Effects of Antiplatelet Therapy After Stroke Caused by Intracerebral Hemorrhage Extended Follow-up of the RESTART Randomized Clinical Trial

Importance: The Restart or Stop Antithrombotics Randomized Trial (RESTART) found that antiplatelet therapy appeared to be safe up to 5 years after intracerebral hemorrhage (ICH) that had occurred during antithrombotic (antiplatelet or anticoagulant) therapy. Objectives: To monitor adherence, increase duration of follow-up, and improve precision of estimates of the effects of antiplatelet therapy on recurrent ICH and major vascular events. Design, Setting and Participants: From May 22, 2013, through May 31, 2018, this prospective, open, blinded end point, parallel-group randomized clinical trial studied 537 participants at 122 hospitals in the UK. Participants were individuals 18 years or older who had taken antithrombotic therapy for the prevention of occlusive vascular disease when they developed ICH, discontinued antithrombotic therapy, and survived for 24 hours. After initial follow-up ended on November 30, 2018, annual follow-up was extended until November 30, 2020, for a median of 3.0 years (interquartile range [IQR], 2.0-5.0 years) for the trial cohort. Interventions: Computerized randomization that incorporated minimization allocated participants (1:1) to start or avoid antiplatelet therapy. Main Outcomes and Measures: Participants were followed up for the primary outcome (recurrent symptomatic ICH) and secondary outcomes (all major vascular events) for up to 7 years. Data from all randomized participants were analyzed using Cox proportional hazards regression, adjusted for minimization covariates. Results: A total of 537 patients (median age, 76.0 years; IQR, 69.0-82.0 years; 360 [67.0%] male; median time after ICH onset, 76.0 days; IQR, 29.0-146.0 days) were randomly allocated to start (n = 268) or avoid (n = 269 [1 withdrew]) antiplatelet therapy. The primary outcome of recurrent ICH affected 22 of 268 participants (8.2%) allocated to antiplatelet therapy compared with 25 of 268 participants (9.3%) allocated to avoid antiplatelet therapy (adjusted hazard ratio, 0.87; 95% CI, 0.49-1.55; P = .64). A major vascular event affected 72 participants (26.8%) allocated to antiplatelet therapy compared with 87 participants (32.5%) allocated to avoid antiplatelet therapy (hazard ratio, 0.79; 95% CI, 0.58-1.08; P = .14). Conclusions and Relevance: Among patients with ICH who had previously taken antithrombotic therapy, this study found no statistically significant effect of antiplatelet therapy on recurrent ICH or all major vascular events. These findings provide physicians with some reassurance about the use of antiplatelet therapy after ICH if indicated for secondary prevention of major vascular events

Is demography destiny? Application of machine learning techniques to accurately predict population health outcomes from a minimal demographic dataset

© 2015 Luo et al. For years, we have relied on population surveys to keep track of regional public health statistics, including the prevalence of non-communicable diseases. Because of the cost and limitations of such surveys, we often do not have the up-to-date data on health outcomes of a region. In this paper, we examined the feasibility of inferring regional health outcomes from socio-demographic data that are widely available and timely updated through national censuses and community surveys. Using data for 50 American states (excluding Washington DC) from 2007 to 2012, we constructed a machine-learning model to predict the prevalence of six non-communicable disease (NCD) outcomes (four NCDs and two major clinical risk factors), based on population socio-demographic characteristics from the American Community Survey. We found that regional prevalence estimates for non-communicable diseases can be reasonably predicted. The predictions were highly correlated with the observed data, in both the states included in the derivation model (median correlation 0.88) and those excluded from the development for use as a completely separated validation sample (median correlation 0.85), demonstrating that the model had sufficient external validity to make good predictions, based on demographics alone, for areas not included in the model development. This highlights both the utility of this sophisticated approach to model development, and the vital importance of simple socio-demographic characteristics as both indicators and determinants of chronic disease

To what extent are land resource managers preparing for high-end climate change in Scotland?

We explore the individual and institutional conditions and the climate information used to underpin decision-making for adaptation to high-end climate change (HECC) scenarios in a land resource management context. HECC refers to extreme projections with global annual temperature increases of over 4 °C. We analyse whether HECC scenarios are used in the adaptation decision-making of stakeholders who will tackle the potential problem. We also explore whether the adaptation actions being considered are pertinent only to future climate change or whether other drivers and information types are used in decision-making (including non-climate drivers). We also address the role of knowledge uncertainty in adaptation decision-making. Decision-makers perceive HECC as having a low probability of occurrence and so they do not directly account for HECC within existing actions to address climate change. Such actions focus on incremental rather than transformative solutions in which non-climate drivers are at least as important, and in many cases more important, than climate change alone. This reflects the need to accommodate multiple concerns and low risk options (i.e. incremental change). Uncertainty in climate change information is not a significant barrier to decision-making and stakeholders indicated little need for more climate information in support of adaptation decision-making. There is, however, an identified need for more information about the implications of particular sectoral and cross-sectoral impacts under HECC scenarios. The outcomes of this study provide evidence to assist in contextualising climate change information by creating usable, cross-sectoral, decision-centred information

Principles of Modular Tumor Therapy

Nature is interwoven with communication and is represented and reproduced through communication acts. The central question is how may multimodal modularly acting and less toxic therapy approaches, defined as modular therapies, induce an objective response or even a continuous complete remission, although single stimulatory or inhibitingly acting drugs neither exert mono-activity in the respective metastatic tumor type nor are they directed to potentially ‘tumor-specific’ targets. Modularity in the present context is a formal pragmatic communicative systems concept, describing the degree to which systems objects (cells, pathways etc.) may be communicatively separated in a virtual continuum, and recombined and rededicated to alter validity and denotation of communication processes in the tumor. Intentional knowledge, discharging in reductionist therapies, disregards the risk-absorbing background knowledge of the tumor’s living world including the holistic communication processes, which we rely on in every therapy. At first, this knowledge constitutes the validity of informative intercellular processes, which is the prerequisite for therapeutic success. All communication-relevant steps, such as intentions, understandings, and the appreciation of messages, may be modulated simultaneously, even with a high grade of specificity. Thus, modular therapy approaches including risk-absorbing and validity-modifying background knowledge may overcome reductionist idealizations. Modular therapies show modular events assembled by the tumor’s living world as an additional evolution-constituting dimension. This way, modular knowledge may be acquired from the environment, either incidentally or constitutionally. The new communicatively defined modular coherency of environment, i.e. the tumor-associated microenvironment, and tumor cells open novel ways for the scientific community in ‘translational medicine’

Evaluation of major depression in a routine clinical assessment

<p>Abstract</p> <p>Background</p> <p>Major depression is a disorder that significantly worsens a patient's morbidity and mortality. The association of depression and diabetes is well documented and has clinical impact in diabetes treatment's outcome. Patients usually aren't evaluated initially by a psychiatrist, so it is important that non-psychiatrists learn to evaluate major depression and its impact.</p> <p>Conclusions</p> <p>Major depression can and should be evaluated on a routine clinical assessment. Depression's impact on the patients' quality of life, productivity and social interactions is well documented. The initial diagnosis of depression should lead to its prompt treatment, and it has to be emphasized that the incorrect treatment can lead to worsening of the condition, relapses, recurrences or even chronification of major depression.</p

Angular and Current-Target Correlations in Deep Inelastic Scattering at HERA

Correlations between charged particles in deep inelastic ep scattering have been studied in the Breit frame with the ZEUS detector at HERA using an integrated luminosity of 6.4 pb-1. Short-range correlations are analysed in terms of the angular separation between current-region particles within a cone centred around the virtual photon axis. Long-range correlations between the current and target regions have also been measured. The data support predictions for the scaling behaviour of the angular correlations at high Q2 and for anti-correlations between the current and target regions over a large range in Q2 and in the Bjorken scaling variable x. Analytic QCD calculations and Monte Carlo models correctly describe the trends of the data at high Q2, but show quantitative discrepancies. The data show differences between the correlations in deep inelastic scattering and e+e- annihilation.Comment: 26 pages including 10 figures (submitted to Eur. J. Phys. C

Plastisol Foaming Process. Decomposition of the Foaming Agent, Polymer Behavior in the Corresponding Temperature Range and Resulting Foam Properties

The decomposition of azodicarbonamide, used as foaming agent in PVC - plasticizer (1/1) plastisols was studied by DSC. Nineteen different plasticizers, all belonging to the ester family, two being polymeric (polyadipates), were compared. The temperature of maximum decomposition rate (in anisothermal regime at 5 K min-1 scanning rate), ranges between 434 and 452 K. The heat of decomposition ranges between 8.7 and 12.5 J g -1. Some trends of variation of these parameters appear significant and are discussed in terms of solvent (matrix) and viscosity effects on the decomposition reactions. The shear modulus at 1 Hz frequency was determined at the temperature of maximum rate of foaming agent decomposition, and differs significantly from a sample to another. The foam density was determined at ambient temperature and the volume fraction of bubbles was used as criterion to judge the efficiency of the foaming process. The results reveal the existence of an optimal shear modulus of the order of 2 kPa that corresponds roughly to plasticizer molar masses of the order of 450 ± 50 g mol-1. Heavier plasticizers, especially polymeric ones are too difficult to deform. Lighter plasticizers such as diethyl phthalate (DEP) deform too easily and presumably facilitate bubble collapse

X-ray Absorption and Reflection in Active Galactic Nuclei

X-ray spectroscopy offers an opportunity to study the complex mixture of emitting and absorbing components in the circumnuclear regions of active galactic nuclei, and to learn about the accretion process that fuels AGN and the feedback of material to their host galaxies. We describe the spectral signatures that may be studied and review the X-ray spectra and spectral variability of active galaxies, concentrating on progress from recent Chandra, XMM-Newton and Suzaku data for local type 1 AGN. We describe the evidence for absorption covering a wide range of column densities, ionization and dynamics, and discuss the growing evidence for partial-covering absorption from data at energies > 10 keV. Such absorption can also explain the observed X-ray spectral curvature and variability in AGN at lower energies and is likely an important factor in shaping the observed properties of this class of source. Consideration of self-consistent models for local AGN indicates that X-ray spectra likely comprise a combination of absorption and reflection effects from material originating within a few light days of the black hole as well as on larger scales. It is likely that AGN X-ray spectra may be strongly affected by the presence of disk-wind outflows that are expected in systems with high accretion rates, and we describe models that attempt to predict the effects of radiative transfer through such winds, and discuss the prospects for new data to test and address these ideas.Comment: Accepted for publication in the Astronomy and Astrophysics Review. 58 pages, 9 figures. V2 has fixed an error in footnote

Citizen Science Reveals Unexpected Continental-Scale Evolutionary Change in a Model Organism

Organisms provide some of the most sensitive indicators of climate change and evolutionary responses are becoming apparent in species with short generation times. Large datasets on genetic polymorphism that can provide an historical benchmark against which to test for recent evolutionary responses are very rare, but an exception is found in the brown-lipped banded snail (Cepaea nemoralis). This species is sensitive to its thermal environment and exhibits several polymorphisms of shell colour and banding pattern affecting shell albedo in the majority of populations within its native range in Europe. We tested for evolutionary changes in shell albedo that might have been driven by the warming of the climate in Europe over the last half century by compiling an historical dataset for 6,515 native populations of C. nemoralis and comparing this with new data on nearly 3,000 populations. The new data were sampled mainly in 2009 through the Evolution MegaLab, a citizen science project that engaged thousands of volunteers in 15 countries throughout Europe in the biggest such exercise ever undertaken. A known geographic cline in the frequency of the colour phenotype with the highest albedo (yellow) was shown to have persisted and a difference in colour frequency between woodland and more open habitats was confirmed, but there was no general increase in the frequency of yellow shells. This may have been because snails adapted to a warming climate through behavioural thermoregulation. By contrast, we detected an unexpected decrease in the frequency of Unbanded shells and an increase in the Mid-banded morph. Neither of these evolutionary changes appears to be a direct response to climate change, indicating that the influence of other selective agents, possibly related to changing predation pressure and habitat change with effects on micro-climate