Country differences in the diagnosis and management of coronary heart disease : a comparison between the US, the UK and Germany

Background The way patients with coronary heart disease (CHD) are treated is partly determined by non-medical factors. There is a solid body of evidence that patient and physician characteristics influence doctors' management decisions. Relatively little is known about the role of structural issues in the decision making process. This study focuses on the question whether doctors' diagnostic and therapeutic decisions are influenced by the health care system in which they take place. This non-medical determinant of medical decision-making was investigated in an international research project in the US, the UK and Germany. Methods Videotaped patients within an experimental study design were used. Experienced actors played the role of patients with symptoms of CHD. Several alternative versions were taped featuring the same script with patients of different sex, age and social status. The videotapes were shown to 384 randomly selected primary care physicians in the three countries under study. The sample was stratified on gender and duration of professional experience. Physicians were asked how they would diagnose and manage the patient after watching the video vignette using a questionnaire with standardised and open-ended questions. Results Results show only small differences in decision making between British and American physicians in essential aspects of care. About 90% of the UK and US doctors identified CHD as one of the possible diagnoses. Further similarities were found in test ordering and lifestyle advice. Some differences between the US and UK were found in the certainty of the diagnoses, prescribed medications and referral behaviour. There are numerous significant differences between Germany and the other two countries. German physicians would ask fewer questions, they would order fewer tests, prescribe fewer medications and give less lifestyle advice. Conclusion Although all physicians in the three countries under study were presented exactly the same patient, some disparities in the diagnostic and patient management decisions were evident. Since other possible influences on doctors treatment decisions are controlled within the experimental design, characteristics of the health care system seem to be a crucial factor within the decision making process

Search algorithms as a framework for the optimization of drug combinations

Combination therapies are often needed for effective clinical outcomes in the management of complex diseases, but presently they are generally based on empirical clinical experience. Here we suggest a novel application of search algorithms, originally developed for digital communication, modified to optimize combinations of therapeutic interventions. In biological experiments measuring the restoration of the decline with age in heart function and exercise capacity in Drosophila melanogaster, we found that search algorithms correctly identified optimal combinations of four drugs with only one third of the tests performed in a fully factorial search. In experiments identifying combinations of three doses of up to six drugs for selective killing of human cancer cells, search algorithms resulted in a highly significant enrichment of selective combinations compared with random searches. In simulations using a network model of cell death, we found that the search algorithms identified the optimal combinations of 6-9 interventions in 80-90% of tests, compared with 15-30% for an equivalent random search. These findings suggest that modified search algorithms from information theory have the potential to enhance the discovery of novel therapeutic drug combinations. This report also helps to frame a biomedical problem that will benefit from an interdisciplinary effort and suggests a general strategy for its solution.Comment: 36 pages, 10 figures, revised versio

Two Earth-sized planets orbiting Kepler-20

Since the discovery of the first extrasolar giant planets around Sun-like stars, evolving observational capabilities have brought us closer to the detection of true Earth analogues. The size of an exoplanet can be determined when it periodically passes in front of (transits) its parent star, causing a decrease in starlight proportional to its radius. The smallest exoplanet hitherto discovered has a radius 1.42 times that of the Earth's radius (R Earth), and hence has 2.9 times its volume. Here we report the discovery of two planets, one Earth-sized (1.03R Earth) and the other smaller than the Earth (0.87R Earth), orbiting the star Kepler-20, which is already known to host three other, larger, transiting planets. The gravitational pull of the new planets on the parent star is too small to measure with current instrumentation. We apply a statistical method to show that the likelihood of the planetary interpretation of the transit signals is more than three orders of magnitude larger than that of the alternative hypothesis that the signals result from an eclipsing binary star. Theoretical considerations imply that these planets are rocky, with a composition of iron and silicate. The outer planet could have developed a thick water vapour atmosphere.Comment: Letter to Nature; Received 8 November; accepted 13 December 2011; Published online 20 December 201

Non-overshooting stabilisation via state and output feedback

The concept of “strong stability” of LTI systems has been introduced in a recent paper [KHP2]. This is a stronger notion of stability compared to alternative definitions (e.g. stability in the sense of Lyapunov, asymptotic stability), which allows the analysis and design of control systems with non-overshooting response in the state-space for arbitrary initial conditions. The paper reviews the notion of “strong stability” [KHP2] and introduces the problem of non-overshooting stabilization. It is shown that non-overshooting stabilization under dynamic and static output feedback are, in a certain sense, equivalent problems. Thus, we turn our attention to static non-overshooting stabilization problems under state-feedback, output injection and output feedback. After developing a number of preliminary results, we give a geometric interpretation to the problem in terms of the intersection of an affine hyperplane and the interior of an open convex cone. A solution to the problem is finally obtained via Linear Matrix Inequalities, along with the complete parametrization of the optimal solution set

Measurements in two bases are sufficient for certifying high-dimensional entanglement

High-dimensional encoding of quantum information provides a promising method of transcending current limitations in quantum communication. One of the central challenges in the pursuit of such an approach is the certification of high-dimensional entanglement. In particular, it is desirable to do so without resorting to inefficient full state tomography. Here, we show how carefully constructed measurements in two bases (one of which is not orthonormal) can be used to faithfully and efficiently certify bipartite high-dimensional states and their entanglement for any physical platform. To showcase the practicality of this approach under realistic conditions, we put it to the test for photons entangled in their orbital angular momentum. In our experimental setup, we are able to verify 9-dimensional entanglement for a pair of photons on a 11-dimensional subspace each, at present the highest amount certified without any assumptions on the state.Comment: 11+14 pages, 2+7 figure

Automatic Network Fingerprinting through Single-Node Motifs

Complex networks have been characterised by their specific connectivity patterns (network motifs), but their building blocks can also be identified and described by node-motifs---a combination of local network features. One technique to identify single node-motifs has been presented by Costa et al. (L. D. F. Costa, F. A. Rodrigues, C. C. Hilgetag, and M. Kaiser, Europhys. Lett., 87, 1, 2009). Here, we first suggest improvements to the method including how its parameters can be determined automatically. Such automatic routines make high-throughput studies of many networks feasible. Second, the new routines are validated in different network-series. Third, we provide an example of how the method can be used to analyse network time-series. In conclusion, we provide a robust method for systematically discovering and classifying characteristic nodes of a network. In contrast to classical motif analysis, our approach can identify individual components (here: nodes) that are specific to a network. Such special nodes, as hubs before, might be found to play critical roles in real-world networks.Comment: 16 pages (4 figures) plus supporting information 8 pages (5 figures

Investigating human audio-visual object perception with a combination of hypothesis-generating and hypothesis-testing fMRI analysis tools

Primate multisensory object perception involves distributed brain regions. To investigate the network character of these regions of the human brain, we applied data-driven group spatial independent component analysis (ICA) to a functional magnetic resonance imaging (fMRI) data set acquired during a passive audio-visual (AV) experiment with common object stimuli. We labeled three group-level independent component (IC) maps as auditory (A), visual (V), and AV, based on their spatial layouts and activation time courses. The overlap between these IC maps served as definition of a distributed network of multisensory candidate regions including superior temporal, ventral occipito-temporal, posterior parietal and prefrontal regions. During an independent second fMRI experiment, we explicitly tested their involvement in AV integration. Activations in nine out of these twelve regions met the max-criterion (A < AV > V) for multisensory integration. Comparison of this approach with a general linear model-based region-of-interest definition revealed its complementary value for multisensory neuroimaging. In conclusion, we estimated functional networks of uni- and multisensory functional connectivity from one dataset and validated their functional roles in an independent dataset. These findings demonstrate the particular value of ICA for multisensory neuroimaging research and using independent datasets to test hypotheses generated from a data-driven analysis

Population-Based Precision Cancer Screening: A Symposium on Evidence, Epidemiology, and Next Steps

Precision medicine, an emerging approach for disease treatment that takes into account individual variability in genes, environment, and lifestyle, is under consideration for preventive interventions, including cancer screening. On September 29, 2015, the National Cancer Institute sponsored a symposium entitled “Precision Cancer Screening in the General Population: Evidence, Epidemiology, and Next Steps”. The goal was two-fold: to share current information on the evidence, practices, and challenges surrounding precision screening for breast, cervical, colorectal, lung, and prostate cancers, and to allow for in-depth discussion among experts in relevant fields regarding how epidemiology and other population sciences can be used to generate evidence to inform precision screening strategies. Attendees concluded that the strength of evidence for efficacy and effectiveness of precision strategies varies by cancer site, that no one research strategy or methodology would be able or appropriate to address the many knowledge gaps in precision screening, and that issues surrounding implementation must be researched as well. Additional discussion needs to occur to identify the high priority research areas in precision cancer screening for pertinent organs and to gather the necessary evidence to determine whether further implementation of precision cancer screening strategies in the general population would be feasible and beneficial

Cognitive and behavioral predictors of light therapy use

Objective: Although light therapy is effective in the treatment of seasonal affective disorder (SAD) and other mood disorders, only 53-79% of individuals with SAD meet remission criteria after light therapy. Perhaps more importantly, only 12-41% of individuals with SAD continue to use the treatment even after a previous winter of successful treatment. Method: Participants completed surveys regarding (1) social, cognitive, and behavioral variables used to evaluate treatment adherence for other health-related issues, expectations and credibility of light therapy, (2) a depression symptoms scale, and (3) self-reported light therapy use. Results: Individuals age 18 or older responded (n = 40), all reporting having been diagnosed with a mood disorder for which light therapy is indicated. Social support and self-efficacy scores were predictive of light therapy use (p's<.05). Conclusion: The findings suggest that testing social support and self-efficacy in a diagnosed patient population may identify factors related to the decision to use light therapy. Treatments that impact social support and self-efficacy may improve treatment response to light therapy in SAD. © 2012 Roecklein et al

Histone deacetylases as new therapy targets for platinum-resistant epithelial ovarian cancer

Introduction: In developed countries, ovarian cancer is the fourth most common cancer in women. Due to the nonspecific symptomatology associated with the disease many patients with ovarian cancer are diagnosed late, which leads to significantly poorer prognosis. Apart from surgery and radiotherapy, a substantial number of ovarian cancer patients will undergo chemotherapy and platinum based agents are the mainstream first-line therapy for this disease. Despite the initial efficacy of these therapies, many women relapse; therefore, strategies for second-line therapies are required. Regulation of DNA transcription is crucial for tumour progression, metastasis and chemoresistance which offers potential for novel drug targets. Methods: We have reviewed the existing literature on the role of histone deacetylases, nuclear enzymes regulating gene transcription. Results and conclusion: Analysis of available data suggests that a signifant proportion of drug resistance stems from abberant gene expression, therefore HDAC inhibitors are amongst the most promising therapeutic targets for cancer treatment. Together with genetic testing, they may have a potential to serve as base for patient-adapted therapies