120 resultados para IRB
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Aims: Obesity is a state of chronic inflammation characterized by depressed Th2 immune response. Animal studies have shown decreased IgA levels in obese rats and Leptin an adipose cell origin cytokine have been shown to enhance the activity of Clostridium difficile Toxin A. Hence we hypothesized that obesity is a risk factor for C. difficile infection (CDI) ^ Methods: 33 cases of CDI and 131 controls matched by age and HORNS index were identified from an IRB approved observational study at St. Luke's Episcopal Hospital in Houston. Variables like age, gender, height, weight, chronic antibiotic use, proton pump inhibitor use, diabetes mellitus, myocardial infarction, inflammatory bowel disease, diverticulitis, transfer from nursing home, hospital or home, nasogastric tube use and use of hemodialysis were provided in the dataset. Height and weight of the patient were used to calculate the BMI, based on which the study subjects were classified as obese and non-obese. Using STATA these variables were analyzed using test, chi square test followed by conditional logistic regression. ^ Results: On univariate analysis and conditional logistic regression, no significant increase in risk was associated with obesity (OR: 1.24; 95% CI: 0.46 - 3.36; p = 0.67) or BMI (OR: 0.98; CI: 0.92 - 1.04; p = 0.92). Hence, we cannot reject our hypothesis and conclude that "obesity is a risk factor associated with higher incidence of CDI in hospitalized patients. On univariate analysis using hemodialysis, nursing home transfer, home transfer, PPI and chronic antibiotics were found to be significantly different (p<0.05) in the cases and controls. On conditional logistic regression home (OR: 3.4; 95% CI: 1.15 - 9.61) and hemodialysis (OR: 4.1; 95% CI: 1.14 - 15.57) were found to be significantly different (p<0.05) between the case and control groups. ^ Conclusion: Our results show that obesity is not a significant risk factor for CDI. Our sample size was small and hence this may need conformation with a larger study. Patients transferred from home to the hospital and patients on hemodialysis had significantly higher incidence of CDI.^
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This theoretical study analyzes the relation between the measures necessesary for the energy retrofitting of a residential building constructed in Madrid, their cost and the improvement of the energy rating of the dwellings. The aim of this work is to establish an evaluation methodology that allows developers and architects to obtain conclusions and orientates therm in the decisioin-making process. It will allow finding the most suitable cost-effective solutions in each case. This paper describes the methodology and the findings obtained. Energy retrofitting and the improvement of the energy behaviour of the building depend on the selection of the retrofitting solutions and also on the investment. In this case study to achieve the best energy rates it is necessary to improve the thermal performance of the envelope as well as the energy systems. Energy retrofitting means an increase in property value but it can't only be considered in economic terms. It is necessary to take into account unquantifiable aspects as increased comfort, improved sound insulation, livability, health, or the elimination of energy poverty situations.
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En 2004 Basilea II introdujo el modelo basado en calificaciones internas (IRB) para el cómputo del capital mínimo regulatorio por riesgo de crédito. Para los defensores de esta metodología, ello supuso una gran innovación con respecto al Acuerdo de 1988, pero a pesar de su extendida implementación, el modelo regulatorio se enfrenta una serie de problemas insuperables que hacen que la estimación y contraste de sus principales parámetros no sea posible en los términos planteados por la misma regulación. En este artículo se analizará la fuente de las debilidades en la estimación y la dificultad de validación de las probabilidades de incumplimiento y las pérdidas en caso de incumplimiento. Esta metodología permanece inalterada después de la reforma que después de la crisis se concreta en Basilea III.
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Tese de mestrado em Matemática Aplicada à Economia e Gestão, apresentada à Universidade de Lisboa, através da Faculdade de Ciências, 2016
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Thesis (Ph.D.)--University of Washington, 2016-04
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Thesis (Master's)--University of Washington, 2016-06
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The objective was to describe the relationship between epidemiological and biomechanical factors in the causal pathway of inflatable rescue boat (IRB)-related injuries in Australian surf lifesavers; to develop epidemiological and biomechanical methodologies and measurement instruments that identify and measure the risk factors, for use in future epidemiological studies. Epidemiological and biomechanical models of injury causation were combined. Host, agent and environmental factors that influenced total available force for transfer to host were specified. Measurement instruments for each of the specified risk factors were developed. Instruments were piloted in a volunteer sample of surf lifesavers. Participant characteristics were recorded using demographic questionnaires; IRB operating techniques were recorded using a custom-made on-board camera (Grand RF-Guard) and images of operating techniques were coded by two independent observers. Ground reaction forces transmitted to the host through the lifesaver's feet at the time of wave impact were measured using a custom-built piezoelectric force platform. The demographic questionnaire was found practical; the on-board camera functioned successfully within the target environment. Agreement between independent coders of IRB operating technique images was significant (p < 0.001) with Kappa values ranging from 0.5 to 0.7. Biomechanical instruments performed successfully in the target environment. Peak biomechanical forces were 415.6N (left foot) and 252.9N (right foot). This study defines the relationship between epidemiological and biomechanical factors in modifying the risk of IRB-related injury in a population of surf lifesavers. Preliminary feasibility of combining epidemiological and biomechanical information has been demonstrated. Further testing of the proposed model and measurement instruments is required.
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The question of what to provide employees in order that they reciprocate with desirable behaviors in the work place has resulted in a great amount of work in the area of social exchange. Although offering fair compensation, including salary or wages and employee benefits, has been extensively studied, the effects of offering specific types of benefits, such as work-life balance benefits, and the intangible rewards that such an offering inadvertently offers, has only been minimally explored. Utilizing past literature, this current research examined the offering of work-life balance benefits, the value employees place on those benefits, the communication of the benefits by the organization to employees, and their effect on employee attitudes and behaviors. The goal was to identify the effect on desirable outcomes when work-life balance benefits are offered to determine the usefulness to the organization of offering such benefits. To test these effects, a study of an organization known to offer a strong work-life balance benefits package was undertaken. This was accomplished through the distribution of questionnaires to identify the possible relationships involving 408 employee respondents and their 79 supervisors. This was followed with interviews of 12 individuals to ascertain the true reasons for links observed through analysis. Analysis of the data was accomplished through correlation analysis, multilevel analysis and regression analysis generated by SPSS. The results of the quantitative analysis showed support for a relationship between the offering of work-life balance benefits and perceived organizational support, perceived distributive justice, job satisfaction and OCBO. The analysis also showed a lack of support for a relationship between the offering of work-life balance benefits and organizational commitment, OCBI and IRB. The interviews offered possible reasons for the lack of support regarding the relationship between the offering of work-life balance benefits and organizational commitment as well as organizational citizenship behaviors (OCBI and IRB). The implications of these findings on future research, theory and practice in the offering of work-life balance benefits are discussed.
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Bilateral Perisylvian Syndrome (BPS) often presents with epilepsy and significant behavioral impairments that can include mental retardation, dysarthria, delayed speech development, and delayed fine motor development (Graff-Radford et al., 1986 and Kuzniecky et al., 1993). While a small subset of BPS cases have been described as having relatively isolated language delays (Leventer et al., 2010), BPS is not expected in children with dyslexia. As part of a Medical University of South Carolina, IRB approved multi-site study involving retrospective and de-identified dyslexia data, we unexpectedly identified a 14.05 year old male with evidence of BPS whose father had been diagnosed with dyslexia and dysgraphia. This child had been recruited for a neuroimaging study on dyslexia from a school specializing in educating children with dyslexia. The T1-weighted MRI scan from this child demonstrated a highly unusual perisylvian sulcal/gyral patterning that is a defining feature of BPS (Fig. 1). BPS cases exhibit bilateral dysgenesis of the Sylvian fissure and surrounding gyri, which appears to occur because of a limited or absent arcuate fasciculus (Kilinc, Ekinci, Demirkol, & Agan, 2015). This BPS case also had a relatively enlarged atrium of the lateral ventricle that is consistent with the BPS anatomical presentation and reduction of parietal white matter (Graff-Radford et al., 1986, Kilinc et al., 2015 and Toldo et al., 2011).
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This dissertation established a software-hardware integrated design for a multisite data repository in pediatric epilepsy. A total of 16 institutions formed a consortium for this web-based application. This innovative fully operational web application allows users to upload and retrieve information through a unique human-computer graphical interface that is remotely accessible to all users of the consortium. A solution based on a Linux platform with My-SQL and Personal Home Page scripts (PHP) has been selected. Research was conducted to evaluate mechanisms to electronically transfer diverse datasets from different hospitals and collect the clinical data in concert with their related functional magnetic resonance imaging (fMRI). What was unique in the approach considered is that all pertinent clinical information about patients is synthesized with input from clinical experts into 4 different forms, which were: Clinical, fMRI scoring, Image information, and Neuropsychological data entry forms. A first contribution of this dissertation was in proposing an integrated processing platform that was site and scanner independent in order to uniformly process the varied fMRI datasets and to generate comparative brain activation patterns. The data collection from the consortium complied with the IRB requirements and provides all the safeguards for security and confidentiality requirements. An 1-MR1-based software library was used to perform data processing and statistical analysis to obtain the brain activation maps. Lateralization Index (LI) of healthy control (HC) subjects in contrast to localization-related epilepsy (LRE) subjects were evaluated. Over 110 activation maps were generated, and their respective LIs were computed yielding the following groups: (a) strong right lateralization: (HC=0%, LRE=18%), (b) right lateralization: (HC=2%, LRE=10%), (c) bilateral: (HC=20%, LRE=15%), (d) left lateralization: (HC=42%, LRE=26%), e) strong left lateralization: (HC=36%, LRE=31%). Moreover, nonlinear-multidimensional decision functions were used to seek an optimal separation between typical and atypical brain activations on the basis of the demographics as well as the extent and intensity of these brain activations. The intent was not to seek the highest output measures given the inherent overlap of the data, but rather to assess which of the many dimensions were critical in the overall assessment of typical and atypical language activations with the freedom to select any number of dimensions and impose any degree of complexity in the nonlinearity of the decision space.
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According to the American Podiatric Medical Association, about 15 percent of the patients with diabetes would develop a diabetic foot ulcer. Furthermore, foot ulcerations leads to 85 percent of the diabetes-related amputations. Foot ulcers are caused due to a combination of factors, such as lack of feeling in the foot, poor circulation, foot deformities and the duration of the diabetes. To date, the wounds are inspected visually to monitor the wound healing, without any objective imaging approach to look before the wound’s surface. Herein, a non-contact, portable handheld optical device was developed at the Optical Imaging Laboratory as an objective approach to monitor wound healing in foot ulcer. This near-infrared optical technology is non-radiative, safe and fast in imaging large wounds on patients. The FIU IRB-approved study will involve subjects that have been diagnosed with diabetes by a physician and who have developed foot ulcers. Currently, in-vivo imaging studies are carried out every week on diabetic patients with foot ulcers at two clinical sites in Miami. Near-infrared images of the wound are captured on subjects every week and the data is processed using customdeveloped Matlab-based image processing tools. The optical contrast of the wound to its peripheries and the wound size are analyzed and compared from the NIR and white light images during the weekly systematic imaging of wound healing.
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ACKNOWLEDGEMENTS We thank J. M. Valverde (IRB) as well as the NMR facilities of the University of Barcelona (CCiT UB) and the Instituto de Química Física Rocasolano (IQFR, CSIC) for their assistance in, respectively, protein production and NMR. This work was supported by IRB, ICREA (X.S.), Obra Social “la Caixa” (Fellowship to E.D.M. and CancerTec grants to X.S.) MICINN (CTQ2009-08850 to X.S.), MINECO (BIO2012-31043 to X.S.; CTQ2014-56361-P to A.R), Marató de TV3 (102030 to X.S. and 102031 to E.E.P) the COFUND programme of the European Commission (C.T.W.P., A. R. and X.S.), the European Research Council (CONCERT, contract number 648201, to X.S.), the Ramón y Cajal program of MICINN (RYC-2011-07873 to C.W.B.) the Serra Hunter Programme (E.E.P.) and AGAUR (SGR-2014-56RR14 to E.E.P). IRB Barcelona is the recipient of a Severo Ochoa Award of Excellence from MINECO (Government of Spain)
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Abstract
The goal of modern radiotherapy is to precisely deliver a prescribed radiation dose to delineated target volumes that contain a significant amount of tumor cells while sparing the surrounding healthy tissues/organs. Precise delineation of treatment and avoidance volumes is the key for the precision radiation therapy. In recent years, considerable clinical and research efforts have been devoted to integrate MRI into radiotherapy workflow motivated by the superior soft tissue contrast and functional imaging possibility. Dynamic contrast-enhanced MRI (DCE-MRI) is a noninvasive technique that measures properties of tissue microvasculature. Its sensitivity to radiation-induced vascular pharmacokinetic (PK) changes has been preliminary demonstrated. In spite of its great potential, two major challenges have limited DCE-MRI’s clinical application in radiotherapy assessment: the technical limitations of accurate DCE-MRI imaging implementation and the need of novel DCE-MRI data analysis methods for richer functional heterogeneity information.
This study aims at improving current DCE-MRI techniques and developing new DCE-MRI analysis methods for particular radiotherapy assessment. Thus, the study is naturally divided into two parts. The first part focuses on DCE-MRI temporal resolution as one of the key DCE-MRI technical factors, and some improvements regarding DCE-MRI temporal resolution are proposed; the second part explores the potential value of image heterogeneity analysis and multiple PK model combination for therapeutic response assessment, and several novel DCE-MRI data analysis methods are developed.
I. Improvement of DCE-MRI temporal resolution. First, the feasibility of improving DCE-MRI temporal resolution via image undersampling was studied. Specifically, a novel MR image iterative reconstruction algorithm was studied for DCE-MRI reconstruction. This algorithm was built on the recently developed compress sensing (CS) theory. By utilizing a limited k-space acquisition with shorter imaging time, images can be reconstructed in an iterative fashion under the regularization of a newly proposed total generalized variation (TGV) penalty term. In the retrospective study of brain radiosurgery patient DCE-MRI scans under IRB-approval, the clinically obtained image data was selected as reference data, and the simulated accelerated k-space acquisition was generated via undersampling the reference image full k-space with designed sampling grids. Two undersampling strategies were proposed: 1) a radial multi-ray grid with a special angular distribution was adopted to sample each slice of the full k-space; 2) a Cartesian random sampling grid series with spatiotemporal constraints from adjacent frames was adopted to sample the dynamic k-space series at a slice location. Two sets of PK parameters’ maps were generated from the undersampled data and from the fully-sampled data, respectively. Multiple quantitative measurements and statistical studies were performed to evaluate the accuracy of PK maps generated from the undersampled data in reference to the PK maps generated from the fully-sampled data. Results showed that at a simulated acceleration factor of four, PK maps could be faithfully calculated from the DCE images that were reconstructed using undersampled data, and no statistically significant differences were found between the regional PK mean values from undersampled and fully-sampled data sets. DCE-MRI acceleration using the investigated image reconstruction method has been suggested as feasible and promising.
Second, for high temporal resolution DCE-MRI, a new PK model fitting method was developed to solve PK parameters for better calculation accuracy and efficiency. This method is based on a derivative-based deformation of the commonly used Tofts PK model, which is presented as an integrative expression. This method also includes an advanced Kolmogorov-Zurbenko (KZ) filter to remove the potential noise effect in data and solve the PK parameter as a linear problem in matrix format. In the computer simulation study, PK parameters representing typical intracranial values were selected as references to simulated DCE-MRI data for different temporal resolution and different data noise level. Results showed that at both high temporal resolutions (<1s) and clinically feasible temporal resolution (~5s), this new method was able to calculate PK parameters more accurate than the current calculation methods at clinically relevant noise levels; at high temporal resolutions, the calculation efficiency of this new method was superior to current methods in an order of 102. In a retrospective of clinical brain DCE-MRI scans, the PK maps derived from the proposed method were comparable with the results from current methods. Based on these results, it can be concluded that this new method can be used for accurate and efficient PK model fitting for high temporal resolution DCE-MRI.
II. Development of DCE-MRI analysis methods for therapeutic response assessment. This part aims at methodology developments in two approaches. The first one is to develop model-free analysis method for DCE-MRI functional heterogeneity evaluation. This approach is inspired by the rationale that radiotherapy-induced functional change could be heterogeneous across the treatment area. The first effort was spent on a translational investigation of classic fractal dimension theory for DCE-MRI therapeutic response assessment. In a small-animal anti-angiogenesis drug therapy experiment, the randomly assigned treatment/control groups received multiple fraction treatments with one pre-treatment and multiple post-treatment high spatiotemporal DCE-MRI scans. In the post-treatment scan two weeks after the start, the investigated Rényi dimensions of the classic PK rate constant map demonstrated significant differences between the treatment and the control groups; when Rényi dimensions were adopted for treatment/control group classification, the achieved accuracy was higher than the accuracy from using conventional PK parameter statistics. Following this pilot work, two novel texture analysis methods were proposed. First, a new technique called Gray Level Local Power Matrix (GLLPM) was developed. It intends to solve the lack of temporal information and poor calculation efficiency of the commonly used Gray Level Co-Occurrence Matrix (GLCOM) techniques. In the same small animal experiment, the dynamic curves of Haralick texture features derived from the GLLPM had an overall better performance than the corresponding curves derived from current GLCOM techniques in treatment/control separation and classification. The second developed method is dynamic Fractal Signature Dissimilarity (FSD) analysis. Inspired by the classic fractal dimension theory, this method measures the dynamics of tumor heterogeneity during the contrast agent uptake in a quantitative fashion on DCE images. In the small animal experiment mentioned before, the selected parameters from dynamic FSD analysis showed significant differences between treatment/control groups as early as after 1 treatment fraction; in contrast, metrics from conventional PK analysis showed significant differences only after 3 treatment fractions. When using dynamic FSD parameters, the treatment/control group classification after 1st treatment fraction was improved than using conventional PK statistics. These results suggest the promising application of this novel method for capturing early therapeutic response.
The second approach of developing novel DCE-MRI methods is to combine PK information from multiple PK models. Currently, the classic Tofts model or its alternative version has been widely adopted for DCE-MRI analysis as a gold-standard approach for therapeutic response assessment. Previously, a shutter-speed (SS) model was proposed to incorporate transcytolemmal water exchange effect into contrast agent concentration quantification. In spite of richer biological assumption, its application in therapeutic response assessment is limited. It might be intriguing to combine the information from the SS model and from the classic Tofts model to explore potential new biological information for treatment assessment. The feasibility of this idea was investigated in the same small animal experiment. The SS model was compared against the Tofts model for therapeutic response assessment using PK parameter regional mean value comparison. Based on the modeled transcytolemmal water exchange rate, a biological subvolume was proposed and was automatically identified using histogram analysis. Within the biological subvolume, the PK rate constant derived from the SS model were proved to be superior to the one from Tofts model in treatment/control separation and classification. Furthermore, novel biomarkers were designed to integrate PK rate constants from these two models. When being evaluated in the biological subvolume, this biomarker was able to reflect significant treatment/control difference in both post-treatment evaluation. These results confirm the potential value of SS model as well as its combination with Tofts model for therapeutic response assessment.
In summary, this study addressed two problems of DCE-MRI application in radiotherapy assessment. In the first part, a method of accelerating DCE-MRI acquisition for better temporal resolution was investigated, and a novel PK model fitting algorithm was proposed for high temporal resolution DCE-MRI. In the second part, two model-free texture analysis methods and a multiple-model analysis method were developed for DCE-MRI therapeutic response assessment. The presented works could benefit the future DCE-MRI routine clinical application in radiotherapy assessment.
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Radiotherapy is commonly used to treat lung cancer. However, radiation induced damage to lung tissue is a major limiting factor to its use. To minimize normal tissue lung toxicity from conformal radiotherapy treatment planning, we investigated the use of Perfluoropropane(PFP)-enhanced MR imaging to assess and guide the sparing of functioning lung. Fluorine Enhanced MRI using Perfluoropropane(PFP) is a dynamic multi-breath steady state technique enabling quantitative and qualitative assessments of lung function(1).
Imaging data was obtained from studies previously acquired in the Duke Image Analysis Laboratory. All studies were approved by the Duke IRB. The data was de-identified for this project, which was also approved by the Duke IRB. Subjects performed several breath-holds at total lung capacity(TLC) interspersed with multiple tidal breaths(TB) of Perfluoropropane(PFP)/oxygen mixture. Additive wash-in intensity images were created through the summation of the wash-in phase breath-holds. Additionally, model based fitting was utilized to create parametric images of lung function(1).
Varian Eclipse treatment planning software was used for putative treatment planning. For each subject two plans were made, a standard plan, with no regional functional lung information considered other than current standard models. Another was created using functional information to spare functional lung while maintaining dose to the target lesion. Plans were optimized to a prescription dose of 60 Gy to the target over the course of 30 fractions.
A decrease in dose to functioning lung was observed when utilizing this functional information compared to the standard plan for all five subjects. PFP-enhanced MR imaging is a feasible method to assess ventilatory lung function and we have shown how this can be incorporated into treatment planning to potentially decrease the dose to normal tissue.
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Purpose – The purpose of this empirical paper is to investigate internal marketing from a behavioural perspective. The impact of internal marketing behaviours, operationalised as an internal market orientation (IMO), on employees' marketing and other in/role behaviours (IRB) were examined. Design/methodology/approach – Survey data measuring IMO, market orientation and a range of constructs relevant to the nomological network in which they are embedded were collected from the UK retail managers. These were tested to establish their psychometric properties and the conceptual model was analysed using structural equations modelling, employing a partial least squares methodology. Findings – IMO has positive consequences for employees' market/oriented and other IRB. These, in turn, influence marketing success. Research limitations/implications – The paper provides empirical support for the long/held assumption that internal and external marketing are related and that organisations should balance their external focus with some attention to employees. Future research could measure the attitudes and behaviours of managers, employees and customers directly and explore the relationships between them. Practical implications – Firm must ensure that they do not put the needs of their employees second to those of managers and shareholders; managers must develop their listening skills and organisations must become more responsive to the needs of their employees. Originality/value – The paper contributes to the scarce body of empirical support for the role of internal marketing in services organisations. For researchers, this paper legitimises the study of internal marketing as a route to external market success; for managers, the study provides quantifiable evidence that focusing on employees' wants and needs impacts their behaviours towards the market. © 2010, Emerald Group Publishing Limited