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#Clinique #Hyperkaliémie #Kaliémie #Médecine
The most serious manifestations of hyperkalemia are muscle weakness or paralysis, cardiac conduction abnormalities, and cardiac arrhythmias. These manifestations usually occur when the serum potassium concentration is ≥7.0 mEq/L with chronic hyperkalemia or possibly at lower levels with an acute rise in serum potassium. Patients with skeletal muscle or cardiac manifestations typically have one or more of the characteristic ECG abnormalities associated with hyperkalemia.

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prevention of hyperkalemia are discussed separately. (See "Causes and evaluation of hyperkalemia in adults" and "Treatment and prevention of hyperkalemia in adults".) CLINICAL MANIFESTATIONS — <span>The most serious manifestations of hyperkalemia are muscle weakness or paralysis, cardiac conduction abnormalities, and cardiac arrhythmias. These manifestations usually occur when the serum potassium concentration is ≥7.0 mEq/L with chronic hyperkalemia or possibly at lower levels with an acute rise in serum potassium. Patients with skeletal muscle or cardiac manifestations typically have one or more of the characteristic ECG abnormalities associated with hyperkalemia. Other manifestations in hyperkalemic patients may be related to the cause of the hyperkalemia, such as polyuria and polydipsia with uncontrolled diabetes. Severe muscle weakness or para




#Kaliémie #Médecine #Physiologie
Acid-base disturbances cause potassium to shift into and out of cells, a phenomenon called "internal potassium balance" [2]. An often-quoted study found that the plasma potassium concentration will rise by 0.6 mEq/L for every 0.1 unit reduction of the extracellular pH [3]. However, this estimate was based upon only five patients with a variety of disturbances, and the range was very broad (0.2 to 1.7 mEq/L). This variability in the rise or fall of the plasma potassium in response to changes in extracellular pH was confirmed in subsequent studies

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[1]. These changes are most pronounced with metabolic acidosis but can also occur with metabolic alkalosis and, to a lesser degree, respiratory acid-base disorders. INTERNAL POTASSIUM BALANCE — <span>Acid-base disturbances cause potassium to shift into and out of cells, a phenomenon called "internal potassium balance" [2]. An often-quoted study found that the plasma potassium concentration will rise by 0.6 mEq/L for every 0.1 unit reduction of the extracellular pH [3]. However, this estimate was based upon only five patients with a variety of disturbances, and the range was very broad (0.2 to 1.7 mEq/L). This variability in the rise or fall of the plasma potassium in response to changes in extracellular pH was confirmed in subsequent studies [2,4]. Metabolic acidosis — In metabolic acidosis, more than one-half of the excess hydrogen ions are buffered in the cells. In this setting, electroneutrality is maintained in part by




#Kaliémie #Médecine #Physiologie
A fall in pH is much less likely to raise the plasma potassium concentration in patients with lactic acidosis or ketoacidosis [7,8]. The hyperkalemia that is commonly seen in diabetic ketoacidosis (DKA), for example, is more closely related to the insulin deficiency and hyperosmolality than to the degree of acidemia.

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uced [5,6]. There is still a relative increase in the plasma potassium concentration, however, as evidenced by a further fall in the plasma potassium concentration if the acidemia is corrected. <span>A fall in pH is much less likely to raise the plasma potassium concentration in patients with lactic acidosis or ketoacidosis [7,8]. The hyperkalemia that is commonly seen in diabetic ketoacidosis (DKA), for example, is more closely related to the insulin deficiency and hyperosmolality than to the degree of acidemia. (See "Diabetic ketoacidosis and hyperosmolar hyperglycemic state in adults: Clinical features, evaluation, and diagnosis".) Why this occurs is not well understood. Two factors that may




Potassium balance in acid-base disorders
#Kaliémie #Médecine #Physiologie

Just as metabolic acidosis can cause hyperkalemia, a rise in the plasma potassium concentration can induce a mild metabolic acidosis. In patients with hypoaldosteronism, for example, the mild metabolic acidosis is primarily due to the associated hyperkalemia [ 11]. Two factors contribute to this phenomenon:

● A transcellular exchange occurs as the entry of most of the excess potassium into the cells is balanced in part by intracellular hydrogen ions moving into the extracellular fluid [12]. The net effect is an extracellular acidosis and an intracellular alkalosis.

● Normally, the kidney increases ammonium excretion after an acid load, an effect that is stimulated in part by a fall in intracellular pH [13]. In hyperkalemia, the associated intracellular alkalosis diminishes ammonium generation by the proximal tubule [14]. Hyperkalemia reduces the expression of ammonia-generating enzymes in the proximal tubule and upregulates expression of the ammonia-recycling enzyme glutamine synthetase [15]. Normally, ammonium exiting the proximal tubule is reabsorbed in the thick ascending limb via the apical Na+-K+/NH4+-2Cl- cotransporter (NKCC2), after which it crosses the interstitium and is excreted into the urine by the collecting duct [16-18]. However, potassium competes with ammonium for reabsorption by NKCC2, and therefore, elevated tubular potassium concentrations can impair normal renal ammonium handling, resulting in acidosis [19]. In addition, hyperkalemia reduces expression of the ammonia transporter family member Rhcg and decreases apical expression of H-ATPase in the inner stripe of the outer medullary collecting duct, further compromising urinary ammonium excretion [15].

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e the ability of the organic anion to accompany the hydrogen ion into the cell, perhaps as the lipid-soluble, intact acid [9], and differential effects on insulin and glucagon secretion [4,10]. <span>Just as metabolic acidosis can cause hyperkalemia, a rise in the plasma potassium concentration can induce a mild metabolic acidosis. In patients with hypoaldosteronism, for example, the mild metabolic acidosis is primarily due to the associated hyperkalemia [11]. Two factors contribute to this phenomenon: ●A transcellular exchange occurs as the entry of most of the excess potassium into the cells is balanced in part by intracellular hydrogen ions moving into the extracellular fluid [12]. The net effect is an extracellular acidosis and an intracellular alkalosis. ●Normally, the kidney increases ammonium excretion after an acid load, an effect that is stimulated in part by a fall in intracellular pH [13]. In hyperkalemia, the associated intracellular alkalosis diminishes ammonium generation by the proximal tubule [14]. Hyperkalemia reduces the expression of ammonia-generating enzymes in the proximal tubule and upregulates expression of the ammonia-recycling enzyme glutamine synthetase [15]. Normally, ammonium exiting the proximal tubule is reabsorbed in the thick ascending limb via the apical Na+-K+/NH4+-2Cl- cotransporter (NKCC2), after which it crosses the interstitium and is excreted into the urine by the collecting duct [16-18]. However, potassium competes with ammonium for reabsorption by NKCC2, and therefore, elevated tubular potassium concentrations can impair normal renal ammonium handling, resulting in acidosis [19]. In addition, hyperkalemia reduces expression of the ammonia transporter family member Rhcg and decreases apical expression of H-ATPase in the inner stripe of the outer medullary collecting duct, further compromising urinary ammonium excretion [15]. The net effect of these changes in cation distribution and renal function is that metabolic acidosis and relative hyperkalemia are often seen together. Metabolic alkalosis — For similar




Potassium balance in acid-base disorders
#Kaliémie #Médecine #Physiologie
In several organic acidoses, the acid anion is excreted in the urine with sodium or potassium as the accompanying cation. Hypokalemia may result despite the concurrent shift of potassium out of cells in response to acidemia. The metabolic acidosis caused by glue sniffing is the most dramatic example of this phenomenon. Inhaled toluene is metabolized to hippuric acid, and the acid anion (hippurate) is eliminated in the urine by both filtration and secretion, commonly resulting in hypokalemia [22]. (See "The delta anion gap/delta HCO3 ratio in patients with a high anion gap metabolic acidosis".)

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potassium. The net result is a normal anion gap metabolic acidosis with potassium depletion and hypokalemia. (See "Causes of hypokalemia in adults", section on 'Lower gastrointestinal losses'.) <span>In several organic acidoses, the acid anion is excreted in the urine with sodium or potassium as the accompanying cation. Hypokalemia may result despite the concurrent shift of potassium out of cells in response to acidemia. The metabolic acidosis caused by glue sniffing is the most dramatic example of this phenomenon. Inhaled toluene is metabolized to hippuric acid, and the acid anion (hippurate) is eliminated in the urine by both filtration and secretion, commonly resulting in hypokalemia [22]. (See "The delta anion gap/delta HCO3 ratio in patients with a high anion gap metabolic acidosis".) Renal potassium wasting also occurs in diabetic ketoacidosis (DKA) and occasionally may lead to hypokalemia (6 percent of patients with DKA in one study) [23]. However, in contrast to t




Potassium balance in acid-base disorders
#Kaliémie #Médecine #Physiologie
In metabolic acidosis, more than one-half of the excess hydrogen ions are buffered in the cells. In this setting, electroneutrality is maintained in part by the movement of intracellular potassium into the extracellular fluid (figure 1). Thus, metabolic acidosis results in a plasma potassium concentration that is elevated in relation to total body stores. The net effect in some cases is overt hyperkalemia. (See 'Metabolic acidosis' above.)

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— Renal potassium wasting resulting in potassium depletion and hypokalemia is a feature of most causes of metabolic alkalosis (eg, vomiting, diuretics, Bartter and Gitelman syndromes). SUMMARY ●<span>In metabolic acidosis, more than one-half of the excess hydrogen ions are buffered in the cells. In this setting, electroneutrality is maintained in part by the movement of intracellular potassium into the extracellular fluid (figure 1). Thus, metabolic acidosis results in a plasma potassium concentration that is elevated in relation to total body stores. The net effect in some cases is overt hyperkalemia. (See 'Metabolic acidosis' above.) ●Just as metabolic acidosis can cause hyperkalemia, a rise in the plasma potassium concentration can induce a mild metabolic acidosis. This is due to transcellular exchange as most of t




Flashcard 4706428128524

Question
Is the ant colony optimization (ACO) algorithm a deterministic or stochastic method?
Answer
In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs.


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Ant colony optimization algorithms - Wikipedia
r than the other, their choice is entirely random. However, those who use the shorter route reach the food faster and therefore go back and forth more often between the anthill and the food.[1] <span>In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs. Artificial Ants stand for multi-agent methods inspired by the behavior of real ants. The pheromone-based communication of biological ants is often the predominant paradigm used.[2] Comb







Flashcard 4706431012108

Question
What is the essential idea of an ant colony optimization (ACO) algorithm?
Answer
  • 'Ants' initially explore randomly, but lay down pheromones of where they've visited
  • Shortest paths to goal that are inititially traversed by a single ant are more likely to be reinforced by other ants (compared to long paths that wander around)
  • Phermones evaporate so that long, useless paths are not re-traversed so readily.

In the natural world, ants of some species (initially) wander randomly, and upon finding food return to their colony while laying down pheromone trails. If other ants find such a path, they are likely not to keep travelling at random, but instead to follow the trail, returning and reinforcing it if they eventually find food (see Ant communication).

Over time, however, the pheromone trail starts to evaporate, thus reducing its attractive strength. The more time it takes for an ant to travel down the path and back again, the more time the pheromones have to evaporate. A short path, by comparison, gets marched over more frequently, and thus the pheromone density becomes higher on shorter paths than longer ones. Pheromone evaporation also has the advantage of avoiding the convergence to a locally optimal solution. If there were no evaporation at all, the paths chosen by the first ants would tend to be excessively attractive to the following ones. In that case, the exploration of the solution space would be constrained. The influence of pheromone evaporation in real ant systems is unclear, but it is very important in artificial systems.[8]

The overall result is that when one ant finds a good (i.e., short) path from the colony to a food source, other ants are more likely to follow that path, and positive feedback eventually leads to many ants following a single path. The idea of the ant colony algorithm is to mimic this behavior with "simulated ants" walking around the graph representing the problem to solve.


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Ant colony optimization algorithms - Wikipedia
5.7 Image processing 5.8 Other applications 6 Definition difficulty 7 Stigmergy algorithms 8 Related methods 9 History 10 References 11 Publications (selected) 12 External links Overview[edit] <span>In the natural world, ants of some species (initially) wander randomly, and upon finding food return to their colony while laying down pheromone trails. If other ants find such a path, they are likely not to keep travelling at random, but instead to follow the trail, returning and reinforcing it if they eventually find food (see Ant communication). Over time, however, the pheromone trail starts to evaporate, thus reducing its attractive strength. The more time it takes for an ant to travel down the path and back again, the more time the pheromones have to evaporate. A short path, by comparison, gets marched over more frequently, and thus the pheromone density becomes higher on shorter paths than longer ones. Pheromone evaporation also has the advantage of avoiding the convergence to a locally optimal solution. If there were no evaporation at all, the paths chosen by the first ants would tend to be excessively attractive to the following ones. In that case, the exploration of the solution space would be constrained. The influence of pheromone evaporation in real ant systems is unclear, but it is very important in artificial systems.[8] The overall result is that when one ant finds a good (i.e., short) path from the colony to a food source, other ants are more likely to follow that path, and positive feedback eventually leads to many ants following a single path. The idea of the ant colony algorithm is to mimic this behavior with "simulated ants" walking around the graph representing the problem to solve. Ambient networks of intelligent objects[edit] New concepts are required since “intelligence” is no longer centralized but can be found throughout all minuscule objects. Anthropocentric







Flashcard 4706436254988

Question

In ant colony optimization, what is the probability of the kth ant selecting edge that moves it to node y from node x?

(May want to recall the notation: \(\tau _{xy}\) is the amount of pheromone deposited for transition from state \(x\) to \(y\) )

Answer

In general, the \(k\)th ant moves from state \(x\) to state \(y\) with probability

\(p_{xy}^{k}={\frac {(\tau _{xy}^{\alpha })(\eta _{xy}^{\beta })}{\sum _{z\in \mathrm {allowed} _{x}}(\tau _{xz}^{\alpha })(\eta _{xz}^{\beta })}}\)

where

\(\tau _{xy}\) is the amount of pheromone deposited for transition from state \(x\) to \(y\), 0 ≤ \(\alpha \) is a parameter to control the influence of \(\tau _{xy}\), \(\eta _{xy}\) is the desirability of state transition \(xy\) (a priori knowledge, typically \(1/d_{{xy}}\), where \(d\) is the distance) and \(\beta \) ≥ 1 is a parameter to control the influence of \(\eta _{xy}\). \(\tau _{xz}\) and \(\eta _{xz}\) represent the trail level and attractiveness for the other possible state transitions.


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Ant colony optimization algorithms - Wikipedia
yle \tau _{xy}} of the move, indicating how proficient it has been in the past to make that particular move. The trail level represents a posteriori indication of the desirability of that move. <span>In general, the k {\displaystyle k} th ant moves from state x {\displaystyle x} to state y {\displaystyle y} with probability p x y k = ( τ x y α ) ( η x y β ) ∑ z ∈ a l l o w e d x ( τ x z α ) ( η x z β ) {\displaystyle p_{xy}^{k}={\frac {(\tau _{xy}^{\alpha })(\eta _{xy}^{\beta })}{\sum _{z\in \mathrm {allowed} _{x}}(\tau _{xz}^{\alpha })(\eta _{xz}^{\beta })}}} where τ x y {\displaystyle \tau _{xy}} is the amount of pheromone deposited for transition from state x {\displaystyle x} to y {\displaystyle y} , 0 ≤ α {\displaystyle \alpha } is a parameter to control the influence of τ x y {\displaystyle \tau _{xy}} , η x y {\displaystyle \eta _{xy}} is the desirability of state transition x y {\displaystyle xy} (a priori knowledge, typically 1 / d x y {\displaystyle 1/d_{xy}} , where d {\displaystyle d} is the distance) and β {\displaystyle \beta } ≥ 1 is a parameter to control the influence of η x y {\displaystyle \eta _{xy}} . τ x z {\displaystyle \tau _{xz}} and η x z {\displaystyle \eta _{xz}} represent the trail level and attractiveness for the other possible state transitions. Pheromone update[edit] Trails are usually updated when all ants have completed their solution, increasing or decreasing the level of trails corresponding to moves that were part of "goo







Flashcard 4706439138572

Question
Recall Wikipedia's example of a global pheromone updating rule for an ant colony optimization (ACO) algorithm.
Answer

An example of a global pheromone updating rule is

\(\tau _{xy}\leftarrow (1-\rho )\tau _{xy}+\sum _{k}\Delta \tau _{xy}^{k}\)

where \(\tau _{xy}\) is the amount of pheromone deposited for a state transition \(xy\), \(\rho \) is the pheromone evaporation coefficient and \(\Delta \tau _{xy}^{k}\) is the amount of pheromone deposited by \(k\)th ant, typically given for a TSP problem (with moves corresponding to arcs of the graph) by

\(\Delta \tau _{xy}^{k}={\begin{cases}Q/L_{k}&{\mbox{if ant }}k{\mbox{ uses curve }}xy{\mbox{ in its tour}}\\0&{\mbox{otherwise}}\end{cases}}\)

where \(L_{k}\) is the cost of the \(k\)th ant's tour (typically length) and \(Q\) is a constant.


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Ant colony optimization algorithms - Wikipedia
s are usually updated when all ants have completed their solution, increasing or decreasing the level of trails corresponding to moves that were part of "good" or "bad" solutions, respectively. <span>An example of a global pheromone updating rule is τ x y ← ( 1 − ρ ) τ x y + ∑ k Δ τ x y k {\displaystyle \tau _{xy}\leftarrow (1-\rho )\tau _{xy}+\sum _{k}\Delta \tau _{xy}^{k}} where τ x y {\displaystyle \tau _{xy}} is the amount of pheromone deposited for a state transition x y {\displaystyle xy} , ρ {\displaystyle \rho } is the pheromone evaporation coefficient and Δ τ x y k {\displaystyle \Delta \tau _{xy}^{k}} is the amount of pheromone deposited by k {\displaystyle k} th ant, typically given for a TSP problem (with moves corresponding to arcs of the graph) by Δ τ x y k = { Q / L k if ant k uses curve x y in its tour 0 otherwise {\displaystyle \Delta \tau _{xy}^{k}={\begin{cases}Q/L_{k}&{\mbox{if ant }}k{\mbox{ uses curve }}xy{\mbox{ in its tour}}\\0&{\mbox{otherwise}}\end{cases}}} where L k {\displaystyle L_{k}} is the cost of the k {\displaystyle k} th ant's tour (typically length) and Q {\displaystyle Q} is a constant. Common extensions[edit] Here are some of the most popular variations of ACO algorithms. Ant System (AS)[edit] The Ant System is the first ACO algorithm. This algorithm corresponds to th







#Clinique #Médecine #Physiologie
To identify and assess heart failure — Many of the symptoms experienced by patients with HF are due to an elevation of the filling pressures of either the right or left ventricle (LV; ie, the RAP or LV end-diastolic pressure [LVEDP], respectively). The above cited review found that an elevated JVP was of value in diagnosing HF across clinical settings [3]. In a primary care setting, an elevated JVP had diagnostic value for detection of LV systolic dysfunction independent of other clinical variables (odds ratio 15.1, 4.6 to 49.3) [7]. The JVP is the most important marker of the intravascular volume status in a patient with HF [8]. Indeed, in the ESCAPE trial of patients with HF, the only two findings from the history and physical examination which were associated with an elevated pulmonary capillary wedge pressure (PCWP) were the presence of orthopnea or an elevated JVP [5].

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an elevated JVP is observed, causes of elevated RAP as well as other causes (eg, superior vena cava obstruction) should be considered. (See 'Causes of elevated jugular venous pressure' below.) <span>To identify and assess heart failure — Many of the symptoms experienced by patients with HF are due to an elevation of the filling pressures of either the right or left ventricle (LV; ie, the RAP or LV end-diastolic pressure [LVEDP], respectively). The above cited review found that an elevated JVP was of value in diagnosing HF across clinical settings [3]. In a primary care setting, an elevated JVP had diagnostic value for detection of LV systolic dysfunction independent of other clinical variables (odds ratio 15.1, 4.6 to 49.3) [7]. The JVP is the most important marker of the intravascular volume status in a patient with HF [8]. Indeed, in the ESCAPE trial of patients with HF, the only two findings from the history and physical examination which were associated with an elevated pulmonary capillary wedge pressure (PCWP) were the presence of orthopnea or an elevated JVP [5]. The JVP is an estimate of the RAP and is not a direct measure of the LV filling pressures (LVEDP). The left atrial pressure is generally a measure of the LVEDP and is estimated on right




To assess risk of progression of ALVSD to heart failure — The presence of an elevated JVP has prognostic significance among asymptomatic patients with systolic LV dysfunction (ALVSD) and patients with current or prior symptomatic HFrEF. In a post-hoc analysis of data from 4102 SOLVD participants with asymptomatic or mildly symptomatic LV systolic dysfunction, presence of elevated JVP and presence of a third heart sound were independent predictors of an increased risk of progression to symptomatic HF [11] during the 34 months mean follow-up.

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he PCWP is high or being high when the PCWP is low [10]. In patients with a discordance of the RAP and PCWP, assessment of the LV filling pressures by an estimate of the JVP will be inaccurate. <span>To assess risk of progression of ALVSD to heart failure — The presence of an elevated JVP has prognostic significance among asymptomatic patients with systolic LV dysfunction (ALVSD) and patients with current or prior symptomatic HFrEF. In a post-hoc analysis of data from 4102 SOLVD participants with asymptomatic or mildly symptomatic LV systolic dysfunction, presence of elevated JVP and presence of a third heart sound were independent predictors of an increased risk of progression to symptomatic HF [11] during the 34 months mean follow-up. To assess prognosis in patients with heart failure — A retrospective analysis of 2569 SOLVD participants with HFrEF (or history of HF) found that an elevated JVP was associated with an




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