Effect of vascular targeting agent in rat tumor model: dynamic contrast-enhanced versus diffusion-weighted MR imaging

PURPOSE: To compare dynamic contrast material-enhanced magnetic resonance (MR) imaging and diffusion-weighted MR imaging for noninvasive evaluation of early and late effects of a vascular targeting agent in a rat tumor model. MATERIALS AND METHODS: The study protocol was approved by the local ethics committee for animal care and use. Thirteen rats with one rhabdomyosarcoma in each flank (26 tumors) underwent dynamic contrast-enhanced imaging and diffusion-weighted echo-planar imaging in a 1.5-T MR unit before intraperitoneal injection of combretastatin A4 phosphate and at early (1 and 6 hours) and later (2 and 9 days) follow-up examinations after the injection. Histopathologic examination was performed at each time point. The apparent diffusion coefficient (ADC) of each tumor was calculated separately on the basis of diffusion-weighted images obtained with low b gradient values (ADC(low); b = 0, 50, and 100 sec/mm(2)) and high b gradient values (ADC(high); b = 500, 750, and 1000 sec/mm(2)). The difference between ADC(low) and ADC(high) was used as a surrogate measure of tissue perfusion (ADC(low) - ADC(high) = ADC(perf)). From the dynamic contrast-enhanced MR images, the volume transfer constant k and the initial slope of the contrast enhancement-time curve were calculated. For statistical analyses, a paired two-tailed Student t test and linear regression analysis were used. RESULTS: Early after administration of combretastatin, all perfusion-related parameters (k, initial slope, and ADC(perf)) decreased significantly (P < .001); at 9 days after combretastatin administration, they increased significantly (P < .001). Changes in ADC(perf) were correlated with changes in k (R(2) = 0.46, P < .001) and the initial slope (R(2) = 0.67, P < .001). CONCLUSION: Both dynamic contrast-enhanced MR imaging and diffusion-weighted MR imaging allow monitoring of perfusion changes induced by vascular targeting agents in tumors. Diffusion-weighted imaging provides additional information about intratumoral cell viability versus necrosis after administration of combretastatin.

Effects of GDNF pretreatment on function and survival of transplanted fetal ventral mesencephalic cells in the 6-OHDA rat model of Parkinson's disease

Transplantation of fetal dopaminergic (DA) neurons offers an experimental therapy for Parkinson's disease (PD). The low availability and the poor survival and integration of transplanted cells in the host brain are major obstacles in this approach. Glial cell line-derived neurotrophic factor (GDNF) is a potent neurotrophic factor with growth- and survival-promoting capabilities for developing DA neurons. In the present study, we examined whether pretreatment of ventral mesencephalic (VM) free-floating roller tube (FFRT) cultures with GDNF would improve graft survival and function. For that purpose organotypic cultures of E14 rat VM were grown for 2, 4 or 8 days in the absence (control) or presence of GDNF [10 ng/ml] and transplanted into the striatum of 6-hydroxydopamine-lesioned rats. While all groups of rats showed a significant reduction in d-amphetamine-induced rotations at 6 weeks posttransplantation a significantly improved graft function was observed only in the days in vitro (DIV) 4 GDNF pretreated group compared to the control group. In addition, no statistical significant differences between groups were found in the number of surviving tyrosine hydroxylase-immunoreactive (TH-ir) neurons assessed at 9 weeks posttransplantation. However, a tendency for higher TH-ir fiber outgrowth from the transplants in the GDNF pretreated groups as compared to corresponding controls was observed. Furthermore, GDNF pretreatment showed a tendency for a higher number of GIRK2 positive neurons in the grafts. In sum, our findings demonstrate that GDNF pretreatment was not disadvantageous for transplants of embryonic rat VM with the FFRT culture technique but only marginally improved graft survival and function.

Datenanalyse. Das Null-Ritual und der Umgang mit Effekten in der Zeitschrift für Sportpsychologie

Ziel dieses Beitrages ist die Analyse der Anwendung empirischer Tests in der deutschsprachigen Sportpsychologie. Die Ergebnisse vergleichbarer Analysen, bspw. in der Psychologie, zeigen, dass zwischen Anforderungen aus Testkonzepten und empirischer Realität Unterschiede existieren, die bislang für die Sportpsychologie nicht beschrieben und bewertet worden sind. Die Jahrgänge 1994–2007 der Zeitschrift für Sportpsychologie (früher psychologie und sport) wurden danach untersucht, ob Forschungsfragen formuliert, welche Stichprobenart gewählt, welches Testkonzept verwendet, welches Signifikanzniveau benutzt und ob statistische Probleme diskutiert wurden. 83 Artikel wurden von zwei unabhängigen Bewertern nach diesen Aspekten kategorisiert. Als Ergebnis ist festzuhalten, dass in der sportpsychologischen Forschung überwiegend eine Mischung aus Fishers Signifikanztesten sowie Neyman-Pearsons-Hypothesentesten zur Anwendung kommt,das sogenannte „Hybrid-Modell” oder „Null-Ritual”. Die Beschreibung der Teststärke ist kaum zu beobachten. Eine zeitliche Analyse der Beiträge zeigt, dass vor allem die Benutzung von Effektgrößen in den letzten Jahren zugenommen hat. Abschließend werden Ansätze zur Verbesserung und der Vereinheitlichung der Anwendung empirischer Tests vorgeschlagen und diskutiert.

Model-Centric, Context-Aware Software Adaptation

Software must be constantly adapted to changing requirements. The time scale, abstraction level and granularity of adaptations may vary from short-term, fine-grained adaptation to long-term, coarse-grained evolution. Fine-grained, dynamic and context-dependent adaptations can be particularly difficult to realize in long-lived, large-scale software systems. We argue that, in order to effectively and efficiently deploy such changes, adaptive applications must be built on an infrastructure that is not just model-driven, but is both model-centric and context-aware. Specifically, this means that high-level, causally-connected models of the application and the software infrastructure itself should be available at run-time, and that changes may need to be scoped to the run-time execution context. We first review the dimensions of software adaptation and evolution, and then we show how model-centric design can address the adaptation needs of a variety of applications that span these dimensions. We demonstrate through concrete examples how model-centric and context-aware designs work at the level of application interface, programming language and runtime. We then propose a research agenda for a model-centric development environment that supports dynamic software adaptation and evolution.

Meta-Environment and Executable Meta-Language using Smalltalk: an Experience Report

Object-oriented modelling languages such as EMOF are often used to specify domain specific meta-models. However, these modelling languages lack the ability to describe behavior or operational semantics. Several approaches have used a subset of Java mixed with OCL as executable meta-languages. In this experience report we show how we use Smalltalk as an executable meta-language in the context of the Moose reengineering environment. We present how we implemented EMOF and its behavioral aspects. Over the last decade we validated this approach through incrementally building a meta-described reengineering environment. Such an approach bridges the gap between a code-oriented view and a meta-model driven one. It avoids the creation of yet another language and reuses the infrastructure and run-time of the underlying implementation language. It offers an uniform way of letting developers focus on their tasks while at the same time allowing them to meta-describe their domain model. The advantage of our approach is that developers use the same tools and environment they use for their regular tasks. Still the approach is not Smalltalk specific but can be applied to language offering an introspective API such as Ruby, Python, CLOS, Java and C#.

A model of osteoporosis impact in Switzerland 2000-2020

The aim of our study was to develop a modeling framework suitable to quantify the incidence, absolute number and economic impact of osteoporosis-attributable hip, vertebral and distal forearm fractures, with a particular focus on change over time, and with application to the situation in Switzerland from 2000 to 2020. A Markov process model was developed and analyzed by Monte Carlo simulation. A demographic scenario provided by the Swiss Federal Statistical Office and various Swiss and international data sources were used as model inputs. Demographic and epidemiologic input parameters were reproduced correctly, confirming the internal validity of the model. The proportion of the Swiss population aged 50 years or over will rise from 33.3% in 2000 to 41.3% in 2020. At the total population level, osteoporosis-attributable incidence will rise from 1.16 to 1.54 per 1,000 person-years in the case of hip fracture, from 3.28 to 4.18 per 1,000 person-years in the case of radiographic vertebral fracture, and from 0.59 to 0.70 per 1,000 person-years in the case of distal forearm fracture. Osteoporosis-attributable hip fracture numbers will rise from 8,375 to 11,353, vertebral fracture numbers will rise from 23,584 to 30,883, and distal forearm fracture numbers will rise from 4,209 to 5,186. Population-level osteoporosis-related direct medical inpatient costs per year will rise from 713.4 million Swiss francs (CHF) to CHF946.2 million. These figures correspond to 1.6% and 2.2% of Swiss health care expenditures in 2000. The modeling framework described can be applied to a wide variety of settings. It can be used to assess the impact of new prevention, diagnostic and treatment strategies. In Switzerland incidences of osteoporotic hip, vertebral and distal forearm fracture will rise by 33%, 27%, and 19%, respectively, between 2000 and 2020, if current prevention and treatment patterns are maintained. Corresponding absolute fracture numbers will rise by 36%, 31%, and 23%. Related direct medical inpatient costs are predicted to increase by 33%; however, this estimate is subject to uncertainty due to limited availability of input data.

The (2 + 1)-d U (1) quantum link model masquerading as deconfined criticality

The (2 + 1)-d U(1) quantum link model is a gauge theory, amenable to quantum simulation, with a spontaneously broken SO(2) symmetry emerging at a quantum phase transition. Its low-energy physics is described by a (2 + 1)-d RP(1) effective field theory, perturbed by an SO(2) breaking operator, which prevents the interpretation of the emergent pseudo-Goldstone boson as a dual photon. At the quantum phase transition, the model mimics some features of deconfined quantum criticality, but remains linearly confining. Deconfinement only sets in at high temperature.

Using state variables to model the response of tumour cells to radiation and heat: a novel multi-hit-repair approach

In order to overcome the limitations of the linear-quadratic model and include synergistic effects of heat and radiation, a novel radiobiological model is proposed. The model is based on a chain of cell populations which are characterized by the number of radiation induced damages (hits). Cells can shift downward along the chain by collecting hits and upward by a repair process. The repair process is governed by a repair probability which depends upon state variables used for a simplistic description of the impact of heat and radiation upon repair proteins. Based on the parameters used, populations up to 4-5 hits are relevant for the calculation of the survival. The model describes intuitively the mathematical behaviour of apoptotic and nonapoptotic cell death. Linear-quadratic-linear behaviour of the logarithmic cell survival, fractionation, and (with one exception) the dose rate dependencies are described correctly. The model covers the time gap dependence of the synergistic cell killing due to combined application of heat and radiation, but further validation of the proposed approach based on experimental data is needed. However, the model offers a work bench for testing different biological concepts of damage induction, repair, and statistical approaches for calculating the variables of state.

Strategies to increase the use and approval of gender-fair language

When masculine forms are used to refer to men and women, this causes male-biased cognitive representations and behavioral consequences, as numerous studies have shown. This effect can be avoided or reduced with the help of gender-fair language. In this talk, we will present different approaches that aim at influencing people’s use of and attitudes towards gender-fair language. Firstly, we tested the influence of gender-fair input on people’s own use of gender-fair language. Based on Irmen and Linner’s (2005) adaptation of the scenario mapping and focus approach (Sanford & Garrod, 1998), we found that after reading a text with gender-fair forms women produced more gender-fair forms than women who read gender-neutral texts or texts containing masculine generics. Men were not affected. Secondly, we examined reactions to arguments which followed the Elaboration Likelihood Model (Petty &Cacioppo, 1986). We assumed that strong pros and cons would be more effective than weak arguments or control statements. The results indicated that strong pros could convince some, but not all participants, suggesting a complex interplay of diverse factors in reaction to attempts at persuasion. The influence of people’s initial characteristics will be discussed. Currently, we are investigating how self-generated refutations, in addition to arguments, may influence initial attitudes. Based on the resistance appraisal hypothesis (Tormala, 2008), we assume that individuals are encouraged in their initial attitude if they manage to refute strong counter-arguments. The results of our studies will be discussed regarding their practical implications.

Image-based vs. mesh-based statistical appearance models of the human femur: Implications for finite element simulations.

Statistical appearance models have recently been introduced in bone mechanics to investigate bone geometry and mechanical properties in population studies. The establishment of accurate anatomical correspondences is a critical aspect for the construction of reliable models. Depending on the representation of a bone as an image or a mesh, correspondences are detected using image registration or mesh morphing. The objective of this study was to compare image-based and mesh-based statistical appearance models of the femur for finite element (FE) simulations. To this aim, (i) we compared correspondence detection methods on bone surface and in bone volume; (ii) we created an image-based and a mesh-based statistical appearance models from 130 images, which we validated using compactness, representation and generalization, and we analyzed the FE results on 50 recreated bones vs. original bones; (iii) we created 1000 new instances, and we compared the quality of the FE meshes. Results showed that the image-based approach was more accurate in volume correspondence detection and quality of FE meshes, whereas the mesh-based approach was more accurate for surface correspondence detection and model compactness. Based on our results, we recommend the use of image-based statistical appearance models for FE simulations of the femur.

Pangea: A Workbench for Statically Analyzing Multi-Language Software Corpora

Software corpora facilitate reproducibility of analyses, however, static analysis for an entire corpus still requires considerable effort, often duplicated unnecessarily by multiple users. Moreover, most corpora are designed for single languages increasing the effort for cross-language analysis. To address these aspects we propose Pangea, an infrastructure allowing fast development of static analyses on multi-language corpora. Pangea uses language-independent meta-models stored as object model snapshots that can be directly loaded into memory and queried without any parsing overhead. To reduce the effort of performing static analyses, Pangea provides out-of-the box support for: creating and refining analyses in a dedicated environment, deploying an analysis on an entire corpus, using a runner that supports parallel execution, and exporting results in various formats. In this tool demonstration we introduce Pangea and provide several usage scenarios that illustrate how it reduces the cost of analysis.

Multi-Environment Model Estimation for Motility Analysis of Caernorhabditis elegans

The nematode Caenorhabditis elegans is a well-known model organism used to investigate fundamental questions in biology. Motility assays of this small roundworm are designed to study the relationships between genes and behavior. Commonly, motility analysis is used to classify nematode movements and characterize them quantitatively. Over the past years, C. elegans' motility has been studied across a wide range of environments, including crawling on substrates, swimming in fluids, and locomoting through microfluidic substrates. However, each environment often requires customized image processing tools relying on heuristic parameter tuning. In the present study, we propose a novel Multi-Environment Model Estimation (MEME) framework for automated image segmentation that is versatile across various environments. The MEME platform is constructed around the concept of Mixture of Gaussian (MOG) models, where statistical models for both the background environment and the nematode appearance are explicitly learned and used to accurately segment a target nematode. Our method is designed to simplify the burden often imposed on users; here, only a single image which includes a nematode in its environment must be provided for model learning. In addition, our platform enables the extraction of nematode ‘skeletons’ for straightforward motility quantification. We test our algorithm on various locomotive environments and compare performances with an intensity-based thresholding method. Overall, MEME outperforms the threshold-based approach for the overwhelming majority of cases examined. Ultimately, MEME provides researchers with an attractive platform for C. elegans' segmentation and ‘skeletonizing’ across a wide range of motility assays.

Consistent estimation of the fixed effects ordered logit model

The paper considers panel data methods for estimating ordered logit models with individual-specific correlated unobserved heterogeneity. We show that a popular approach is inconsistent, whereas some consistent and efficient estimators are available, including minimum distance and generalized method-of-moment estimators. A Monte Carlo study reveals the good properties of an alternative estimator that has not been considered in econometric applications before, is simple to implement and almost as efficient. An illustrative application based on data from the German Socio-Economic Panel confirms the large negative effect of unemployment on life satisfaction that has been found in the previous literature.

Beyond sexist beliefs: How do people decide to use gender-inclusive language?

When people use generic masculine language instead of more gender-inclusive forms, they communicate gender stereotypes and sometimes exclusion of women from certain social roles. Past research related gender-inclusive language use to sexist beliefs and attitudes. Given that this aspect of language use may be transparent to users, it is unclear whether people explicitly act on these beliefs when using gender-exclusive language forms or whether these are more implicit, habitual patterns. In two studies with German-speaking participants, we showed that spontaneous use of gender-inclusive personal nouns is guided by explicitly favorable intentions as well as habitual processes involving past use of such language. Further indicating the joint influence of deliberate and habitual processes, Study 2 revealed that language-use intentions are embedded in explicit sexist ideologies. As anticipated in our decision-making model, the effects of sexist beliefs on language emerged through deliberate mechanisms involving attitudes and intentions.