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The ODYSSEY COMBO I study (http://clinicaltrials.gov/show/NCT01644175) evaluated efficacy and safety of alirocumab as add-on therapy to stable maximally tolerated daily statin with or without other lipid-lowering therapy in high cardiovascular risk patients with suboptimally controlled hypercholesterolemia. This multicenter, phase 3, randomized (2:1 alirocumab vs placebo), double-blind, 52-week trial enrolled 316 patients with established coronary heart disease or coronary heart disease risk equivalents and hypercholesterolemia. Alirocumab (75 mg every 2 weeks [Q2W]) or placebo Q2W was self-administered subcutaneously via 1 mL prefilled pen. The alirocumab dose was increased to 150 mg Q2W (also 1 mL) at week 12 if week 8 low-density lipoprotein cholesterol (LDL-C) was ≥70 mg/dL. The primary efficacy end point was percent change in LDL-C from baseline to week 24 (intention-to-treat analysis). At week 24, estimated mean (95% CI) changes in LDL-C from baseline were −48.2% (−52.0% to −44.4%) and −2.3% (−7.6% to 3.1%) for alirocumab and placebo, respectively, an estimated mean (95% CI) difference of −45.9% (−52.5% to −39.3%) (P < .0001). Low-density lipoprotein cholesterol <70 mg/dL was achieved by 75% alirocumab versus 9% placebo patients at week 24. At week 12, 83.2% of evaluable alirocumab-treated patients remained on 75-mg Q2W. Treatment-emergent adverse events were comparable between groups. Alirocumab treatment achieved a significantly greater reduction in LDL-C and allowed a greater proportion of patients to achieve LDL-C goals, versus placebo after 24 weeks in high cardiovascular risk patients with suboptimally controlled hypercholesterolemia at baseline despite receiving maximally tolerated statin with or without other lipid-lowering therapy. The frequency of treatment-emergent adverse events and study medication discontinuations were generally comparable between treatment groups.

تذهب رحلة الإنجليزي روبنسون ليز التي وضعها في كتابه \"ما وراء الأردن : حياة ومغامرات\" نحو عمون وجلعاد والقدس، ثم إلى درعا ودمشق، ثم إلى أشجار الأرز وجبل الشيخ في لبنان عودة إلى عمان والزرقاء. وعلى الرغم من أن معظم المواقع التي زارها الرحالة هي خارج الأردن إلا إنه سمى كتابه \"ما وراء الأردن\"، ويشتمل الكتاب على تفصيلات مهمة عن أحوال البدو وعاداتهم ومحاولات لاستكشاف بعض المواقع التاريخية والأثرية، إلا أن هذه المحاولات لا تبدو ذات قيمة علمية نظرا لتواضع ثقافته واعتماده على أفكار دينية مسبقة كما يصفه المترجم.

An anthology of Jackie Robinson's columns in the New York Post and the New York Amsterdam News newspapers.

In a randomized trial involving patients with previously untreated advanced non–small-cell lung cancer, pembrolizumab was associated with a higher response rate, longer progression-free and overall survival, and fewer adverse events than was platinum-based chemotherapy. Approximately 23 to 28% of patients with advanced non–small-cell lung cancer (NSCLC) have a high level of programmed death ligand 1 (PD-L1) expression, which is defined as membranous PD-L1 expression on at least 50% of tumor cells, regardless of the staining intensity (i.e., a PD-L1 tumor proportion score of 50% or greater). 1 , 2 Data from the phase 1 KEYNOTE-001 and phase 3 KEYNOTE-010 studies indicated that patients with advanced NSCLC and a PD-L1 tumor proportion score of 50% or greater were more likely than those with lower tumor proportion scores to have a response to pembrolizumab, a highly selective, humanized . . .

Many important decisions historically made by people are now made by computers. Algorithms count votes, approve loan and credit card applications, target citizens or neighborhoods for police scrutiny, select taxpayers for IRS audit, grant or deny immigration visas, and more. The accountability mechanisms and legal standards that govern such decision processes have not kept pace with technology. The tools currently available to policymakers, legislators, and courts were developed to oversee human decisionmakers and often fail when applied to computers instead. For example, how do you judge the intent of a piece of software? Because automated decision systems can return potentially incorrect, unjustified, or unfair results, additional approaches are needed to make such systems accountable and governable. This Article reveals a new technological toolkit to verify that automated decisions comply with key standards of legal fairness. We challenge the dominant position in the legal literature that transparency will solve these problems. Disclosure of source code is often neither necessary (because of alternative techniques from computer science) nor sufficient (because of the issues analyzing code) to demonstrate the fairness of a process. Furthermore, transparency may be undesirable, such as when it discloses private information or permits tax cheats or terrorists to game the systems determining audits or security screening. The central issue is how to assure the interests of citizens, and society as a whole, in making these processes more accountable. This Article argues that technology is creating new opportunities—subtler and more flexible than total transparency—to design decisionmaking algorithms so that they better align with legal and policy objectives. Doing so will improve not only the current governance of automated decisions, but also—in certain cases—the governance of decisionmaking in general. The implicit (or explicit) biases of human decisionmakers can be difficult to find and root out, but we can peer into the \"brain\" of an algorithm: computational processes and purpose specifications can be declared prior to use and verified afterward. The technological tools introduced in this Article apply widely. They can be used in designing decisionmaking processes from both the private and public sectors, and they can be tailored to verify different characteristics as desired by decisionmakers, regulators, or the public. By forcing a more careful consideration of the effects of decision rules, they also engender policy discussions and closer looks at legal standards. As such, these tools have far-reaching implications throughout law and society. Part I of this Article provides an accessible and concise introduction to foundational computer science techniques that can be used to verify and demonstrate compliance with key standards of legal fairness for automated decisions without revealing key attributes of the decisions or the processes by which the decisions were reached. Part II then describes how these techniques can assure that decisions are made with the key governance attribute of procedural regularity, meaning that decisions are made under an announced set of rules consistently applied in each case. We demonstrate how this approach could be used to redesign and resolve issues with the State Department's diversity visa lottery. In Part III, we go further and explore how other computational techniques can assure that automated decisions preserve fidelity to substantive legal and policy choices. We show how these tools may be used to assure that certain kinds of unjust discrimination are avoided and that automated decision processes behave in ways that comport with the social or legal standards that govern the decision. We also show how automated decisionmaking may even complicate existing doctrines of disparate treatment and disparate impact, and we discuss some recent computer science work on detecting and removing discrimination in algorithms, especially in the context of big data and machine learning. And lastly, in Part IV, we propose an agenda to further synergistic collaboration between computer science, law, and policy to advance the design of automated decision processes for accountability.

This handbook provides insights to the ways in which globalisation is affecting the whole agri-food system, from farms to the consumer. The expert contributors cover themes including the physical basis of agriculture, the influence of trade policies, the nature of globalised agriculture, and resistance to globalisation in the form of attempts to foster sustainability and multifunctional agricultural systems.

Objective: To review the world's (English-language) publications related to depression following stroke. Method: The databases from MEDLINE and PubMed were reviewed for articles related to poststroke depression (PSD), depression and cerebral vascular accident, depression and cerebral vascular disease, and depression and cerebral infarction. Results: Most studies examined prevalence rates of depression and the clinical correlates of depression. Based on pooled data, the overall prevalence of major depression was 21.7% and minor depression was 19.5%. The strongest single correlate of depression was severity of impairment in activities of daily living. However, the existence of depression at baseline was found to be associated with greater impairment at follow-up, ranging from 6 weeks to 2 years in 83% of studies. Further, depression following acute stroke was also associated with greater cognitive impairment and increased mortality. PSD has been shown in 6 double-blind controlled studies to be effectively treated with antidepressants, and 1 study has recently shown that PSD can be effectively prevented. Conclusions: During the past 20 years, significant progress has been made in the identification and treatment of depression following stroke. In the future, antidepressant treatment will likely play an increasing role in the management of patients with acute stroke. Further research is needed to identify the mechanisms of depression and why antidepressants lead to improved physical and cognitive recovery and decreased mortality.