What interventions facilitate client progress through the assimilation model? A task analysis of interventions in the psychodynamic treatment of depression.

A variation of task analysis was used to build an empirical model of how therapists may facilitate client assimilation process, described in the Assimilation of Problematic Experiences Scale. A rational model was specified and considered in light of an analysis of therapist in-session performances (N = 117) drawn from six inpatient therapies for depression. The therapist interventions were measured by the Comprehensive Psychotherapeutic Interventions Rating Scale. Consistent with the rational model, confronting interventions were particularly useful in helping clients elaborate insight. However, rather than there being a small number of progress-related interventions at lower levels of assimilation, therapists' use of interventions was broader than hypothesized and drew from a wide range of therapeutic approaches. Concerning the higher levels of assimilation, there was insufficient data to allow an analysis of the therapist's progress-related interventions.

Automatic Segmentation of the Eye in 3D Magnetic Resonance Imaging: A Novel Statistical Shape Model for Treatment Planning of Retinoblastoma.

PURPOSE: Proper delineation of ocular anatomy in 3-dimensional (3D) imaging is a big challenge, particularly when developing treatment plans for ocular diseases. Magnetic resonance imaging (MRI) is presently used in clinical practice for diagnosis confirmation and treatment planning for treatment of retinoblastoma in infants, where it serves as a source of information, complementary to the fundus or ultrasonographic imaging. Here we present a framework to fully automatically segment the eye anatomy for MRI based on 3D active shape models (ASM), and we validate the results and present a proof of concept to automatically segment pathological eyes. METHODS AND MATERIALS: Manual and automatic segmentation were performed in 24 images of healthy children's eyes (3.29 ± 2.15 years of age). Imaging was performed using a 3-T MRI scanner. The ASM consists of the lens, the vitreous humor, the sclera, and the cornea. The model was fitted by first automatically detecting the position of the eye center, the lens, and the optic nerve, and then aligning the model and fitting it to the patient. We validated our segmentation method by using a leave-one-out cross-validation. The segmentation results were evaluated by measuring the overlap, using the Dice similarity coefficient (DSC) and the mean distance error. RESULTS: We obtained a DSC of 94.90 ± 2.12% for the sclera and the cornea, 94.72 ± 1.89% for the vitreous humor, and 85.16 ± 4.91% for the lens. The mean distance error was 0.26 ± 0.09 mm. The entire process took 14 seconds on average per eye. CONCLUSION: We provide a reliable and accurate tool that enables clinicians to automatically segment the sclera, the cornea, the vitreous humor, and the lens, using MRI. We additionally present a proof of concept for fully automatically segmenting eye pathology. This tool reduces the time needed for eye shape delineation and thus can help clinicians when planning eye treatment and confirming the extent of the tumor.

Supporting Business Model Modelling: a Compromise between Creativity and Constraints

Diagrams and tools help to support task modelling in engi- neering and process management. Unfortunately they are unfit to help in a business context at a strategic level, because of the flexibility needed for creative thinking and user friendly interactions. We propose a tool which bridges the gap between freedom of actions, encouraging creativity, and constraints, allowing validation and advanced features.

Data Envelopment Analysis and non-discretionary inputs : How to select the most suitable model using multi-criteria decision analysis

Within Data Envelopment Analysis, several alternative models allow for an environmental adjustment. The majority of them deliver divergent results. Decision makers face the difficult task of selecting the most suitable model. This study is performed to overcome this difficulty. By doing so, it fills a research gap. First, a two-step web-based survey is conducted. It aims (1) to identify the selection criteria, (2) to prioritize and weight the selection criteria with respect to the goal of selecting the most suitable model and (3) to collect the preferences about which model is preferable to fulfil each selection criterion. Second, Analytic Hierarchy Process is used to quantify the preferences expressed in the survey. Results show that the understandability, the applicability and the acceptability of the alternative models are valid selection criteria. The selection of the most suitable model depends on the preferences of the decision makers with regards to these criteria.

Modelling the curing process in magneto-sensitive polymers: Rate-dependence and shrinkage

This paper deals with a phenomenologically motivated magneto-viscoelastic coupled finite strain framework for simulating the curing process of polymers under the application of a coupled magneto-mechanical road. Magneto-sensitive polymers are prepared by mixing micron-sized ferromagnetic particles in uncured polymers. Application of a magnetic field during the curing process causes the particles to align and form chain-like structures lending an overall anisotropy to the material. The polymer curing is a viscoelastic complex process where a transformation from fluid. to solid occurs in the course of time. During curing, volume shrinkage also occurs due to the packing of polymer chains by chemical reactions. Such reactions impart a continuous change of magneto-mechanical properties that can be modelled by an appropriate constitutive relation where the temporal evolution of material parameters is considered. To model the shrinkage during curing, a magnetic-induction-dependent approach is proposed which is based on a multiplicative decomposition of the deformation gradient into a mechanical and a magnetic-induction-dependent volume shrinkage part. The proposed model obeys the relevant laws of thermodynamics. Numerical examples, based on a generalised Mooney-Rivlin energy function, are presented to demonstrate the model capacity in the case of a magneto-viscoelastically coupled load.

A multistep process of cancer associated fibroblasts determination under CSL-p53 control

Stromal fibroblast senescence has been linked to the aging-associated increase of tumors. However, in epithelial cancer, density and proliferation of cancer associated fibroblasts (CAF) are frequently increased, rather than decreased. We previously showed that genetic deletion or down-modulation of the canonical Notch effector CSL/RBP-JK in dermal fibroblasts is sufficient for CAF activation with consequent development of keratinocyte-derived tumors. We show here that CSL silencing induces senescence of primary fibroblasts from dermis, oral mucosa, breast and lung. CSL functions in these cells as direct repressor of multiple senescence- and CAF-effector genes. It also physically interacts with p53, repressing its activity. CSL is down-modulated in stromal fibroblasts of premalignant skin actinic keratosis lesions and squamous cell carcinomas (SCC), while p53 gene expression and function is down-modulated only in the latter, with paracrine influences of incipient cancer cells as a likely culprit. Concomitant loss of CSL and p53 overcomes fibroblast senescence, enhances CAF effector gene expression and promotes stromal and cancer cell expansion. The findings support a CAF activation/stromal co-evolution model under convergent CSL/p53 control of likely clinical relevance.

A statistical shape model of the human second cervical vertebra.

PURPOSE: Statistical shape and appearance models play an important role in reducing the segmentation processing time of a vertebra and in improving results for 3D model development. Here, we describe the different steps in generating a statistical shape model (SSM) of the second cervical vertebra (C2) and provide the shape model for general use by the scientific community. The main difficulties in its construction are the morphological complexity of the C2 and its variability in the population. METHODS: The input dataset is composed of manually segmented anonymized patient computerized tomography (CT) scans. The alignment of the different datasets is done with the procrustes alignment on surface models, and then, the registration is cast as a model-fitting problem using a Gaussian process. A principal component analysis (PCA)-based model is generated which includes the variability of the C2. RESULTS: The SSM was generated using 92 CT scans. The resulting SSM was evaluated for specificity, compactness and generalization ability. The SSM of the C2 is freely available to the scientific community in Slicer (an open source software for image analysis and scientific visualization) with a module created to visualize the SSM using Statismo, a framework for statistical shape modeling. CONCLUSION: The SSM of the vertebra allows the shape variability of the C2 to be represented. Moreover, the SSM will enable semi-automatic segmentation and 3D model generation of the vertebra, which would greatly benefit surgery planning.

Immune Memory and Exhaustion: Clinically Relevant Lessons from the LCMV Model.

The development of dysfunctional or exhausted T cells is characteristic of immune responses to chronic viral infections and cancer. Exhausted T cells are defined by reduced effector function, sustained upregulation of multiple inhibitory receptors, an altered transcriptional program and perturbations of normal memory development and homeostasis. This review focuses on (a) illustrating milestone discoveries that led to our present understanding of T cell exhaustion, (b) summarizing recent developments in the field, and (c) identifying new challenges for translational research. Exhausted T cells are now recognized as key therapeutic targets in human infections and cancer. Much of our knowledge of the clinically relevant process of exhaustion derives from studies in the mouse model of Lymphocytic choriomeningitis virus (LCMV) infection. Studies using this model have formed the foundation for our understanding of human T cell memory and exhaustion. We will use this example to discuss recent advances in our understanding of T cell exhaustion and illustrate the value of integrated mouse and human studies and will emphasize the benefits of bi-directional mouse-to-human and human-to-mouse research approaches.

The effect of learning on the evolution of new courtship behavior: a simulation model

The fact that individuals learn can change the relationship between genotype and phenotype in the population, and thus affect the evolutionary response to selection. Here we ask how male ability to learn from female response affects the evolution of a novel male behavioral courtship trait under pre-existing female preference (sensory drive). We assume a courtship trait which has both a genetic and a learned component, and a two-level female response to males. With individual-based simulations we show that, under this scenario, learning generally increases the strength of selection on the genetic component of the courtship trait, at least when the population genetic mean is still low. As a consequence, learning not only accelerates the evolution of the courtship trait, but also enables it when the trait is costly, which in the absence of learning results in an adaptive valley. Furthermore, learning can enable the evolution of the novel trait in the face of gene flow mediated by immigration of males that show superior attractiveness to females based on another, non-heritable trait. However, rather than increasing monotonically with the speed of learning, the effect of learning on evolution is maximized at intermediate learning rates. This model shows that, at least under some scenarios, the ability to learn can drive the evolution of mating behaviors through a process equivalent to Waddington's genetic assimilation.

How to Model Heterogeneity in Costly Punishment: Insights from Responders' Response Times

We investigate what processes may underlie heterogeneity in social preferences. We address this question by examining participants' decisions and associated response times across 12 mini-ultimatum games. Using a finite mixture model and cross-validating its classification with a response time analysis, we identified four groups of responders: one group takes little to no account of the proposed split or the foregone allocation and swiftly accepts any positive offer; two groups process primarily the objective properties of the allocations (fairness and kindness) and need more time the more properties need to be examined; and a fourth group, which takes more time than the others, appears to take into account what they would have proposed had they been put in the role of the proposer. We discuss implications of this joint decision-response time analysis.

The forced adoption of a fast-track appraisal process for a breast cancer treatment in UK

Trastuzumab (Herceptin ®, Roche) is approved in UK for the treatment of the metastatic breast cancer since 2001. As of 2005, concomitantly with the publication of 3 studies that showed it produces a 50% reduction of the recurrence rates of breast cancer, trastuzumab started to be prescribed in the earlt adjuvant treatrnent of this disease. Und June 2006, trastuzumab did not have both: 1) regulatory approval and 2) NICE [National Institute for Health and Clinical Excellence] recommendation for the use in early stages of breast cancer. During the period until June 2006, the trastuzumab use in those patients was not reimbursed and because the cost of trastuzumab is equal with the yearly UK average income, most of patients could not self fund their treatrnent. Before the publication of the final NICE guidance, the new data of trastuzumab in early breast cancer raised enormous patient and professional interest and expectations. A great volume of public and professional pressure was generated to transcend a system by which Primary Care Trusts can reimburse a treatment only after a formal guidance was issued. This paper draw on a case study depicting and analyzing the process by which regulatory approval and NICE recommendations were achieved in a record time and how trastuzumab became a standard treatment on early adjuvant breast cancer. According to the data we gathered in this work we were witnessing one of the fastest processes of adoption of a health care technology since the creation of NICE, in 1999. This study addresses the following research question: How and why does the adoption pattern of trastuzumab differ from the rational decision-making model of the reimbursement process in UK? [Author, p. 4]