Genome wide analysis of gene expression changes in skin from patients with type 2 diabetes

Non-healing chronic ulcers are a serious complication of diabetes and are a major healthcare problem. While a host of treatments have been explored to heal or prevent these ulcers from forming, these treatments have not been found to be consistently effective in clinical trials. An understanding of the changes in gene expression in the skin of diabetic patients may provide insight into the processes and mechanisms that precede the formation of non-healing ulcers. In this study, we investigated genome wide changes in gene expression in skin between patients with type 2 diabetes and non-diabetic patients using next generation sequencing. We compared the gene expression in skin samples taken from 27 patients (13 with type 2 diabetes and 14 non-diabetic). This information may be useful in identifying the causal factors and potential therapeutic targets for the prevention and treatment of diabetic related diseases

Methods for Estimating Kidney Disease Stage Transition Probabilities Using Electronic Medical Records

Chronic diseases are often described by stages of severity. Clinical decisions about what to do are influenced by the stage, whether a patient is progressing, and the rate of progression. For chronic kidney disease (CKD), relatively little is known about the transition rates between stages. To address this, we used electronic health records (EHR) data on a large primary care population, which should have the advantage of having both sufficient follow-up time and sample size to reliably estimate transition rates for CKD. However, EHR data have some features that threaten the validity of any analysis. In particular, the timing and frequency of labratory values and clinical measurements are not determined a priori by research investigators, but rather, depend on many factors, including the current health of the patient. We developed an approach for estimatating CKD stage transition rates using hidden Markov models (HMMs), when the level of information and observation time vary among individuals. To estimate the HMMs in a computationally manageable way, we used a “discretization” method to transform daily data into intervals of 30 days, 90 days, or 180 days. We assessed the accuracy and computation time of this method via simulation studies. We also used simulations to study the effect of informative observation times on the estimated transition rates. Our simulation results showed good performance of the method, even when missing data are non-ignorable. We applied the methods to EHR data from over 60,000 primary care patients who have chronic kidney disease (stage 2 and above). We estimated transition rates between six underlying disease states. The results were similar for men and women

Accounting for the effect of heterogeneous plastic deformation on the formability of aluminium and steel sheets

Forming Limit Curves characterise ‘mean’ failure strains of sheet metals. Safety levels from the curves define the deterministic upper limit of the processing and part design window, which can be small for high strength, low formability materials. Effects of heterogeneity of plastic deformation, widely accepted to occur on the microscale, are neglected. Marciniak tests were carried out on aluminium alloys (AA6111-T4, NG5754-O), dual-phase steel (DP600) and mild steel (MS3). Digital image correlation was used to measure the effect of heterogeneity on failure. Heterogeneity, based on strain variance was modelled with the 2-component Gaussian Mixture Model and a framework was proposed to 1) identify the onset of necking and to 2) re-define formability as a probability to failure. The result were ‘forming maps’ in major-minor strain space of contours of constant probability (from probability, P=0 to P=1), which showed how failure risk increased with major strain. The contour bands indicated the unique degree of heterogeneity in each material. NG5754-O had the greatest width (0.07 strain) in plane strain and MS3 the lowest (0.03 strain). This novel characterisation will allow engineers to balance a desired forming window for a component design with the risk to failure of the material

Simulations of the 2004 North American Monsoon: NAMAP2

The second phase of the North American Monsoon Experiment (NAME) Model Assessment Project (NAMAP2) was carried out to provide a coordinated set of simulations from global and regional models of the 2004 warm season across the North American monsoon domain. This project follows an earlier assessment, called NAMAP, that preceded the 2004 field season of the North American Monsoon Experiment. Six global and four regional models are all forced with prescribed, time-varying ocean surface temperatures. Metrics for model simulation of warm season precipitation processes developed in NAMAP are examined that pertain to the seasonal progression and diurnal cycle of precipitation, monsoon onset, surface turbulent fluxes, and simulation of the low-level jet circulation over the Gulf of California. Assessment of the metrics is shown to be limited by continuing uncertainties in spatially averaged observations, demonstrating that modeling and observational analysis capabilities need to be developed concurrently. Simulations of the core subregion (CORE) of monsoonal precipitation in global models have improved since NAMAP, despite the lack of a proper low-level jet circulation in these simulations. Some regional models run at higher resolution still exhibit the tendency observed in NAMAP to overestimate precipitation in the CORE subregion; this is shown to involve both convective and resolved components of the total precipitation. The variability of precipitation in the Arizona/New Mexico (AZNM) subregion is simulated much better by the regional models compared with the global models, illustrating the importance of transient circulation anomalies (prescribed as lateral boundary conditions) for simulating precipitation in the northern part of the monsoon domain. This suggests that seasonal predictability derivable from lower boundary conditions may be limited in the AZNM subregion.open131

Talin-KANK1 interaction controls the recruitment of cortical microtubule stabilizing complexes to focal adhesions

The cross-talk between dynamic microtubules and integrin-based adhesions to the extracellular matrix plays a crucial role in cell polarity and migration. Microtubules regulate the turnover of adhesion sites, and, in turn, focal adhesions promote cortical microtubule capture and stabilization in their vicinity, but the underlying mechanism is unknown. Here, we show that cortical microtubule stabilization sites containing CLASPs, KIF21A, LL5? and liprins are recruited to focal adhesions by the adaptor protein KANK1, which directly interacts with the major adhesion component, talin. Structural studies showed that the conserved KN domain in KANK1 binds to the talin rod domain R7. Perturbation of this interaction, including a single point mutation in talin, which disrupts KANK1 binding but not the talin function in adhesion, abrogates the association of microtubule-stabilizing complexes with focal adhesions. We propose that the talin-KANK1 interaction links the two macromolecular assemblies that control cortical attachment of actin fibers and microtubules

Transcriptomic Analyses of Sexual Dimorphism of the Zebrafish Liver and the Effect of Sex Hormones

10.1371/journal.pone.0053562PLoS ONE81

Small business economics: A perspective from The Netherlands

In the analysis of economic phenomena either within or across industries there is room for integrating the role of small business. This contribution can be made by aggregation or generalization of the findings at the meso level, which again are partly based upon analyses at the micro level. The Netherlands has a long history in macro model building. A recent discussion among Dutch macro-economists considered the future of econometric model building at the macro level, and considered how best to improve this model building. The explicit integration of scale effects, however, was not mentioned. I am convinced that improvements in this respect are possible. In particular, I have in mind the role which small businesses play in certain areas such as wage structure, employment or investments. The dissection of macro prognoses into a small business component and a remaining component is a traditional practice in The Netherlands.1 Finally, there is much concern in The Netherlands for the calculation of regulatory effects, decomposed into effects for small and large businesses. If anywhere in the world there is a solid foundation for studying scale effects in both macro and sectoral models, it most certainly has been in The Netherlands. There is a strong tradition of macro-econometric model building; groups of econometricians specialized in small business research exist; Dutch policymakers show concern and the required research apparatus is available

Surrogate Markers for Time-Varying Treatments and Outcomes

BACKGROUND: A surrogate marker is a variable commonly used in clinical trials to guide treatment decisions when the outcome of ultimate interest is not available. A good surrogate marker is one where the treatment effect on the surrogate is a strong predictor of the effect of treatment on the outcome. We review the situation when there is one treatment delivered at baseline, one surrogate measured at one later time point, and one ultimate outcome of interest and discuss new issues arising when variables are time-varying. METHODS: Most of the literature on surrogate markers has only considered simple settings with one treatment, one surrogate, and one outcome of interest at a fixed time point. However, more complicated time-varying settings are common in practice. In this article, we describe the unique challenges in two settings, time-varying treatments and time-varying surrogates, while relating the ideas back to the causal-effects and causal-association paradigms. CONCLUSION: In addition to discussing and extending popular notions of surrogacy to time-varying settings, we give examples illustrating that one can be misled by not taking into account time-varying information about the surrogate or treatment. We hope this article has provided some motivation for future work on estimation and inference in such settings

Multidrug-resistant Tuberculosis in Central Asia

Multidrug-resistant tuberculosis (MDR-TB) has emerged as a major threat to TB control, particularly in the former Soviet Union. To determine levels of drug resistance within a directly observed treatment strategy (DOTS) program supported by Médecins Sans Frontières in two regions in Uzbekistan and Turkmenistan, Central Asia, we conducted a cross-sectional survey of smear-positive TB patients in selected districts of Karakalpakstan (Uzbekistan) and Dashoguz (Turkmenistan). High levels of MDR-TB were found in both regions. In Karakalpakstan, 14 (13%) of 106 new patients were infected with MDR-TB; 43 (40%) of 107 previously treated patients were similarly infected. The proportions for Dashoguz were 4% (4/105 patients) and 18% (18/98 patients), respectively. Overall, 27% of patients with positive smear results whose infections were treated through the DOTS program in Karakalpakstan and 11% of similar patients in Dashoguz were infected with multidrug-resistant strains of TB on admission. These results show the need for concerted action by the international community to contain transmission and reduce the effects of MDR-TB