High resolution quantitative computed tomography-based assessment of trabecular microstructure and strength estimates by finite-element analysis of the spine, but not DXA, reflects vertebral fracture status in men with glucocorticoid-induced osteoporosis

High-resolution quantitative computed tomography (HRQCT)-based analysis of spinal bone density and microstructure, finite element analysis (FEA), and DXA were used to investigate the vertebral bone status of men with glucocorticoid-induced osteoporosis (GIO). DXA of L1–L3 and total hip, QCT of L1–L3, and HRQCT of T12 were available for 73 men (54.6±14.0years) with GIO. Prevalent vertebral fracture status was evaluated on radiographs using a semi-quantitative (SQ) score (normal=0 to severe fracture=3), and the spinal deformity index (SDI) score (sum of SQ scores of T4 to L4 vertebrae). Thirty-one (42.4%) subjects had prevalent vertebral fractures. Cortical BMD (Ct.BMD) and thickness (Ct.Th), trabecular BMD (Tb.BMD), apparent trabecular bone volume fraction (app.BV/TV), and apparent trabecular separation (app.Tb.Sp) were analyzed by HRQCT. Stiffness and strength of T12 were computed by HRQCT-based nonlinear FEA for axial compression, anterior bending and axial torsion. In logistic regressions adjusted for age, glucocorticoid dose and osteoporosis treatment, Tb.BMD was most closely associated with vertebral fracture status (standardized odds ratio [sOR]: Tb.BMD T12: 4.05 [95% CI: 1.8–9.0], Tb.BMD L1–L3: 3.95 [1.8–8.9]). Strength divided by cross-sectional area for axial compression showed the most significant association with spine fracture status among FEA variables (2.56 [1.29–5.07]). SDI was best predicted by a microstructural model using Ct.Th and app.Tb.Sp (r2=0.57, p<0.001). Spinal or hip DXA measurements did not show significant associations with fracture status or severity. In this cross-sectional study of males with GIO, QCT, HRQCT-based measurements and FEA variables were superior to DXA in discriminating between patients of differing prevalent vertebral fracture status. A microstructural model combining aspects of cortical and trabecular bone reflected fracture severity most accurately.

Robust Denoising using Feature and Color Information

We propose a method that robustly combines color and feature buffers to denoise Monte Carlo renderings. On one hand, feature buffers, such as per pixel normals, textures, or depth, are effective in determining denoising filters because features are highly correlated with rendered images. Filters based solely on features, however, are prone to blurring image details that are not well represented by the features. On the other hand, color buffers represent all details, but they may be less effective to determine filters because they are contaminated by the noise that is supposed to be removed. We propose to obtain filters using a combination of color and feature buffers in an NL-means and cross-bilateral filtering framework. We determine a robust weighting of colors and features using a SURE-based error estimate. We show significant improvements in subjective and quantitative errors compared to the previous state-of-the-art. We also demonstrate adaptive sampling and space-time filtering for animations.

Behavioral Outcomes of Home-Based Services for Children and Adolescents with Serious Emotional Disorders

The current study evaluates the effectiveness of an intensive home-based treatment program, Families First, on the behaviors of children and adolescents suffering from mental disorders and being at risk for out-ofi home placement. The sample included 85 youngsters and their families from a semi-rural community. The Diagnostic Interview for Children and Adolescents-Revised (DICA-R) was administered to the children, and the Child Behavior Checklist (CBCL) was completed by a parent at pretreatment and posttreatment. The families participated in a 4-6 week, intensive home intervention where crisis intervention, social support services, and needed psychological services were offered. The results indicated that both externalizing and internalizing behavior problems in youngsters with different diagnoses of mental disorders were significantly reduced at posttreatment as indicated by their CBCL scores. Furthermore, youngsters with a diagnosis of Oppositional Defiant Disorder seemed to benefit the most, as evidenced by the improved scores on most subscales of the CBCL. Youngsters with mood disorders and conduct disorders seemed to benefit in their most deficient areas, internalizing behavior problems and delinquent behaviors, respectively. Finally, after participating in Families First, more than half of the youngsters in the sample were able to stay home with their families

Grazing response patterns indicate isolation of semi-natural European grasslands

Identifying drivers of species diversity is a major challenge in understanding and predicting the dynamics of species-rich semi-natural grasslands. In particular in temperate grasslands changes in land use and its consequences, i.e. increasing fragmentation, the on-going loss of habitat and the declining importance of regional processes such as seed dispersal by livestock, are considered key drivers of the diversity loss witnessed within the last decades. It is a largely unresolved question to what degree current temperate grassland communities already reflect a decline of regional processes such as longer distance seed dispersal. Answering this question is challenging since it requires both a mechanistic approach to community dynamics and a sufficient data basis that allows identifying general patterns. Here, we present results of a local individual- and trait-based community model that was initialized with plant functional types (PFTs) derived from an extensive empirical data set of species-rich grasslands within the `Biodiversity Exploratories' in Germany. Driving model processes included above- and belowground competition, dynamic resource allocation to shoots and roots, clonal growth, grazing, and local seed dispersal. To test for the impact of regional processes we also simulated seed input from a regional species pool. Model output, with and without regional seed input, was compared with empirical community response patterns along a grazing gradient. Simulated response patterns of changes in PFT richness, Shannon diversity, and biomass production matched observed grazing response patterns surprisingly well if only local processes were considered. Already low levels of additional regional seed input led to stronger deviations from empirical community pattern. While these findings cannot rule out that regional processes other than those considered in the modeling study potentially play a role in shaping the local grassland communities, our comparison indicates that European grasslands are largely isolated, i.e. local mechanisms explain observed community patterns to a large extent.

A Food Recognition System for Diabetic Patients based on an Optimized Bag of Features Model

Computer vision-based food recognition could be used to estimate a meal's carbohydrate content for diabetic patients. This study proposes a methodology for automatic food recognition, based on the Bag of Features (BoF) model. An extensive technical investigation was conducted for the identification and optimization of the best performing components involved in the BoF architecture, as well as the estimation of the corresponding parameters. For the design and evaluation of the prototype system, a visual dataset with nearly 5,000 food images was created and organized into 11 classes. The optimized system computes dense local features, using the scale-invariant feature transform on the HSV color space, builds a visual dictionary of 10,000 visual words by using the hierarchical k-means clustering and finally classifies the food images with a linear support vector machine classifier. The system achieved classification accuracy of the order of 78%, thus proving the feasibility of the proposed approach in a very challenging image dataset.

Development and Validation of a Symptom-Based Activity Index for Adults with Eosinophilic Esophagitis

BACKGROUND & Aims: Standardized instruments are needed to assess the activity of eosinophilic esophagitis (EoE), to provide endpoints for clinical trials and observational studies. We aimed to develop and validate a patient-reported outcome (PRO) instrument and score, based on items that could account for variations in patients' assessments of disease severity. We also evaluated relationships between patients' assessment of disease severity and EoE-associated endoscopic, histologic, and laboratory findings. METHODS We collected information from 186 patients with EoE in Switzerland and the US (69.4% male; median age, 43 years) via surveys (n = 135), focus groups (n = 27), and semi-structured interviews (n = 24). Items were generated for the instruments to assess biologic activity based on physician input. Linear regression was used to quantify the extent to which variations in patient-reported disease characteristics could account for variations in patients' assessment of EoE severity. The PRO instrument was prospectively used in 153 adult patients with EoE (72.5% male; median age, 38 years), and validated in an independent group of 120 patients with EoE (60.8% male; median age, 40.5 years). RESULTS Seven PRO factors that are used to assess characteristics of dysphagia, behavioral adaptations to living with dysphagia, and pain while swallowing accounted for 67% of the variation in patients' assessment of disease severity. Based on statistical consideration and patient input, a 7-day recall period was selected. Highly active EoE, based on endoscopic and histologic findings, was associated with an increase in patient-assessed disease severity. In the validation study, the mean difference between patient assessment of EoE severity and PRO score was 0.13 (on a scale from 0 to 10). CONCLUSIONS We developed and validated an EoE scoring system based on 7 PRO items that assesses symptoms over a 7-day recall period. Clinicaltrials.gov number: NCT00939263.

Beneficial Effects of a Semi-Intensive Stroke Unit are Beyond the Monitor.

BACKGROUND AND PURPOSE Precise mechanisms underlying the effectiveness of the stroke unit (SU) are not fully established. Studies that compare monitored stroke units (semi-intensive type, SI-SU) versus an intensive care unit (ICU)-based mobile stroke team (MST-ICU) are lacking. Although inequalities in access to stroke unit care are globally improving, acute stroke patients may be admitted to Intensive Care Units for monitoring and followed by a mobile stroke team in hospital's lacking an SU with continuous cardiovascular monitoring. We aimed at comparing the stroke outcome between SI-SU and MST-ICU and hypothesized that the benefits of SI-SU are driven by additional elements other than cardiovascular monitoring, which is equally offered in both care systems. METHODS In a single-center setting, we compared the unfavorable outcomes (dependency and mortality) at 3 months in consecutive patients with ischemic stroke or spontaneous intracerebral hemorrhage admitted to a stroke unit with semi-intensive monitoring (SI-SU) to a cohort of stroke patients hospitalized in an ICU and followed by a mobile stroke team (MST-ICU) during an equal observation period of 27 months. Secondary objectives included comparing mortality and the proportion of patients with excellent outcomes (modified Rankin Score (mRS) 0-1). Equal cardiovascular monitoring was offered in patients admitted in both SI-SU and MST-ICU. RESULTS 458 patients were treated in the SI-SU and compared to the MST-ICU (n = 370) cohort. The proportion of death and dependency after 3 months was significantly improved for patients in the SI-SU compared to MST-ICU (p < 0.001; aOR = 0.45; 95% CI: 0.31-0.65). The shift analysis of the mRS distribution showed significant shift to the lower mRS in the SI-SU group, p < 0.001. The proportion of mortality in patients after 3 months also differed between the MST-ICU and the SI-SU (p < 0.05), but after adjusting for confounders this association was not significant (aOR = 0.59; 95% CI: 0.31-1.13). The proportion of patients with excellent outcome was higher in the SI-SU (59.4 vs. 44.9%, p < 0.001) but the relationship was no more significant after adjustment (aOR = 1.17; 95% CI: 0.87-1.5). CONCLUSIONS Our study shows that moving from a stroke team in a monitored setting (ICU) to an organized stroke unit leads to a significant reduction in the 3 months unfavorable outcome in patients with an acute ischemic or hemorrhagic stroke. Cardiovascular monitoring is indispensable, but benefits of a semi-intensive Stroke Unit are driven by additional elements beyond intensive cardiovascular monitoring. This observation supports the ongoing development of Stroke Centers for efficient stroke care. © 2015 S. Karger AG, Basel.

Associations between mood, anxiety or substance use disorders and inflammatory markers after adjustment for multiple covariates in a population-based study.

Inflammation is one possible mechanism underlying the associations between mental disorders and cardiovascular diseases (CVD). However, studies on mental disorders and inflammation have yielded inconsistent results and the majority did not adjust for potential confounding factors. We examined the associations of several pro-inflammatory cytokines (IL-1β, IL-6 and TNF-α) and high sensitive C-reactive protein (hsCRP) with lifetime and current mood, anxiety and substance use disorders (SUD), while adjusting for multiple covariates. The sample included 3719 subjects, randomly selected from the general population, who underwent thorough somatic and psychiatric evaluations. Psychiatric diagnoses were made with a semi-structured interview. Major depressive disorder was subtyped into "atypical", "melancholic", "combined atypical-melancholic" and "unspecified". Associations between inflammatory markers and psychiatric diagnoses were assessed using multiple linear and logistic regression models. Lifetime bipolar disorders and atypical depression were associated with increased levels of hsCRP, but not after multivariate adjustment. After multivariate adjustment, SUD remained associated with increased hsCRP levels in men (β = 0.13 (95% CI: 0.03,0.23)) but not in women. After multivariate adjustment, lifetime combined and unspecified depression were associated with decreased levels of IL-6 (β = -0.27 (-0.51,-0.02); β = -0.19 (-0.34,-0.05), respectively) and TNF-α (β = -0.16 (-0.30,-0.01); β = -0.10 (-0.19,-0.02), respectively), whereas current combined and unspecified depression were associated with decreased levels of hsCRP (β = -0.20 (-0.39,-0.02); β = -0.12 (-0.24,-0.01), respectively). Our data suggest that the significant associations between increased hsCRP levels and mood disorders are mainly attributable to the effects of comorbid disorders, medication as well as behavioral and physical CVRFs.

Adaptable Visualisation Based On User Needs

Software developers often ask questions about software systems and software ecosystems that entail exploration and navigation, such as who uses this component?, and where is this feature implemented?. Software visualisation can be a great aid to understanding and exploring the answers to such questions, but visualisations require expertise to implement effectively, and they do not always scale well to large systems. We propose to automatically generate software visualisations based on software models derived from open source software corpora and from an analysis of the properties of typical developers queries and commonly used visualisations. The key challenges we see are (1) understanding how to match queries to suitable visualisations, and (2) scaling visualisations effectively to very large software systems and corpora. In the paper we motivate the idea of automatic software visualisation, we enumerate the challenges and our proposals to address them, and we describe some very initial results in our attempts to develop scalable visualisations of open source software corpora.

Fully automatic segmentation of AP pelvis X-rays via random forest regression with efficient feature selection and hierarchical sparse shape composition

In clinical practice, traditional X-ray radiography is widely used, and knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic approach for landmark detection and shape segmentation of both pelvis and femur in conventional AP X-ray images. Our approach is based on the framework of landmark detection via Random Forest (RF) regression and shape regularization via hierarchical sparse shape composition. We propose a visual feature FL-HoG (Flexible- Level Histogram of Oriented Gradients) and a feature selection algorithm based on trace radio optimization to improve the robustness and the efficacy of RF-based landmark detection. The landmark detection result is then used in a hierarchical sparse shape composition framework for shape regularization. Finally, the extracted shape contour is fine-tuned by a post-processing step based on low level image features. The experimental results demonstrate that our feature selection algorithm reduces the feature dimension in a factor of 40 and improves both training and test efficiency. Further experiments conducted on 436 clinical AP pelvis X-rays show that our approach achieves an average point-to-curve error around 1.2 mm for femur and 1.9 mm for pelvis.

Ruler Based Automatic C-Arm Image Stitching Without Overlapping Constraint

In this paper, we propose a new method for stitching multiple fluoroscopic images taken by a C-arm instrument. We employ an X-ray radiolucent ruler with numbered graduations while acquiring the images, and the image stitching is based on detecting and matching ruler parts in the images to the corresponding parts of a virtual ruler. To achieve this goal, we first detect the regular spaced graduations on the ruler and the numbers. After graduation labeling, for each image, we have the location and the associated number for every graduation on the ruler. Then, we initialize the panoramic X-ray image with the virtual ruler, and we “paste” each image by aligning the detected ruler part on the original image, to the corresponding part of the virtual ruler on the panoramic image. Our method is based on ruler matching but without the requirement of matching similar feature points in pairwise images, and thus, we do not necessarily require overlap between the images. We tested our method on eight different datasets of X-ray images, including long bones and a complete spine. Qualitative and quantitative experiments show that our method achieves good results.

CD47 protein expression in acute myeloid leukemia: A tissue microarray-based analysis

Binding of CD47 to signal regulatory protein alpha (SIRPα), an inhibitory receptor, negatively regulates phagocytosis. In acute myeloid leukemia (AML), CD47 is overexpressed on peripheral blasts and leukemia stem cells and inversely correlates with survival. Aim of the study was to investigate the correlation between CD47 protein expression by immunohistochemistry (IHC) in a bone marrow (BM) tissue microarray (TMA) and clinical outcome in AML patients. CD47 staining on BM leukemia blasts was scored semi-quantitatively and correlated with clinical parameters and known prognostic factors in AML. Low (scores 0-2) and high (score 3) CD47 protein expression were observed in 75% and 25% of AML patients. CD47 expression significantly correlated with percentage BM blast infiltration and peripheral blood blasts. Moreover, high CD47 expression was associated with nucleophosmin (NPM1) gene mutations. In contrast, CD47 expression did not significantly correlate with overall or progression free survival or response to therapy. In summary, a BM TMA permits rapid and reproducible semi-quantitative analysis of CD47 protein expression by IHC. While CD47 expression on circulating AML blasts has been shown to be a negative prognostic marker for a very defined population of AML patients with NK AML, CD47 expression on AML BM blasts is not.

The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink

The growth rate of atmospheric carbondioxide(CO2) concentrations since industrialization is characterized by large interannual variability, mostly resulting from variability in CO 2 uptake by terrestrial ecosystems (typically termed carbon sink). However, the contributions of regional ecosystems to that variability are not well known. Using an ensemble of ecosystem and land-surface models and an empirical observation-based product of global gross primary production, we show that the mean sink, trend, and interannual variability in CO2 uptake by terrestrial ecosystems are dominated by distinct biogeographic regions. Whereas the mean sink is dominated by highly productive lands (mainly tropical forests), the trend and interannual variability of the sink are dominated by semi-arid ecosystems whose carbon balance is strongly associated with circulation-driven variations in both precipitation and temperature.

Video-based quantification of body movement indicates negative symptoms: a replication

Objective: In schizophrenia, abnormalities in nonverbal behaviors have always been considered as highly relevant. However, due to methodological limitations, nonverbal behavior was rarely quantified objectively. Recent methodological advances now allow a quantification of body movement from ordinary video recordings. We showed that patients’ objectively measured amount of movement in social role-play interactions was closely associated with their symptom profiles (Kupper, Ramseyer, Hoffmann, & Tschacher, Schizophrenia Research 2010). In the present study, a replication of these results in the context of semi-standardized PANSS (Positive and Negative Syndrome Scale) interviews was intended. Methods: 17 patients with schizophrenia were analyzed during the initial 15-min sequence of a videotaped PANSS interview using Motion Energy Analysis (MEA). The amount of patients’ movement was then correlated with their PANSS symptom scores. Results: Sizeable and significant correlations between negative symptoms and reduced movements (r = -.68, p<0.01) and reduced movement speed (r = -.80, p<0.001) were found. Moreover, cognitive symptoms were related to reduced movement speed (r = -.70, p<.01). Conclusion: Negative symptoms were reliably indicated by patients’ nonverbal behavior in psychopathology interviews. Hence, the main result of our earlier study, examining patients’ nonverbal behavior in role play tests, was replicated for the less structured interactions in psychopathological interviews. Results could encourage the use of MEA in a wide range of videotaped social interactions of patients with schizophrenia and other psychiatric disorders.

Efficient luminescent solar concentrators based on self-absorption free, Tm2+ doped halides

The optical and luminescence properties of CaI2 and NaCl doped with divalent thulium are reported for solar energy applications. These halides strongly absorb solar light from the UV up to 900 nm due to the intense Tm2+ 4f13→4f125d1 electronic transitions. Absorption is followed by emission of 1140 nm light due to the 2F5/2→2F7/2 transition of the 4f13 configuration that can be efficiently converted to electric power by thin film CuInSe2 (CIS) solar cells. Because of a negligible spectral overlap between absorption and emission spectra, a luminescent solar concentrator (LSC) based on these black luminescent materials would not suffer from self-absorption losses. The Tm2+ doped halides may therefore lead to efficient semi-transparent power generating windows that absorb solar light over the whole visible spectrum. It will be shown that the power efficiency of the Tm2+ based LSCs can be up to four times higher compared to LSCs based on organic dyes or quantum dots.