984 resultados para multiple signals
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This trial was aimed to explore the efficacy of pegfilgrastim to accelerate neutrophil engraftment after stem cell autotransplant. Twenty patients with multiple myeloma and 20 with lymphoma received pegfilgrastim 6 mg on day +1. Forty cases treated with daily filgrastim starting at median day +7 (5-7), matched by age, sex, diagnosis, high-dose chemotherapy schedule, CD34 + cell-dose, and prior therapy lines, were used for comparison. Median time to neutrophil engraftment was 9.5 vs. 11 days for pegfilgrastim and filgrastim, respectively (p < 0.0001). Likewise, duration of neutropenia, intravenous antibiotic use, and hospitalization favored pegfilgrastim, while platelet engraftment, transfusion requirement, and fever duration were equivalent in both groups. No grade ≥ 3 toxicities were observed. Patients with lymphoma performed similarly to the entire cohort, while patients with myeloma showed faster neutrophil engraftment and shorter neutropenia but not shorter hospitalization and antibiotic use. The possibility of different outcomes for lymphoma and myeloma suggests that stratification by diagnosis may be useful in future phase III studies.
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Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions
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The integration of geophysical data into the subsurface characterization problem has been shown in many cases to significantly improve hydrological knowledge by providing information at spatial scales and locations that is unattainable using conventional hydrological measurement techniques. In particular, crosshole ground-penetrating radar (GPR) tomography has shown much promise in hydrology because of its ability to provide highly detailed images of subsurface radar wave velocity, which is strongly linked to soil water content. Here, we develop and demonstrate a procedure for inverting together multiple crosshole GPR data sets in order to characterize the spatial distribution of radar wave velocity below the water table at the Boise Hydrogeophysical Research Site (BHRS) near Boise, Idaho, USA. Specifically, we jointly invert 31 intersecting crosshole GPR profiles to obtain a highly resolved and consistent radar velocity model along the various profile directions. The model is found to be strongly correlated with complementary neutron porosity-log data and is further corroborated by larger-scale structural information at the BHRS. This work is an important prerequisite to using crosshole GPR data together with existing hydrological measurements for improved groundwater flow and contaminant transport modeling.
Resumo:
Introduction: The Thalidomide-Dexamethasone (TD) regimen has provided encouraging results in relapsed MM. To improve results, bortezomib (Velcade) has been added to the combination in previous phase II studies, the so called VTD regimen. In January 2006, the European Group for Blood and Marrow Transplantation (EBMT) and the Intergroupe Francophone du Myélome (IFM) initiated a prospective, randomized, parallel-group, open-label phase III, multicenter study, comparing VTD (arm A) with TD (arm B) for MM patients progressing or relapsing after autologous transplantation. Patients and Methods: Inclusion criteria: patients in first progression or relapse after at least one autologous transplantation, including those who had received bortezomib or thalidomide before transplant. Exclusion criteria: subjects with neuropathy above grade 1 or non secretory MM. Primary study end point was time to progression (TTP). Secondary end points included safety, response rate, progression-free survival (PFS) and overall survival (OS). Treatment was scheduled as follows: bortezomib 1.3 mg/m2 was given as an i.v bolus on Days 1, 4, 8 and 11 followed by a 10-Day rest period (days 12 to 21) for 8 cycles (6 months) and then on Days 1, 8, 15, 22 followed by a 20-Day rest period (days 23 to 42) for 4 cycles (6 months). In both arms, thalidomide was scheduled at 200 mg/Day orally for one year and dexamethasone 40 mg/Day orally four days every three weeks for one year. Patients reaching remission could proceed to a new stem cell harvest. However, transplantation, either autologous or allogeneic, could only be performed in patients who completed the planned one year treatment period. Response was assessed by EBMT criteria, with additional category of near complete remission (nCR). Adverse events were graded by the NCI-CTCAE, Version 3.0.The trial was based on a group sequential design, with 4 planned interim analyses and one final analysis that allowed stopping for efficacy as well as futility. The overall alpha and power were set equal to 0.025 and 0.90 respectively. The test for decision making was based on the comparison in terms of the ratio of the cause-specific hazards of relapse/progression, estimated in a Cox model stratified on the number of previous autologous transplantations. Relapse/progression cumulative incidence was estimated using the proper nonparametric estimator, the comparison was done by the Gray test. PFS and OS probabilities were estimated by the Kaplan-Meier curves, the comparison was performed by the Log-Rank test. An interim safety analysis was performed when the first hundred patients had been included. The safety committee recommended to continue the trial. Results: As of 1st July 2010, 269 patients had been enrolled in the study, 139 in France (IFM 2005-04 study), 21 in Italy, 38 in Germany, 19 in Switzerland (a SAKK study), 23 in Belgium, 8 in Austria, 8 in the Czech republic, 11 in Hungary, 1 in the UK and 1 in Israel. One hundred and sixty nine patients were males and 100 females; the median age was 61 yrs (range 29-76). One hundred and thirty six patients were randomized to receive VTD and 133 to receive TD. The current analysis is based on 246 patients (124 in arm A, 122 in arm B) included in the second interim analysis, carried out when 134 events were observed. Following this analysis, the trial was stopped because of significant superiority of VTD over TD. The remaining patients were too premature to contribute to the analysis. The number of previous autologous transplants was one in 63 vs 60 and two or more in 61 vs 62 patients in arm A vs B respectively. The median follow-up was 25 months. The median TTP was 20 months vs 15 months respectively in arm A and B, with cumulative incidence of relapse/progression at 2 years equal to 52% (95% CI: 42%-64%) vs 70% (95% CI: 61%-81%) (p=0.0004, Gray test). The same superiority of arm A was also observed when stratifying on the number of previous autologous transplantations. At 2 years, PFS was 39% (95% CI: 30%-51%) vs 23% (95% CI: 16%-34%) (A vs B, p=0.0006, Log-Rank test). OS in the first two years was comparable in the two groups. Conclusion: VTD resulted in significantly longer TTP and PFS in patients relapsing after ASCT. Analysis of response and safety data are on going and results will be presented at the meeting.
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Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.
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Multiple Sclerosis is the most common non-traumatic cause of neurologicaldisability in young people. There is no cure yet, and until recently, few long-termtherapies existed. Interferon beta (IFNβ) was the first treatment, and remains the mostcommonly prescribed. One of the most significant problems of IFNβ therapy is theproduction of drug specific antibodies. Up to 45% of patients develop neutralizingantibodies (NAbs) to IFNβ products. The neutralizing antibody binds to the biologicalagent preventing its interaction with its receptor, inhibiting the biological action of theprotein, which abrogates the clinical efficacy of IFNβ treatment. Interferon-betamediates its response by binding to its high affinity cell surface receptor and initiatingthe JAK/STAT signalling cascade. In this project we have analyzed the IFNβ signalingpathway in macrophages when neutralizing antibodies are present. The response tothis pathway after IFNβ stimulation shows a transient oscillatory rhythm of STAT1phosphorylation, which varies as NAbs concentration increases. To improve ourunderstanding of that behavior, we extended an existing mathematical model based onnonlinear ordinary differential equations of JAK/STAT pathway by including IFN-NAbassociation and IFN-activation receptor. Combining our theoretical model withexperimental data we could study the role of neutralizing antibodies on the molecularresponse and determine its lifetime after cytokine stimulation.
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Persistence in canine distemper virus (CDV) infection is correlated with very limited cell-cell fusion and lack of cytolysis induced by the neurovirulent A75/17-CDV compared to that of the cytolytic Onderstepoort vaccine strain. We have previously shown that this difference was at least in part due to the amino acid sequence of the fusion (F) protein (P. Plattet, J. P. Rivals, B. Zuber, J. M. Brunner, A. Zurbriggen, and R. Wittek, Virology 337:312-326, 2005). Here, we investigated the molecular mechanisms of the neurovirulent CDV F protein underlying limited membrane fusion activity. By exchanging the signal peptide between both F CDV strains or replacing it with an exogenous signal peptide, we demonstrated that this domain controlled intracellular and consequently cell surface protein expression, thus indirectly modulating fusogenicity. In addition, by serially passaging a poorly fusogenic virus and selecting a syncytium-forming variant, we identified the mutation L372W as being responsible for this change of phenotype. Intriguingly, residue L372 potentially is located in the helical bundle domain of the F(1) subunit. We showed that this mutation drastically increased fusion activity of F proteins of both CDV strains in a signal peptide-independent manner. Due to its unique structure even among morbilliviruses, our findings with respect to the signal peptide are likely to be specifically relevant to CDV, whereas the results related to the helical bundle add new insights to our growing understanding of this class of F proteins. We conclude that different mechanisms involving multiple domains of the neurovirulent A75/17-CDV F protein act in concert to limit fusion activity, preventing lysis of infected cells, which ultimately may favor viral persistence.
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BACKGROUND: Surveillance of multiple congenital anomalies is considered to be more sensitive for the detection of new teratogens than surveillance of all or isolated congenital anomalies. Current literature proposes the manual review of all cases for classification into isolated or multiple congenital anomalies. METHODS: Multiple anomalies were defined as two or more major congenital anomalies, excluding sequences and syndromes. A computer algorithm for classification of major congenital anomaly cases in the EUROCAT database according to International Classification of Diseases (ICD)v10 codes was programmed, further developed, and implemented for 1 year's data (2004) from 25 registries. The group of cases classified with potential multiple congenital anomalies were manually reviewed by three geneticists to reach a final agreement of classification as "multiple congenital anomaly" cases. RESULTS: A total of 17,733 cases with major congenital anomalies were reported giving an overall prevalence of major congenital anomalies at 2.17%. The computer algorithm classified 10.5% of all cases as "potentially multiple congenital anomalies". After manual review of these cases, 7% were agreed to have true multiple congenital anomalies. Furthermore, the algorithm classified 15% of all cases as having chromosomal anomalies, 2% as monogenic syndromes, and 76% as isolated congenital anomalies. The proportion of multiple anomalies varies by congenital anomaly subgroup with up to 35% of cases with bilateral renal agenesis. CONCLUSIONS: The implementation of the EUROCAT computer algorithm is a feasible, efficient, and transparent way to improve classification of congenital anomalies for surveillance and research.
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Sleep spindles are approximately 1 s bursts of 10-16 Hz activity that occur during stage 2 sleep. Spindles are highly synchronous across the cortex and thalamus in animals, and across the scalp in humans, implying correspondingly widespread and synchronized cortical generators. However, prior studies have noted occasional dissociations of the magnetoencephalogram (MEG) from the EEG during spindles, although detailed studies of this phenomenon have been lacking. We systematically compared high-density MEG and EEG recordings during naturally occurring spindles in healthy humans. As expected, EEG was highly coherent across the scalp, with consistent topography across spindles. In contrast, the simultaneously recorded MEG was not synchronous, but varied strongly in amplitude and phase across locations and spindles. Overall, average coherence between pairs of EEG sensors was approximately 0.7, whereas MEG coherence was approximately 0.3 during spindles. Whereas 2 principle components explained approximately 50% of EEG spindle variance, >15 were required for MEG. Each PCA component for MEG typically involved several widely distributed locations, which were relatively coherent with each other. These results show that, in contrast to current models based on animal experiments, multiple asynchronous neural generators are active during normal human sleep spindles and are visible to MEG. It is possible that these multiple sources may overlap sufficiently in different EEG sensors to appear synchronous. Alternatively, EEG recordings may reflect diffusely distributed synchronous generators that are less visible to MEG. An intriguing possibility is that MEG preferentially records from the focal core thalamocortical system during spindles, and EEG from the distributed matrix system.
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There are many known examples of multiple semi-independent associations at individual loci; such associations might arise either because of true allelic heterogeneity or because of imperfect tagging of an unobserved causal variant. This phenomenon is of great importance in monogenic traits but has not yet been systematically investigated and quantified in complex-trait genome-wide association studies (GWASs). Here, we describe a multi-SNP association method that estimates the effect of loci harboring multiple association signals by using GWAS summary statistics. Applying the method to a large anthropometric GWAS meta-analysis (from the Genetic Investigation of Anthropometric Traits consortium study), we show that for height, body mass index (BMI), and waist-to-hip ratio (WHR), 3%, 2%, and 1%, respectively, of additional phenotypic variance can be explained on top of the previously reported 10% (height), 1.5% (BMI), and 1% (WHR). The method also permitted a substantial increase (by up to 50%) in the number of loci that replicate in a discovery-validation design. Specifically, we identified 74 loci at which the multi-SNP, a linear combination of SNPs, explains significantly more variance than does the best individual SNP. A detailed analysis of multi-SNPs shows that most of the additional variability explained is derived from SNPs that are not in linkage disequilibrium with the lead SNP, suggesting a major contribution of allelic heterogeneity to the missing heritability.
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In my thesis I present the findings of a multiple-case study on the CSR approach of three multinational companies, applying Basu and Palazzo's (2008) CSR-character as a process model of sensemaking, Suchman's (1995) framework on legitimation strategies, and Habermas (1996) concept of deliberative democracy. The theoretical framework is based on the assumption of a postnational constellation (Habermas, 2001) which sends multinational companies onto a process of sensemaking (Weick, 1995) with regards to their responsibilities in a globalizing world. The major reason is that mainstream CSR-concepts are based on the assumption of a liberal market economy embedded in a nation state that do not fit the changing conditions for legitimation of corporate behavior in a globalizing world. For the purpose of this study, I primarily looked at two research questions: (i) How can the CSR approach of a multinational corporation be systematized empirically? (ii) What is the impact of the changing conditions in the postnational constellation on the CSR approach of the studied multinational corporations? For the analysis, I adopted a holistic approach (Patton, 1980), combining elements of a deductive and inductive theory building methodology (Eisenhardt, 1989b; Eisenhardt & Graebner, 2007; Glaser & Strauss, 1967; Van de Ven, 1992) and rigorous qualitative data analysis. Primary data was collected through 90 semi-structured interviews in two rounds with executives and managers in three multinational companies and their respective stakeholders. Raw data originating from interview tapes, field notes, and contact sheets was processed, stored, and managed using the software program QSR NVIVO 7. In the analysis, I applied qualitative methods to strengthen the interpretative part as well as quantitative methods to identify dominating dimensions and patterns. I found three different coping behaviors that provide insights into the corporate mindset. The results suggest that multinational corporations increasingly turn towards relational approaches of CSR to achieve moral legitimacy in formalized dialogical exchanges with their stakeholders since legitimacy can no longer be derived only from a national framework. I also looked at the degree to which they have reacted to the postnational constellation by the assumption of former state duties and the underlying reasoning. The findings indicate that CSR approaches become increasingly comprehensive through integrating political strategies that reflect the growing (self-) perception of multinational companies as political actors. Based on the results, I developed a model which relates the different dimensions of corporate responsibility to the discussion on deliberative democracy, global governance and social innovation to provide guidance for multinational companies in a postnational world. With my thesis, I contribute to management research by (i) delivering a comprehensive critique of the mainstream CSR-literature and (ii) filling the gap of thorough qualitative research on CSR in a globalizing world using the CSR-character as an empirical device, and (iii) to organizational studies by further advancing a deliberative view of the firm proposed by Scherer and Palazzo (2008).
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Since it is established that human chorionic gonadotropin (hCG) affects testosterone production and release in the human body, the use of this hormone as a performance enhancing drug has been prohibited by the World Anti-Doping Agency. Nowadays, the only validated biomarker of a hCG doping is its direct quantification in urine. However, this specific parameter is subjected to large inter-individual variability and its determination is directly dependent on the reliability of hCG immunoassays used. In order to counteract these weaknesses, new biomarkers need to be evidenced. To address this issue, a pilot clinical study was performed on 10 volunteers submitted to 3 subsequent hCG injections. Blood and urine samples were collected during two weeks in order to follow the physiological effects on related compounds such as the steroid profile or hormones involved in the hypothalamo-pituitary axis. The hCG pharmacokinetic observed in all subjects was, as expected, prone to important inter-individual variations. Using ROC plots, level of testosterone and testosterone on luteinizing hormone ratio in both blood and urine were found to be the most relevant biomarker of a hCG abuse, regardless of inter-individual variations. In conclusion, this study showed the crucial importance of reliable quantification methods to assess low differences in hormonal patterns. In regard to these results and to anti-doping requirements and constraints, blood together with urine matrix should be included in the anti-doping testing program. Together with a longitudinal follow-up approach it could constitute a new strategy to detect a hCG abuse, applicable to further forms of steroid or other forbidden drug manipulation.