Mindfulness-based cognitive therapie for depression (MBCT) in clinical practice - baseline patient characteristics, process and outcome

Introduction: Mindfulness based cognitive therapy for depression (MBCT) has shown to be effective for the reduction of depressive relapse. However, additional information regarding baseline patient characteristics and process features related to positive response could be helpful both for the provision of MBCT in clinical practice, as well as for its further development. Method: Baseline characteristics, process data, and immediate outcome (symptom change, change in attitudes and trait mindfulness) of 108 patients receiving MBCT in routine care were recorded. A newly developed self-report measure (Daily Mindfulness Scale, DMS) was applied daily during the MBCT program. Additionally, patients filed daily reports on their mindfulness practice. There was no control group available. Results: Patients with more severe initial symptoms indicated greater amounts of symptom improvement, but did not show great rates of dropout from the MBCT intervention. Younger age was related to higher rates of dropout. Contradictory to some previous data, patients with lower levels of initial trait mindfulness showed greater improvement in symptoms, even after controlling for initial levels of symptoms. Adherence to daily mindfulness practice was high. Consistent with this result, the duration of daily mindfulness practice was not related to immediate outcome. Process studies using multivariate time series analysis revealed a specific role of daily mindfulness in reducing subsequent negative mood. Conclusions: Within the range of patient present in this study and the given study design, results support the use of MBCT in more heterogeneous groups. This demanding intervention was well tolerated by patients with higher levels of symptoms, and resulted in significant improvements regarding residual symptoms. Process-outcome analyses of initial trait mindfulness and daily mindfulness both support the crucial role of changes in mindfulness for the effects of MBCT.

Evidence Based Development of a Novel Lateral Fibula Plate (VariAx Fibula) Using a Real CT Bone Data Based Optimization Process During Device Development

Development of novel implants in orthopaedic trauma surgery is based on limited datasets of cadaver trials or artificial bone models. A method has been developed whereby implants can be constructed in an evidence based method founded on a large anatomic database consisting of more than 2.000 datasets of bones extracted from CT scans. The aim of this study was the development and clinical application of an anatomically pre-contoured plate for the treatment of distal fibular fractures based on the anatomical database. 48 Caucasian and Asian bone models (left and right) from the database were used for the preliminary optimization process and validation of the fibula plate. The implant was constructed to fit bilaterally in a lateral position of the fibula. Then a biomechanical comparison of the designed implant to the current gold standard in the treatment of distal fibular fractures (locking 1/3 tubular plate) was conducted. Finally, a clinical surveillance study to evaluate the grade of implant fit achieved was performed. The results showed that with a virtual anatomic database it was possible to design a fibula plate with an optimized fit for a large proportion of the population. Biomechanical testing showed the novel fibula plate to be superior to 1/3 tubular plates in 4-point bending tests. The clinical application showed a very high degree of primary implant fit. Only in a small minority of cases further intra-operative implant bending was necessary. Therefore, the goal to develop an implant for the treatment of distal fibular fractures based on the evidence of a large anatomical database could be attained. Biomechanical testing showed good results regarding the stability and the clinical application confirmed the high grade of anatomical fit.

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.

Finite element analysis of aortic root dilation: a new procedure to reproduce pathology based on experimental data

Sinotubular junction dilation is one of the most frequent pathologies associated with aortic root incompetence. Hence, we create a finite element model considering the whole root geometry; then, starting from healthy valve models and referring to measures of pathological valves reported in the literature, we reproduce the pathology of the aortic root by imposing appropriate boundary conditions. After evaluating the virtual pathological process, we are able to correlate dimensions of non-functional valves with dimensions of competent valves. Such a relation could be helpful in recreating a competent aortic root and, in particular, it could provide useful information in advance in aortic valve sparing surgery.

Tracing of 15N in a mountain spruce forest: comparison of experimental data with th TRACE model

Despite numerous studies about nitrogen-cycling in forest ecosystems, many uncertainties remain, especially regarding the longer-term nitrogen accumulation. To contribute to filling this gap, the dynamic process-based model TRACE, with the ability to simulate 15N tracer redistribution in forest ecosystems was used to study N cycling processes in a mountain spruce forest of the northern edge of the Alps in Switzerland (Alptal, SZ). Most modeling analyses of N-cycling and C-N interactions have very limited ability to determine whether the process interactions are captured correctly. Because the interactions in such a system are complex, it is possible to get the whole-system C and N cycling right in a model without really knowing if the way the model combines fine-scale interactions to derive whole-system cycling is correct. With the possibility to simulate 15N tracer redistribution in ecosystem compartments, TRACE features a very powerful tool for the validation of fine-scale processes captured by the model. We first adapted the model to the new site (Alptal, Switzerland; long-term low-dose N-amendment experiment) by including a new algorithm for preferential water flow and by parameterizing of differences in drivers such as climate, N deposition and initial site conditions. After the calibration of key rates such as NPP and SOM turnover, we simulated patterns of 15N redistribution to compare against 15N field observations from a large-scale labeling experiment. The comparison of 15N field data with the modeled redistribution of the tracer in the soil horizons and vegetation compartments shows that the majority of fine-scale processes are captured satisfactorily. Particularly, the model is able to reproduce the fact that the largest part of the N deposition is immobilized in the soil. The discrepancies of 15N recovery in the LF and M soil horizon can be explained by the application method of the tracer and by the retention of the applied tracer by the well developed moss layer, which is not considered in the model. Discrepancies in the dynamics of foliage and litterfall 15N recovery were also observed and are related to the longevity of the needles in our mountain forest. As a next step, we will use the final Alptal version of the model to calculate the effects of climate change (temperature, CO2) and N deposition on ecosystem C sequestration in this regionally representative Norway spruce (Picea abies) stand.

High-resolution computer simulation of the dynamics of isoelectric focusing using carrier ampholytes: focusing with concurrent electrophoretic mobilization is an isotachophoretic process

Focusing of four hemoglobins with concurrent electrophoretic mobilization was studied by computer simulation. A dynamic electrophoresis simulator was first used to provide a detailed description of focusing in a 100-carrier component, pH 6-8 gradient using phosphoric acid as anolyte and NaOH as catholyte. These results are compared to an identical simulation except that the catholyte contained both NaOH and NaCl. A stationary, steady-state distribution of carrier components and hemoglobins is produced in the first configuration. In the second, the chloride ion migrates into and through the separation space. It is shown that even under these conditions of chloride ion flux a pH gradient forms. All amphoteric species acquire a slight positive charge upon focusing and the whole pattern is mobilized towards the cathode. The cathodic gradient end is stable whereas the anodic end is gradually degrading due to the continuous accumulation of chloride. The data illustrate that the mobilization is a cationic isotachophoretic process with the sodium ion being the leading cation. The peak height of the hemoglobin zones decreases somewhat upon mobilization, but the zones retain a relatively sharp profile, thus facilitating detection. The electropherograms that would be produced by whole column imaging and by a single detector placed at different locations along the focusing column are presented and show that focusing can be commenced with NaCl present in the catholyte at the beginning of the experiment. However, this may require detector placement on the cathodic side of the catholyte/sample mixture interface.

Sedation and weaning from mechanical ventilation: effects of process optimization outside a clinical trial

PURPOSE: We studied the effects of reorganization and changes in the care process, including use of protocols for sedation and weaning from mechanical ventilation, on the use of sedative and analgesic drugs and on length of respiratory support and stay in the intensive care unit (ICU). MATERIALS AND METHODS: Three cohorts of 100 mechanically ventilated ICU patients, admitted in 1999 (baseline), 2000 (implementation I, after a change in ICU organization and in diagnostic and therapeutic approaches), and 2001 (implementation II, after introduction of protocols for weaning from mechanical ventilation and sedation), were studied retrospectively. RESULTS: Simplified Acute Physiology Score II (SAPS II), diagnostic groups, and number of organ failures were similar in all groups. Data are reported as median (interquartile range).Time on mechanical ventilation decreased from 18 (7-41) (baseline) to 12 (7-27) hours (implementation II) (P = .046), an effect which was entirely attributable to noninvasive ventilation, and length of ICU stay decreased in survivors from 37 (21-71) to 25 (19-63) hours (P = .049). The amount of morphine (P = .001) and midazolam (P = .050) decreased, whereas the amount of propofol (P = .052) and fentanyl increased (P = .001). Total Therapeutic Intervention Scoring System-28 (TISS-28) per patient decreased from 137 (99-272) to 113 (87-256) points (P = .009). Intensive care unit mortality was 19% (baseline), 8% (implementation I), and 7% (implementation II) (P = .020). CONCLUSIONS: Changes in organizational and care processes were associated with an altered pattern of sedative and analgesic drug prescription, a decrease in length of (noninvasive) respiratory support and length of stay in survivors, and decreases in resource use as measured by TISS-28 and mortality.

Accurate and robust reconstruction of proximal femur from sparse intraoperative data and dense point distribution model for surgical navigation

Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.

Can outcome prediction data change patient outcomes and organizational outcomes?

PURPOSE OF REVIEW: Intensive care medicine consumes a high share of healthcare costs, and there is growing pressure to use the scarce resources efficiently. Accordingly, organizational issues and quality management have become an important focus of interest in recent years. Here, we will review current concepts of how outcome data can be used to identify areas requiring action. RECENT FINDINGS: Using recently established models of outcome assessment, wide variability between individual ICUs is found, both with respect to outcome and resource use. Such variability implies that there are large differences in patient care processes not only within the ICU but also in pre-ICU and post-ICU care. Indeed, measures to improve the patient process in the ICU (including care of the critically ill, patient safety, and management of the ICU) have been presented in a number of recently published papers. SUMMARY: Outcome assessment models provide an important framework for benchmarking. They may help the individual ICU to spot appropriate fields of action, plan and initiate quality improvement projects, and monitor the consequences of such activity.

Evaluation of early tissue reactions after lumbar intertransverse process fusion using CT in a rabbit

OBJECTIVE: The objective of the study was to evaluate tissue reactions such as bone genesis, cartilage genesis and graft materials in the early phase of lumbar intertransverse process fusion in a rabbit model using computed tomography (CT) imaging with CT intensity (Hounsfield units) measurement, and to compare these data with histological results. MATERIALS AND METHODS: Lumbar intertransverse process fusion was performed on 18 rabbits. Four graft materials were used: autograft bone (n = 3); collagen membrane soaked with recombinant human bone morphogenetic protein-2 (rhBMP-2) (n = 5); granular calcium phosphate (n = 5); and granular calcium phosphate coated with rhBMP-2 (n = 5). All rabbits were euthanized 3 weeks post-operatively and lumbar spines were removed for CT imaging and histological examination. RESULTS: Computed tomography imaging demonstrated that each fusion mass component had the appropriate CT intensity range. CT also showed the different distributions and intensities of bone genesis in the fusion masses between the groups. Each component of tissue reactions was identified successfully on CT images using the CT intensity difference. Using CT color mapping, these observations could be easily visualized, and the results correlated well with histological findings. CONCLUSIONS: The use of CT intensity is an effective approach for observing and comparing early tissue reactions such as newly synthesized bone, newly synthesized cartilage, and graft materials after lumbar intertransverse process fusion in a rabbit model.

Tree phenology and carbon dioxide fluxes - use of digital photography for process-based interpretation at the ecosystem scale

Vegetation phenology is an important indicator of climate change and climate variability and it is strongly connected to biospheric–atmospheric gas exchange. We aimed to evaluate the applicability of phenological information derived from digital imagery for the interpretation of CO2 exchange measurements. For the years 2005–2007 we analyzed seasonal phenological development of 2 temperate mixed forests using tower-based imagery from standard RGB cameras. Phenological information was jointly analyzed with gross primary productivity (GPP) derived from net ecosystem exchange data. Automated image analysis provided reliable information on vegetation developmental stages of beech and ash trees covering all seasons. A phenological index derived from image color values was strongly correlated with GPP, with a significant mean time lag of several days for ash trees and several weeks for beech trees in early summer (May to mid-July). Leaf emergence dates for the dominant tree species partly explained temporal behaviour of spring GPP but were also masked by local meteorological conditions. We conclude that digital cameras at flux measurement sites not only provide an objective measure of the physiological state of a forest canopy at high temporal and spatial resolutions, but also complement CO2 and water exchange measurements, improving our knowledge of ecosystem processes.

A Nonstationary Space-Time Gaussian Process Model for Partially Converged Simulations

In the context of expensive numerical experiments, a promising solution for alleviating the computational costs consists of using partially converged simulations instead of exact solutions. The gain in computational time is at the price of precision in the response. This work addresses the issue of fitting a Gaussian process model to partially converged simulation data for further use in prediction. The main challenge consists of the adequate approximation of the error due to partial convergence, which is correlated in both design variables and time directions. Here, we propose fitting a Gaussian process in the joint space of design parameters and computational time. The model is constructed by building a nonstationary covariance kernel that reflects accurately the actual structure of the error. Practical solutions are proposed for solving parameter estimation issues associated with the proposed model. The method is applied to a computational fluid dynamics test case and shows significant improvement in prediction compared to a classical kriging model.

Genetic diversity in the modern horse illustrated from genome-wide SNP data.

Horses were domesticated from the Eurasian steppes 5,000-6,000 years ago. Since then, the use of horses for transportation, warfare, and agriculture, as well as selection for desired traits and fitness, has resulted in diverse populations distributed across the world, many of which have become or are in the process of becoming formally organized into closed, breeding populations (breeds). This report describes the use of a genome-wide set of autosomal SNPs and 814 horses from 36 breeds to provide the first detailed description of equine breed diversity. F(ST) calculations, parsimony, and distance analysis demonstrated relationships among the breeds that largely reflect geographic origins and known breed histories. Low levels of population divergence were observed between breeds that are relatively early on in the process of breed development, and between those with high levels of within-breed diversity, whether due to large population size, ongoing outcrossing, or large within-breed phenotypic diversity. Populations with low within-breed diversity included those which have experienced population bottlenecks, have been under intense selective pressure, or are closed populations with long breed histories. These results provide new insights into the relationships among and the diversity within breeds of horses. In addition these results will facilitate future genome-wide association studies and investigations into genomic targets of selection.

A Concept of Semantics Extraction from Web Data by Induction of Fuzzy Ontologies

Traditionally, ontologies describe knowledge representation in a denotational, formalized, and deductive way. In addition, in this paper, we propose a semiotic, inductive, and approximate approach to ontology creation. We define a conceptual framework, a semantics extraction algorithm, and a first proof of concept applying the algorithm to a small set of Wikipedia documents. Intended as an extension to the prevailing top-down ontologies, we introduce an inductive fuzzy grassroots ontology, which organizes itself organically from existing natural language Web content. Using inductive and approximate reasoning to reflect the natural way in which knowledge is processed, the ontology’s bottom-up build process creates emergent semantics learned from the Web. By this means, the ontology acts as a hub for computing with words described in natural language. For Web users, the structural semantics are visualized as inductive fuzzy cognitive maps, allowing an initial form of intelligence amplification. Eventually, we present an implementation of our inductive fuzzy grassroots ontology Thus,this paper contributes an algorithm for the extraction of fuzzy grassroots ontologies from Web data by inductive fuzzy classification.