991 resultados para value-mapping
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OER-based learning has the potential to overcome many shortcomings and problems of traditional education. It is not hampered by IP restrictions; can depend on collaborative, cumulative, iterative refinement of resources; and the digital form provides unprecedented flexibility with respect to configuration and delivery. The OER community is a progressive group of educators and learners with decades of learning research to draw from, who know that we must prepare learners for an evolving and diverse reality. Despite this OER tends to replicate the unsuccessful characteristics of traditional education. To remedy this we may need to remember the importance of imperfection, mistakes, problems, disagreement, and the incomplete for engaged learning, and relinquish our notions of perfection, acknowledging that learners learn differently and we need diverse learners. We must stretch our perceptions of quality and provide mechanisms for engaging the incredible pool of educators globally to fulfill the promise of inclusive education.
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OBJECTIVE: To explore the potential of deep HIV-1 sequencing for adding clinically relevant information relative to viral population sequencing in heavily pre-treated HIV-1-infected subjects. METHODS: In a proof-of-concept study, deep sequencing was compared to population sequencing in HIV-1-infected individuals with previous triple-class virological failure who also developed virologic failure to deep salvage therapy including, at least, darunavir, tipranavir, etravirine or raltegravir. Viral susceptibility was inferred before salvage therapy initiation and at virological failure using deep and population sequencing genotypes interpreted with the HIVdb, Rega and ANRS algorithms. The threshold level for mutant detection with deep sequencing was 1%. RESULTS: 7 subjects with previous exposure to a median of 15 antiretrovirals during a median of 13 years were included. Deep salvage therapy included darunavir, tipranavir, etravirine or raltegravir in 4, 2, 2 and 5 subjects, respectively. Self-reported treatment adherence was adequate in 4 and partial in 2; one individual underwent treatment interruption during follow-up. Deep sequencing detected all mutations found by population sequencing and identified additional resistance mutations in all but one individual, predominantly after virological failure to deep salvage therapy. Additional genotypic information led to consistent decreases in predicted susceptibility to etravirine, efavirenz, nucleoside reverse transcriptase inhibitors and indinavir in 2, 1, 2 and 1 subject, respectively. Deep sequencing data did not consistently modify the susceptibility predictions achieved with population sequencing for darunavir, tipranavir or raltegravir. CONCLUSIONS: In this subset of heavily pre-treated individuals, deep sequencing improved the assessment of genotypic resistance to etravirine, but did not consistently provide additional information on darunavir, tipranavir or raltegravir susceptibility. These data may inform the design of future studies addressing the clinical value of minority drug-resistant variants in treatment-experienced subjects.
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Background: We aim to investigate the possibility of using 18F-positron emission tomography/computer tomography (PET-CT) to predict the histopathologic response in locally advanced rectal cancer (LARC) treated with preoperative chemoradiation (CRT). Methods: The study included 50 patients with LARC treated with preoperative CRT. All patients were evaluated by PET-CT before and after CRT, and results were compared to histopathologic response quantified by tumour regression grade (patients with TRG 1-2 being defined as responders and patients with grade 3-5 as non-responders). Furthermore, the predictive value of metabolic imaging for pathologic complete response (ypCR) was investigated. Results: Responders and non-responders showed statistically significant differences according to Mandard's criteria for maximum standardized uptake value (SUVmax) before and after CRT with a specificity of 76,6% and a positive predictive value of 66,7%. Furthermore, SUVmax values after CRT were able to differentiate patients with ypCR with a sensitivity of 63% and a specificity of 74,4% (positive predictive value 41,2% and negative predictive value 87,9%); This rather low sensitivity and specificity determined that PET-CT was only able to distinguish 7 cases of ypCR from a total of 11 patients. Conclusions: We conclude that 18-F PET-CT performed five to seven weeks after the end of CRT can visualise functional tumour response in LARC. In contrast, metabolic imaging with 18-F PET-CT is not able to predict patients with ypCR accurately
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One major goal of research on Chagas disease is the development of effective chemotherapy to eliminate the infection from individuals who have not yet developed cardiac and/or digestive disease manifestations. Cure evaluation is the more complex aspect of its treatment, often leading to diverse and controversial results. The absence of reliable methods or a diagnostic gold standard to assess etiologic treatment efficacy still constitutes a major challenge. In an effort to develop more sensitive tools, polymerase chain reaction (PCR)-based assays were introduced to detect low amounts of Trypanosoma cruzi DNA in blood samples from chagasic patients, thus improving the diagnosis and follow-up evaluation after chemotherapy. In this article, I review the main problems concerning drug efficacy and criteria used for cure estimation in treated chagasic patients, and the work conducted by different groups on developing PCR methodologies to monitor treatment outcome of congenital infections as well as recent and late chronic T. cruzi infections.
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This paper proposes a high-level reinforcement learning (RL) control system for solving the action selection problem of an autonomous robot. Although the dominant approach, when using RL, has been to apply value function based algorithms, the system here detailed is characterized by the use of direct policy search methods. Rather than approximating a value function, these methodologies approximate a policy using an independent function approximator with its own parameters, trying to maximize the future expected reward. The policy based algorithm presented in this paper is used for learning the internal state/action mapping of a behavior. In this preliminary work, we demonstrate its feasibility with simulated experiments using the underwater robot GARBI in a target reaching task
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MRI visualization of devices is traditionally based on signal loss due to T(2)* effects originating from local susceptibility differences. To visualize nitinol devices with positive contrast, a recently introduced postprocessing method is adapted to map the induced susceptibility gradients. This method operates on regular gradient-echo MR images and maps the shift in k-space in a (small) neighborhood of every voxel by Fourier analysis followed by a center-of-mass calculation. The quantitative map of the local shifts generates the positive contrast image of the devices, while areas without susceptibility gradients render a background with noise only. The positive signal response of this method depends only on the choice of the voxel neighborhood size. The properties of the method are explained and the visualizations of a nitinol wire and two stents are shown for illustration.
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This paper presents a complete solution for creating accurate 3D textured models from monocular video sequences. The methods are developed within the framework of sequential structure from motion, where a 3D model of the environment is maintained and updated as new visual information becomes available. The camera position is recovered by directly associating the 3D scene model with local image observations. Compared to standard structure from motion techniques, this approach decreases the error accumulation while increasing the robustness to scene occlusions and feature association failures. The obtained 3D information is used to generate high quality, composite visual maps of the scene (mosaics). The visual maps are used to create texture-mapped, realistic views of the scene
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Schistosomiasis mansoni is not just a physical disease, but is related to social and behavioural factors as well. Snails of the Biomphalaria genus are an intermediate host for Schistosoma mansoni and infect humans through water. The objective of this study is to classify the risk of schistosomiasis in the state of Minas Gerais (MG). We focus on socioeconomic and demographic features, basic sanitation features, the presence of accumulated water bodies, dense vegetation in the summer and winter seasons and related terrain characteristics. We draw on the decision tree approach to infection risk modelling and mapping. The model robustness was properly verified. The main variables that were selected by the procedure included the terrain's water accumulation capacity, temperature extremes and the Human Development Index. In addition, the model was used to generate two maps, one that included risk classification for the entire of MG and another that included classification errors. The resulting map was 62.9% accurate.
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Bronchoalveolar lavage (BAL) is a minimally invasive procedure used to characterize the status of the alveolar space. Standardization of the procedure and the analysis of samples taken is essential for their proper interpretation. In nonresolving or ventilator-associated pneumonia, BAL contributes to the detection of resistant pathogens and noninfectious etiologies. In immunocompromised hosts with radiological infiltrates, BAL should be performed early during work-up since outcome is significantly modified in this population group. In cases of interstitial lung disease, BAL can exclude infectious or neoplastic causes. Associated with a clinical and radiological evaluation, it provides valuables additional diagnostic information.
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BACKGROUND Ovarian carcinoma is the most important cause of gynecological cancer-related mortality in Western societies. Despite the improved median overall survival in patients receiving chemotherapy regimens such as paclitaxel and carboplatin combination, relapse still occurs in most advanced diseased patients. Increased angiogenesis is associated with rapid recurrence and decreased survival in ovarian cancer. This study was planned to identify an angiogenesis-related gene expression profile with prognostic value in advanced ovarian carcinoma patients. METHODOLOGY/PRINCIPAL FINDINGS RNAs were collected from formalin-fixed paraffin-embedded samples of 61 patients with III/IV FIGO stage ovarian cancer who underwent surgical cytoreduction and received a carboplatin plus paclitaxel regimen. Expression levels of 82 angiogenesis related genes were measured by quantitative real-time polymerase chain reaction using TaqMan low-density arrays. A 34-gene-profile which was able to predict the overall survival of ovarian carcinoma patients was identified. After a leave-one-out cross validation, the profile distinguished two groups of patients with different outcomes. Median overall survival and progression-free survival for the high risk group was 28.3 and 15.0 months, respectively, and was not reached by patients in the low risk group at the end of follow-up. Moreover, the profile maintained an independent prognostic value in the multivariate analysis. The hazard ratio for death was 2.3 (95% CI, 1.5 to 3.2; p<0.001). CONCLUSIONS/SIGNIFICANCE It is possible to generate a prognostic model for advanced ovarian carcinoma based on angiogenesis-related genes using formalin-fixed paraffin-embedded samples. The present results are consistent with the increasing weight of angiogenesis genes in the prognosis of ovarian carcinoma.
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Contexte : Les patients souffrant d'un épisode dépressif sévère sont fréquemment traités par des inhibiteurs sélectifs de la recapture de la sérotonine (SSRI). Cependant, seulement 30-50% des patients répondront à ce type de traitement. Actuellement, il n'existe pas de marqueur biologique utilisable pour prédire la réponse à un traitement par SSRI. Un délai dans la mise en place d'une thérapie efficace peut avoir comme conséquences néfastes une augmentation du risque de suicide et une association avec un moins bon pronostic à long terme lors d'épisodes ultérieurs. Objectif : Par l'étude du métabolisme cérébral par tomographie par émission de positons (PET) au F-18-fluorodeoxyglucose (FDG), nous étudierons la présence de corrélations éventuelles entre la réponse clinique, qui généralement survient dans les 4 à 6 semaines après l'instauration du traitement antidépresseur, et une modification du métabolisme cérébral mesuré plus précocement, dans le but d'identifier les futurs répondeurs au traitement par SSRI. Méthodes : Cette étude longitudinale comprendra 20 patients unipolaires avec un épisode dépressif sévère au bénéfice d'un traitement par SSRI. Chacun des patients aura deux examens PET cérébraux au F-18-FDG. Le premier PET aura lieu juste avant le début du traitement aux SSRI et le second dans la 3ème semaine après début du traitement. La réponse clinique sera mesurée à 3 mois, et les répondeurs seront identifiés par une diminution significative des scores lors d'évaluation sur échelles de dépression. La recherche d'altérations métaboliques cérébrales sera faite en évaluant: (1) l'examen de base ou (2) l'examen PET précoce, à la recherche d'altérations spécifiques corrélées à une bonne réponse clinique, afin d'obtenir une valeur pronostique quant à la réponse au traitement. L'analyse de l'imagerie cérébrale utilisera la technique SPM (Statistical Parameter Mapping) impliquant un traitement numérique voxel par voxel des images PET. Résultats escomptés : Cette étude caractérisant les variations du métabolisme cérébral dans la phase précoce d'un traitement par SSRI vise à identifier des marqueurs métaboliques potentiels fournissant une valeur prédictive quant à la future efficacité du traitement SSRI introduit. Plus-value escomptée : L'identification d'un tel marqueur métabolique permettrait d'identifier rapidement les futurs répondeurs aux SSRI, et par conséquent d'éviter de proposer aux non-répondeurs la poursuite d'une médication, pendant plusieurs semaines, qui aurait peu de chance d'être efficace. Ainsi, une identification précoce des répondeurs aux SSRI pourrait permettre d'éviter des délais dans la mise en place d'une thérapie efficace et d'obtenir une amélioration du pronostic à plus long terme, avec une influence favorable sur les coûts de la santé.
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BACKGROUND: The ASTRAL score was recently shown to reliably predict three-month functional outcome in patients with acute ischemic stroke. AIM: The study aims to investigate whether information from multimodal imaging increases ASTRAL score's accuracy. METHODS: All patients registered in the ASTRAL registry until March 2011 were included. In multivariate logistic-regression analyses, we added covariates derived from parenchymal, vascular, and perfusion imaging to the 6-parameter model of the ASTRAL score. If a specific imaging covariate remained an independent predictor of three-month modified Rankin score > 2, the area-under-the-curve (AUC) of this new model was calculated and compared with ASTRAL score's AUC. We also performed similar logistic regression analyses in arbitrarily chosen patient subgroups. RESULTS: When added to the ASTRAL score, the following covariates on admission computed tomography/magnetic resonance imaging-based multimodal imaging were not significant predictors of outcome: any stroke-related acute lesion, any nonstroke-related lesions, chronic/subacute stroke, leukoaraiosis, significant arterial pathology in ischemic territory on computed tomography angiography/magnetic resonance angiography/Doppler, significant intracranial arterial pathology in ischemic territory, and focal hypoperfusion on perfusion-computed tomography. The Alberta Stroke Program Early CT score on plain imaging and any significant extracranial arterial pathology on computed tomography angiography/magnetic resonance angiography/Doppler were independent predictors of outcome (odds ratio: 0·93, 95% CI: 0·87-0·99 and odds ratio: 1·49, 95% CI: 1·08-2·05, respectively) but did not increase ASTRAL score's AUC (0·849 vs. 0·850, and 0·8563 vs. 0·8564, respectively). In exploratory analyses in subgroups of different prognosis, age or stroke severity, no covariate was found to increase ASTRAL score's AUC, either. CONCLUSIONS: The addition of information derived from multimodal imaging does not increase ASTRAL score's accuracy to predict functional outcome despite having an independent prognostic value. More selected radiological parameters applied in specific subgroups of stroke patients may add prognostic value of multimodal imaging.
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In this study we have demonstrated the potential of two-dimensional electrophoresis (2DE)-based technologies as tools for characterization of the Leishmania proteome (the expressed protein complement of the genome). Standardized neutral range (pH 5-7) proteome maps of Leishmania (Viannia) guyanensis and Leishmania (Viannia) panamensis promastigotes were reproducibly generated by 2DE of soluble parasite extracts, which were prepared using lysis buffer containing urea and nonidet P-40 detergent. The Coomassie blue and silver nitrate staining systems both yielded good resolution and representation of protein spots, enabling the detection of approximately 800 and 1,500 distinct proteins, respectively. Several reference protein spots common to the proteomes of all parasite species/strains studied were isolated and identified by peptide mass spectrometry (LC-ES-MS/MS), and bioinformatics approaches as members of the heat shock protein family, ribosomal protein S12, kinetoplast membrane protein 11 and a hypothetical Leishmania-specific 13 kDa protein of unknown function. Immunoblotting of Leishmania protein maps using a monoclonal antibody resulted in the specific detection of the 81.4 kDa and 77.5 kDa subunits of paraflagellar rod proteins 1 and 2, respectively. Moreover, differences in protein expression profiles between distinct parasite clones were reproducibly detected through comparative proteome analyses of paired maps using image analysis software. These data illustrate the resolving power of 2DE-based proteome analysis. The production and basic characterization of good quality Leishmania proteome maps provides an essential first step towards comparative protein expression studies aimed at identifying the molecular determinants of parasite drug resistance and virulence, as well as discovering new drug and vaccine targets.