933 resultados para Diet self-selection
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Positive selection (PS) in the thymus involves the presentation of self-peptides that are bound to MHC class II on the surface of cortical thymus epithelial cells (cTECs). Prss16 gene corresponds to one important element regulating the PS of CD4(+) T lymphocytes, which encodes Thymus-specific serine protease (Tssp), a cTEC serine-type peptidase involved in the proteolytic generation of self-peptides. Nevertheless, additional peptidase genes participating in the generation of self-peptides need to be found. Because of its role in the mechanism of PS and its expression in cTECs, the Prss16 gene might be used as a transcriptional marker to identify new genes that share the same expression profile and that encode peptidases in the thymus. To test this hypothesis, we compared the differential thymic expression of 4,500 mRNAs of wild-type (WT) C57BL/6 mice with their respective Prss16-knockout (KO) mutants by using microarrays. From these, 223 genes were differentially expressed, of which 115 had known molecular/biological functions. Four endopeptidase genes (Casp1, Casp2, Psmb3 and Tpp2) share the same expression profile as the Prss16 gene; i.e., induced in WT and repressed in KO while one endopeptidase gene, Capns1, features opposite expression profile. The Tpp2 gene is highlighted because it encodes a serine-type endopeptidase functionally similar to the Tssp enzyme. Profiling of the KO mice featured down-regulation of Prss16, as expected, along with the genes mentioned above. Considering that the Prss16-KO mice featured impaired PS, the shared regulation of the four endopeptidase genes suggested their participation in the mechanism of self-peptide generation and PS.
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This study aimed to evaluate the relationship between the cost and energy density of diet consumed in Brazilian households. Data from the Brazilian Household Budget Survey (POF 200812009) were used to identify the main foods and their prices. Similar items were grouped, resulting in a basket of 67 products. Linear programming was applied for the composition of isoenergetic baskets, minimizing the deviation from the average household diet. Restrictions were imposed on the inclusion of items and the energy contribution of the various food groups. A reduction in average cost of diet was applied at intervals of R$0.15 to the lowest possible cost. We identified an inverse association between energy density and cost of diet (p < 0.05), and at the lowest possible cost we obtained the maximum value of energy density Restrictions on the diet's cost resulted in the selection of diets with higher energy density, indicating that cost of diet may lead to the adoption of inadequate diets in Brazil.
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Background: Duodenal stenting has become a broadly accepted first line of treatment for patients with advanced malignant gastroduodenal obstruction as these patients are difficult to treat and are poor surgical candidates. Aims: To document duodenal stent performance for palliative management of malignant gastroduodenal obstruction. Methods: Multicentre, single arm, prospective registry documenting peroral endoscopic duodenal stenting procedures in 202 patients. Results: Technical success achieved in 98% (CI. 95%, 99%) of stent placements. Increase of Gastric Outlet Obstruction Score by at least 1 point compared to baseline was achieved in 91% (CI, 86%, 95%) of patients persisting for a median of 184 days (CI, 109, 266). By day 5 (CI, 4,6) after stent placement, 50% of patients experienced a score increase of at least 1 point. Improvement from 14% of patients at baseline tolerating soft solids or low residue/normal diet to 84% at 15 days, 86% at 30 days, 81% at 90 days, 79% at 180 days, and 70% at 270 days. Complications included stent ingrowth and/or overgrowth (12.4%), transient periprocedural symptoms (3%), bleeding (3%), stent migration (1.5%), and perforation (0.5%). Conclusions: Safety and effectiveness of duodenal stenting for palliation of malignant gastroduodenal obstruction was confirmed in the largest international prospective series to date. (C) 2011 Editrice Gastroenterologica Italiana S.r.l. Published by Elsevier Ltd. All rights reserved.
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In this work, two different systems were investigated to develop fundamental understanding of the self-assembly behavior of polyelectrolytes and small organic counterions with a certain geometry. Complexes formed were characterized by light scattering in solution, as well as UV-Vis spectroscopy, analytical ultracentrifugation, gel electrophoresis, zeta potential and IR spectroscopy. The morphologies of the aggregates were observed by AFM in dried state on surface. The charge ratio, the valence and the structure of the counterion were shown to represent key parameters in the complexation. The influence of polyelectrolyte type and molecular weights was also determined for the structure formed.rnrnOne system was mainly focused on the association of double-strand DNA with non-intercalating divalent and tetravalent organic counterions. The other model system involved linear NaPSS and oligolysines. In addition, various influences on the morphology of the charged self-assembly complexes in AFM studies were discussed. It was shown that electrostatic self-assembly of DNA and non-intercalating counterions as well as of a linear synthetic polyelectrolyte with oligolysine counterions that can build mutual hydrogen bonds can yield supramolecular aggregates of a defined size. Various morphologies (flower-like, rod-like, toroidal and spherical) of the assemblies were obtained for different combinations of polyelectrolyte and counterions. Results presented in this work are of importance for the fundamental understanding of the association behavior of various polyelectrolytes and organic counterions. The selection of biopolymers for the study may give an opportunity to transfer the basic research results into biological applications, such as gene therapy or drug delivery.rn
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Whether the use of mobile phones is a risk factor for brain tumors in adolescents is currently being studied. Case--control studies investigating this possible relationship are prone to recall error and selection bias. We assessed the potential impact of random and systematic recall error and selection bias on odds ratios (ORs) by performing simulations based on real data from an ongoing case--control study of mobile phones and brain tumor risk in children and adolescents (CEFALO study). Simulations were conducted for two mobile phone exposure categories: regular and heavy use. Our choice of levels of recall error was guided by a validation study that compared objective network operator data with the self-reported amount of mobile phone use in CEFALO. In our validation study, cases overestimated their number of calls by 9% on average and controls by 34%. Cases also overestimated their duration of calls by 52% on average and controls by 163%. The participation rates in CEFALO were 83% for cases and 71% for controls. In a variety of scenarios, the combined impact of recall error and selection bias on the estimated ORs was complex. These simulations are useful for the interpretation of previous case-control studies on brain tumor and mobile phone use in adults as well as for the interpretation of future studies on adolescents.
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The present research was conducted in two studies. The first study examined how mating intelligence, self-esteem, and self-perceived attractiveness are related to each other. The second study examined how these three constructs relate to partner choice. It was hypothesized that participants who score high on mating intelligence will also score high on self-esteem and self-perceived attractiveness. Furthermore, those that score high on self-esteem will also score high on self-perceived attractiveness. It was expected that the results would be more significant for women than for men. For the second study, it was hypothesized that participants who score high on all three constructs will be more likely to select the attractive partner. The results did not show a significant interaction between mating intelligence, self-esteem, and self-perceived attractiveness. They also did not indicate higher significance levels for women. However, there were significant effects between the constructs. Additionally, participants with an average or a high score on mating intelligence were more likely to select the attractive partner.
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PURPOSE: Glioblastomas are notorious for resistance to therapy, which has been attributed to DNA-repair proficiency, a multitude of deregulated molecular pathways, and, more recently, to the particular biologic behavior of tumor stem-like cells. Here, we aimed to identify molecular profiles specific for treatment resistance to the current standard of care of concomitant chemoradiotherapy with the alkylating agent temozolomide. PATIENTS AND METHODS: Gene expression profiles of 80 glioblastomas were interrogated for associations with resistance to therapy. Patients were treated within clinical trials testing the addition of concomitant and adjuvant temozolomide to radiotherapy. RESULTS: An expression signature dominated by HOX genes, which comprises Prominin-1 (CD133), emerged as a predictor for poor survival in patients treated with concomitant chemoradiotherapy (n = 42; hazard ratio = 2.69; 95% CI, 1.38 to 5.26; P = .004). This association could be validated in an independent data set. Provocatively, the HOX cluster was reminiscent of a "self-renewal" signature (P = .008; Gene Set Enrichment Analysis) recently characterized in a mouse leukemia model. The HOX signature and EGFR expression were independent prognostic factors in multivariate analysis, adjusted for the O-6-methylguanine-DNA methyltransferase (MGMT) methylation status, a known predictive factor for benefit from temozolomide, and age. Better outcome was associated with gene clusters characterizing features of tumor-host interaction including tumor vascularization and cell adhesion, and innate immune response. CONCLUSION: This study provides first clinical evidence for the implication of a "glioma stem cell" or "self-renewal" phenotype in treatment resistance of glioblastoma. Biologic mechanisms identified here to be relevant for resistance will guide future targeted therapies and respective marker development for individualized treatment and patient selection.
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In this paper we examined whether defenders of victims of school bullying befriended similar peers, and whether the similarity is due to selection or influence processes or both. We examined whether these processes result in different degrees of similarity between peers depending on teachers’ self-efficacy and the school climate. We analyzed longitudinal data of 478 Swiss school students employing actor-based stochastic models. Our analyses showed that similarity in defending behavior among friends was due to selection rather than influence. The extent to which adolescents selected peers showing similar defending behavior was related to contextual factors. In fact, lower self-efficacy of teachers and positive school climate were associated with increased selection effects in terms of defending behavior.
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BACKGROUND: Most theories of health-behavior change focus exclusively on individual self-regulation without taking social factors, such as social support, into account. This study's first aim was to systematically test the added value of received instrumental and emotional social support within the Health Action Process Approach (HAPA) in the context of dietary change. In the social support literature, gender effects emerge with regard to the effectiveness of social support. Thus, a second aim was the examination of gender differences in the association of social support with dietary behavior. METHODS: Participants were 252 overweight and obese individuals. At baseline and 12 months later, participants completed questionnaires on HAPA variables; diet-specific received social support and low-fat diet. RESULTS: For the prediction of intentions 12 months later, instrumental support was more beneficial for men than for women over and above individual self-regulation. In terms of dietary behavior at T2, a moderate main effect of instrumental support emerged. Moreover, received emotional social support was beneficial for men, but not for women in terms of a low-fat diet 12 months later. CONCLUSIONS: Effects of received instrumental social support found in this study provide new evidence for the added value of integrating social support into the HAPA.
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Doing something moral gives one a license to do something immoral. This form of moral compen-sation is called “moral self-licensing”. Interestingly, the moral behavior can take place in another domain than the subsequent immoral behavior. For example, buying eco-friendly products gives one a license to steal. This article is based on the idea that a healthy diet has a moral dimension. As a consequence, consuming a healthy product should give one a license for immoral behavior. This research supports this hypothesis on a playful study. This study shows that drinking sauerkraut juice contributes to a stronger support of Nazi-esque right wing ideology than drinking either nothing or a less-healthy beverage (Nestea).
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Background: Diabetes mellitus is spreading throughout the world and diabetic individuals have been shown to often assess their food intake inaccurately; therefore, it is a matter of urgency to develop automated diet assessment tools. The recent availability of mobile phones with enhanced capabilities, together with the advances in computer vision, have permitted the development of image analysis apps for the automated assessment of meals. GoCARB is a mobile phone-based system designed to support individuals with type 1 diabetes during daily carbohydrate estimation. In a typical scenario, the user places a reference card next to the dish and acquires two images using a mobile phone. A series of computer vision modules detect the plate and automatically segment and recognize the different food items, while their 3D shape is reconstructed. Finally, the carbohydrate content is calculated by combining the volume of each food item with the nutritional information provided by the USDA Nutrient Database for Standard Reference. Objective: The main objective of this study is to assess the accuracy of the GoCARB prototype when used by individuals with type 1 diabetes and to compare it to their own performance in carbohydrate counting. In addition, the user experience and usability of the system is evaluated by questionnaires. Methods: The study was conducted at the Bern University Hospital, “Inselspital” (Bern, Switzerland) and involved 19 adult volunteers with type 1 diabetes, each participating once. Each study day, a total of six meals of broad diversity were taken from the hospital’s restaurant and presented to the participants. The food items were weighed on a standard balance and the true amount of carbohydrate was calculated from the USDA nutrient database. Participants were asked to count the carbohydrate content of each meal independently and then by using GoCARB. At the end of each session, a questionnaire was completed to assess the user’s experience with GoCARB. Results: The mean absolute error was 27.89 (SD 38.20) grams of carbohydrate for the estimation of participants, whereas the corresponding value for the GoCARB system was 12.28 (SD 9.56) grams of carbohydrate, which was a significantly better performance ( P=.001). In 75.4% (86/114) of the meals, the GoCARB automatic segmentation was successful and 85.1% (291/342) of individual food items were successfully recognized. Most participants found GoCARB easy to use. Conclusions: This study indicates that the system is able to estimate, on average, the carbohydrate content of meals with higher accuracy than individuals with type 1 diabetes can. The participants thought the app was useful and easy to use. GoCARB seems to be a well-accepted supportive mHealth tool for the assessment of served-on-a-plate meals.
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Purpose. To determine if self-efficacy (SE) changes predicted total fat (TF) and total fiber (TFB) intake and the relationship between SE changes and the two dietary outcomes. ^ Design. This is a secondary analysis, utilizing baseline and first follow up (FFU) data from the NULIFE, a randomized trial. ^ Setting. Nutrition classes were taught in the Texas Medical Center in Houston, Texas. ^ Participants. 79 pre-menopausal, 25--45 year old African American women with an 85% response rate at FFU. ^ Method. Dietary intake was assessed with the Arizona Food Frequency Questionnaire and SE with the Self Efficacy for Dietary Change Questionnaire. Analysis was done using Stata version 9. Linear and logistic regression was used with adjustment for confounders. ^ Results. Linear regression analyses showed that SE changes for eating fruits and vegetables predicted total fiber intake in the control group for both the univariate (P = 0.001) and multivariate (P = 0.01) models while SE for eating fruits and vegetables at first follow-up predicted total fiber intake in the intervention for both models (P = 0.000). Logistic regression analyses of low fat SE changes and 30% or less for total fat intake, showed an adjusted OR of 0.22 (95% CI = 0.03, 1.48; P = 0.12) in the intervention group. The logistic regression analyses of SE changes in fruits and vegetables and 10g or more for total fiber intake, showed an adjusted OR of 6.25 (95% CI = 0.53, 72.78; P = 0.14) in the control group. ^ Conclusion. SE for eating fruits and vegetables at first follow-up predicted intervention groups' TFB intake and intervention women that increased their SE for eating a low fat diet were more likely to achieve the study goal of 30% or less calories from TF. SE changes for eating fruits and vegetables predicted the control's TFB intake and control women that increased their SE for eating fruits and vegetables were more likely to achieve the study goal of 10 g or more from TFB. Limitations are use of self-report measures, small sample size, and possible control group contamination.^
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The Self-OrganizingMap (SOM) is a neural network model that performs an ordered projection of a high dimensional input space in a low-dimensional topological structure. The process in which such mapping is formed is defined by the SOM algorithm, which is a competitive, unsupervised and nonparametric method, since it does not make any assumption about the input data distribution. The feature maps provided by this algorithm have been successfully applied for vector quantization, clustering and high dimensional data visualization processes. However, the initialization of the network topology and the selection of the SOM training parameters are two difficult tasks caused by the unknown distribution of the input signals. A misconfiguration of these parameters can generate a feature map of low-quality, so it is necessary to have some measure of the degree of adaptation of the SOM network to the input data model. The topologypreservation is the most common concept used to implement this measure. Several qualitative and quantitative methods have been proposed for measuring the degree of SOM topologypreservation, particularly using Kohonen's model. In this work, two methods for measuring the topologypreservation of the Growing Cell Structures (GCSs) model are proposed: the topographic function and the topology preserving map
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— In 2000, according to the World Health Organization, at least 171 million people, 2.8% of the population worldwide, suffered from diabetes. The Centres for Disease Control has defined it as an epidemic disease. Its incidence is increasing rapidly, and it is estimated that by 2030 this number will almost double. Diabetes mellitus occurs throughout the world, but is more common (especially type 2) in the more developed countries. Diabetes is a chronic condition that occurs when pancreas does not assure enough insulin secretion or when the body does not consume the insulin produced. Insulin is a hormone that regulates blood sugar. The effect of uncontrolled diabetes is the hyperglycaemia (blood sugar), which eventually seriously damage many organs and systems, especially the nerves and blood vessels. Diabetes type 2 (most common type of diabetes) is highly correlated with elderly people, obesity or overweight. Promoting a healthy lifestyle helps patients to improve their quality of life and in many cases to avoid complications related to the disease. This paper is intended to describe an iPhone-based application for self-management of type 2 diabetic patients, which allow them improving their lifestyle through healthy diet, physical activity and education
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In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.