What are the implications of changing treatment delivery models for patients with inflammatory bowel disease: a discussion paper.

An integrated model of care has been used effectively to manage chronic diseases; however, there is limited, yet encouraging evidence on its introduction in the management of inflammatory bowel disease (IBD), a chronic gastrointestinal condition. Here, the rationale for and implications of introducing an integrated model of care for patients with IBD are discussed, with a particular focus on psychology input, patient-centred care, efficiency as perceived by patients and doctors, financial implications and the possible means of model introduction. This is a discussion paper on the integrated model of care for IBD against a background of what has been learned from an integrated model of care established in other chronic conditions. Although limited, the emerging data on an integrated model of care in IBD are encouraging with respect to patient outcomes and savings in healthcare costs. In other conditions, the model has been well received by both patients and practitioners, although the loss of autonomy by doctors is listed among its drawbacks. The cost-effectiveness data are now sufficiently convincing to recommend the model's acceptance in principle. The model should be promoted at the policy level rather than by individual practitioners to facilitate equal access for patients with IBD on a larger scale than currently.

Linking local knowledge, conservation practices and ecosystem diversity: comparing two communities in the Tunari National Park (Bolivia)

Combined approaches to conserve both biological and cultural diversity are seen as an alternative to classical nature conservation instruments. The objective of this study was to examine the influence of urbanization coupled with exclusive conservation measures, on land use, local knowledge and biodiversity in two Quechua speaking communities of Bolivia located within the Tunari National Park. We assessed and compared the links between land use, its transformation through conservation practices, local institutions and the worldviews of both communities and the implications they have for biodiversity at the level of ecosystems. Our results show that in both communities, people’s worldviews and environmental knowledge are linked with an integral and diversified use of their territory. However, the community most affected by urbanization and protected area regulations has intensified agriculture in a small area and has abandoned the use of large areas. This was accompanied by a loss of local environmental knowledge and a decrease in the diversity of ecosystems. The second community, where the park was not enforced, continues to manage their territory as a material expression of local environmental knowledge, while adopting community-based conservation measures with external support. Our findings highlight a case in which urbanization coupled with exclusive conservation approaches affects the components of both cultural and biological diversity. Actions that aim to enhance biocultural diversity in this context should therefore address the impact of factors identified as responsible for change in integrated social-ecological systems.

Lobe specific Ca2+-calmodulin nano-domain in neuronal spines: a single molecule level analysis.

Calmodulin (CaM) is a ubiquitous Ca(2+) buffer and second messenger that affects cellular function as diverse as cardiac excitability, synaptic plasticity, and gene transcription. In CA1 pyramidal neurons, CaM regulates two opposing Ca(2+)-dependent processes that underlie memory formation: long-term potentiation (LTP) and long-term depression (LTD). Induction of LTP and LTD require activation of Ca(2+)-CaM-dependent enzymes: Ca(2+)/CaM-dependent kinase II (CaMKII) and calcineurin, respectively. Yet, it remains unclear as to how Ca(2+) and CaM produce these two opposing effects, LTP and LTD. CaM binds 4 Ca(2+) ions: two in its N-terminal lobe and two in its C-terminal lobe. Experimental studies have shown that the N- and C-terminal lobes of CaM have different binding kinetics toward Ca(2+) and its downstream targets. This may suggest that each lobe of CaM differentially responds to Ca(2+) signal patterns. Here, we use a novel event-driven particle-based Monte Carlo simulation and statistical point pattern analysis to explore the spatial and temporal dynamics of lobe-specific Ca(2+)-CaM interaction at the single molecule level. We show that the N-lobe of CaM, but not the C-lobe, exhibits a nano-scale domain of activation that is highly sensitive to the location of Ca(2+) channels, and to the microscopic injection rate of Ca(2+) ions. We also demonstrate that Ca(2+) saturation takes place via two different pathways depending on the Ca(2+) injection rate, one dominated by the N-terminal lobe, and the other one by the C-terminal lobe. Taken together, these results suggest that the two lobes of CaM function as distinct Ca(2+) sensors that can differentially transduce Ca(2+) influx to downstream targets. We discuss a possible role of the N-terminal lobe-specific Ca(2+)-CaM nano-domain in CaMKII activation required for the induction of synaptic plasticity.

Molecular cross talk between misfolded proteins in animal models of Alzheimer's and prion diseases.

The central event in protein misfolding disorders (PMDs) is the accumulation of a misfolded form of a naturally expressed protein. Despite the diversity of clinical symptoms associated with different PMDs, many similarities in their mechanism suggest that distinct pathologies may cross talk at the molecular level. The main goal of this study was to analyze the interaction of the protein misfolding processes implicated in Alzheimer's and prion diseases. For this purpose, we inoculated prions in an Alzheimer's transgenic mouse model that develop typical amyloid plaques and followed the progression of pathological changes over time. Our findings show a dramatic acceleration and exacerbation of both pathologies. The onset of prion disease symptoms in transgenic mice appeared significantly faster with a concomitant increase on the level of misfolded prion protein in the brain. A striking increase in amyloid plaque deposition was observed in prion-infected mice compared with their noninoculated counterparts. Histological and biochemical studies showed the association of the two misfolded proteins in the brain and in vitro experiments showed that protein misfolding can be enhanced by a cross-seeding mechanism. These results suggest a profound interaction between Alzheimer's and prion pathologies, indicating that one protein misfolding process may be an important risk factor for the development of a second one. Our findings may have important implications to understand the origin and progression of PMDs.

Values of children and family models of adolescents: An eleven-culture study

Starting from Kagitcibasi's (2007) conceptualization of family models, this study compared N = 2961 adolescents' values across eleven cultures and explored whether patterns of values were related to the three proposed family models through cluster analyses. Three clusters with value profiles corresponding to the family models of interdependence, emotional interdependence, and independence were identified on the cultural as well as on the individual level. Furthermore, individual-level clusters corresponded to culture-level clusters in terms of individual cluster membership. The results largely support Kagitcibasi's proposition of changing family models and demonstrate their representation as individual-level value profiles across cultures.

Design and analysis for three level hierarchical structures with count response

In numerous intervention studies and education field trials, random assignment to treatment occurs in clusters rather than at the level of observation. This departure of random assignment of units may be due to logistics, political feasibility, or ecological validity. Data within the same cluster or grouping are often correlated. Application of traditional regression techniques, which assume independence between observations, to clustered data produce consistent parameter estimates. However such estimators are often inefficient as compared to methods which incorporate the clustered nature of the data into the estimation procedure (Neuhaus 1993).1 Multilevel models, also known as random effects or random components models, can be used to account for the clustering of data by estimating higher level, or group, as well as lower level, or individual variation. Designing a study, in which the unit of observation is nested within higher level groupings, requires the determination of sample sizes at each level. This study investigates the design and analysis of various sampling strategies for a 3-level repeated measures design on the parameter estimates when the outcome variable of interest follows a Poisson distribution. ^ Results study suggest that second order PQL estimation produces the least biased estimates in the 3-level multilevel Poisson model followed by first order PQL and then second and first order MQL. The MQL estimates of both fixed and random parameters are generally satisfactory when the level 2 and level 3 variation is less than 0.10. However, as the higher level error variance increases, the MQL estimates become increasingly biased. If convergence of the estimation algorithm is not obtained by PQL procedure and higher level error variance is large, the estimates may be significantly biased. In this case bias correction techniques such as bootstrapping should be considered as an alternative procedure. For larger sample sizes, those structures with 20 or more units sampled at levels with normally distributed random errors produced more stable estimates with less sampling variance than structures with an increased number of level 1 units. For small sample sizes, sampling fewer units at the level with Poisson variation produces less sampling variation, however this criterion is no longer important when sample sizes are large. ^ 1Neuhaus J (1993). “Estimation efficiency and Tests of Covariate Effects with Clustered Binary Data”. Biometrics , 49, 989–996^

Sequential updating via dynamic hierarchical models: A Bayesian approach to longitudinal data analysis

Most statistical analysis, theory and practice, is concerned with static models; models with a proposed set of parameters whose values are fixed across observational units. Static models implicitly assume that the quantified relationships remain the same across the design space of the data. While this is reasonable under many circumstances this can be a dangerous assumption when dealing with sequentially ordered data. The mere passage of time always brings fresh considerations and the interrelationships among parameters, or subsets of parameters, may need to be continually revised. ^ When data are gathered sequentially dynamic interim monitoring may be useful as new subject-specific parameters are introduced with each new observational unit. Sequential imputation via dynamic hierarchical models is an efficient strategy for handling missing data and analyzing longitudinal studies. Dynamic conditional independence models offers a flexible framework that exploits the Bayesian updating scheme for capturing the evolution of both the population and individual effects over time. While static models often describe aggregate information well they often do not reflect conflicts in the information at the individual level. Dynamic models prove advantageous over static models in capturing both individual and aggregate trends. Computations for such models can be carried out via the Gibbs sampler. An application using a small sample repeated measures normally distributed growth curve data is presented. ^

Effect of nonnormal random components on level and power in group-randomized trials

The use of group-randomized trials is particularly widespread in the evaluation of health care, educational, and screening strategies. Group-randomized trials represent a subset of a larger class of designs often labeled nested, hierarchical, or multilevel and are characterized by the randomization of intact social units or groups, rather than individuals. The application of random effects models to group-randomized trials requires the specification of fixed and random components of the model. The underlying assumption is usually that these random components are normally distributed. This research is intended to determine if the Type I error rate and power are affected when the assumption of normality for the random component representing the group effect is violated. ^ In this study, simulated data are used to examine the Type I error rate, power, bias and mean squared error of the estimates of the fixed effect and the observed intraclass correlation coefficient (ICC) when the random component representing the group effect possess distributions with non-normal characteristics, such as heavy tails or severe skewness. The simulated data are generated with various characteristics (e.g. number of schools per condition, number of students per school, and several within school ICCs) observed in most small, school-based, group-randomized trials. The analysis is carried out using SAS PROC MIXED, Version 6.12, with random effects specified in a random statement and restricted maximum likelihood (REML) estimation specified. The results from the non-normally distributed data are compared to the results obtained from the analysis of data with similar design characteristics but normally distributed random effects. ^ The results suggest that the violation of the normality assumption for the group component by a skewed or heavy-tailed distribution does not appear to influence the estimation of the fixed effect, Type I error, and power. Negative biases were detected when estimating the sample ICC and dramatically increased in magnitude as the true ICC increased. These biases were not as pronounced when the true ICC was within the range observed in most group-randomized trials (i.e. 0.00 to 0.05). The normally distributed group effect also resulted in bias ICC estimates when the true ICC was greater than 0.05. However, this may be a result of higher correlation within the data. ^

Portfolio-optimization models for small investors

Since 2010, the client base of online-trading service providers has grown significantly. Such companies enable small investors to access the stock market at advantageous rates. Because small investors buy and sell stocks in moderate amounts, they should consider fixed transaction costs, integral transaction units, and dividends when selecting their portfolio. In this paper, we consider the small investor’s problem of investing capital in stocks in a way that maximizes the expected portfolio return and guarantees that the portfolio risk does not exceed a prescribed risk level. Portfolio-optimization models known from the literature are in general designed for institutional investors and do not consider the specific constraints of small investors. We therefore extend four well-known portfolio-optimization models to make them applicable for small investors. We consider one nonlinear model that uses variance as a risk measure and three linear models that use the mean absolute deviation from the portfolio return, the maximum loss, and the conditional value-at-risk as risk measures. We extend all models to consider piecewise-constant transaction costs, integral transaction units, and dividends. In an out-of-sample experiment based on Swiss stock-market data and the cost structure of the online-trading service provider Swissquote, we apply both the basic models and the extended models; the former represent the perspective of an institutional investor, and the latter the perspective of a small investor. The basic models compute portfolios that yield on average a slightly higher return than the portfolios computed with the extended models. However, all generated portfolios yield on average a higher return than the Swiss performance index. There are considerable differences between the four risk measures with respect to the mean realized portfolio return and the standard deviation of the realized portfolio return.

Evaluating the Quality and Accuracy of TanDEM-X Digital Elevation Models at Archaeological Sites in the Cilician Plain, Turkey

Satellite remote sensing provides a powerful instrument for mapping and monitoring traces of historical settlements and infrastructure, not only in distant areas and crisis regions. It helps archaeologists to embed their findings from field surveys into the broader context of the landscape. With the start of the TanDEM-X mission, spatially explicit 3D-information is available to researchers at an unprecedented resolution worldwide. We examined different experimental TanDEM-X digital elevation models (DEM) that were processed from two different imaging modes (Stripmap/High Resolution Spotlight) using the operational alternating bistatic acquisition mode. The quality and accuracy of the experimental DEM products was compared to other available DEM products and a high precision archaeological field survey. The results indicate the potential of TanDEM-X Stripmap (SM) data for mapping surface elements at regional scale. For the alluvial plain of Cilicia, a suspected palaeochannel could be reconstructed. At the local scale, DEM products from TanDEM-X High Resolution Spotlight (HS) mode were processed at 2 m spatial resolution using a merge of two monostatic/bistatic interferograms. The absolute and relative vertical accuracy of the outcome meet the specification of high resolution elevation data (HRE) standards from the National System for Geospatial Intelligence (NSG) at the HRE20 level.

Predicting 3-year mortality after percutaneous coronary intervention: updated logistic clinical SYNTAX score based on patient-level data from 7 contemporary stent trials

OBJECTIVES This study aimed to update the Logistic Clinical SYNTAX score to predict 3-year survival after percutaneous coronary intervention (PCI) and compare the performance with the SYNTAX score alone. BACKGROUND The SYNTAX score is a well-established angiographic tool to predict long-term outcomes after PCI. The Logistic Clinical SYNTAX score, developed by combining clinical variables with the anatomic SYNTAX score, has been shown to perform better than the SYNTAX score alone in predicting 1-year outcomes after PCI. However, the ability of this score to predict long-term survival is unknown. METHODS Patient-level data (N = 6,304, 399 deaths within 3 years) from 7 contemporary PCI trials were analyzed. We revised the overall risk and the predictor effects in the core model (SYNTAX score, age, creatinine clearance, and left ventricular ejection fraction) using Cox regression analysis to predict mortality at 3 years. We also updated the extended model by combining the core model with additional independent predictors of 3-year mortality (i.e., diabetes mellitus, peripheral vascular disease, and body mass index). RESULTS The revised Logistic Clinical SYNTAX models showed better discriminative ability than the anatomic SYNTAX score for the prediction of 3-year mortality after PCI (c-index: SYNTAX score, 0.61; core model, 0.71; and extended model, 0.73 in a cross-validation procedure). The extended model in particular performed better in differentiating low- and intermediate-risk groups. CONCLUSIONS Risk scores combining clinical characteristics with the anatomic SYNTAX score substantially better predict 3-year mortality than the SYNTAX score alone and should be used for long-term risk stratification of patients undergoing PCI.

General distress, hopelessness—suicidal ideation and worrying in adolescence: Concurrent and predictive validity of a symptom-level bifactor model for clinical diagnoses

BACKGROUND: Clinical disorders often share common symptoms and aetiological factors. Bifactor models acknowledge the role of an underlying general distress component and more specific sub-domains of psychopathology which specify the unique components of disorders over and above a general factor. METHODS: A bifactor model jointly calibrated data on subjective distress from The Mood and Feelings Questionnaire and the Revised Children's Manifest Anxiety Scale. The bifactor model encompassed a general distress factor, and specific factors for (a) hopelessness-suicidal ideation, (b) generalised worrying and (c) restlessness-fatigue at age 14 which were related to lifetime clinical diagnoses established by interviews at ages 14 (concurrent validity) and current diagnoses at 17 years (predictive validity) in a British population sample of 1159 adolescents. RESULTS: Diagnostic interviews confirmed the validity of a symptom-level bifactor model. The underlying general distress factor was a powerful but non-specific predictor of affective, anxiety and behaviour disorders. The specific factors for hopelessness-suicidal ideation and generalised worrying contributed to predictive specificity. Hopelessness-suicidal ideation predicted concurrent and future affective disorder; generalised worrying predicted concurrent and future anxiety, specifically concurrent generalised anxiety disorders. Generalised worrying was negatively associated with behaviour disorders. LIMITATIONS: The analyses of gender differences and the prediction of specific disorders was limited due to a low frequency of disorders other than depression. CONCLUSIONS: The bifactor model was able to differentiate concurrent and predict future clinical diagnoses. This can inform the development of targeted as well as non-specific interventions for prevention and treatment of different disorders.

Preclinical studies identify non-apoptotic low-level caspase-3 as therapeutic target in pemphigus vulgaris

The majority of pemphigus vulgaris (PV) patients suffer from a live-threatening loss of intercellular adhesion between keratinocytes (acantholysis). The disease is caused by auto-antibodies that bind to desmosomal cadherins desmoglein (Dsg) 3 or Dsg3 and Dsg1 in mucous membranes and skin. A currently unresolved controversy in PV is whether apoptosis is involved in the pathogenic process. The objective of this study was to perform preclinical studies to investigate apoptotic pathway activation in PV pathogenesis with the goal to assess its potential for clinical therapy. For this purpose, we investigated mouse and human skin keratinocyte cultures treated with PV antibodies (the experimental Dsg3 monospecific antibody AK23 or PV patients IgG), PV mouse models (passive transfer of AK23 or PVIgG into adult and neonatal mice) as well as PV patients' biopsies (n=6). A combination of TUNEL assay, analyses of membrane integrity, early apoptotic markers such as cleaved poly-ADP-ribose polymerase (PARP) and the collapse of actin cytoskeleton failed to provide evidence for apoptosis in PV pathogenesis. However, the in vitro and in vivo PV models, allowing to monitor progression of lesion formation, revealed an early, transient and low-level caspase-3 activation. Pharmacological inhibition confirmed the functional implication of caspase-3 in major events in PV such as shedding of Dsg3, keratin retraction, proliferation including c-Myc induction, p38MAPK activation and acantholysis. Together, these data identify low-level caspase-3 activation downstream of disrupted Dsg3 trans- or cis-adhesion as a major event in PV pathogenesis that is non-synonymous with apoptosis and represents, unlike apoptotic components, a promising target for clinical therapy. At a broader level, these results posit that an impairment of adhesive functions in concert with low-level, non-lethal caspase-3 activation can evoke profound cellular changes which may be of relevance for other diseases including cancer.

"Of course I will...": The combined effect of certainty and level of expectancies on persistence and performance

The importance of performance expectancies for the prediction of regulation of behavior and actual performance has long been established. Building on theories from the field of social cognition, we suggest that the level of performance expectancies, as well as the certainty of the expectancy, have a joint influence on an individual’s beliefs and behavior. In two studies (one cross sectional using a sample of secondary school students and one longitudinal using a sample of university students) we found that expectancies more strongly predicted persistence, and subsequent performance, the more certain the expectancy was. This pattern was found even if prior performance was controlled, as in Study 2. The data give an indication that it may be useful to include certainty as an additional variable in expectancy models.

Cardiopulmonary Bypass has No Significant Impact on Survival in Patients Undergoing Nephrectomy and Level III-IV Inferior Vena Cava Thrombectomy. A Multi-Institutional Analysis.

PURPOSE The impact of cardiopulmonary bypass in level III-IV tumor thrombectomy on surgical and oncologic outcomes is unknown. We determine the impact of cardiopulmonary bypass on overall and cancer specific survival, as well as surgical complication rates and immediate outcomes in patients undergoing nephrectomy and level III-IV tumor thrombectomy with or without cardiopulmonary bypass. MATERIALS AND METHODS We retrospectively analyzed 362 patients with renal cell cancer and with level III or IV tumor thrombus from 1992 to 2012 at 22 U.S. and European centers. Cox proportional hazards models were used to compare overall and cancer specific survival between patients with and without cardiopulmonary bypass. Perioperative mortality and complication rates were assessed using logistic regression analyses. RESULTS Median overall survival was 24.6 months in noncardiopulmonary bypass cases and 26.6 months in cardiopulmonary bypass cases. Overall survival and cancer specific survival did not differ significantly in both groups on univariate analysis or when adjusting for known risk factors. On multivariate analysis no significant differences were seen in hospital length of stay, Clavien 1-4 complication rate, intraoperative or 30-day mortality and cancer specific survival. Limitations include the retrospective nature of the study. CONCLUSIONS In our multi-institutional analysis the use of cardiopulmonary bypass did not significantly impact cancer specific survival or overall survival in patients undergoing nephrectomy and level III or IV tumor thrombectomy. Neither approach was independently associated with increased mortality on multivariate analysis. Greater surgical complications were not independently associated with the use of cardiopulmonary bypass.