Возможности радикального лечения варикотромбофлебита на фоне варикозной болезни и трофических язв

КОНЕЧНОСТИ НИЖНЕЙ ЯЗВАТРОМБОФЛЕБИТ /ХИРВАРИКОЗНАЯ ЯЗВАВАРИКОЗНОЕ РАСШИРЕНИЕ ВЕН /ОС

Does wage rank affect employees' well-being?

How do workers make wage comparisons? Both an experimental study and an analysis of 16,000 British employees are reported. Satisfaction and well-being levels are shown to depend on more than simple relative pay. They depend upon the ordinal rank of an individual's wage within a comparison group. “Rank” itself thus seems to matter to human beings. Moreover, consistent with psychological theory, quits in a workplace are correlated with pay distribution skewness

Brief cognitive behavioral therapy in primary care: a hybrid type 2 patient-randomized effectiveness-implementation design

BACKGROUND: Despite the availability of evidence-based psychotherapies for depression and anxiety, they are underused in non-mental health specialty settings such as primary care. Hybrid effectiveness-implementation designs have the potential to evaluate clinical and implementation outcomes of evidence-based psychotherapies to improve their translation into routine clinical care practices. METHODS: This protocol article discusses the study methodology and implementation strategies employed in an ongoing, hybrid, type 2 randomized controlled trial with two primary aims: (1) to determine whether a brief, manualized cognitive behavioral therapy administered by Veterans Affairs Primary Care Mental Health Integration program clinicians is effective in treating depression and anxiety in a sample of medically ill (chronic cardiopulmonary diseases) primary care patients and (2) to examine the acceptability, feasibility, and preliminary outcomes of a focused implementation strategy on improving adoption and fidelity of brief cognitive behavioral therapy at two Primary Care-Mental Health Integration clinics. The study uses a hybrid type 2 effectiveness/implementation design to simultaneously test clinical effectiveness and to collect pilot data on a multifaceted implementation strategy that includes an online training program, audit and feedback of session content, and internal and external facilitation. Additionally, the study engages the participation of an advisory council consisting of stakeholders from Primary Care-Mental Health Integration, as well as regional and national mental health leaders within the Veterans Administration. It targets recruitment of 320 participants randomized to brief cognitive behavioral therapy (n = 200) or usual care (n = 120). Both effectiveness and implementation outcomes are being assessed using mixed methods, including quantitative evaluation (e.g., intent-to-treat analyses across multiple time points) and qualitative methods (e.g., focus interviews and surveys from patients and providers). Patient-effectiveness outcomes include measures of depression, anxiety, and physical health functioning using blinded independent evaluators. Implementation outcomes include patient engagement and adherence and clinician brief cognitive behavioral therapy adoption and fidelity. CONCLUSIONS: Hybrid designs are needed to advance clinical effectiveness and implementation knowledge to improve healthcare practices. The current article describes the rationale and challenges associated with the use of a hybrid design for the study of brief cognitive behavioral therapy in primary care. Although trade-offs exist between scientific control and external validity, hybrid designs are part of an emerging approach that has the potential to rapidly advance both science and practice. TRIAL REGISTRATION: NCT01149772 at http://www.clinicaltrials.gov/ct2/show/NCT0114977

Assay strategies for the discovery and validation of therapeutics targeting <i>Brugia pahangi</i> Hsp90

The chemotherapy of lymphatic filariasis relies upon drugs such as diethylcarbamazine and ivermectin that largely target the microfilarial stages of the parasite, necessitating continued treatment over the long reproductive life span of the adult worm. The identification of compounds that target adult worms has been a long-term goal of WHO. Here we describe a fluorescence polarization assay for the identification of compounds that target Hsp90 in adult filarial worms. The assay was originally developed to identify inhibitors of Hsp90 in tumor cells, and relies upon the ability of small molecules to inhibit the binding of fluorescently labelled geldanamycin to Hsp90. We demonstrate that the assay works well with soluble extracts of Brugia, while extracts of the free-living nematode C. elegans fail to bind the probe, in agreement with data from other experiments. The assay was validated using known inhibitors of Hsp90 that compete with geldanamycin for binding to Hsp90, including members of the synthetic purine-scaffold series of compounds. The efficacy of some of these compounds against adult worms was confirmed in vitro. Moreover, the assay is sufficiently sensitive to differentiate between binding of purine-scaffold compounds to human and Brugia Hsp90. The assay is suitable for high-throughput screening and provides the first example of a format with the potential to identify novel inhibitors of Hsp90 in filarial worms and in other parasitic species where Hsp90 may be a target

Fast transport of resonant electrons in phase space due to nonlinear trapping by whistler waves

International audienceWe present an analytical, simplified formulation accounting for the fast transport of relativistic electrons in phase space due to wave-particle resonant interactions in the inhomogeneous magnetic field of Earth's radiation belts. We show that the usual description of the evolution of the particle velocity distribution based on the Fokker-Planck equation can be modified to incorporate nonlinear processes of wave-particle interaction, including particle trapping. Such a modification consists in one additional operator describing fast particle jumps in phase space. The proposed, general approach is used to describe the acceleration of relativistic electrons by oblique whistler waves in the radiation belts. We demonstrate that for a wave power distribution with a hard enough power law tail inline image such that η < 5/2, the efficiency of nonlinear acceleration could be more effective than the conventional quasi-linear acceleration for 100 keV electrons

QuerySnout: automating the discovery of attribute inference attacks against query-based systems

Although query-based systems (QBS) have become one of the main solutions to share data anonymously, building QBSes that robustly protect the privacy of individuals contributing to the dataset is a hard problem. Theoretical solutions relying on differential privacy guarantees are difficult to implement correctly with reasonable accuracy, while ad-hoc solutions might contain unknown vulnerabilities. Evaluating the privacy provided by QBSes must thus be done by evaluating the accuracy of a wide range of privacy attacks. However, existing attacks against QBSes require time and expertise to develop, need to be manually tailored to the specific systems attacked, and are limited in scope. In this paper, we develop QuerySnout, the first method to automatically discover vulnerabilities in query-based systems. QuerySnout takes as input a target record and the QBS as a black box, analyzes its behavior on one or more datasets, and outputs a multiset of queries together with a rule to combine answers to them in order to reveal the sensitive attribute of the target record. QuerySnout uses evolutionary search techniques based on a novel mutation operator to find a multiset of queries susceptible to lead to an attack, and a machine learning classifier to infer the sensitive attribute from answers to the queries selected. We showcase the versatility of QuerySnout by applying it to two attack scenarios (assuming access to either the private dataset or to a different dataset from the same distribution), three real-world datasets, and a variety of protection mechanisms. We show the attacks found by QuerySnout to consistently equate or outperform, sometimes by a large margin, the best attacks from the literature. We finally show how QuerySnout can be extended to QBSes that require a budget, and apply QuerySnout to a simple QBS based on the Laplace mechanism. Taken together, our results show how powerful and accurate attacks against QBSes can already be found by an automated system, allowing for highly complex QBSes to be automatically tested "at the pressing of a button". We believe this line of research to be crucial to improve the robustness of systems providing privacy-preserving access to personal data in theory and in practice

Facile access to a heterocyclic, sp3-rich chemical scaffold via a tandem condensation/intramolecular nitrone–alkene [3+2] cycloaddition strategy

A heterocyclic, sp3-rich chemical scaffold was synthesised in just 6 steps via a highly regio- and diastereo-selective tandem nitrone formation/intramolecular nitrone–alkene [3+2] cycloaddition reaction. A library of 543 lead-like compounds based on the scaffold core has been produced

Quality-diversity optimization: a novel branch of stochastic optimization

Traditional optimization algorithms search for a single global optimum that maximizes (or minimizes) the objective function. Multimodal optimization algorithms search for the highest peaks in the search space that can be more than one. Quality-Diversity algorithms are a recent addition to the evolutionary computation toolbox that do not only search for a single set of local optima, but instead try to illuminate the search space. In effect, they provide a holistic view of how high-performing solutions are distributed throughout a search space. The main differences with multimodal optimization algorithms are that (1) Quality-Diversity typically works in the behavioral space (or feature space), and not in the genotypic (or parameter) space, and (2) Quality-Diversity attempts to fill the whole behavior space, even if the niche is not a peak in the fitness landscape. In this chapter, we provide a gentle introduction to Quality-Diversity optimization, discuss the main representative algorithms, and the main current topics under consideration in the community. Throughout the chapter, we also discuss several successful applications of Quality-Diversity algorithms, including deep learning, robotics, and reinforcement learning