990 resultados para Medicine, State


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Objective: Integrated behavior therapy approaches are defined by the combination of behavioral and or cognitive interventions targeting neurocognition combined with other goal-oriented treatment targets such as social cognition, social skills, or educational issues. The Integrated Psychological Therapy Program (IPT) represents one of the very first behavior therapy approaches combining interventions of neurocognition, social cognition, and social competence. This comprehensive group-based bottom-up and top-down approach consists of five subprograms, each with incremental steps. IPT has been successfully implemented in several countries in Europe, America, Australia and in Asia. IPT worked as a model for some other approaches designed in the USA. IPT was undergone two further developments: based on the social competence part of IPT, the three specific therapy programs focusing residential, occupational or recreational topics were developed. Recently, the cognitive part of INT was rigorously expanded into the Integrated Neurocognitive Therapy (INT) designed exclusively for outpatient treatment: INT includes interventions targeting all neurocognitive and social cognitive domains defined by the NIMH-MATRICS initiative. These group and partially PC-based exercises are structured into four therapy modules, each starting with exercises on neurocognitive domains followed by social cognitive targets. Efficacy: The evidence of integrated therapy approaches and its advantage compared to of one-track interventions was becoming a discussion tool in therapy research as well as in mental health systems. Results of meta-analyses support superiority of integrated approaches compared to one-track interventions in more distal outcome areas such as social functioning. These results are in line with the large body of 37 independent IPT studies in 12 countries. Moreover, IPT research indicates the maintenance of therapy effects after the end of therapy and some evidence generalization effects. Additionally, the international randomized multi-center study on INT with 169 outpatients strongly supports the successful therapy of integrated therapy in proximal and distal outcome such as significant effects in cognition, functioning and negative symptoms. Clinical implication: therapy research as well as expert’s clinical experience recommends integrated therapy approaches such as IPT to be successful agents within multimodal psychiatric treatment concepts. Finally, integrated group therapy based on cognitive remediation seems to motivate and stimulate schizophrenia inpatients and outpatients to more successful and independent life also demanded by the recovery movement.

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The use of complementary and alternative Medicine (CAM) has increased over the past two decades in Europe. Nonetheless, research investigating the evidence to support its use remains limited. The CAMbrella project funded by the European Commission aimed to develop a strategic research agenda starting by systematically evaluating the state of CAM in the EU. CAMbrella involved 9 work packages covering issues such as the definition of CAM; its legal status, provision and use in the EU; and a synthesis of international research perspectives. Based on the work package reports, we developed a strategic and methodologically robust research roadmap based on expert workshops, a systematic Delphi-based process and a final consensus conference. The CAMbrella project suggests six core areas for research to examine the potential contribution of CAM to the health care challenges faced by the EU. These areas include evaluating the prevalence of CAM use in Europe; the EU cititzens’ needs and attitudes regarding CAM; the safety of CAM; the comparative effectiveness of CAM; the effects of meaning and context on CAM outcomes; and different models for integrating CAM into existing health care systems. CAM research should use methods generally accepted in the evaluation of health services, including comparative effectiveness studies and mixed-methods designs. A research strategy is urgently needed, ideally led by a European CAM coordinating research office dedicated to fostering systematic communication between EU governments, the public, charitable and industry funders, researchers and other stakeholders. A European Centre for CAM should also be established to monitor and further a coordinated research strategy with sufficient funds to commission and promote high quality, independent research focusing on the public’s health needs and pan-European collaboration. There is a disparity between highly prevalent use of CAM in Europe and solid knowledge about it. A strategic approach on CAM research should be established to investigate the identified gaps of knowledge and to address upcoming health care challenges.

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Recently, many studies about a network active during rest and deactivated during tasks emerged in the literature: the default mode network (DMN). Spatial and temporal DMN features are important markers for psychiatric diseases. Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects. From these findings, the conclusion can be drawn that an increase in resting state DMN activity may go along with an increase in theta power in high-load WM conditions. We followed this hypothesis in a study on 17 healthy subjects performing a visual Sternberg WM task. The DMN was obtained by a BOLD-ICA approach and its dynamics represented by the percent-strength during pre-stimulus periods. DMN dynamics were temporally correlated with EEG theta spectral power from retention intervals. This so-called covariance mapping yielded the spatial distribution of the theta EEG fluctuations associated with the dynamics of the DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention. However, load-dependent correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance during later retention. Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over the course of the retention period. Since both, WM performance and DMN activity, are markers of mental health, our results could be important for further investigations of psychiatric populations.

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Recently, multiple studies showed that spatial and temporal features of a task-negative default mode network (DMN) (Greicius et al., 2003) are important markers for psychiatric diseases (Balsters et al., 2013). Another prominent indicator of cognitive functioning, yielding information about the mental condition in health and disease, is working memory (WM) processing. In EEG and MEG studies, frontal-midline theta power has been shown to increase with load during WM retention in healthy subjects (Brookes et al., 2011). Negative correlations between DMN activity and theta amplitude have been found during resting state (Jann et al., 2010) as well as during WM (Michels et al., 2010). Likewise, WM training resulted in higher resting state theta power as well as increased small-worldness of the resting brain (Langer et al., 2013). Further, increased fMRI connectivity between nodes of the DMN correlated with better WM performance (Hampson et al., 2006). Hence, the brain’s default state might influence it’s functioning during task. We therefore hypothesized correlations between pre-stimulus DMN activity and EEG-theta power during WM maintenance, depending on the WM load. 17 healthy subjects performed a Sternberg WM task while being measured simultaneously with EEG and fMRI. Data was recorded within a multicenter-study: 12 subjects were measured in Zurich with a 64-channels MR-compatible system (Brain Products) in a 3T Philips scanner, 5 subjects with a 96-channel MR-compatible system (Brain Products) in a 3T Siemens Scanner in Bern. The DMN components was obtained by a group BOLD-ICA approach over the full task duration (figure 1). The subject-wise dynamics were obtained by back-reconstructed onto each subject’s fMRI data and normalized to percent signal change values. The single trial pre-stimulus-DMN activation was then temporally correlated with the single trial EEG-theta (3-8 Hz) spectral power during retention intervals. This so-called covariance mapping (Jann et al., 2010) yielded the spatial distribution of the theta EEG fluctuations during retention associated with the dynamics of the pre-stimulus DMN. In line with previous findings, theta power was increased at frontal-midline electrodes in high- versus low-load conditions during early WM retention (figure 2). However, correlations of DMN with theta power resulted in primarily positive correlations in low-load conditions, while during high-load conditions negative correlations of DMN activity and theta power were observed at frontal-midline electrodes. This DMN-dependent load effect reached significance in the middle of the retention period (TANOVA, p<0.05) (figure 3). Our results show a complex and load-dependent interaction of pre-stimulus DMN activity and theta power during retention, varying over time. While at a more global, load-independent view pre-stimulus DMN activity correlated positively with theta power during retention, the correlation was inversed during certain time windows in high-load trials, meaning that in trials with enhanced pre-stimulus DMN activity theta power decreases during retention. Since both WM performance and DMN activity are markers of mental health our results could be important for further investigations of psychiatric populations.

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Neutropenia is probably the strongest known predisposition to infection with otherwise harmless environmental or microbiota-derived species. Because initial swarming of neutrophils at the site of infection occurs within minutes, rather than the hours required to induce "emergency granulopoiesis," the relevance of having high numbers of these cells available at any one time is obvious. We observed that germ-free (GF) animals show delayed clearance of an apathogenic bacterium after systemic challenge. In this article, we show that the size of the bone marrow myeloid cell pool correlates strongly with the complexity of the intestinal microbiota. The effect of colonization can be recapitulated by transferring sterile heat-treated serum from colonized mice into GF wild-type mice. TLR signaling was essential for microbiota-driven myelopoiesis, as microbiota colonization or transferring serum from colonized animals had no effect in GF MyD88(-/-)TICAM1(-/-) mice. Amplification of myelopoiesis occurred in the absence of microbiota-specific IgG production. Thus, very low concentrations of microbial Ags and TLR ligands, well below the threshold required for induction of adaptive immunity, sets the bone marrow myeloid cell pool size. Coevolution of mammals with their microbiota has probably led to a reliance on microbiota-derived signals to provide tonic stimulation to the systemic innate immune system and to maintain vigilance to infection. This suggests that microbiota changes observed in dysbiosis, obesity, or antibiotic therapy may affect the cross talk between hematopoiesis and the microbiota, potentially exacerbating inflammatory or infectious states in the host.

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Endovascular aortic repair (EVAR) necessitates lifelong surveillance for the patient, in order to detect complications timely. Endoleaks (ELs) are among the most common complications of EVAR. Especially type II ELs can have a very unpredictable clinical course and this can range from spontaneous sealing to aortic rupture. Subgroups of this type of EL need to be identified in order to make a proper risk stratification. Aim of this review is to describe the existing imaging techniques, including their advantages and disadvantages in the context of post-EVAR surveillance with a particular emphasis on low-flow ELs. Low flow ELs cause pressurization of the aortic aneurysm sac with a low velocity filling, leading to difficulty of detection by routine imaging protocols for EVAR surveillance, e.g. bi- or triphasic multislice computed tomographic angiography, magnetic resonance imaging and contrast enhanced ultrasound. In this article, we review the imaging possibilities of ELs and discuss the different imaging strategies available for depicting low flow ELs.

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Throughout the last decade, increasing awareness has been raised on issues related to reproduction in rheumatic diseases including basic research to clarify the important role of estrogens in the etiology and pathophysiology of immune/inflammatory diseases. Sub- or infertility is a heterogeneous condition that can be related to immunological mechanisms, to pregnancy loss, to disease burden, to therapy, and to choices in regard to family size. Progress in reproductive medicine has made it possible for more patients with rheumatic disease to have children. Active disease in women with rheumatoid arthritis (RA) affects their children's birth weight and may have long-term effects on their future health status. Pregnancy complications as preeclampsia and intrauterine growth restriction are still increased in patients with systemic lupus erythematosus (SLE) and antiphospholipid syndrome (APS), however, biomarkers can monitor adverse events, and several new therapies may improve outcomes. Pregnancies in women with APS remain a challenge, and better therapies for the obstetric APS are needed. New prospective studies indicate improved outcomes for pregnancies in women with rare diseases like systemic sclerosis and vasculitis. TNF inhibitors hold promise for maintaining remission in rheumatological patients and may be continued at least in the first half of pregnancy. Pre-conceptional counseling and interdisciplinary management of pregnancies are essential for ensuring optimal pregnancy outcomes.

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With the increasing production and use of engineered nanoparticles it is crucial that their interaction with biological systems is understood. Due to the small size of nanoparticles, their identification and localization within single cells is extremely challenging. Therefore, various cutting-edge techniques are required to detect and to quantify metals, metal oxides, magnetic, fluorescent, as well as electron-dense nanoparticles. Several techniques will be discussed in detail, such as inductively coupled plasma atomic emission spectroscopy, flow cytometry, laser scanning microscopy combined with digital image restoration, as well as quantitative analysis by means of stereology on transmission electron microscopy images. An overview will be given regarding the advantages of those visualization/quantification systems, including a thorough discussion about limitations and pitfalls.

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The alternative classification system for personality disorders in DSM-5 features a hierarchical model of maladaptive personality traits. This trait model comprises five broad trait domains and 25 specific trait facets that can be reliably assessed using the Personality Inventory for DSM-5 (PID-5). Although there is a steadily growing literature on the validity of the PID-5, issues of temporal stability and situational influences on test scores are currently unexplored. We addressed these issues using a sample of 611 research participants who completed the PID-5 three times, with time intervals of two months. Latent state-trait (LST) analyses for each of the 25 PID-5 trait facets showed that, on average, 79.5% of the variance was due to stable traits (i.e., consistency), and 7.7% of the variance was due to situational factors (i.e., occasion specificity). Our findings suggest that the PID-5 trait facets predominantly capture individual differences that are stable across time.

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Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.