Acute ischemic cerebrovascular events on antiplatelet therapy: what is the optimal prevention strategy?

Even though patients who develop ischemic stroke despite taking antiplatelet drugs represent a considerable proportion of stroke hospital admissions, there is a paucity of data from investigational studies regarding the most suitable therapeutic intervention. There have been no clinical trials to test whether increasing the dose or switching antiplatelet agents reduces the risk for subsequent events. Certain issues have to be considered in patients managed for a first or recurrent stroke while receiving antiplatelet agents. Therapeutic failure may be due to either poor adherence to treatment, associated co-morbid conditions and diminished antiplatelet effects (resistance to treatment). A diagnostic work up is warranted to identify the etiology and underlying mechanism of stroke, thereby guiding further management. Risk factors (including hypertension, dyslipidemia and diabetes) should be treated according to current guidelines. Aspirin or aspirin plus clopidogrel may be used in the acute and early phase of ischemic stroke, whereas in the long-term, antiplatelet treatment should be continued with aspirin, aspirin/extended release dipyridamole or clopidogrel monotherapy taking into account tolerance, safety, adherence and cost issues. Secondary measures to educate patients about stroke, the importance of adherence to medication, behavioral modification relating to tobacco use, physical activity, alcohol consumption and diet to control excess weight should also be implemented.

Definition of key variables for the induction of optimal NY-ESO-1-specific T cells in HLA transgene mice.

An attractive treatment of cancer consists in inducing tumor-eradicating CD8(+) CTL specific for tumor-associated Ags, such as NY-ESO-1 (ESO), a strongly immunogenic cancer germ line gene-encoded tumor-associated Ag, widely expressed on diverse tumors. To establish optimal priming of ESO-specific CTL and to define critical vaccine variables and mechanisms, we used HLA-A2/DR1 H-2(-/-) transgenic mice and sequential immunization with immunodominant DR1- and A2-restricted ESO peptides. Immunization of mice first with the DR1-restricted ESO(123-137) peptide and subsequently with mature dendritic cells (DCs) presenting this and the A2-restriced ESO(157-165) epitope generated abundant, circulating, high-avidity primary and memory CD8(+) T cells that efficiently killed A2/ESO(157-165)(+) tumor cells. This prime boost regimen was superior to other vaccine regimes and required strong Th1 cell responses, copresentation of MHC class I and MHC class II peptides by the same DC, and resulted in upregulation of sphingosine 1-phosphate receptor 1, and thus egress of freshly primed CD8(+) T cells from the draining lymph nodes into circulation. This well-defined system allowed detailed mechanistic analysis, which revealed that 1) the Th1 cytokines IFN-gamma and IL-2 played key roles in CTL priming, namely by upregulating on naive CD8(+) T cells the chemokine receptor CCR5; 2) the inflammatory chemokines CCL4 (MIP-1beta) and CCL3 (MIP-1alpha) chemoattracted primed CD4(+) T cells to mature DCs and activated, naive CD8(+) T cells to DC-CD4 conjugates, respectively; and 3) blockade of these chemokines or their common receptor CCR5 ablated priming of CD8(+) T cells and upregulation of sphingosine 1-phosphate receptor 1. These findings provide new opportunities for improving T cell cancer vaccines.

Choice of Optimal MembraneProcesses for Economical Treatment of Paper Machine Clear Filtrate

In this thesis membrane filtration of paper machnie clear filtrate was studied. The aim of the study was to find membrane processes which are able to produce economically water of sufficient purity from paper machine white water or its saveall clarified fractions for reuse in the paper machnie short circulation. Factors affecting membrane fouling in this application were also studied. The thesis gives an overview af experiments done on a laboratory and a pilot scale with several different membranes and membrane modules. The results were judged by the obtained flux, the fouling tendency and the permeate quality assessed with various chemical analyses. It was shown that membrane modules which used a turbulence promotor of some kind gave the highest fluexes. However, the results showed that the greater the reduction in the concentration polarisation layer caused by increased turbulence in the module, the smaller the reductions in measured substances. Out of the micro-, ultra- and nanofiltration membranes tested, only nanofiltration memebranes produced permeate whose quality was very close to that of the chemically treated raw water used as fresh water in most paper mills today and which should thus be well suited for reuse as shower water both in the wire and press section. It was also shown that a one stage nanofiltration process was more effective than processes in which micro- or ultrafiltration was used as pretreatment for nanofiltration. It was generally observed that acidic pH, high organic matter content, the presence of multivalent ions, hydrophobic membrane material and high membrane cutoff increased the fouling tendency of the membranes.

Réhabilitation améliorée après chirurgie--L'ere de la prise en charge optimale du patient chirurgical [Enhanced Recovery After Surgery--optimal management of the surgical patient].

Enhanced Recovery After Surgery (ERAS) is a multimodal, standardized and evidence-based perioperative care pathway. With ERAS, postoperative complications are significantly lowered, and, as a secondary effect, length of hospital stay and health cost are reduced. The patient recovers better and faster allowing to reduce in addition the workload of healthcare providers. Despite the hospital discharge occurs sooner, there is no increased charge of the outpatient care. ERAS can be safely applied to any patient by a tailored approach. The general practitioner plays an essential role in ERAS by assuring the continuity of the information and the follow-up of the patient.

Clinical trial designs for rare diseases: studies developed and discussed by the International Rare Cancers Initiative.

BACKGROUND: The past three decades have seen rapid improvements in the diagnosis and treatment of most cancers and the most important contributor has been research. Progress in rare cancers has been slower, not least because of the challenges of undertaking research. SETTINGS: The International Rare Cancers Initiative (IRCI) is a partnership which aims to stimulate and facilitate the development of international clinical trials for patients with rare cancers. It is focused on interventional--usually randomized--clinical trials with the clear goal of improving outcomes for patients. The key challenges are organisational and methodological. A multi-disciplinary workshop to review the methods used in ICRI portfolio trials was held in Amsterdam in September 2013. Other as-yet unrealised methods were also discussed. RESULTS: The IRCI trials are each presented to exemplify possible approaches to designing credible trials in rare cancers. Researchers may consider these for use in future trials and understand the choices made for each design. INTERPRETATION: Trials can be designed using a wide array of possibilities. There is no 'one size fits all' solution. In order to make progress in the rare diseases, decisions to change practice will have to be based on less direct evidence from clinical trials than in more common diseases.

Optimal capital structure: a trade-off model and its empirical testing

In the present research we have set forth a new, simple, Trade-Off model that would allow us to calculate how much debt and, by default, how much equity a company should have, using easily available information and calculating the cost of debt dynamically on the basis of the effect that the capital structure of the company has on the risk of bankruptcy; in an attempt to answer this question. The proposed model has been applied to the companies that make up the Dow Jones Industrial Average (DJIA) in 2007. We have used consolidated financial data from 1996 to 2006, published by Bloomberg. We have used simplex optimization method to find the debt level that maximizes firm value. Then, we compare the estimated debt with real debt of companies using statistical nonparametric Mann-Whitney. The results indicate that 63% of companies do not show a statistically significant difference between the real and the estimated debt.

Preferred Spatial Frequencies for Human Face Processing Are Associated with Optimal Class Discrimination in the Machine

Psychophysical studies suggest that humans preferentially use a narrow band of low spatial frequencies for face recognition. Here we asked whether artificial face recognition systems have an improved recognition performance at the same spatial frequencies as humans. To this end, we estimated recognition performance over a large database of face images by computing three discriminability measures: Fisher Linear Discriminant Analysis, Non-Parametric Discriminant Analysis, and Mutual Information. In order to address frequency dependence, discriminabilities were measured as a function of (filtered) image size. All three measures revealed a maximum at the same image sizes, where the spatial frequency content corresponds to the psychophysical found frequencies. Our results therefore support the notion that the critical band of spatial frequencies for face recognition in humans and machines follows from inherent properties of face images, and that the use of these frequencies is associated with optimal face recognition performance.

Data-division-specific robustness and power of randomization tests for ABAB designs

This study deals with the statistical properties of a randomization test applied to an ABAB design in cases where the desirable random assignment of the points of change in phase is not possible. In order to obtain information about each possible data division we carried out a conditional Monte Carlo simulation with 100,000 samples for each systematically chosen triplet. Robustness and power are studied under several experimental conditions: different autocorrelation levels and different effect sizes, as well as different phase lengths determined by the points of change. Type I error rates were distorted by the presence of autocorrelation for the majority of data divisions. Satisfactory Type II error rates were obtained only for large treatment effects. The relationship between the lengths of the four phases appeared to be an important factor for the robustness and the power of the randomization test.

Rapid optimization of drug combinations for the optimal angiostatic treatment of cancer.

Drug combinations can improve angiostatic cancer treatment efficacy and enable the reduction of side effects and drug resistance. Combining drugs is non-trivial due to the high number of possibilities. We applied a feedback system control (FSC) technique with a population-based stochastic search algorithm to navigate through the large parametric space of nine angiostatic drugs at four concentrations to identify optimal low-dose drug combinations. This implied an iterative approach of in vitro testing of endothelial cell viability and algorithm-based analysis. The optimal synergistic drug combination, containing erlotinib, BEZ-235 and RAPTA-C, was reached in a small number of iterations. Final drug combinations showed enhanced endothelial cell specificity and synergistically inhibited proliferation (p < 0.001), but not migration of endothelial cells, and forced enhanced numbers of endothelial cells to undergo apoptosis (p < 0.01). Successful translation of this drug combination was achieved in two preclinical in vivo tumor models. Tumor growth was inhibited synergistically and significantly (p < 0.05 and p < 0.01, respectively) using reduced drug doses as compared to optimal single-drug concentrations. At the applied conditions, single-drug monotherapies had no or negligible activity in these models. We suggest that FSC can be used for rapid identification of effective, reduced dose, multi-drug combinations for the treatment of cancer and other diseases.

Capital Controls with International Reserve Accumulation: Can this Be Optimal ?

Motivated by the Chinese experience, we analyze a semi-open economy where the central bank has access to international capital markets, but the private sector has not. This enables the central bank to choose an interest rate different from the international rate. We examine the optimal policy of the central bank by modelling it as a Ramsey planner who can choose the level of domestic public debt and of international reserves. The central bank can improve savings opportunities of credit-constrained consumers modelled as in Woodford (1990). We find that in a steady state it is optimal for the central bank to replicate the open economy, i.e., to issue debt financed by the accumulation of reserves so that the domestic interest rate equals the foreign rate. When the economy is in transition, however, a rapidly growing economy has a higher welfare without capital mobility and the optimal interest rate differs from the international rate. We argue that the domestic interest rate should be temporarily above the international rate. We also find that capital controls can still help reach the first best when the planner has more fiscal instruments.

Gene filtering with optimal threshold selection

Gene filtering is a useful preprocessing technique often applied to microarray datasets. However, it is no common practice because clear guidelines are lacking and it bears the risk of excluding some potentially relevant genes. In this work, we propose to model microarray data as a mixture of two Gaussian distributions that will allow us to obtain an optimal filter threshold in terms of the gene expression level.

Optimal Exchange Rate Policy in a Growing Semi-Open Economy

This paper considers an alternative perspective to China's exchange rate policy. It studies a semi-open economy where the private sector has no access to international capital markets but the central bank has full access. Moreover, it assumes limited financial development generating a large demand for saving instruments by the private sector. The paper analyzes the optimal exchange rate policy by modeling the central bank as a Ramsey planner. Its main result is that in a growth acceleration episode it is optimal to have an initial real depreciation of the currency combined with an accumulation of reserves, which is consistent with the Chinese experience. This depreciation is followed by an appreciation in the long run. The paper also shows that the optimal exchange rate path is close to the one that would result in an economy with full capital mobility and no central bank intervention.

Regression-based techniques for statistical decision making in single-case designs

The present study evaluates the performance of four methods for estimating regression coefficients used to make statistical decisions regarding intervention effectiveness in single-case designs. Ordinary least squares estimation is compared to two correction techniques dealing with general trend and one eliminating autocorrelation whenever it is present. Type I error rates and statistical power are studied for experimental conditions defined by the presence or absence of treatment effect (change in level or in slope), general trend, and serial dependence. The results show that empirical Type I error rates do not approximate the nominal ones in presence of autocorrelation or general trend when ordinary and generalized least squares are applied. The techniques controlling trend show lower false alarm rates, but prove to be insufficiently sensitive to existing treatment effects. Consequently, the use of the statistical significance of the regression coefficients for detecting treatment effects is not recommended for short data series.

Randomization tests for ABAB designs: Comparing-data-division-specific and common distributions

Monte Carlo simulations were used to generate data for ABAB designs of different lengths. The points of change in phase are randomly determined before gathering behaviour measurements, which allows the use of a randomization test as an analytic technique. Data simulation and analysis can be based either on data-division-specific or on common distributions. Following one method or another affects the results obtained after the randomization test has been applied. Therefore, the goal of the study was to examine these effects in more detail. The discrepancies in these approaches are obvious when data with zero treatment effect are considered and such approaches have implications for statistical power studies. Data-division-specific distributions provide more detailed information about the performance of the statistical technique.