The adsorption of biomolecules to multi-walled carbon nanotubes is influenced by both pulmonary surfactant lipids and surface chemistry

Background During production and processing of multi-walled carbon nanotubes (MWCNTs), they may be inhaled and may enter the pulmonary circulation. It is essential that interactions with involved body fluids like the pulmonary surfactant, the blood and others are investigated, particularly as these interactions could lead to coating of the tubes and may affect their chemical and physical characteristics. The aim of this study was to characterize the possible coatings of different functionalized MWCNTs in a cell free environment. Results To simulate the first contact in the lung, the tubes were coated with pulmonary surfactant and subsequently bound lipids were characterized. The further coating in the blood circulation was simulated by incubating the tubes in blood plasma. MWCNTs were amino (NH2)- and carboxyl (-COOH)-modified, in order to investigate the influence on the bound lipid and protein patterns. It was shown that surfactant lipids bind unspecifically to different functionalized MWCNTs, in contrast to the blood plasma proteins which showed characteristic binding patterns. Patterns of bound surfactant lipids were altered after a subsequent incubation in blood plasma. In addition, it was found that bound plasma protein patterns were altered when MWCNTs were previously coated with pulmonary surfactant. Conclusions A pulmonary surfactant coating and the functionalization of MWCNTs have both the potential to alter the MWCNTs blood plasma protein coating and to determine their properties and behaviour in biological systems.

Evidence of viral adaptation to HLA class I-restricted immune pressure in chronic hepatitis C virus infection

Cellular immune responses are an important correlate of hepatitis C virus (HCV) infection outcome. These responses are governed by the host's human leukocyte antigen (HLA) type, and HLA-restricted viral escape mutants are a critical aspect of this host-virus interaction. We examined the driving forces of HCV evolution by characterizing the in vivo selective pressure(s) exerted on single amino acid residues within nonstructural protein 3 (NS3) by the HLA types present in two host populations. Associations between polymorphisms within NS3 and HLA class I alleles were assessed in 118 individuals from Western Australia and Switzerland with chronic hepatitis C infection, of whom 82 (69%) were coinfected with human immunodeficiency virus. The levels and locations of amino acid polymorphisms exhibited within NS3 were remarkably similar between the two cohorts and revealed regions under functional constraint and selective pressures. We identified specific HCV mutations within and flanking published epitopes with the correct HLA restriction and predicted escaped amino acid. Additional HLA-restricted mutations were identified that mark putative epitopes targeted by cell-mediated immune responses. This analysis of host-virus interaction reveals evidence of HCV adaptation to HLA class I-restricted immune pressure and identifies in vivo targets of cellular immune responses at the population level.

Pancreatic carcinoma, pancreatitis, and healthy controls: metabolite models in a three-class diagnostic dilemma

Metabolomics as one of the most rapidly growing technologies in the "-omics" field denotes the comprehensive analysis of low molecular-weight compounds and their pathways. Cancer-specific alterations of the metabolome can be detected by high-throughput mass-spectrometric metabolite profiling and serve as a considerable source of new markers for the early differentiation of malignant diseases as well as their distinction from benign states. However, a comprehensive framework for the statistical evaluation of marker panels in a multi-class setting has not yet been established. We collected serum samples of 40 pancreatic carcinoma patients, 40 controls, and 23 pancreatitis patients according to standard protocols and generated amino acid profiles by routine mass-spectrometry. In an intrinsic three-class bioinformatic approach we compared these profiles, evaluated their selectivity and computed multi-marker panels combined with the conventional tumor marker CA 19-9. Additionally, we tested for non-inferiority and superiority to determine the diagnostic surplus value of our multi-metabolite marker panels. Compared to CA 19-9 alone, the combined amino acid-based metabolite panel had a superior selectivity for the discrimination of healthy controls, pancreatitis, and pancreatic carcinoma patients [Formula: see text] We combined highly standardized samples, a three-class study design, a high-throughput mass-spectrometric technique, and a comprehensive bioinformatic framework to identify metabolite panels selective for all three groups in a single approach. Our results suggest that metabolomic profiling necessitates appropriate evaluation strategies and-despite all its current limitations-can deliver marker panels with high selectivity even in multi-class settings.

Multivariate modelling of responses to conditional items: New possibilities for latent class analysis

Questionnaire data may contain missing values because certain questions do not apply to all respondents. For instance, questions addressing particular attributes of a symptom, such as frequency, triggers or seasonality, are only applicable to those who have experienced the symptom, while for those who have not, responses to these items will be missing. This missing information does not fall into the category 'missing by design', rather the features of interest do not exist and cannot be measured regardless of survey design. Analysis of responses to such conditional items is therefore typically restricted to the subpopulation in which they apply. This article is concerned with joint multivariate modelling of responses to both unconditional and conditional items without restricting the analysis to this subpopulation. Such an approach is of interest when the distributions of both types of responses are thought to be determined by common parameters affecting the whole population. By integrating the conditional item structure into the model, inference can be based both on unconditional data from the entire population and on conditional data from subjects for whom they exist. This approach opens new possibilities for multivariate analysis of such data. We apply this approach to latent class modelling and provide an example using data on respiratory symptoms (wheeze and cough) in children. Conditional data structures such as that considered here are common in medical research settings and, although our focus is on latent class models, the approach can be applied to other multivariate models.

Push-out bond strength of CAD/CAM-ceramic luted to dentin with self-adhesive resin cements

OBJECTIVES: This study evaluated the initial and the artificially aged push-out bond strength between ceramic and dentin produced by one of five resin cements. METHODS: Two-hundred direct ceramic restorations (IPS Empress CAD) were luted to standardized Class I cavities in extracted human molars using one of four self-adhesive cements (SpeedCEM, RelyX Unicem Aplicap, SmartCem2 and iCEM) or a reference etch-and-rinse resin cement (Syntac/Variolink II) (n=40/cement). Push-out bond strength (PBS) was measured (1) after 24h water storage (non-aged group; n=20/cement) or (2) after artificial ageing with 5000 thermal cycles followed by 6 months humid storage (aged group; n=20/cement). Nonparametrical ANOVA and pairwise Wilcoxon rank-sum tests with Bonferroni-Holm adjustment were applied for statistical analysis. The significance level was set at alpha=0.05. In addition, failure mode and fracture pattern were analyzed by stereomicroscope and scanning electron microscopy. RESULTS: Whereas no statistically significant effect of storage condition was found (p=0.441), there was a significant effect of resin cement (p<0.0001): RelyX Unicem showed significantly higher PBS than the other cements. Syntac/Variolink II showed significantly higher PBS than SmartCEM2 (p<0.001). No significant differences were found between SpeedCEM, SmartCem2, and iCEM. The predominant failure mode was adhesive failure of cements at the dentin interface except for RelyX Unicem which in most cases showed cohesive failure in ceramic. SIGNIFICANCE: The resin cements showed marked differences in push-out bond strength when used for luting ceramic restorations to dentin. Variolink II with the etch-and-rinse adhesive Syntac did not perform better than three of the four self-adhesive resin cements tested.

Avoiding misclassification bias with the traditional Charnley classification: rationale for a fourth Charnley class BB

Long-term follow up of patients with total hip arthroplasty (THA) revealed a marked deterioration of walking capacities in Charnley class B after postoperative year 4. We hypothesized that a specific group of patients, namely those with unilateral hip arthroplasty and an untreated but affected contralateral hip was responsible for this observation. Therefore, we conducted a study taking into consideration the two subclasses that make up Charnley class B: patients with unilateral THA and contralateral hip disease and patients with bilateral THA. A sample of 15,160 patients with 35,773 follow ups that were prospectively collected over 10 years was evaluated. The sample was categorized into four classes according to a new modified Charnley classification. Annual analyses of the proportion of patients with ambulation longer than 60 min were conducted. The traditionally labeled Charnley class B consists of two very different patient groups with respect to their walking capacities. Those with unilateral THA and contralateral hip disease have underaverage walking capacities and a deterioration of ambulation beginning 3 to 4 years after surgery. Those with bilateral THA have stable overaverage walking capacities similar to Charnley class A. An extension of the traditional Charnley classification is proposed, taking into account the two different patient groups in Charnley class B. The new fourth Charnley class consists of patients with bilateral THA and was labeled BB in order to express the presence of two artificial hip joints and to preserve the traditional classification A through C.

Evaluation of texture features in hepatic tissue characterization from non-enhanced CT images

Aim of this paper is to evaluate the diagnostic contribution of various types of texture features in discrimination of hepatic tissue in abdominal non-enhanced Computed Tomography (CT) images. Regions of Interest (ROIs) corresponding to the classes: normal liver, cyst, hemangioma, and hepatocellular carcinoma were drawn by an experienced radiologist. For each ROI, five distinct sets of texture features are extracted using First Order Statistics (FOS), Spatial Gray Level Dependence Matrix (SGLDM), Gray Level Difference Method (GLDM), Laws' Texture Energy Measures (TEM), and Fractal Dimension Measurements (FDM). In order to evaluate the ability of the texture features to discriminate the various types of hepatic tissue, each set of texture features, or its reduced version after genetic algorithm based feature selection, was fed to a feed-forward Neural Network (NN) classifier. For each NN, the area under Receiver Operating Characteristic (ROC) curves (Az) was calculated for all one-vs-all discriminations of hepatic tissue. Additionally, the total Az for the multi-class discrimination task was estimated. The results show that features derived from FOS perform better than other texture features (total Az: 0.802+/-0.083) in the discrimination of hepatic tissue.

Code-specific learning rules improve action selection by populations of spiking neurons

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

Adherence as a Predictor of the Development of Class-Specific Resistance Mutations: The Swiss HIV Cohort Study

Background Non-adherence is one of the strongest predictors of therapeutic failure in HIV-positive patients. Virologic failure with subsequent emergence of resistance reduces future treatment options and long-term clinical success. Methods Prospective observational cohort study including patients starting new class of antiretroviral therapy (ART) between 2003 and 2010. Participants were naïve to ART class and completed ≥1 adherence questionnaire prior to resistance testing. Outcomes were development of any IAS-USA, class-specific, or M184V mutations. Associations between adherence and resistance were estimated using logistic regression models stratified by ART class. Results Of 314 included individuals, 162 started NNRTI and 152 a PI/r regimen. Adherence was similar between groups with 85% reporting adherence ≥95%. Number of new mutations increased with increasing non-adherence. In NNRTI group, multivariable models indicated a significant linear association in odds of developing IAS-USA (odds ratio (OR) 1.66, 95% confidence interval (CI): 1.04-2.67) or class-specific (OR 1.65, 95% CI: 1.00-2.70) mutations. Levels of drug resistance were considerably lower in PI/r group and adherence was only significantly associated with M184V mutations (OR 8.38, 95% CI: 1.26-55.70). Adherence was significantly associated with HIV RNA in PI/r but not NNRTI regimens. Conclusion Therapies containing PI/r appear more forgiving to incomplete adherence compared with NNRTI regimens, which allow higher levels of resistance, even with adherence above 95%. However, in failing PI/r regimens good adherence may prevent accumulation of further resistance mutations and therefore help to preserve future drug options. In contrast, adherence levels have little impact on NNRTI treatments once the first mutations have emerged.

Atmospheric CO₂ response to volcanic eruptions: The role of ENSO, season, and variability

Tropical explosive volcanism is one of the most important natural factors that significantly impact the climate system and the carbon cycle on annual to multi-decadal time scales. The three largest explosive eruptions in the last 50�years�Agung, El Chichón, and Pinatubo�occurred in spring/summer in conjunction with El Niño events and left distinct negative signals in the observational temperature and CO2 records. However, confounding factors such as seasonal variability and El Niño-Southern Oscillation (ENSO) may obscure the forcing-response relationship. We determine for the first time the extent to which initial conditions, i.e., season and phase of the ENSO, and internal variability influence the coupled climate and carbon cycle response to volcanic forcing and how this affects estimates of the terrestrial and oceanic carbon sinks. Ensemble simulations with the Earth System Model (Climate System Model 1.4-carbon) predict that the atmospheric CO2 response is �60 larger when a volcanic eruption occurs during El Niño and in winter than during La Niña conditions. Our simulations suggest that the Pinatubo eruption contributed 11�±�6 to the 25�Pg terrestrial carbon sink inferred over the decade 1990�1999 and �2�±�1 to the 22�Pg oceanic carbon sink. In contrast to recent claims, trends in the airborne fraction of anthropogenic carbon cannot be detected when accounting for the decadal-scale influence of explosive volcanism and related uncertainties. Our results highlight the importance of considering the role of natural variability in the carbon cycle for interpretation of observations and for data-model intercomparison.

Reversal of gender differences in Educational Attainment – historical analysis of the West German Case

Background information: During the late 1970s and the early 1980s, West Germany witnessed a reversal of gender differences in educational attainment, as females began to outperform males. Purpose: The main objective was to analyse which processes were behind the reversal of gender differences in educational attainment after 1945. The theoretical reflections and empirical evidence presented for the US context by DiPrete and Buchmann (Gender-specific trends in the value of education and the emerging gender gap in college completion, Demography 43: 1–24, 2006) and Buchmann, DiPrete, and McDaniel (Gender inequalities in education, Annual Review of Sociology 34: 319–37, 2008) are considered and applied to the West German context. It is suggested that the reversal of gender differences is a consequence of the change in female educational decisions, which are mainly related to labour market opportunities and not, as sometimes assumed, a consequence of a ‘boy’s crisis’. Sample: Several databases, such as the German General Social Survey, the German Socio-economic Panel and the German Life History Study, are employed for the longitudinal analysis of the educational and occupational careers of birth cohorts born in the twentieth century. Design and methods: Changing patterns of eligibility for university studies are analysed for successive birth cohorts and gender. Binary logistic regressions are employed for the statistical modelling of the individuals’ achievement, educational decision and likelihood for social mobility – reporting average marginal effects (AME). Results: The empirical results suggest that women’s better school achievement being constant across cohorts does not contribute to the explanation of the reversal of gender differences in higher education attainment, but the increase of benefits for higher education explains the changing educational decisions of women regarding their transition to higher education. Conclusions: The outperformance of females compared with males in higher education might have been initialised by several social changes, including the expansion of public employment, the growing demand for highly qualified female workers in welfare and service areas, the increasing returns of women’s increased education and training, and the improved opportunities for combining family and work outside the home. The historical data show that, in terms of (married) women’s increased labour market opportunities and female life-cycle labour force participation, the raising rates of women’s enrolment in higher education were – among other reasons – partly explained by their rising access to service class positions across birth cohorts, and the rise of their educational returns in terms of wages and long-term employment.

A new measure for party coherence: Applying a physics-based concept to the Swiss party system

The paper revives a theoretical definition of party coherence as being composed of two basic elements, cohesion and factionalism, to propose and apply a novel empirical measure based on spin physics. The simultaneous analysis of both components using a single measurement concept is applied to data representing the political beliefs of candidates in the Swiss general elections of 2003 and 2007, proposing a connection between the coherence of the beliefs party members hold and the assessment of parties being at risk of splitting. We also compare our measure with established polarization measures and demonstrate its advantage with respect to multi-dimensional data that lack clear structure. Furthermore, we outline how our analysis supports the distinction between bottom-up and top-down mechanisms of party splitting. In this way, we are able to turn the intuition of coherence into a defined quantitative concept that, additionally, offers a methodological basis for comparative research of party coherence. Our work serves as an example of how a complex systems approach allows to get a new perspective on a long-standing issue in political science.

Stable carbon and oxygen isotopes in tree rings show physiological responses of Pericopsis elata to precipitation in the Congo Basin

In equatorial regions, where tree rings are less distinct or even absent, the response of forests to high-frequency climate variability is poorly understood. We measured stable carbon and oxygen isotopes in anatomically distinct, annual growth rings of four Pericopsis elata trees from a plantation in the Congo Basin, to assess their sensitivity to recorded changes in precipitation over the last 50 y. Our results suggest that oxygen isotopes have high common signal strength (EPS = 0.74), and respond to multi-annual precipitation variability at the regional scale, with low δ18O values (28–29‰) during wetter conditions (1960–1970). Conversely, δ13C are mostly related to growth variation, which in a light-demanding species are driven by competition for light. Differences in δ13C values between fast- and slow-growing trees (c. 2‰), result in low common signal strength (EPS = 0.37) and are driven by micro-site conditions rather than by climate. This study highlights the potential for understanding the causes of growth variation in P. elata as well as past hydroclimatic changes, in a climatically complex region characterized by a bimodal distribution in precipitation.