Homology-based identification of capsid determinants that protect HIV1 from human TRIM5{alpha} restriction.

The tropism of retroviruses relies on their ability to exploit cellular factors for their replication as well as to avoid host-encoded inhibitory activities such as TRIM5α. N-tropic murine leukemia virus (MLV) is sensitive to human TRIM5α restriction, whereas human immunodeficiency virus type 1 (HIV1) escapes this antiviral factor. We showed previously that mutation of four critical amino acid residues within the capsid (CA) can render MLV resistant to huTRIM5α. Here, we exploit the high degree of conservation in the tertiary structure of retroviral capsids to map the corresponding positions on the HIV1 capsid. We then demonstrate that, by introducing changes at some of these positions, HIV1 becomes sensitive to huTRIM5α restriction, a phenomenon reinforced by additionally mutating the nearby cyclophilin A (CypA)-binding loop of the viral protein. These results indicate that retroviruses have evolved similar mechanisms to escape TRIM5α restriction, via the interference of structurally homologous determinants in the viral capsid.

A connectome-based comparison of diffusion MRI schemes.

Diffusion MRI has evolved towards an important clinical diagnostic and research tool. Though clinical routine is using mainly diffusion weighted and tensor imaging approaches, Q-ball imaging and diffusion spectrum imaging techniques have become more widely available. They are frequently used in research-oriented investigations in particular those aiming at measuring brain network connectivity. In this work, we aim at assessing the dependency of connectivity measurements on various diffusion encoding schemes in combination with appropriate data modeling. We process and compare the structural connection matrices computed from several diffusion encoding schemes, including diffusion tensor imaging, q-ball imaging and high angular resolution schemes, such as diffusion spectrum imaging with a publically available processing pipeline for data reconstruction, tracking and visualization of diffusion MR imaging. The results indicate that the high angular resolution schemes maximize the number of obtained connections when applying identical processing strategies to the different diffusion schemes. Compared to the conventional diffusion tensor imaging, the added connectivity is mainly found for pathways in the 50-100mm range, corresponding to neighboring association fibers and long-range associative, striatal and commissural fiber pathways. The analysis of the major associative fiber tracts of the brain reveals striking differences between the applied diffusion schemes. More complex data modeling techniques (beyond tensor model) are recommended 1) if the tracts of interest run through large fiber crossings such as the centrum semi-ovale, or 2) if non-dominant fiber populations, e.g. the neighboring association fibers are the subject of investigation. An important finding of the study is that since the ground truth sensitivity and specificity is not known, the comparability between results arising from different strategies in data reconstruction and/or tracking becomes implausible to understand.

A new early and automated MRI-based predictor of motor improvement after stroke.

OBJECTIVES: In this study, we investigated the structural plasticity of the contralesional motor network in ischemic stroke patients using diffusion magnetic resonance imaging (MRI) and explored a model that combines a MRI-based metric of contralesional network integrity and clinical data to predict functional outcome at 6 months after stroke. METHODS: MRI and clinical examinations were performed in 12 patients in the acute phase, at 1 and 6 months after stroke. Twelve age- and gender-matched controls underwent 2 MRIs 1 month apart. Structural remodeling after stroke was assessed using diffusion MRI with an automated measurement of generalized fractional anisotropy (GFA), which was calculated along connections between contralesional cortical motor areas. The predictive model of poststroke functional outcome was computed using a linear regression of acute GFA measures and the clinical assessment. RESULTS: GFA changes in the contralesional motor tracts were found in all patients and differed significantly from controls (0.001 ≤ p < 0.05). GFA changes in intrahemispheric and interhemispheric motor tracts correlated with age (p ≤ 0.01); those in intrahemispheric motor tracts correlated strongly with clinical scores and stroke sizes (p ≤ 0.001). GFA measured in the acute phase together with a routine motor score and age were a strong predictor of motor outcome at 6 months (r(2) = 0.96, p = 0.0002). CONCLUSION: These findings represent a proof of principle that contralesional diffusion MRI measures may provide reliable information for personalized rehabilitation planning after ischemic motor stroke. Neurology® 2012;79:39-46.

Ambiguous nucleotide calls from population-based sequencing of HIV-1 are a marker for viral diversity and the age of infection.

Background. The time passed since the infection of a human immunodeficiency virus (HIV)-infected individual (the age of infection) is an important but often only poorly known quantity. We assessed whether the fraction of ambiguous nucleotides obtained from bulk sequencing as done for genotypic resistance testing can serve as a proxy of this parameter. Methods. We correlated the age of infection and the fraction of ambiguous nucleotides in partial pol sequences of HIV-1 sampled before initiation of antiretroviral therapy (ART). Three groups of Swiss HIV Cohort Study participants were analyzed, for whom the age of infection was estimated on the basis of Bayesian back calculation (n = 3,307), seroconversion (n = 366), or diagnoses of primary HIV infection (n = 130). In addition, we studied 124 patients for whom longitudinal genotypic resistance testing was performed while they were still ART-naive. Results. We found that the fraction of ambiguous nucleotides increased with the age of infection with a rate of .2% per year within the first 8 years but thereafter with a decreasing rate. We show that this pattern is consistent with population-genetic models for realistic parameters. Finally, we show that, in this highly representative population, a fraction of ambiguous nucleotides of >.5% provides strong evidence against a recent infection event < 1 year prior to sampling (negative predictive value, 98.7%). Conclusions. These findings show that the fraction of ambiguous nucleotides is a useful marker for the age of infection.

The Atherosclerosis Burden Score (ABS): a Convenient Ultrasound-Based Score of Peripheral Atherosclerosis for Coronary Artery Disease Prediction.

Ultrasonographic detection of subclinical atherosclerosis improves cardiovascular risk stratification, but uncertainty persists about the most discriminative method to apply. In this study, we found that the "atherosclerosis burden score (ABS)", a novel straightforward ultrasonographic score that sums the number of carotid and femoral arterial bifurcations with plaques, significantly outperformed common carotid intima-media thickness, carotid mean/maximal thickness, and carotid/femoral plaque scores for the detection of coronary artery disease (CAD) (receiver operating characteristic (ROC) curve area under the curve (AUC) = 0.79; P = 0.027 to <0.001 with the other five US endpoints) in 203 patients undergoing coronary angiography. ABS was also more correlated with CAD extension (R = 0.55; P < 0.001). Furthermore, in a second group of 1128 patients without cardiovascular disease, ABS was weakly correlated with the European Society of Cardiology chart risk categories (R (2) = 0.21), indicating that ABS provided information beyond usual cardiovascular risk factor-based risk stratification. Pending prospective studies on hard cardiovascular endpoints, ABS appears as a promising tool in primary prevention.

The resource-based view of the firm - resources, capabilities and sustainable competitive advantage

The main objective of this research paper was to synthesize, integrate and analyze the theoretical foundation of the resource-based view of the firm on sustainable competitive advantage. Accordingly, this research was a literature research employing the methodology of interpretative study of concept and unobtrusive measures. The core and majority of the research data was gathered from the major online journal databases. Only peer-reviewed articles from highly-esteemed journals on the subject of competitive advantage were used. The theoretical core of the research paper was centred on resources, capabilities, and the sustainability dilemma of competitive advantage. Furthermore, other strategic management concepts relating to the resource-based view of the firm were used with reference to the research objectives. The resource-based view of the firm continues to be a controversial but important are of strategic management research on sustainable competitive advantage. Consequently, the theoretical foundation and the empirical testing of the framework needs further work. However, it is evident that internal organizational factors in the form of resources and capabilities are vital for the formation of sustainable competitive advantage. Resources and capabilities are not, however, valuable on their own - competitive advantage requires seamless interplay and complementarity between bundles of resources and capabilities.

Arsenic trioxide-based therapy of relapsed acute promyelocytic leukemia: registry results from the European LeukemiaNet.

In 2008, a European registry of relapsed acute promyelocytic leukemia was established by the European LeukemiaNet. Outcome data were available for 155 patients treated with arsenic trioxide in first relapse. In hematological relapse (n=104), 91% of the patients entered complete hematological remission (CR), 7% had induction death and 2% resistance, 27% developed differentiation syndrome and 39% leukocytosis, whereas no death or side effects occurred in patients treated in molecular relapse (n=40). The rate of molecular (m)CR was 74% in hematological and 62% in molecular relapse (P=0.3). All patients with extramedullary relapse (n=11) entered clinical and mCR. After 3.2 years median follow-up, the 3-year overall survival (OS) and cumulative incidence of second relapse were 68% and 41% in hematological relapse, 66% and 48% in molecular relapse and 90 and 11% in extramedullary relapse, respectively. After allogeneic or autologous transplantation in second CR (n=93), the 3-year OS was 80% compared with 59% without transplantation (n=55) (P=0.03). Multivariable analysis demonstrated the favorable prognostic impact of first remission duration ⩾1.5 years, achievement of mCR and allogeneic or autologous transplantation on OS of patients alive after induction (P=0.03, P=0.01, P=0.01) and on leukemia-free survival (P=0.006, P<0.0001, P=0.003), respectively.

Blood culture-based diagnosis of bacteraemia: state of the art.

Blood culture remains the best approach to identify the incriminating microorganisms when a bloodstream infection is suspected, and to guarantee that the antimicrobial treatment is adequate. Major improvements have been made in the last years to increase the sensitivity and specificity and to reduce the time to identification of microorganisms recovered from blood cultures. Among other factors, the introduction in clinical microbiology laboratories of the matrix-assisted laser desorption ionization time-of-flight mass spectrometry technology revolutionized the identification of microorganisms whereas the introduction of nucleic-acid-based methods, such as DNA hybridization or rapid PCR-based test, significantly reduce the time to results. Together with traditional antimicrobial susceptibility testing, new rapid methods for the detection of resistance mechanisms respond to major epidemiological concerns such as methicillin-resistant Staphylococcus aureus, extended-spectrum β-lactamase or carbapenemases. This review presents and discusses the recent developments in microbial diagnosis of bloodstream infections based on blood cultures.

Classification-Based compression of Multispectral Images

The purpose of this thesis is to present a new approach to the lossy compression of multispectral images. Proposed algorithm is based on combination of quantization and clustering. Clustering was investigated for compression of the spatial dimension and the vector quantization was applied for spectral dimension compression. Presenting algo¬rithms proposes to compress multispectral images in two stages. During the first stage we define the classes' etalons, another words to each uniform areas are located inside the image the number of class is given. And if there are the pixels are not yet assigned to some of the clusters then it doing during the second; pass and assign to the closest eta¬lons. Finally a compressed image is represented with a flat index image pointing to a codebook with etalons. The decompression stage is instant too. The proposed method described in this paper has been tested on different satellite multispectral images from different resources. The numerical results and illustrative examples of the method are represented too.

Moral disengagement: Towards a context-general category-based measure of the concept

Bandura (1986) developed the concept of moral disengagement to explain how individuals can engage in detrimental behavior while experiencing low levels of negative feelings such as guilt-feelings. Most of the research conducted on moral disengagement investigated this concept as a global concept (e.g., Bandura, Barbaranelli, Caprara, & Pastorelli, 1996; Moore, Detert, Klebe Treviño, Baker, & Mayer, 2012) while Bandura (1986, 1990) initially developed eight distinct mechanisms of moral disengagement grouped into four categories representing the various means through which moral disengagement can operate. In our work, we propose to develop measures of this concept based on its categories, namely rightness of actions, rejection of personal responsibility, distortion of negative consequences, and negative perception of the victims, and which is not specific a particular area of research. Through our measures, we aim at better understanding the cognitive process leading individuals to behave unethically by investigating which category plays a role in explaining unethical behavior depending on the situations in which individuals are. To this purpose, we conducted five studies to develop the measures and to test its predictive validity. Particularly, we assessed the ability of the newly developed measures to predict two types of unethical behaviors, i.e. discriminatory behavior and cheating behavior. Confirmatory Factor analyses demonstrated a good fit of the model and findings generally supported our predictions.