985 resultados para Adaptive negotiation agents
Resumo:
The treatment of multiple myeloma has undergone significant changes in the recent past. The arrival of novel agents, especially thalidomide, bortezomib and lenalidomide, has expanded treatment options and patient outcomes are improving significantly. This article summarises the discussions of an expert meeting which was held to debate current treatment practices for multiple myeloma in Switzerland concerning the role of the novel agents and to provide recommendations for their use in different treatment stages based on currently available clinical data. Novel agent combinations for the treatment of newly diagnosed, as well as relapsed multiple myeloma are examined. In addition, the role of novel agents in patients with cytogenetic abnormalities and renal impairment, as well as the management of the most frequent side effects of the novel agents are discussed. The aim of this article is to assist in treatment decisions in daily clinical practice to achieve the best possible outcome for patients with multiple myeloma.
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Biologic agents have substantially advanced the treatment of immunological disorders, including chronic inflammatory and autoimmune diseases. However, these drugs are often associated with adverse events (AEs), including allergic, immunological and other unwanted reactions. AEs can affect almost any organ or system in the body and can occur immediately, within minutes to hours, or with a delay of several days or more after initiation of biologic therapy. Although some AEs are a direct consequence of the functional inhibition of biologic-agent-targeted antigens, the pathogenesis of other AEs results from a drug-induced imbalance of the immune system, intermediary factors and cofactors, a complexity that complicates their prediction. Herein, we review the AEs associated with biologic therapy most relevant to rheumatic and immunological diseases, and discuss their underlying pathogenesis. We also include our recommendations for the medical management of such AEs. Increased understanding and improved risk management of AEs induced by biologic agents will enable better use of these versatile immune-response modifiers.
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Niche construction, by which organisms modify the environment in which they live, has been proposed to affect the evolution of many phenotypic traits. But what about the evolution of a niche constructing trait itself, whose expression changes the pattern of natural selection to which the trait is exposed in subsequent generations? This article provides an inclusive fitness analysis of selection on niche constructing phenotypes, which can affect their environment from local to global scales in arbitrarily spatially subdivided populations. The model shows that phenotypic effects of genes extending far beyond the life span of the actor can be affected by natural selection, provided they modify the fitness of those individuals living in the future that are likely to have inherited the niche construction lineage of the actor. Present benefits of behaviors are thus traded off against future indirect costs. The future costs will generally result from a complicated interplay of phenotypic effects, population demography and environmental dynamics. To illustrate these points, I derive the adaptive dynamics of a trait involved in the consumption of an abiotic resource, where resource abundance in future generations feeds back to the evolutionary dynamics of the trait.
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An epidemic model is formulated by a reactionâeuro"diffusion system where the spatial pattern formation is driven by cross-diffusion. The reaction terms describe the local dynamics of susceptible and infected species, whereas the diffusion terms account for the spatial distribution dynamics. For both self-diffusion and cross-diffusion, nonlinear constitutive assumptions are suggested. To simulate the pattern formation two finite volume formulations are proposed, which employ a conservative and a non-conservative discretization, respectively. An efficient simulation is obtained by a fully adaptive multiresolution strategy. Numerical examples illustrate the impact of the cross-diffusion on the pattern formation.
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Plant circadian clock controls a wide variety of physiological and developmental events, which include the short-days (SDs)-specific promotion of the elongation of hypocotyls during de-etiolation and also the elongation of petioles during vegetative growth. In A. thaliana, the PIF4 gene encoding a phytochrome-interacting basic helix-loop-helix (bHLH) transcription factor plays crucial roles in this photoperiodic control of plant growth. According to the proposed external coincidence model, the PIF4 gene is transcribed precociously at the end of night specifically in SDs, under which conditions the protein product is stably accumulated, while PIF4 is expressed exclusively during the daytime in long days (LDs), under which conditions the protein product is degraded by the light-activated phyB and also the residual proteins are inactivated by the DELLA family of proteins. A number of previous reports provided solid evidence to support this coincidence model mainly at the transcriptional level of the PIF 4 and PIF4-traget genes. Nevertheless, the diurnal oscillation profiles of PIF4 proteins, which were postulated to be dependent on photoperiod and ambient temperature, have not yet been demonstrated. Here we present such crucial evidence on PIF4 protein level to further support the external coincidence model underlying the temperature-adaptive photoperiodic control of plant growth in A. thaliana.
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BACKGROUND: The increasing use of erythropoietins with long half-lives and the tendency to lengthen the administration interval to monthly injections call for raising awareness on the pharmacokinetics and risks of new erythropoietin stimulating agents (ESA). Their pharmacodynamic complexity and individual variability limit the possibility of attaining comprehensive clinical experience. In order to help physicians acquiring prescription abilities, we have built a prescription computer model to be used both as a simulator and education tool. METHODS: The pharmacokinetic computer model was developed using Visual Basic on Excel and tested with 3 different ESA half-lives (24, 48 and 138 hours) and 2 administration intervals (weekly vs. monthly). Two groups of 25 nephrologists were exposed to the six randomised combinations of half-life and administration interval. They were asked to achieve and maintain, as precisely as possible, the haemoglobin target of 11-12 g/dL in a simulated naïve patient. Each simulation was repeated twice, with or without randomly generated bleeding episodes. RESULTS: The simulation using an ESA with a half-life of 138 hours, administered monthly, compared to the other combinations of half-lives and administration intervals, showed an overshooting tendency (percentages of Hb values > 13 g/dL 15.8 ± 18.3 vs. 6.9 ± 12.2; P < 0.01), which was quickly corrected with experience. The prescription ability appeared to be optimal with a 24 hour half-life and weekly administration (ability score indexing values in the target 1.52 ± 0.70 vs. 1.24 ± 0.37; P < 0.05). The monthly prescription interval, as suggested in the literature, was accompanied by less therapeutic adjustments (4.9 ± 2.2 vs. 8.2 ± 4.9; P < 0.001); a direct correlation between haemoglobin variability and number of therapy modifications was found (P < 0.01). CONCLUSIONS: Computer-based simulations can be a useful tool for improving ESA prescription abilities among nephrologists by raising awareness about the pharmacokinetic characteristics of the various ESAs and recognizing the factors that influence haemoglobin variability.
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Background- Cardiac hypertrophy involves growth responses to a variety of stimuli triggered by increased workload. It is an independent risk factor for heart failure and sudden death. Mammalian target of rapamycin (mTOR) plays a key role in cellular growth responses by integrating growth factor and energy status signals. It is found in 2 structurally and functionally distinct multiprotein complexes called mTOR complex (mTORC) 1 and mTORC2. The role of each of these branches of mTOR signaling in the adult heart is currently unknown. Methods and Results- We generated mice with deficient myocardial mTORC1 activity by targeted ablation of raptor, which encodes an essential component of mTORC1, during adulthood. At 3 weeks after the deletion, atrial and brain natriuretic peptides and β-myosin heavy chain were strongly induced, multiple genes involved in the regulation of energy metabolism were altered, but cardiac function was normal. Function deteriorated rapidly afterward, resulting in dilated cardiomyopathy and high mortality within 6 weeks. Aortic banding-induced pathological overload resulted in severe dilated cardiomyopathy already at 1 week without a prior phase of adaptive hypertrophy. The mechanism involved a lack of adaptive cardiomyocyte growth via blunted protein synthesis capacity, as supported by reduced phosphorylation of ribosomal S6 kinase 1 and 4E-binding protein 1. In addition, reduced mitochondrial content, a shift in metabolic substrate use, and increased apoptosis and autophagy were observed. Conclusions- Our results demonstrate an essential function for mTORC1 in the heart under physiological and pathological conditions and are relevant for the understanding of disease states in which the insulin/insulin-like growth factor signaling axis is affected such as diabetes mellitus and heart failure or after cancer therapy.
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Two hybrid compounds comprising an antimetastatic ruthenium-arene fragment tethered to an indazole-3-carboxylic acid derivative that inhibits aerobic glycolysis in cancer cells have been prepared and evaluated in a variety of cancer cell lines, including highly relevant human glioblastoma cells, with an apparent synergistic action between the two components observed.
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Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated