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Obesity, especially in the presence of hypertension and insulin resistance, causes important structural and functional changes in the heart Increased volume and pressure loading of the left ventricle lead to left ventricular hypertrophy (LVH), which increases the risk of CHD, cardiac failure, arrhythmias and cardiac death Right ventricular hypertrophy and left atrial enlargement may also occur Obesity, especially visceral, strongly predicts hypertension, which affects 40% of obese subjects (six times more common than in lean people) Possible mechanisms include increased reninangiotensin system (RAS) activity; raised levels of insulin and leptin, causing SNS activation; enhanced sodium retention due to hyperinsulinaemia; and loss of leptin s direct vasodilator action through leptin resistance Congestive heart failure is associated with obesity and can complicate LVH, especially in the presence of hypertension Intracardiac triglyceride deposition may also impair contractile function.

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Paradoxically, low BMI may increase the risk of death in patients with severe heart failure, possibly because of the confounding effects of the associated hypercatabolic state ( cardiac cachexia ) Obesity, especially visceral, is a major independent risk factor for CHD, its effects being amplified by coexistent risk factors such as hypertension, smoking, type 2 diabetes and dyslipidaemia Peripheral arterial disease, including stroke and claudication, is also more common Obesity causes endothelial dysfunction, an early marker of atherogenic risk; raised FFA levels and loss of leptin s vasodilator action may contribute Obesity increases the risk of arrhythmias, especially chronic atrial fibrillation (associated with LVH and left atrial enlargement), QTc interval prolongation and sudden death Some metabolically healthy obese subjects are apparently spared cardiovascular complications, including hypertension, LVH and CHD, even in the presence of severe obesity The reasons are unexplained.

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While the use of policies to handle specific requirements allows considerable simplification of the optimization task to be performed by the path selection algorithm, it is not always the most effective w9, 13x have shown a simple yet effective solution that can be constructed when the delay is assumed to be of a particular form 822 Weighted Graph Model A network can be modeled as a graph G s V, E . Nodes V of the graph represent switches, routers, and hosts Edges E represent communication links The edges are undirected only if the communication links are always symmetric A symmetric link has the same properties capacity, propagation delay, etc. and the same traffic volume in both directions For most real networks the communication links are asymmetric, and hence every link is represented by two directed edges in opposite directions Figure 815 shows a weighted graph model.

All obese patients require full cardiovascular assessment, including measurements of visceral obesity, blood pressure (measured with a wide cuff), and estimation of cardiovascular risk from smoking, blood glucose and lipids ECG and echocardiography may require careful interpretation in the obese Weight loss improves cardiovascular risk, lowering blood pressure, low density lipoprotein (LDL)-cholesterol and triglycerides, and raising high density lipoprotein (HDL)-cholesterol Lifestyle modification can be supplemented in selected cases by anti-obesity drugs; bariatric surgery may be appropriate and can halve predicted cardiovascular risk Hypertension should be managed by lifestyle improvement, aiming to reduce weight, increase exercise and limit sodium and alcohol intake Antihypertensive drugs are indicated if lifestyle measures fail, and if blood pressure exceeds 140/90 mm Hg ACE inhibitors (or angiotensin receptor blockers) are first-line therapy, supplemented if necessary by a thiazide diuretic, calciumchannel blocker or -adrenoceptor blocker.

speci city/selectivity, a linearity check, robustness studies, and eventually, based on the practical requirements of the method, an assessment of the limits of detection and/or quanti cation The objective of validation is to verify that the measurement conditions and the equation used to calculate the nal result include all the in uences that will affect the nal result Validation measures the different effects throughout the whole analytical system which have an in uence on the result and ensures that no other effects have to be taken into account A speci city test ensures that the method responds to the speci c analyte of interest only, and not to other interferents or contaminants A linearity check veri es that the supposed relationship between the signal and units used for the analyte may actually be used.

Every link has a state measured by the QoS metrics of concern For example, the link state could be bandwidth, delay, cost, or any possible combination of these Every node also has a state The node state can be either measured independently or combined into the state of the adjacent links In the latter case, the residual bandwidth is the minimum of the link bandwidth and the CPU bandwidth The CPU bandwidth is defined as the maximum rate at which the node can.

Multiple drug therapy is usually required; drug choices should be informed by the patient s clinical condition, including complications such as angina..

GroupList=news.list()[1] print filter(lambda x:x[0].find( fish )!=-1,GroupList)

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