Primary dengue haemorrhagic fever in patients from northeast of Brazil is associated with high levels of interferon-β during acute phase

Dengue is an acute febrile disease caused by the mosquito-borne dengue virus (DENV) that according to clinical manifestations can be classified as asymptomatic, mild or severe dengue. Severe dengue cases have been associated with an unbalanced immune response characterised by an over secretion of inflammatory cytokines. In the present study we measured type I interferon (IFN-I) transcript and circulating levels in primary and secondary DENV infected patients. We observed that dengue fever (DF) and dengue haemorrhagic fever (DHF) patients express IFN-I differently. While DF and DHF patients express interferon-α similarly (52,71 ± 7,40 and 49,05 ± 7,70, respectively), IFN- β were associated with primary DHF patients. On the other hand, secondary DHF patients were not able to secrete large amounts of IFN- β which in turn may have influenced the high-level of viraemia. Our results suggest that, in patients from our cohort, infection by DENV serotype 3 elicits an innate response characterised by higher levels of IFN- β in the DHF patients with primary infection, which could contribute to control infection evidenced by the low-level of viraemia in these patients. The present findings may contribute to shed light in the role of innate immune response in dengue pathogenesis.

Immunohistochemistry as a valuable tool to assess CD30 expression in peripheral T-cell lymphomas: high correlation with mRNA levels.

The extended use of brentuximab-vedotin was reported for CD30(+) nonanaplastic peripheral T-cell lymphomas (PTCLs) with promising efficacy. CD30 status assessment is thus a critical factor for therapeutic decision, but the reliability of immunohistochemistry (IHC) in evaluating its expression remains to be defined. This prompted us to investigate the correlation between semiquantitative CD30 protein assessment by IHC and messenger RNA (mRNA) assessment by microarrays in a cohort of 376 noncutaneous PTCLs representative of the main entities. By IHC, CD30 expression was heterogeneous across and within entities and significantly associated with large tumor cell size. In addition to 100% anaplastic large-cell lymphomas, 57% of other PTCL entities were CD30-positive at a 5% threshold. CD30 protein expression was highly correlated to mRNA levels. mRNA levels were bimodal, separating high from low CD30-expressing PTCL cases. We conclude that IHC is a valuable tool in clinical practice to assess CD30 expression in PTCLs.

Optimisation of stir bar sorptive extraction and liquid desorption combined with large volume injection-gas chromatography–quadrupole mass spectrometry for the determination of volatile compounds in wines

Stir bar sorptive extraction and liquid desorption followed by large volume injection coupled to gas chromatography–quadrupole mass spectrometry (SBSE–LD/LVI-GC–qMS) had been applied for the determination of volatiles in wines. The methodology was optimised in terms of extraction time and influence of ethanol in the matrix; LD conditions, and instrumental settings. The optimisation was carried out by using 10 standards representative of the main chemical families of wine, i.e. guaiazulene, E,E-farnesol, β-ionone, geranylacetone, ethyl decanoate, β-citronellol, 2-phenylethanol, linalool, hexyl acetate and hexanol. The methodology shows good linearity over the concentration range tested, with correlation coefficients higher than 0.9821, a good reproducibility was attained (8.9–17.8%), and low detection limits were achieved for nine volatile compounds (0.05–9.09 μg L−1), with the exception of 2-phenylethanol due to low recovery by SBSE. The analytical ability of the SBSE–LD/LVI-GC–qMS methodology was tested in real matrices, such as sparkling and table wines using analytical curves prepared by using the 10 standards where each one was applied to quantify the structurally related compounds. This methodology allowed, in a single run, the quantification of 67 wine volatiles at levels lower than their respective olfactory thresholds. The proposed methodology demonstrated to be easy to work-up, reliable, sensitive and with low sample requirement to monitor the volatile fraction of wine.

DIAGNOSIS of REGIONAL CEREBRAL BLOOD FLOW ABNORMALITIES USING SPECT: AGREEMENT BETWEEN INDIVIDUALIZED STATISTICAL PARAMETRIC MAPS and VISUAL INSPECTION BY NUCLEAR MEDICINE PHYSICIANS WITH DIFFERENT LEVELS of EXPERTISE IN NUCLEAR NEUROLOGY

INTRODUCTION: Visual analysis is widely used to interpret regional cerebral blood flow (rCBF) SPECT images in clinical practice despite its limitations. Automated methods are employed to investigate between-group rCBF differences in research Studies but have rarely been explored in individual analyses.OBJECTIVES: To compare visual inspection by nuclear physicians with the automated statistical parametric mapping program using a SPECT dataset of patients with neurological disorders and normal control images.METHODS: Using statistical parametric mapping, 14 SPECT images from patients with various neurological disorders were compared individually with a databank of 32 normal images using a statistical threshold of p<0.05 (corrected for multiple comparisons at the level of individual voxels or clusters). Statistical parametric mapping results were compared with Visual analyses by a nuclear physician highly experienced in neurology (A) as well as a nuclear physician with a general background of experience (B) who independently classified images as normal or altered, and determined the location of changes and the severity.RESULTS: of the 32 images of the normal databank, 4 generated maps showing rCBF abnormalities (p<0.05, corrected). Among the 14 images from patients with neurological disorders, 13 showed rCBF alterations. Statistical parametric mapping and physician A completely agreed on 84.37% and 64.28% of cases from the normal databank and neurological disorders, respectively. The agreement between statistical parametric mapping and ratings of physician B were lower (71.18% and 35.71%, respectively).CONCLUSION: Statistical parametric mapping replicated the findings described by the more experienced nuclear physician. This finding suggests that automated methods for individually analyzing rCBF SPECT images may be a valuable resource to complement visual inspection in clinical practice.

Vocal and territorial behavior in the Smith frog (Hypsiboas faber): Relationships with plasma levels of corticosterone and testosterone

The possible trade-off between the roles of glucocorticoids as facilitators of energy substrate mobilization and neural inhibitors of sexual behavior during breeding season is under debate. We studied the relationship between calling and territorial behavior with plasma levels of corticosterone (CORT) and plasma levels of testosterone (T) across the breeding season of Hypsiboas faber, a large and territorial Neotropical treefrog. We investigated these relationships through focal observations of males calling naturally, followed by blood sampling for hormonal radioimmunoassay. We additionally used an experimental approach, which consisted of broadcasting recorded advertisement calls for 10 min to simulate an invasion in the territory of the focal subjects, followed by behavioral observation and blood sampling for hormonal radioimmunoassay. Results showed a pattern of co-variation between CORT and T across the breeding season. Furthermore, individual variation in CORT and T was related to different aspects of behavior: individuals with higher CORT showed higher calling rates, and individuals with higher steroid levels, mainly T, showed higher responsivity to social stimulation by other males in the chorus. Experimental simulation of territorial intrusion by using playback of advertisement calls of this species did not elicit consistent changes in agonistic behavior and CORT, but decreased T in focal males. (C) 2012 Elsevier Inc. All rights reserved.

Specific and Nonspecific Psychological Interventions for PTSD Symptoms: A Meta-Analysis With Problem Complexity as a Moderator

CONTEXT The necessity of specific intervention components for the successful treatment of patients with posttraumatic stress disorder is the subject of controversy. OBJECTIVE To investigate the complexity of clinical problems as a moderator of relative effects between specific and nonspecific psychological interventions. METHODS We included 18 randomized controlled trials, directly comparing specific and nonspecific psychological interventions. We conducted moderator analyses, including the complexity of clinical problems as predictor. RESULTS Our results have confirmed the moderate superiority of specific over nonspecific psychological interventions; however, the superiority was small in studies with complex clinical problems and large in studies with noncomplex clinical problems. CONCLUSIONS For patients with complex clinical problems, our results suggest that particular nonspecific psychological interventions may be offered as an alternative to specific psychological interventions. In contrast, for patients with noncomplex clinical problems, specific psychological interventions are the best treatment option.

Tailored instructional methods for students with diverse levels of computer knowledge and skills

The purpose of this online course is to ensure new nursing graduate students know how to use computer technologies required to complete academic and research activities. Powerful computers, high speed internet, digitalized resources and databases are widely available in educational institutes. New renovation and updates are being released at faster pace than ever. All these developments are necessary for a student to utilize computer programs and synthesize large amount of data in a limited time for any given academic research project. [See PDF for complete abstract]

No evidence for an association of posttraumatic stress disorder with circulating levels of CRP and IL-18 in a population-based study.

Several studies have shown associations of posttraumatic stress disorder (PTSD) with the development of cardiometabolic diseases. The underlying psychopathological mechanisms, including potential links to inflammatory processes, have been discussed but remain elusive. Therefore, the aim of the present study was to evaluate the association of PTSD symptoms with the inflammatory biomarkers C-reactive protein (CRP) and interleukin-18 (IL-18). The study population consisted of 3012 participants aged 32-81years drawn from the population-based KORA F4 study conducted in 2006-08 in the Augsburg region (Southern Germany). PTSD symptoms were measured by the Impact of Event Scale, the Posttraumatic Diagnostic Scale and interview data and classified as no, partial or full PTSD. The associations of PTSD with CRP and IL-18 concentrations were estimated by multiple regression analyses with adjustments for age, sex and cardiometabolic risk factors. Linear regression analyses showed no significant association between PTSD and CRP or IL-18 concentration: adjusted for age and sex, the geometric mean concentrations in participants with full PTSD was for CRP 9% lower and for IL-18 1% higher than in participants with no PTSD (p values 0.53 and 0.89). However, further analyses indicated that individuals with partial PTSD had an increased chance of belonging to the highest quartile of the IL-18 concentration. No significant association was observed for any of the three subscales intrusion, avoidance or hyperarousal with CRP or IL-18 concentration. This large, population-based study could not find an association of full PTSD with CRP and IL-18 concentrations. Further research is needed to analyse these relationships.

An MILP-based heuristic for staff scheduling problems with acceptance levels

We present a real-world staff-assignment problem that was reported to us by a provider of an online workforce scheduling software. The problem consists of assigning employees to work shifts subject to a large variety of requirements related to work laws, work shift compatibility, workload balancing, and personal preferences of employees. A target value is given for each requirement, and all possible deviations from these values are associated with acceptance levels. The objective is to minimize the total number of deviations in ascending order of the acceptance levels. We present an exact lexicographic goal programming MILP formulation and an MILP-based heuristic. The heuristic consists of two phases: in the first phase a feasible schedule is built and in the second phase parts of the schedule are iteratively re-optimized by applying an exact MILP model. A major advantage of such MILP-based approaches is the flexibility to account for additional constraints or modified planning objectives, which is important as the requirements may vary depending on the company or planning period. The applicability of the heuristic is demonstrated for a test set derived from real-world data. Our computational results indicate that the heuristic is able to devise optimal solutions to non-trivial problem instances, and outperforms the exact lexicographic goal programming formulation on medium- and large-sized problem instances.

Browsing for information by highlighting automatically generated annotations:a user study and evaluation

The realization of the Semantic Web is constrained by a knowledge acquisition bottleneck, i.e. the problem of how to add RDF mark-up to the millions of ordinary web pages that already exist. Information Extraction (IE) has been proposed as a solution to the annotation bottleneck. In the task based evaluation reported here, we compared the performance of users without access to annotation, users working with annotations which had been produced from manually constructed knowledge bases, and users working with annotations augmented using IE. We looked at retrieval performance, overlap between retrieved items and the two sets of annotations, and usage of annotation options. Automatically generated annotations were found to add value to the browsing experience in the scenario investigated. Copyright 2005 ACM.

Stretching the life of Twitter classifiers with time-stamped semantic graphs

Social media has become an effective channel for communicating both trends and public opinion on current events. However the automatic topic classification of social media content pose various challenges. Topic classification is a common technique used for automatically capturing themes that emerge from social media streams. However, such techniques are sensitive to the evolution of topics when new event-dependent vocabularies start to emerge (e.g., Crimea becoming relevant to War Conflict during the Ukraine crisis in 2014). Therefore, traditional supervised classification methods which rely on labelled data could rapidly become outdated. In this paper we propose a novel transfer learning approach to address the classification task of new data when the only available labelled data belong to a previous epoch. This approach relies on the incorporation of knowledge from DBpedia graphs. Our findings show promising results in understanding how features age, and how semantic features can support the evolution of topic classifiers.

An experiment on the parameter uncertainty of hydrological models with different levels of complexity in a climate change context

La possibilité d’estimer l’impact du changement climatique en cours sur le comportement hydrologique des hydro-systèmes est une nécessité pour anticiper les adaptations inévitables et nécessaires que doivent envisager nos sociétés. Dans ce contexte, ce projet doctoral présente une étude sur l’évaluation de la sensibilité des projections hydrologiques futures à : (i) La non-robustesse de l’identification des paramètres des modèles hydrologiques, (ii) l’utilisation de plusieurs jeux de paramètres équifinaux et (iii) l’utilisation de différentes structures de modèles hydrologiques. Pour quantifier l’impact de la première source d’incertitude sur les sorties des modèles, quatre sous-périodes climatiquement contrastées sont tout d’abord identifiées au sein des chroniques observées. Les modèles sont calés sur chacune de ces quatre périodes et les sorties engendrées sont analysées en calage et en validation en suivant les quatre configurations du Different Splitsample Tests (Klemeš, 1986;Wilby, 2005; Seiller et al. (2012);Refsgaard et al. (2014)). Afin d’étudier la seconde source d’incertitude liée à la structure du modèle, l’équifinalité des jeux de paramètres est ensuite prise en compte en considérant pour chaque type de calage les sorties associées à des jeux de paramètres équifinaux. Enfin, pour évaluer la troisième source d’incertitude, cinq modèles hydrologiques de différents niveaux de complexité sont appliqués (GR4J, MORDOR, HSAMI, SWAT et HYDROTEL) sur le bassin versant québécois de la rivière Au Saumon. Les trois sources d’incertitude sont évaluées à la fois dans conditions climatiques observées passées et dans les conditions climatiques futures. Les résultats montrent que, en tenant compte de la méthode d’évaluation suivie dans ce doctorat, l’utilisation de différents niveaux de complexité des modèles hydrologiques est la principale source de variabilité dans les projections de débits dans des conditions climatiques futures. Ceci est suivi par le manque de robustesse de l’identification des paramètres. Les projections hydrologiques générées par un ensemble de jeux de paramètres équifinaux sont proches de celles associées au jeu de paramètres optimal. Par conséquent, plus d’efforts devraient être investis dans l’amélioration de la robustesse des modèles pour les études d’impact sur le changement climatique, notamment en développant les structures des modèles plus appropriés et en proposant des procédures de calage qui augmentent leur robustesse. Ces travaux permettent d’apporter une réponse détaillée sur notre capacité à réaliser un diagnostic des impacts des changements climatiques sur les ressources hydriques du bassin Au Saumon et de proposer une démarche méthodologique originale d’analyse pouvant être directement appliquée ou adaptée à d’autres contextes hydro-climatiques.

A Binary Classifier for Test Case Feasibility Applied to Automatically Generated Tests of Event-Driven Software

Modern software application testing, such as the testing of software driven by graphical user interfaces (GUIs) or leveraging event-driven architectures in general, requires paying careful attention to context. Model-based testing (MBT) approaches first acquire a model of an application, then use the model to construct test cases covering relevant contexts. A major shortcoming of state-of-the-art automated model-based testing is that many test cases proposed by the model are not actually executable. These \textit{infeasible} test cases threaten the integrity of the entire model-based suite, and any coverage of contexts the suite aims to provide. In this research, I develop and evaluate a novel approach for classifying the feasibility of test cases. I identify a set of pertinent features for the classifier, and develop novel methods for extracting these features from the outputs of MBT tools. I use a supervised logistic regression approach to obtain a model of test case feasibility from a randomly selected training suite of test cases. I evaluate this approach with a set of experiments. The outcomes of this investigation are as follows: I confirm that infeasibility is prevalent in MBT, even for test suites designed to cover a relatively small number of unique contexts. I confirm that the frequency of infeasibility varies widely across applications. I develop and train a binary classifier for feasibility with average overall error, false positive, and false negative rates under 5\%. I find that unique event IDs are key features of the feasibility classifier, while model-specific event types are not. I construct three types of features from the event IDs associated with test cases, and evaluate the relative effectiveness of each within the classifier. To support this study, I also develop a number of tools and infrastructure components for scalable execution of automated jobs, which use state-of-the-art container and continuous integration technologies to enable parallel test execution and the persistence of all experimental artifacts.

Primary dengue haemorrhagic fever in patients from northeast of Brazil is associated with high levels of interferon-b during acute phase

Dengue is an acute febrile disease caused by the mosquito-borne dengue virus (DENV) that according to clinical manifestations can be classified as asymptomatic, mild or severe dengue. Severe dengue cases have been associated with an unbalanced immune response characterised by an over secretion of inflammatory cytokines. In the present study we measured type I interferon (IFN-I) transcript and circulating levels in primary and secondary DENV infected patients. We observed that dengue fever (DF) and dengue haemorrhagic fever (DHF) patients express IFN-I differently. While DF and DHF patients express interferon-a similarly (52,71 ± 7,40 and 49,05 ± 7,70, respectively), high levels of circulating IFN-b were associated with primary DHF patients. On the other hand, secondary DHF patients were not able to secrete large amounts of IFN-b which in turn may have influenced the high-level of viraemia. Our results suggest that, in patients from our cohort, infection by DENV serotype 3 elicits an innate response characterised by higher levels of IFN-b in the DHF patients with primary infection, which could contribute to control infection evidenced by the low-level of viraemia in these patients. The present findings may contribute to shed light in the role of innate immune response in dengue pathogenesis.