Coronary symptoms associated with conditions related to mast cell activation and inflammatory cell interactions, such as those involving T-lymphocytes and macrophages, further inducing allergic, hypersensitivity, anaphylactic, or anaphylactic insults, are currently referred to as the Kounis syndrome. Kounis syndrome is caused by inflammatory mediators released during allergic insults, postinflammatory cell activation, and interactions via multidirectional stimuli. A platelet subset of 20% with high-and low-affinity IgE surface receptors is also involved in this process. Kounis syndrome is not just a single-organ but also a complex multisystem and multiorgan arterial clinical condition; it affects the coronary, mesenteric, and cerebral arteries and is accompanied by allergy-hypersensitivityanaphylaxis involving the skin, respiratory, and vascular systems in the context of anesthesia, surgery, radiology, oncology, or even dental and psychiatric medicine; further, it has significantly influences both morbidity and mortality. Kounis syndrome might be caused by numerous and continuously increasing causes, with broad clinical symptoms and signs, via multi-organ arterial system involvement, in patients of any age, thereby demonstrating predominant anaphylactic features in terms of a wide spectrum of mast cell-association disorders. Cardiac symptoms, such as chest pain, coronary vasospasm, angina pectoris, myocardial infarction, stent thrombosis, acute cardiac failure, and sudden cardiac death associated with subclinical, clinical, acute, or chronic allergic reactions, constitute the clinical manifestations of this syndrome. Since its first description, a common pathway between allergic and non-allergic coronary events has been demonstrated. The hypothesis is based on the existence of a much higher degree of mast cell degranulation at plaque erosion or rupture sites compared with at the adjacent areas or even more distant segments in post-acute myocardial infarction of non-allergic etiology. Although mast cell activation, differentiation, and mediator release takes days or weeks, the mast cell degranulation may occur just before any acute coronary event, further resulting in coronary artery vasoconstriction and atheromatous plaque rupture. It seems that medications and natural molecules stabilizing the mast cell membrane as well as monoclonal antibodies protecting the mast cell surface can emerge as novel therapeutic modalities for acute coronary and cerebrovascular event prevention.

Veterans Affairs Center for Health Equity Research and Promotion.

Warfarin is a commonly used oral anticoagulant, and has well-established clinical efficacy. However, it has a narrow therapeutic window, and a mode-of-action affected by inter-individual differences and environmental factors. The effectiveness and safety of warfarin are closely related to maintenance of the international normalized ratio (INR) within therapeutic range. A supra-therapeutic INR puts patients at risk of bleeding, whereas a sub-therapeutic INR may not protect against thromboembolic complications. Research suggests a lack of anticoagulation control during warfarin therapy in different settings. Careful monitoring of the INR is essential, especially in geriatric or cancer populations who are at an increased risk of major hemorrhage. Warfarin is an effective treatment but optimization of the risk-benefit ratio is crucial in order to maximize efficacy and safety. Here, we will assess the extent to which INRs are an issue in the management of warfarin therapy, and the effect INRs may have on clinical outcomes.

This paper studies the problem of predicting future values for a number of water quality variables, based on measurements from under-water sensors. It performs both exploratory and automatic analysis of the collected data with a variety of linear and nonlinear modeling methods. The paper investigates issues, such as the ability to predict future values for a varying number of days ahead and the effect of including values from a varying number of past days. Experimental results provide interesting insights on the predictability of the target variables and the performance of the different learning algorithms.

No abstract