Copper and human health: biochemistry, genetics, and strategies for modeling dose-response relationships

Copper (Cu) and its alloys are used extensively in domestic and industrial applications. Cu is also an essential element in mammalian nutrition. Since both copper deficiency and copper excess produce adverse health effects, the dose-response curve is U-shaped, although the precise form has not yet been well characterized. Many animal and human studies were conducted on copper to provide a rich database from which data suitable for modeling the dose-response relationship for copper may be extracted. Possible dose-response modeling strategies are considered in this review, including those based on the benchmark dose and categorical regression. The usefulness of biologically based dose-response modeling techniques in understanding copper toxicity was difficult to assess at this time since the mechanisms underlying copper-induced toxicity have yet to be fully elucidated. A dose-response modeling strategy for copper toxicity was proposed associated with both deficiency and excess. This modeling strategy was applied to multiple studies of copper-induced toxicity, standardized with respect to severity of adverse health outcomes and selected on the basis of criteria reflecting the quality and relevance of individual studies. The use of a comprehensive database on copper-induced toxicity is essential for dose-response modeling since there is insufficient information in any single study to adequately characterize copper dose-response relationships. The dose-response modeling strategy envisioned here is designed to determine whether the existing toxicity data for copper excess or deficiency may be effectively utilized in defining the limits of the homeostatic range in humans and other species. By considering alternative techniques for determining a point of departure and low-dose extrapolation (including categorical regression, the benchmark dose, and identification of observed no-effect levels) this strategy will identify which techniques are most suitable for this purpose. This analysis also serves to identify areas in which additional data are needed to better define the characteristics of dose-response relationships for copper-induced toxicity in relation to excess or deficiency.

In-plane thermal conductivity modeling of carbon filled liquid crystal polymer based resins

Adding conductive carbon fillers to insulating thermoplastic resins increases composite electrical and thermal conductivity. Often, as much of a single type of carbon filler is added to achieve the desired conductivity, while still allowing the material to be molded into a bipolar plate for a fuel cell. In this study, varying amounts of three different carbons (carbon black, synthetic graphite particles, and carbon fiber) were added to Vectra A950RX Liquid Crystal Polymer. The in-plane thermal conductivity of the resulting single filler composites were tested. The results showed that adding synthetic graphite particles caused the largest increase in the in-plane thermal conductivity of the composite. The composites were modeled using ellipsoidal inclusion problems to predict the effective in-plane thermal conductivities at varying volume fractions with only physical property data of constituents. The synthetic graphite and carbon black were modeled using the average field approximation with ellipsoidal inclusions and the model showed good agreement with the experimental data. The carbon fiber polymer composite was modeled using an assemblage of coated ellipsoids and the model showed good agreement with the experimental data.

Erythropoietin or Darbepoetin for patients with cancer--meta-analysis based on individual patient data

BACKGROUND: Erythropoiesis-stimulating agents (ESAs) reduce anemia in cancer patients and may improve quality of life, but there are concerns that ESAs might increase mortality. OBJECTIVES: Our objectives were to examine the effect of ESAs and identify factors that modify the effects of ESAs on overall survival, progression free survival, thromboembolic and cardiovascular events as well as need for transfusions and other important safety and efficacy outcomes in cancer patients. SEARCH STRATEGY: We searched the Cochrane Library, Medline, Embase and conference proceedings for eligible trials. Manufacturers of ESAs were contacted to identify additional trials. SELECTION CRITERIA: We included randomized controlled trials comparing epoetin or darbepoetin plus red blood cell transfusions (as necessary) versus red blood cell transfusions (as necessary) alone, to prevent or treat anemia in adult or pediatric cancer patients with or without concurrent antineoplastic therapy. DATA COLLECTION AND ANALYSIS: We performed a meta-analysis of randomized controlled trials comparing epoetin alpha, epoetin beta or darbepoetin alpha plus red blood cell transfusions versus transfusion alone, for prophylaxis or therapy of anemia while or after receiving anti-cancer treatment. Patient-level data were obtained and analyzed by independent statisticians at two academic departments, using fixed-effects and random-effects meta-analysis. Analyses were according to the intention-to-treat principle. Primary endpoints were on study mortality and overall survival during the longest available follow-up, regardless of anticancer treatment, and in patients receiving chemotherapy. Tests for interactions were used to identify differences in effects of ESAs on mortality across pre-specified subgroups. The present review reports only the results for the primary endpoint. MAIN RESULTS: A total of 13933 cancer patients from 53 trials were analyzed, 1530 patients died on-study and 4993 overall. ESAs increased on study mortality (combined hazard ratio [cHR] 1.17; 95% CI 1.06-1.30) and worsened overall survival (cHR 1.06; 95% CI 1.00-1.12), with little heterogeneity between trials (I(2) 0%, p=0.87 and I(2) 7.1%, p=0.33, respectively). Thirty-eight trials enrolled 10441 patients receiving chemotherapy. The cHR for on study mortality was 1.10 (95% CI 0.98-1.24) and 1.04; 95% CI 0.97-1.11) for overall survival. There was little evidence for a difference between trials of patients receiving different cancer treatments (P for interaction=0.42). AUTHORS' CONCLUSIONS: ESA treatment in cancer patients increased on study mortality and worsened overall survival. For patients undergoing chemotherapy the increase was less pronounced, but an adverse effect could not be excluded.

The Assessment of Multiple Processes Underlying the Attentional Blink: A Fixed - links Modeling Approach based on Behavioral and Electrophysiological Data

When observers are presented with two visual targets appearing in the same position in close temporal proximity, a marked reduction in detection performance of the second target has often been reported, the so-called attentional blink phenomenon. Several studies found a similar decrement of P300 amplitudes during the attentional blink period as observed with detection performances of the second target. However, whether the parallel courses of second target performances and corresponding P300 amplitudes resulted from the same underlying mechanisms remained unclear. The aim of our study was therefore to investigate whether the mechanisms underlying the AB can be assessed by fixed-links modeling and whether this kind of assessment would reveal the same or at least related processes in the behavioral and electrophysiological data. On both levels of observation three highly similar processes could be identified: an increasing, a decreasing and a u-shaped trend. Corresponding processes from the behavioral and electrophysiological data were substantially correlated, with the two u-shaped trends showing the strongest association with each other. Our results provide evidence for the assumption that the same mechanisms underlie attentional blink task performance at the electrophysiological and behavioral levels as assessed by fixed-links models.

Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

Volcanic forcing for climate modeling: a new microphysics-based data set covering years 1600–present

As the understanding and representation of the impacts of volcanic eruptions on climate have improved in the last decades, uncertainties in the stratospheric aerosol forcing from large eruptions are now linked not only to visible optical depth estimates on a global scale but also to details on the size, latitude and altitude distributions of the stratospheric aerosols. Based on our understanding of these uncertainties, we propose a new model-based approach to generating a volcanic forcing for general circulation model (GCM) and chemistry–climate model (CCM) simulations. This new volcanic forcing, covering the 1600–present period, uses an aerosol microphysical model to provide a realistic, physically consistent treatment of the stratospheric sulfate aerosols. Twenty-six eruptions were modeled individually using the latest available ice cores aerosol mass estimates and historical data on the latitude and date of eruptions. The evolution of aerosol spatial and size distribution after the sulfur dioxide discharge are hence characterized for each volcanic eruption. Large variations are seen in hemispheric partitioning and size distributions in relation to location/date of eruptions and injected SO2 masses. Results for recent eruptions show reasonable agreement with observations. By providing these new estimates of spatial distributions of shortwave and long-wave radiative perturbations, this volcanic forcing may help to better constrain the climate model responses to volcanic eruptions in the 1600–present period. The final data set consists of 3-D values (with constant longitude) of spectrally resolved extinction coefficients, single scattering albedos and asymmetry factors calculated for different wavelength bands upon request. Surface area densities for heterogeneous chemistry are also provided.

Time-Series Panel Analysis (TSPA): Multivariate Modeling of Temporal Associations in Psychotherapy Process.

Objective: Processes occurring in the course of psychotherapy are characterized by the simple fact that they unfold in time and that the multiple factors engaged in change processes vary highly between individuals (idiographic phenomena). Previous research, however, has neglected the temporal perspective by its traditional focus on static phenomena, which were mainly assessed at the group level (nomothetic phenomena). To support a temporal approach, the authors introduce time-series panel analysis (TSPA), a statistical methodology explicitly focusing on the quantification of temporal, session-to-session aspects of change in psychotherapy. TSPA-models are initially built at the level of individuals and are subsequently aggregated at the group level, thus allowing the exploration of prototypical models. Method: TSPA is based on vector auto-regression (VAR), an extension of univariate auto-regression models to multivariate time-series data. The application of TSPA is demonstrated in a sample of 87 outpatient psychotherapy patients who were monitored by postsession questionnaires. Prototypical mechanisms of change were derived from the aggregation of individual multivariate models of psychotherapy process. In a 2nd step, the associations between mechanisms of change (TSPA) and pre- to postsymptom change were explored. Results: TSPA allowed a prototypical process pattern to be identified, where patient's alliance and self-efficacy were linked by a temporal feedback-loop. Furthermore, therapist's stability over time in both mastery and clarification interventions was positively associated with better outcomes. Conclusions: TSPA is a statistical tool that sheds new light on temporal mechanisms of change. Through this approach, clinicians may gain insight into prototypical patterns of change in psychotherapy.

Individual group efficacy beliefs and performance motivation: A mediational approach

Introduction: According to the theoretical model of Cranach, Ochsenbein, and Valach (1986) understanding group actions needs consideration of aspects at both the group level and the level of individual members. For example individual action units constituting group actions are motivated at the individual level while potentially being affected by characteristics of the group. Theoretically, group efficacy beliefs could be a part of this motivational process as they are an individual’s cognitive contents about group-level abilities to perform well in a specific task. Positive relations between group level efficacy-beliefs and group performance have been reported and Bandura and Locke (2003) argue that this relationship is being mediated by motivational processes and goal setting. The aims of this study were a) to examine the effects of group characteristics on individual performance motivation and b) to test if those are mediated by individual group efficacy beliefs. Methods: Forty-seven students (M=22.83 years, SD=2.83, 34% women) of the university of Berne participated in this scenario based experiment. Data were collected on two collection points. Subjects were provided information about fictive team members with whom they had to perform a group triathlon. Three values (low, medium, high) of the other team members’ abilities to perform in their parts of the triathlon (swimming and biking respectively) were combined in a 3x3 full factorial design (Anderson, 1982) yielding nine groups. Subjects were asked how confident they were that the teams would perform well in the task (individual group efficacy beliefs), and to provide information about their motivation to perform at their best in the respective group contexts (performance motivation). Multilevel modeling (Mplus) was used to estimate the effects of the factors swim and bike, and the context-varying covariate individual group efficacy beliefs on performance motivation. Further analyses were undertaken to test if the effects of group contexts on performance motivation are mediated by individual group efficacy beliefs. Results: Significant effects were reported for both the group characteristics (βswim = 7.86; βbike = 8.57; both p < .001) and the individual group efficacy beliefs (βigeb; .40, p < .001) on performance motivation. The subsequent mediation model indicated that the effects of group characteristics on performance motivation were partly mediated by the individual group efficacy beliefs of the subjects with significant mediation effects for both factors swim and bike. Discussion/Conclusion: The results of the study provide further support for the motivational character of efficacy beliefs and point out a mechanism by which team characteristics influence performance relevant factors at the level of individual team members. The study indicates that high team abilities lead to augmented performance motivation, adding a psychological advantage to teams already high on task relevant abilities. Future investigations will be aiming at possibilities to keep individual performance motivation high in groups with low task relevant abilities. One possibility could be the formulation of individual task goals. References: Anderson, N. H. (1982). Methods of information integration theory. New York: Academic Press. Bandura, A. & Locke, E. A. (2003). Negative self-efficacy and goal effects revisited. Journal of Applied Psychology, 88, 87-99. Cranach, M. von, Ochsenbein, G. & Valach, L. (1986). The group as a self-active system: Outline of a theory of group action. European Journal of Social Psychology, 16, 193-229.

Achieving a more realistic assessment of rockfall hazards by coupling three-dimensional process models and field-based tree-ring data

Sound knowledge of the spatial and temporal patterns of rockfalls is fundamental for the management of this very common hazard in mountain environments. Process-based, three-dimensional simulation models are nowadays capable of reproducing the spatial distribution of rockfall occurrences with reasonable accuracy through the simulation of numerous individual trajectories on highly-resolved digital terrain models. At the same time, however, simulation models typically fail to quantify the ‘real’ frequency of rockfalls (in terms of return intervals). The analysis of impact scars on trees, in contrast, yields real rockfall frequencies, but trees may not be present at the location of interest and rare trajectories may not necessarily be captured due to the limited age of forest stands. In this article, we demonstrate that the coupling of modeling with tree-ring techniques may overcome the limitations inherent to both approaches. Based on the analysis of 64 cells (40 m × 40 m) of a rockfall slope located above a 1631-m long road section in the Swiss Alps, we illustrate results from 488 rockfalls detected in 1260 trees. We illustrate that tree impact data cannot only be used (i) to reconstruct the real frequency of rockfalls for individual cells, but that they also serve (ii) the calibration of the rockfall model Rockyfor3D, as well as (iii) the transformation of simulated trajectories into real frequencies. Calibrated simulation results are in good agreement with real rockfall frequencies and exhibit significant differences in rockfall activity between the cells (zones) along the road section. Real frequencies, expressed as rock passages per meter road section, also enable quantification and direct comparison of the hazard potential between the zones. The contribution provides an approach for hazard zoning procedures that complements traditional methods with a quantification of rockfall frequencies in terms of return intervals through a systematic inclusion of impact records in trees.

VIRTOPSY--scientific documentation, reconstruction and animation in forensic: individual and real 3D data based geo-metric approach including optical body/object surface and radiological CT/MRI scanning.

Until today, most of the documentation of forensic relevant medical findings is limited to traditional 2D photography, 2D conventional radiographs, sketches and verbal description. There are still some limitations of the classic documentation in forensic science especially if a 3D documentation is necessary. The goal of this paper is to demonstrate new 3D real data based geo-metric technology approaches. This paper present approaches to a 3D geo-metric documentation of injuries on the body surface and internal injuries in the living and deceased cases. Using modern imaging methods such as photogrammetry, optical surface and radiological CT/MRI scanning in combination it could be demonstrated that a real, full 3D data based individual documentation of the body surface and internal structures is possible in a non-invasive and non-destructive manner. Using the data merging/fusing and animation possibilities, it is possible to answer reconstructive questions of the dynamic development of patterned injuries (morphologic imprints) and to evaluate the possibility, that they are matchable or linkable to suspected injury-causing instruments. For the first time, to our knowledge, the method of optical and radiological 3D scanning was used to document the forensic relevant injuries of human body in combination with vehicle damages. By this complementary documentation approach, individual forensic real data based analysis and animation were possible linking body injuries to vehicle deformations or damages. These data allow conclusions to be drawn for automobile accident research, optimization of vehicle safety (pedestrian and passenger) and for further development of crash dummies. Real 3D data based documentation opens a new horizon for scientific reconstruction and animation by bringing added value and a real quality improvement in forensic science.

A fixed-links modeling approach to assess individual differences in the attentional blink: Analysis of behavioral and psychophysiological data

The attentional blink (AB) is a fundamental limitation of the ability to select relevant information from irrelevant information. It can be observed with the detection rate in an AB task as well as with the corresponding P300 amplitude of the event-related potential. In previous research, however, correlations between these two levels of observation were weak and rather inconsistent. A possible explanation of this finding might be that multiple processes underlie the AB and, thus, obscure a possible relationship between AB-related detection rate and the corresponding P300 amplitude. The present study investigated this assumption by applying a fixed-links modeling approach to represent behavioral individual differences in the AB as a latent variable. Concurrently, this approach enabled us to control for additional sources of variance in AB performance by deriving two additional latent variables. The correlation between the latent variable reflecting behavioral individual differences in AB magnitude and a corresponding latent variable derived from the P300 amplitude was high (r=.70). Furthermore, this correlation was considerably stronger than the correlations of other behavioral measures of the AB magnitude with their psychophysiological counterparts (all rs<.40). Our findings clearly indicate that the systematic disentangling of various sources of variance by utilizing the fixed-links modeling approach is a promising tool to investigate behavioral individual differences in the AB and possible psychophysiological correlates of these individual differences.

A sorrow shared is a sorrow halved? Internet-based group therapy versus individual therapy for social anxiety disorder: A randomized controlled trial

Purpose: Social anxiety disorder is one of the most researched conditions in the field of Internet-based self-help. Various studies have shown that cognitive-behavioral treatments can be efficacious to reduce social phobic symptoms. Most of the interventions tested include some form of support, whereas the efficacy of a web-based group format has yet to be investigated. The present study aims at investigating the possible added value of therapist-guided group support in an Internet-based guided self-help treatment for SAD. Methods: A total of 150 adults with a diagnosis of SAD are randomly assigned to either a wait-list control group or one of two active treatment conditions. Participants in the two active conditions use the same Internet-based self-help program, either with individual guidance by a therapist or with the support of a therapist-guided group of 6 individuals. In the group condition, participants communicate with each other via an integrated, protected discussion forum. The primary outcome variables are symptoms of SAD and diagnostic status immediately after the intervention (12 weeks) and at 6-month follow-up. Secondary endpoints are general symptomatology, depression, quality of life and adherence to treatment. Furthermore, process variables such as group processes and the working alliance are studied. Results: Results are currently being analyzed. Results at post-treatment will be presented and discussed. Potential moderating and mediating variables of treatment success will be addressed. Conclusion: The results of this study should indicate whether therapist-guided group support could enhance the efficacy of an internet based self-help treatment for SAD. This novel treatment format, if shown efficacious, could represent a cost-effective option and could be further modified to treat other conditions.