular function to clinical application

Prostate cancer is a leading contributor to male cancer-related deaths worldwide. Kallikrein-related peptidases (KLKs) are serine proteases that exhibit deregulated expression in prostate cancer, with KLK3, or prostate specific antigen (PSA), being the widely-employed clinical biomarker for prostate cancer. Other KLKs, such as KLK2, show promise as prostate cancer biomarkers and, additionally, their altered expression has been utilised for the design of KLK-targeted therapies. There is also a large body of in vitro and in vivo evidence supporting their role in cancer-related processes. Here, we review the literature on studies to date investigating the potential of other KLKs, in addition to PSA, as biomarkers and in therapeutic options, as well as their current known functional roles in cancer progression. Increased knowledge of these KLK-mediated functions, including degradation of the extracellular matrix, local invasion, cancer cell proliferation, interactions with fibroblasts, angiogenesis, migration, bone metastasis and tumour growth in vivo, may help define new roles as prognostic biomarkers and novel therapeutic targets for this cancer.

Effects of the sensorimotor training volume on sensorimotor function in patients following lower limb arthroplasty

Background Sensorimotor function is degraded in patients after lower limb arthroplasty. Sensorimotor training is thought to improve sensorimotor skills, however, the optimal training stimulus with regard to volume, frequency, duration, and intensity is still unknown. The aim of this study, therefore, was to firstly quantify the progression of sensorimotor function after total hip (THA) or knee (TKA) arthroplasty and, as second step, to evaluate effects of different sensorimotor training volumes. Methods 58 in-patients during their rehabilitation after THA or TKA participated in this prospective cohort study. Sensorimotor function was assessed using a test battery including measures of stabilization capacity, static balance, proprioception, and gait, along with a self-reported pain and function. All participants were randomly assigned to one of three intervention groups performing sensorimotor training two, four, or six times per week. Outcome measures were taken at three instances, at baseline (pre), after 1.5 weeks (mid) and at the conclusion of the 3 week program (post). Results All measurements showed significant improvements over time, with the exception of proprioception and static balance during quiet bipedal stance which showed no significant main effects for time or intervention. There was no significant effect of sensorimotor training volume on any of the outcome measures. Conclusion We were able to quantify improvements in measures of dynamic, but not static, sensorimotor function during the initial three weeks of rehabilitation following TKA/THA. Although sensorimotor improvements were independent of the training volume applied in the current study, long-term effects of sensorimotor training volume need to be investigated to optimize training stimulus recommendations.

A generalized estimating equations approach for analysis of the impact of new technology on a trawl fishery

The article describes a generalized estimating equations approach that was used to investigate the impact of technology on vessel performance in a trawl fishery during 1988-96, while accounting for spatial and temporal correlations in the catch-effort data. Robust estimation of parameters in the presence of several levels of clustering depended more on the choice of cluster definition than on the choice of correlation structure within the cluster. Models with smaller cluster sizes produced stable results, while models with larger cluster sizes, that may have had complex within-cluster correlation structures and that had within-cluster covariates, produced estimates sensitive to the correlation structure. The preferred model arising from this dataset assumed that catches from a vessel were correlated in the same years and the same areas, but independent in different years and areas. The model that assumed catches from a vessel were correlated in all years and areas, equivalent to a random effects term for vessel, produced spurious results. This was an unexpected finding that highlighted the need to adopt a systematic strategy for modelling. The article proposes a modelling strategy of selecting the best cluster definition first, and the working correlation structure (within clusters) second. The article discusses the selection and interpretation of the model in the light of background knowledge of the data and utility of the model, and the potential for this modelling approach to apply in similar statistical situations.

A quasi-likelihood approach for ordered categorical data with overdispersion

Quasi-likelihood (QL) methods are often used to account for overdispersion in categorical data. This paper proposes a new way of constructing a QL function that stems from the conditional mean-variance relationship. Unlike traditional QL approaches to categorical data, this QL function is, in general, not a scaled version of the ordinary log-likelihood function. A simulation study is carried out to examine the performance of the proposed QL method. Fish mortality data from quantal response experiments are used for illustration.

Serum immunoreactive pancreatic lipase and cationic trypsinogen for the assessment of exocrine pancreatic function in older patients with cystic fibrosis

Indirect and qualitative tests of pancreatic function are commonly used to screen patients with cystic fibrosis for pancreatic insufficiency. In an attempt to develop a more quantitative assessment, we compared the usefulness of measuring serum pancreatic lipase using a newly developed enzyme-linked immunosorbent immunoassay with that of cationic trypsinogen using a radioimmunoassay in the assessment of exocrine pancreatic function in patients with cystic fibrosis. Previously, we have shown neither lipase nor trypsinogen to be of use in assessing pancreatic function prior to 5 years of age because the majority of patients with cystic fibrosis in early infancy have elevated serum levels regardless of pancreatic function. Therefore, we studied 77 patients with cystic fibrosis older than 5 years of age, 41 with steatorrhea and 36 without steatorrhea. In addition, 28 of 77 patients consented to undergo a quantitative pancreatic stimulation test. There was a significant difference between the steatorrheic and nonsteatorrheic patients with the steatorrheic group having lower lipase and trypsinogen values than the nonsteatorrheic group (P < .001). Sensitivities and specificities in detecting steatorrhea were 95% and 86%, respectively, for lipase and 93% and 92%, respectively, for trypsinogen. No correlations were found between the serum levels of lipase and trypsinogen and their respective duodenal concentrations because of abnormally high serum levels of both enzymes found in some nonsteatorrheic patients. We conclude from this study that both serum lipase and trypsinogen levels accurately detect steatorrhea in patients with cystic fibrosis who are older than 5 years but are imprecise indicators of specific pancreatic exocrine function above the level needed for normal fat absorption.

Impaired physical function associated with childhood obesity: How should we intervene?

- Background This study examined relationships between adiposity, physical functioning and physical activity. - Methods Obese (N=107) and healthy-weight (N=132) children aged 10-13 years underwent assessments of percent body fat (%BF, dual energy X-ray absorptiometry), knee extensor strength (KE, isokinetic dynamometry), cardiorespiratory fitness (CRF, peak oxygen uptake by cycle ergometry), physical health-related quality of life (HRQOL), worst pain intensity and walking capacity [six-minute walk (6MWT)]. Structural equation modelling was used to assess relationships between variables. - Results Moderate relationships were observed between %BF and 6MWT, KE strength corrected for mass and CRF relative to mass (r -.36 to -.69, P≤.007). Weak relationships were found between: %BF and physical HRQOL (r -.27, P=.008); CRF relative to mass and physical HRQOL (r -.24, P=.003); physical activity and 6MWT (r .17, P=.004). Squared multiple correlations showed that 29.6% variance in physical HRQOL was explained by %BF, pain and CRF relative to mass, while 28% variance in 6MWT was explained by %BF and physical activity. - Conclusions It appears that children with a higher body fat percentage have poorer KE strength, CRF and overall physical functioning. Reducing percent fat appears to be the best target to improve functioning. However, a combined approach to intervention, targeting reductions in body fat percentage, pain and improvements in physical activity and CRF may assist physical functioning.

The mechanisms of human renal epithelial cell modulation of autologous dendritic cell phenotype and function

Proximal tubule epithelial cells (PTEC) of the kidney line the proximal tubule downstream of the glomerulus and play a major role in the re-absorption of small molecular weight proteins that may pass through the glomerular filtration process. In the perturbed disease state PTEC also contribute to the inflammatory disease process via both positive and negative mechanisms via the production of inflammatory cytokines which chemo-attract leukocytes and the subsequent down-modulation of these cells to prevent uncontrolled inflammatory responses. It is well established that dendritic cells are responsible for the initiation and direction of adaptive immune responses. Both resident and infiltrating dendritic cells are localised within the tubulointerstitium of the renal cortex, in close apposition to PTEC, in inflammatory disease states. We previously demonstrated that inflammatory PTEC are able to modulate autologous human dendritic cell phenotype and functional responses. Here we extend these findings to characterise the mechanisms of this PTEC immune-modulation using primary human PTEC and autologous monocyte-derived dendritic cells (MoDC) as the model system. We demonstrate that PTEC express three inhibitory molecules: (i) cell surface PD-L1 that induces MoDC expression of PD-L1; (ii) intracellular IDO that maintains the expression of MoDC CD14, drives the expression of CD80, PD-L1 and IL-10 by MoDC and inhibits T cell stimulatory capacity; and (iii) soluble HLA-G (sHLA-G) that inhibits HLA-DR and induces IL-10 expression by MoDC. Collectively the results demonstrate that primary human PTEC are able to modulate autologous DC phenotype and function via multiple complex pathways. Further dissection of these pathways is essential to target therapeutic strategies in the treatment of inflammatory kidney disorders.

Age-related changes in hepatic function: An update on implications for drug therapy

The accumulation of deficits with increasing age results in a decline in the functional capacity of multiple organs and systems. These changes can have a significant influence on the pharmacokinetics and pharmacodynamics of prescribed drugs. Although alterations in body composition and worsening renal clearance are important considerations, for most drugs the liver has the greatest effect on metabolism. Age-related change in hepatic function thereby causes much of the variability in older people’s responses to medication. In this review, we propose that a decline in the ability of the liver to inactivate toxins may contribute to a proinflammatory state in which frailty can develop. Since inflammation also downregulates drug metabolism, medication prescribed to frail older people in accordance with disease-specific guidelines may undergo reduced systemic clearance, leading to adverse drug reactions, further functional decline and increasing polypharmacy, exacerbating rather than ameliorating frailty status. We also describe how increasing chronological age and frailty status impact liver size, blood flow and protein binding and enzymes of drug metabolism. This is used to contextualise our discussion of appropriate prescribing practices. For example, while the general axiom of ‘start low, go slow’ should underpin the initiation of medication (titrating to a defined therapeutic goal), it is important to consider whether drug clearance is flow or capacity-limited. By summarising the effect of age-related changes in hepatic function on medications commonly used in older people, we aim to provide a guide that will have high clinical utility for practising geriatricians.

Time evolution of graphene growth on SiC as a function of annealing temperature

We followed by X-ray Photoelectron Spectroscopy (XPS) the time evolution of graphene layers obtained by annealing 3C SiC(111)/Si(111) crystals at different temperatures. The intensity of the carbon signal provides a quantification of the graphene thickness as a function of the annealing time, which follows a power law with exponent 0.5. We show that a kinetic model, based on a bottom-up growth mechanism, provides a full explanation to the evolution of the graphene thickness as a function of time, allowing to calculate the effective activation energy of the process and the energy barriers, in excellent agreement with previous theoretical results. Our study provides a complete and exhaustive picture of Si diffusion into the SiC matrix, establishing the conditions for a perfect control of the graphene growth by Si sublimation.

Exercise and vascular function in child obesity: A meta-analysis

CONTEXT: Conduit artery flow-mediated dilation (FMD) is a noninvasive index of preclinical atherosclerosis in humans. Exercise interventions can improve FMD in both healthy and clinical populations. OBJECTIVE: This systematic review and meta-analysis aimed to summarize the effect of exercise training on FMD in overweight and obese children and adolescents as well as investigate the role of cardiorespiratory fitness (peak oxygen consumption [Vo2peak]) on effects observed. DATA SOURCES: PubMed, Medline, Embase, and Cinahl databases were searched from the earliest available date to February 2015. STUDY SELECTION: Studies of children and/or adolescents who were overweight or obese were included. DATA EXTRACTION: Standardized data extraction forms were used for patient and intervention characteristics, control/comparator groups, and key outcomes. Procedural quality of the studies was assessed using a modified version of the Physiotherapy Evidence Base Database scale. RESULTS: A meta-analysis involving 219 participants compared the mean difference of pre- versus postintervention vascular function (FMD) and Vo2peak between an exercise training intervention and a control condition. There was a significantly greater improvement in FMD (mean difference 1.54%, P < .05) and Vo2peak (mean difference 3.64 mL/kg/min, P < .05) after exercise training compared with controls. LIMITATIONS: Given the diversity of exercise prescriptions, participant characteristics, and FMD measurement protocols, varying FMD effect size was noted between trials. CONCLUSIONS: Exercise training improves vascular function in overweight and obese children, as indicated by enhanced FMD. Further research is required to establish the optimum exercise program for maintenance of healthy vascular function in this at-risk pediatric population.

A new family of multivariate heavy-tailed distributions with variable marginal amounts of tailweight: Application to robust clustering

We propose a family of multivariate heavy-tailed distributions that allow variable marginal amounts of tailweight. The originality comes from introducing multidimensional instead of univariate scale variables for the mixture of scaled Gaussian family of distributions. In contrast to most existing approaches, the derived distributions can account for a variety of shapes and have a simple tractable form with a closed-form probability density function whatever the dimension. We examine a number of properties of these distributions and illustrate them in the particular case of Pearson type VII and t tails. For these latter cases, we provide maximum likelihood estimation of the parameters and illustrate their modelling flexibility on simulated and real data clustering examples.