Analysis of the association between chondrocalcinosis and osteoarthritis: a community based study

To analyse the association between chondrocalcinosis and osteoarthritis (OA) of the hands and knees in an unselected elderly rural population. METHODS--A community based cross sectional study was performed in individuals randomly selected from a previous epidemiological survey on the prevalence of chondrocalcinosis in people older than 60 years from Osona county, Catalonia, northeastern Spain. Radiological OA (grade 2 or more of Kellgren's classification) was evaluated in 26 individuals with chondrocalcinosis and in 104 controls. A total of 18 articular areas of both knees (medial and lateral tibiofemoral compartments) and hands (first, second and third metacarpophalangeal (MCP), first carpometacarpal, trapezium-scaphoid, radiocarpal and distal radioulnar joints) were studied. RESULTS--Radiological changes of OA in the knees were more common in subjects with chondrocalcinosis than in those without it, with an odds ratio adjusted for age and gender (aOR) of 4.3 (95% confidence interval (CI) 1.6 to 11.8, p = 0.005). OA was also more frequent in almost all areas of the hands in individuals with chondrocalcinosis, though the difference reached statistical significance only in the MCP joints (aOR 3.1; 95% CI 1.1 to 8.8; p = 0.033). However, taking into account the side and the different joint compartments analysed, the association between chondrocalcinosis and OA was significant only in the lateral tibiofemoral compartment and the left MCP joints. CONCLUSIONS--In an elderly population unselected for their rheumatic complaints, there was a real association between OA and chondrocalcinosis. This association was particularly relevant in the lateral tibiofemoral compartment of the knee and in the first three left MCP joints.

A multicenter, cross-sectional study on the prevalence and risk factors for nasal colonization with Staphylococcus aureus in patients admitted to children's hospitals in Switzerland.

The rate of nasal carriage of Staphylococcus aureus and associated risk factors were determined in a cross-sectional study involving Swiss children's hospitals. S. aureus was isolated in 562 of 1363 cases. In a stepwise multivariate analysis, the variables age, duration of antibiotic use, and hospitalization of a household member were independently associated with carriage of S. aureus.

Analysis and spatial modeling of the indoor radon Swiss data

The present research deals with an important public health threat, which is the pollution created by radon gas accumulation inside dwellings. The spatial modeling of indoor radon in Switzerland is particularly complex and challenging because of many influencing factors that should be taken into account. Indoor radon data analysis must be addressed from both a statistical and a spatial point of view. As a multivariate process, it was important at first to define the influence of each factor. In particular, it was important to define the influence of geology as being closely associated to indoor radon. This association was indeed observed for the Swiss data but not probed to be the sole determinant for the spatial modeling. The statistical analysis of data, both at univariate and multivariate level, was followed by an exploratory spatial analysis. Many tools proposed in the literature were tested and adapted, including fractality, declustering and moving windows methods. The use of Quan-tité Morisita Index (QMI) as a procedure to evaluate data clustering in function of the radon level was proposed. The existing methods of declustering were revised and applied in an attempt to approach the global histogram parameters. The exploratory phase comes along with the definition of multiple scales of interest for indoor radon mapping in Switzerland. The analysis was done with a top-to-down resolution approach, from regional to local lev¬els in order to find the appropriate scales for modeling. In this sense, data partition was optimized in order to cope with stationary conditions of geostatistical models. Common methods of spatial modeling such as Κ Nearest Neighbors (KNN), variography and General Regression Neural Networks (GRNN) were proposed as exploratory tools. In the following section, different spatial interpolation methods were applied for a par-ticular dataset. A bottom to top method complexity approach was adopted and the results were analyzed together in order to find common definitions of continuity and neighborhood parameters. Additionally, a data filter based on cross-validation was tested with the purpose of reducing noise at local scale (the CVMF). At the end of the chapter, a series of test for data consistency and methods robustness were performed. This lead to conclude about the importance of data splitting and the limitation of generalization methods for reproducing statistical distributions. The last section was dedicated to modeling methods with probabilistic interpretations. Data transformation and simulations thus allowed the use of multigaussian models and helped take the indoor radon pollution data uncertainty into consideration. The catego-rization transform was presented as a solution for extreme values modeling through clas-sification. Simulation scenarios were proposed, including an alternative proposal for the reproduction of the global histogram based on the sampling domain. The sequential Gaussian simulation (SGS) was presented as the method giving the most complete information, while classification performed in a more robust way. An error measure was defined in relation to the decision function for data classification hardening. Within the classification methods, probabilistic neural networks (PNN) show to be better adapted for modeling of high threshold categorization and for automation. Support vector machines (SVM) on the contrary performed well under balanced category conditions. In general, it was concluded that a particular prediction or estimation method is not better under all conditions of scale and neighborhood definitions. Simulations should be the basis, while other methods can provide complementary information to accomplish an efficient indoor radon decision making.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Diallel analysis for grain yield and mineral absorption rate of soybeans grown in acid brazilian savannah soil

High available aluminium and low levels of calcium below the ploughed zone of the soil are limiting factors for agricultural sustainability in the Brazilian Cerrados (Savannahs). The mineral stresses compound with dry spells effect by preventing deep root growth of cultivated plants and causes yield instability. The mode of inheritance for grain yield and mineral absorption ratio of a diallel cross in soybeans [Glycine max (L.) Merrill] grown in high and low Al areas was identified. Differences among the genotypes for grain yield were more evident in the high Al, by grouping tolerant and non-tolerant genotypes for their respective arrays in the hybrids. A large proportion of genetic variance was additive for grain yield and mineral absorption ratio in both environments. High heritability values suggest that soybeans can be improved by crosses among Al-tolerant genotypes, using modified pedigree, early generation and recurrent selection schemes.

Systems analysis of MVA-C induced immune response reveals its significance as a vaccine candidate against HIV/AIDS of clade C.

Based on the partial efficacy of the HIV/AIDS Thai trial (RV144) with a canarypox vector prime and protein boost, attenuated poxvirus recombinants expressing HIV-1 antigens are increasingly sought as vaccine candidates against HIV/AIDS. Here we describe using systems analysis the biological and immunological characteristics of the attenuated vaccinia virus Ankara strain expressing the HIV-1 antigens Env/Gag-Pol-Nef of HIV-1 of clade C (referred as MVA-C). MVA-C infection of human monocyte derived dendritic cells (moDCs) induced the expression of HIV-1 antigens at high levels from 2 to 8 hpi and triggered moDCs maturation as revealed by enhanced expression of HLA-DR, CD86, CD40, HLA-A2, and CD80 molecules. Infection ex vivo of purified mDC and pDC with MVA-C induced the expression of immunoregulatory pathways associated with antiviral responses, antigen presentation, T cell and B cell responses. Similarly, human whole blood or primary macrophages infected with MVA-C express high levels of proinflammatory cytokines and chemokines involved with T cell activation. The vector MVA-C has the ability to cross-present antigens to HIV-specific CD8 T cells in vitro and to increase CD8 T cell proliferation in a dose-dependent manner. The immunogenic profiling in mice after DNA-C prime/MVA-C boost combination revealed activation of HIV-1-specific CD4 and CD8 T cell memory responses that are polyfunctional and with effector memory phenotype. Env-specific IgG binding antibodies were also produced in animals receiving DNA-C prime/MVA-C boost. Our systems analysis of profiling immune response to MVA-C infection highlights the potential benefit of MVA-C as vaccine candidate against HIV/AIDS for clade C, the prevalent subtype virus in the most affected areas of the world.

Functional analysis of HLA-A*0201/Melan-A peptide multimer+ CD8+ T cells isolated from an HLA-A*0201- donor: exploring tumor antigen allorestricted recognition.

Recent studies in mouse models have suggested that genetic transfer of tumor antigen-specific high affinity T cell receptors (TCR) into host lymphocytes could be a viable strategy for the rapid induction of tumor-specific immunity. A previously proposed approach for the isolation of such TCRs consists in circumventing tolerance to self-restricting HLA/peptide complexes by deriving them from PMBCs of allogenic donors. Towards this aim, we used fluorescent HLA-A2 class-I/peptide soluble multimers to isolate A2-restricted CD8+ T cells specific for a previously described Melan-A peptide enhanced analog (Melan-A 26-35 A27L) from an HLA-A*0201 (A2) negative donor. We isolated two distinct groups of Melan-A 26-35 A27L-specific clones. Clones from the first group recognized the analog peptide with high avidity but showed very low recognition of Melan-A parental peptides. In contrast, clones from the second group efficiently recognized Melan-A parental peptides. Surprisingly however, most clones recognized not only A2+ Melan-A+ targets, but also A2+ Melan-A- targets suggesting that they can also recognize endogenous peptides other than Melan-A. In addition, one clone showed full cross-recognition of an antigenically unrelated peptide. Together, our data show that HLA-A2/peptide multimers can be successfully used for the isolation of allorestricted CD8+ T cells reactive with tumor antigen-derived peptides. However, as the cross-reactivity of these apparently peptide-specific allorestricted TCRs is presently unpredictable, a careful in vitro analysis of their reactivity to the host's normal cells is recommended.

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.

Cross-cultural clinical competence and post-graduate teaching: any impact(s) on doctors?

Context: Cross-cultural clinical competence (CCC) requires a mixtureof "knowledge" (K), "attitude" (A) and "skills" (S), in order to develop theability to give quality care to patients of different cultures. Theseattributes allow, while providing medical care, consideration of thepatient's medical, social, cultural and language needs. The LausanneUniversity Medical Policlinic (PMU) provides approximately 30000consultations per year to migrant patients and over the past five yearshas implemented a training course on CCC that focuses on trialogue,stereotypes and administrative procedures for the healthcare ofmigrants.Method: A quantitative survey of 18 new residents, was carried outusing a validated questionnaire, the "Multicultural AssessmentQuestionnaire" (the MAQ, 16 questions on K, A and S) to evaluate theimpact of CCC training. The questionnaire was distributed before theCCC course (J-1), three days after (J+3) and three months later (J+90).A descriptive univariate analysis of the difference in MAQ scoresbetween the times J-1 - J+3 and J-1 - J+90 was made. Three FocusGroups were conducted, at three months, to explore residents' thoughtsabout the course.Results: A significant increase was observed in global performancedeclared by residents. Following the intervention, the score of the MAQincreased from 31.4 points to 38.0 points at three days (p = 0.004) andto 37.7 points at three months (p = 0.003). This increase was mostnoticeable in the field of acquiring K: total score J-1: 118, J+3: 189,J+90: 190 (difference J-1 - J+3 and J-1 - J+90: p <0.005). There was nosignificant difference in acquiring A (J-1: 222, J+3: 228, J+90: 229), andS increases in a significant way at first (J-1: 222, J+3: 265, J-1 - J+3:p = 0.035), then comes back to the start value (J+90: 217). The residentswere interested by the course which they felt provides useful informationfor clinical practice. They had a great number of expectations in varyingfields (medical anthropology, cultural differences, epidemiology, etc.),hoping a "ready-made" solution for the approach of migrant patients.Conclusions: A unique training of CCC at the post-graduate level,upgraded K, and to a lesser extent A and S, for these 18 residents. Theywere interest and they had many expectations. Subsequent coursesshould consolidate these acquisitions. Future study should demonstratethe impact on patients' clinical outcome.

Wind Tunnel Analysis of the Effects of Planting at Highway Grade Separation Structures, HR-202, 1979

Blowing and drifting snow has been a problem for the highway maintenance engineer virtually since the inception of the automobile. In the early days, highway engineers were limited in their capability to design and construct drift free roadway cross sections, and the driving public tolerated the delays associated with snow storms. Modern technology, however, has long since provided the design expertise, financial resources, and construction capability for creating relatively snowdrift free highways, and the driver today has come to expect a highway facility that is free of snowdrifts, and if drifts develop they expect highway maintenance crews to open the highway within a short time. Highway administrators have responded to this charge for better control of snowdrifting. Modern highway designs in general provide an aerodynamic cross section that inhibits the deposition of snow on the roadway insofar as it is economically feasible to do so.

Prediction of cross-recognition of peptide-HLA A2 by Melan-A-specific cytotoxic T lymphocytes using three-dimensional quantitative structure-activity relationships.

The cross-recognition of peptides by cytotoxic T lymphocytes is a key element in immunology and in particular in peptide based immunotherapy. Here we develop three-dimensional (3D) quantitative structure-activity relationships (QSARs) to predict cross-recognition by Melan-A-specific cytotoxic T lymphocytes of peptides bound to HLA A*0201 (hereafter referred to as HLA A2). First, we predict the structure of a set of self- and pathogen-derived peptides bound to HLA A2 using a previously developed ab initio structure prediction approach [Fagerberg et al., J. Mol. Biol., 521-46 (2006)]. Second, shape and electrostatic energy calculations are performed on a 3D grid to produce similarity matrices which are combined with a genetic neural network method [So et al., J. Med. Chem., 4347-59 (1997)] to generate 3D-QSAR models. The models are extensively validated using several different approaches. During the model generation, the leave-one-out cross-validated correlation coefficient (q (2)) is used as the fitness criterion and all obtained models are evaluated based on their q (2) values. Moreover, the best model obtained for a partitioned data set is evaluated by its correlation coefficient (r = 0.92 for the external test set). The physical relevance of all models is tested using a functional dependence analysis and the robustness of the models obtained for the entire data set is confirmed using y-randomization. Finally, the validated models are tested for their utility in the setting of rational peptide design: their ability to discriminate between peptides that only contain side chain substitutions in a single secondary anchor position is evaluated. In addition, the predicted cross-recognition of the mono-substituted peptides is confirmed experimentally in chromium-release assays. These results underline the utility of 3D-QSARs in peptide mimetic design and suggest that the properties of the unbound epitope are sufficient to capture most of the information to determine the cross-recognition.

Standardizing admission and discharge processes to improve patient flow: A cross sectional study

Background: The aim of this study was to evaluate how hospital capacity was managed focusing on standardizing the admission and discharge processes. Methods: This study was set in a 900-bed university affiliated hospital of the National Health Service, near Barcelona (Spain). This is a cross-sectional study of a set of interventions which were gradually implemented between April and December 2008. Mainly, they were focused on standardizing the admission and discharge processes to improve patient flow. Primary administrative data was obtained from the 2007 and 2009 Hospital Database. Main outcome measures were median length of stay, percentage of planned discharges, number of surgery cancellations and median number of delayed emergency admissions at 8:00 am. For statistical bivariate analysis, we used a Chi-squared for linear trend for qualitative variables and a Wilcoxon signed ranks test and a Mann–Whitney test for non-normal continuous variables. Results: The median patients’ global length of stay was 8.56 days in 2007 and 7.93 days in 2009 (p<0.051). The percentage of patients admitted the same day as surgery increased from 64.87% in 2007 to 86.01% in 2009 (p<0.05). The number of cancelled interventions due to lack of beds was 216 patients in 2007 and 42 patients in 2009. The median number of planned discharges went from 43.05% in 2007 to 86.01% in 2009 (p<0.01). The median number of emergency patients waiting for an in-hospital bed at 8:00 am was 5 patients in 2007 and 3 patients in 2009 (p<0.01). Conclusions: In conclusion, standardization of admission and discharge processes are largely in our control. There is a significant opportunity to create important benefits for increasing bed capacity and hospital throughput.

Standardizing admission and discharge processes to improve patient flow: A cross sectional study

Background: The aim of this study was to evaluate how hospital capacity was managed focusing on standardizing the admission and discharge processes. Methods: This study was set in a 900-bed university affiliated hospital of the National Health Service, near Barcelona (Spain). This is a cross-sectional study of a set of interventions which were gradually implemented between April and December 2008. Mainly, they were focused on standardizing the admission and discharge processes to improve patient flow. Primary administrative data was obtained from the 2007 and 2009 Hospital Database. Main outcome measures were median length of stay, percentage of planned discharges, number of surgery cancellations and median number of delayed emergency admissions at 8:00¿am. For statistical bivariate analysis, we used a Chi-squared for linear trend for qualitative variables and a Wilcoxon signed ranks test and a Mann¿Whitney test for non-normal continuous variables. Results:The median patients' global length of stay was 8.56 days in 2007 and 7.93 days in 2009 (p<0.051). The percentage of patients admitted the same day as surgery increased from 64.87% in 2007 to 86.01% in 2009 (p<0.05). The number of cancelled interventions due to lack of beds was 216 patients in 2007 and 42 patients in 2009. The median number of planned discharges went from 43.05% in 2007 to 86.01% in 2009 (p<0.01). The median number of emergency patients waiting for an in-hospital bed at 8:00¿am was 5 patients in 2007 and 3 patients in 2009 (p<0.01). Conclusions: In conclusion, standardization of admission and discharge processes are largely in our control. There is a significant opportunity to create important benefits for increasing bed capacity and hospital throughput.

Performance Analysis of Two Quantum Reaction Dynamics Codes: Time-Dependent and Time-Independent Strategies

The computer simulation of reaction dynamics has nowadays reached a remarkable degree of accuracy. Triatomic elementary reactions are rigorously studied with great detail on a straightforward basis using a considerable variety of Quantum Dynamics computational tools available to the scientific community. In our contribution we compare the performance of two quantum scattering codes in the computation of reaction cross sections of a triatomic benchmark reaction such as the gas phase reaction Ne + H2+ %12. NeH++ H. The computational codes are selected as representative of time-dependent (Real Wave Packet [ ]) and time-independent (ABC [ ]) methodologies. The main conclusion to be drawn from our study is that both strategies are, to a great extent, not competing but rather complementary. While time-dependent calculations advantages with respect to the energy range that can be covered in a single simulation, time-independent approaches offer much more detailed information from each single energy calculation. Further details such as the calculation of reactivity at very low collision energies or the computational effort related to account for the Coriolis couplings are analyzed in this paper.