915 resultados para data treatment
Resumo:
Novel imaging techniques are playing an increasingly important role in drug development, providing insight into the mechanism of action of new chemical entities. The data sets obtained by these methods can be large with complex inter-relationships, but the most appropriate statistical analysis for handling this data is often uncertain - precisely because of the exploratory nature of the way the data are collected. We present an example from a clinical trial using magnetic resonance imaging to assess changes in atherosclerotic plaques following treatment with a tool compound with established clinical benefit. We compared two specific approaches to handle the correlations due to physical location and repeated measurements: two-level and four-level multilevel models. The two methods identified similar structural variables, but higher level multilevel models had the advantage of explaining a greater proportion of variation, and the modeling assumptions appeared to be better satisfied.
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The formation of Christendom – of Europe – was associated with a standardized worldview expressing dominion over the natural world. While some sections of medieval society, specifically monasteries and the aristocratic class, appear to have developed this paradigm, there is also evidence for heterogeneity in practice and belief. Zooarchaeologists have accumulated vast quantities of data from medieval contexts which has enabled the ecological signatures of specific social groups to be identified, and how these developed from the latter centuries of the first millennium ad. It is possible from this to consider whether trends in animal exploitation can be associated with the Christian world view of dominion, and with the very idea of what it meant to be Christian. This may enable zooarchaeologists to situate the ecological trends of the Middle Ages within the context of Europeanization, and the consolidation of a Christian society.
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Colorectal cancer (CRC) is one of the commonest malignancies of Western countries, with approximately half the incidence occurring in patients >70 years of age. Elderly CRC patients, however, are understaged, undertreated and underrepresented in clinical trials. The International Society of Geriatric Oncology created a task force with a view to assessing the potential for developing guidelines for the treatment of elderly (geriatric) CRC patients. A review of the evidence presented by the task force members confirmed the paucity of clinical trial data in elderly people and the lack of evidence-based guidelines. However, recommendations have been proposed on the basis of the available data and on the emerging evidence that treatment outcomes for fit, elderly CRC patients can be similar to those of younger patients. It is hoped that these will pave the way for formal treatment guidelines based upon solid scientific evidence in the future.
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In the last decade, a vast number of land surface schemes has been designed for use in global climate models, atmospheric weather prediction, mesoscale numerical models, ecological models, and models of global changes. Since land surface schemes are designed for different purposes they have various levels of complexity in the treatment of bare soil processes, vegetation, and soil water movement. This paper is a contribution to a little group of papers dealing with intercomparison of differently designed and oriented land surface schemes. For that purpose we have chosen three schemes for classification: i) global climate models, BATS (Dickinson et al., 1986; Dickinson et al., 1992); ii) mesoscale and ecological models, LEAF (Lee, 1992) and iii) mesoscale models, LAPS (Mihailović, 1996; Mihailović and Kallos, 1997; Mihailović et al., 1999) according to the Shao et al. (1995) classification. These schemes were compared using surface fluxes and leaf temperature outputs obtained by time integrations of data sets derived from the micrometeorological measurements above a maize field at an experimental site in De Sinderhoeve (The Netherlands) for 18 August, 8 September, and 4 October 1988. Finally, comparison of the schemes was supported applying a simple statistical analysis on the surface flux outputs.
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Prostate cancer is poised to become the most prevalent male cancer in the Western world. In Japan and China, incidence rates are almost 10-fold less those reported in the United States and the European Union. Epidemiological data suggest that environmental factors such as diet can significantly influence the incidence and mortality of prostate cancer. The differences in lifestyle between East and West are one of the major risk factors for developing prostate cancer. Traditional Japanese and Chinese diets are rich in foods containing phytoestrogenic compounds, whereas the Western diet is a poor source of these phytochemicals. The lignan phytoestrogens are the most widely occurring of these compounds. In vitro and in vivo reports in the literature indicate that lignans have the capacity to affect the pathogenesis of prostate cancer. However, their precise mechanism of action in prostate carcinogenesis remains unclear. This article outlines the possible role of lignans in prostate cancer by reviewing the current in vitro and in vivo evidence for their anticancer activities. The intriguing concept that lignans may play a role in the prevention and treatment of prostate cancer over the lifetime of an individual is discussed.
Resumo:
In the last decade, a vast number of land surface schemes has been designed for use in global climate models, atmospheric weather prediction, mesoscale numerical models, ecological models, and models of global changes. Since land surface schemes are designed for different purposes they have various levels of complexity in the treatment of bare soil processes, vegetation, and soil water movement. This paper is a contribution to a little group of papers dealing with intercomparison of differently designed and oriented land surface schemes. For that purpose we have chosen three schemes for classification: i) global climate models, BATS (Dickinson et al., 1986; Dickinson et al., 1992); ii) mesoscale and ecological models, LEAF (Lee, 1992) and iii) mesoscale models, LAPS (Mihailović, 1996; Mihailović and Kallos, 1997; Mihailović et al., 1999) according to the Shao et al. (1995) classification. These schemes were compared using surface fluxes and leaf temperature outputs obtained by time integrations of data sets derived from the micrometeorological measurements above a maize field at an experimental site in De Sinderhoeve (The Netherlands) for 18 August, 8 September, and 4 October 1988. Finally, comparison of the schemes was supported applying a simple statistical analysis on the surface flux outputs.
Resumo:
Advances in hardware and software technology enable us to collect, store and distribute large quantities of data on a very large scale. Automatically discovering and extracting hidden knowledge in the form of patterns from these large data volumes is known as data mining. Data mining technology is not only a part of business intelligence, but is also used in many other application areas such as research, marketing and financial analytics. For example medical scientists can use patterns extracted from historic patient data in order to determine if a new patient is likely to respond positively to a particular treatment or not; marketing analysts can use extracted patterns from customer data for future advertisement campaigns; finance experts have an interest in patterns that forecast the development of certain stock market shares for investment recommendations. However, extracting knowledge in the form of patterns from massive data volumes imposes a number of computational challenges in terms of processing time, memory, bandwidth and power consumption. These challenges have led to the development of parallel and distributed data analysis approaches and the utilisation of Grid and Cloud computing. This chapter gives an overview of parallel and distributed computing approaches and how they can be used to scale up data mining to large datasets.
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The Minneapolis Domestic Violence Experiment (MDVE) is a randomized social experiment with imperfect compliance which has been extremely influential in how police officers respond to misdemeanor domestic violence. This paper re-examines data from the MDVE, using recent literature on partial identification to find recidivism associated with a policy that arrests misdemeanor domestic violence suspects rather than not arresting them. Using partially identified bounds on the average treatment effect I find that arresting rather than not arresting suspects can potentially reduce recidivism by more than two-and-a-half times the corresponding intent-to-treat estimate and more than two times the corresponding local average treatment effect, even when making minimal assumptions on counterfactuals.
Resumo:
In order to best utilize the limited resource of medical resources, and to reduce the cost and improve the quality of medical treatment, we propose to build an interoperable regional healthcare systems among several levels of medical treatment organizations. In this paper, our approaches are as follows:(1) the ontology based approach is introduced as the methodology and technological solution for information integration; (2) the integration framework of data sharing among different organizations are proposed(3)the virtual database to realize data integration of hospital information system is established. Our methods realize the effective management and integration of the medical workflow and the mass information in the interoperable regional healthcare system. Furthermore, this research provides the interoperable regional healthcare system with characteristic of modularization, expansibility and the stability of the system is enhanced by hierarchy structure.
Resumo:
Background Major depressive disorders (MDD) are a debilitating and pervasive group of mental illnesses afflicting many millions of people resulting in the loss of 110 million working days and more than 2,500 suicides per annum. Adolescent MDD patients attending NHS clinics show high rates of recurrence into adult life. A meta-analysis of recent research shows that psychological treatments are not as efficacious as previously thought. Modest treatment outcomes of approximately 65% of cases responding suggest that aetiological and clinical heterogeneity may hamper the better use of existing therapies and discovery of more effective treatments. Information with respect to optimal treatment choice for individuals is lacking, with no validated biomarkers to aid therapeutic decision-making. Methods/Design Magnetic resonance-Improving Mood with Psychoanalytic and Cognitive Therapies, the MR-IMPACT study, plans to identify brain regions implicated in the pathophysiology of depressions and examine whether there are specific behavioural or neural markers predicting remission and/or subsequent relapse in a subsample of depressed adolescents recruited to the IMPACT randomised controlled trial (Registration # ISRCTN83033550). Discussion MR-IMPACT is an investigative biomarker component of the IMPACT pragmatic effectiveness trial. The aim of this investigation is to identify neural markers and regional indicators of the pathophysiology of and treatment response for MDD in adolescents. We anticipate that these data may enable more targeted treatment delivery by identifying those patients who may be optimal candidates for therapeutic response.
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Variations in lake area and depth reflect climatically induced changes in the water balance of overflowing as well as closed lakes. A new global data base of lake status has been assembled, and is used to compare two simulations for 6 ka (6000 yr ago) made with successive R15 versions of the NCAR Community Climate Model (CCM). Simulated water balance was expressed as anomalies of annual precipitation minus evaporation (P-E); observed water balance as anomalies of lake status. Comparisons were made visually, by comparing regional averages, and by a statistic that compares the signs of simulated P-E anomalies (smoothly interpolated to the lake sites) with the status anomalies. Both CCM0 and CCM1 showed enhanced Northern-Hemisphere monsoons at 6 ka. Both underestimated the effect, but CCM1 fitted the spatial patterns better. In the northern mid- and high-latitudes the two versions differed more, and fitted the data less satisfactorily. CCM1 performed better than CCM0 in North America and central Eurasia, but not in Europe. Both models (especially CCM0) simulated excessive aridity in interior Eurasia. The models were systematically wrong in the southern mid-latitudes. Problems may have been caused by inadequate treatment of changes in sea-surface conditions in both models. Palaeolake status data will continue to provide a benchmark for the evaluation of modelling improvements.
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Owing to continuous advances in the computational power of handheld devices like smartphones and tablet computers, it has become possible to perform Big Data operations including modern data mining processes onboard these small devices. A decade of research has proved the feasibility of what has been termed as Mobile Data Mining, with a focus on one mobile device running data mining processes. However, it is not before 2010 until the authors of this book initiated the Pocket Data Mining (PDM) project exploiting the seamless communication among handheld devices performing data analysis tasks that were infeasible until recently. PDM is the process of collaboratively extracting knowledge from distributed data streams in a mobile computing environment. This book provides the reader with an in-depth treatment on this emerging area of research. Details of techniques used and thorough experimental studies are given. More importantly and exclusive to this book, the authors provide detailed practical guide on the deployment of PDM in the mobile environment. An important extension to the basic implementation of PDM dealing with concept drift is also reported. In the era of Big Data, potential applications of paramount importance offered by PDM in a variety of domains including security, business and telemedicine are discussed.
Resumo:
Avian intestinal spirochaetosis (AIS) results from the colonization of the caeca and colon of poultry by pathogenic Brachyspira, notably Brachyspira pilosicoli. Following the ban on the use of antibiotic growth promoters in the European Union in 2006, the number of cases of AIS has increased, which, alongside emerging antimicrobial resistance in Brachyspira, has driven renewed interest in alternative intervention strategies. Lactobacillus-based probiotics have been shown to protect against infection with common enteric pathogens in livestock. Our previous studies have shown that Lactobacillus reuteri LM1 antagonizes aspects of the pathobiology of Brachyspira in vitro. Here, we showed that L. reuteri LM1 mitigates the clinical symptoms of AIS in chickens experimentally challenged with B. pilosicoli. Two groups of 15 commercial laying hens were challenged experimentally by oral gavage with B. pilosicoli B2904 at 18 weeks of age; one group received unsupplemented drinking water and the other received L. reuteri LM1 in drinking water from 1 week prior to challenge with Brachyspira and thereafter for the duration of the study. This treatment regime was protective. Specifically, B. pilosicoli was detected by culture in fewer birds, bird weights were higher, faecal moisture contents were significantly lower (P<0.05) and egg production as assessed by egg weight and faecal staining score was improved (P<0.05). Also, at post-mortem examination, significantly fewer B. pilosicoli were recovered from treated birds (P<0.05), with only mild–moderate histopathological changes observed. These data suggest that L. reuteri LM1 may be a useful tool in the control of AIS.
Resumo:
The ability to match individual patients to tailored treatments has the potential to greatly improve outcomes for individuals suffering from major depression. In particular, while the vast majority of antidepressant treatments affect either serotonin or noradrenaline or a combination of these two neurotransmitters, it is not known whether there are particular patients or symptom profiles which respond preferentially to the potentiation of serotonin over noradrenaline or vice versa. Experimental medicine models suggest that the primary mode of action of these treatments may be to remediate negative biases in emotional processing. Such models may provide a useful framework for interrogating the specific actions of antidepressants. Here, we therefore review evidence from studies examining the effects of drugs which potentiate serotonin, noradrenaline or a combination of both neurotransmitters on emotional processing. These results suggest that antidepressants targeting serotonin and noradrenaline may have some specific actions on emotion and reward processing which could be used to improve tailoring of treatment or to understand the effects of dual-reuptake inhibition. Specifically, serotonin may be particularly important in alleviating distress symptoms, while noradrenaline may be especially relevant to anhedonia. The data reviewed here also suggest that noradrenergic-based treatments may have earlier effects on emotional memory that those which affect serotonin.