Anesthetic considerations in the child with Gaucher disease

Alpidem, an imidazopyridine that acts at the gamma-aminobutyric acid/benzodiazepine receptor complex, has been reported to be an effective anxiolytic with a more favorable side effect profile than benzodiazepines. The effect of alpidem was investigated in an 8-week, open, clinical trial in 13 patients with panic disorder, with or without agoraphobia. Three patients were responders (much improved or very much improved), five patients were nonresponders, and five patients dropped out after less than 6 weeks of treatment. Significant improvement was seen in the sample as a whole for spontaneous panic attacks, phobic avoidance, and anticipatory anxiety. Most improvement occurred during the first 4 weeks of treatment, and responders had milder panic disorder at baseline. Adverse effects were generally mild. After 8 weeks of treatment, taper of medication over 2 weeks occurred without significant worsening of panic disorder symptoms. The efficacy of alpidem in the treatment of panic disorder remains uncertain and requires assessment in a controlled trial.     

Purification and characterization of an endopeptidase from Lactobacillus delbrueckii subsp. bulgaricus B14

An intracellular endopeptidase was purified from cell-free extracts of Lactobacillus delbrueckii subsp. bulgaricus B14 by anion exchange chromatography on DEAE-Sepharose, hydroxyapatite chromatography, second anion exchange chromatography on Mono-Q, and metal-chelating affinity chromatography. The endopeptidase was a monomer with a molecular mass of approximately 70 kDa determined by SDS-PAGE and gel filtration. Various oligopeptides (e.g. Met-enkephalin, bradykinin) were hydrolysed by the endopeptidase. Exopeptidase activity and cleavage of dipeptides or tripeptides was not observed. The K_M value for the cleavage of Metenkephalin was 1.2 mM. Temperature and pH optima were 47 °C and pH 7.7, respectively. The endopeptidase was inhibited by the classical agents for metal-dependent (EDTA) and serine (DFP) enzymes. Activity was increased by Co²⁺ and Mg²⁺, no effect was observed with Ca²⁺. After inhibition with EDTA, enzyme activity could be restored fully by Co²⁺. Activity was inhibited by Zn²⁺, Mn²⁺, Fe²⁺, Cu²⁺, Cd²⁺ and Hg²⁺. The N-terminal sequence of the endopeptidase was determined as: H₂N-Val-Arg-Gly-Gly-Ser-Gly-Asp-Thr-Thr-Val-0H.     

Performance-Analyse und -Optimierung in der Softwareentwicklung

Nicht-funktionale Anforderungen an ein Softwaresystem beschreiben Aspekte, die nicht direkt die Funktionalit?t, wie sie der Benutzer sieht, betreffen.     

Role of construal processes in conformity and dissent.

Develops 3 hypotheses to explain the role of construal processes in conformity behavior. According to the preconformity change of meaning hypothesis, social influence leads to changes in situational construal that precede and mediate conformity behavior; according to the postconformity change of meaning hypothesis, construal change follows and justifies conformity; and according to the construal-consistency hypothesis, preexisting situational construal distinguishes those who conform from those who dissent. Four experimental studies with varying methodology and involving a total of 361 undergraduate students were performed to test these hypotheses. The results of all studies provide strong evidence for postconformity change of meaning effects. Discussion centers on possible domains in which the different construal mechanisms might operate. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Dysregulated CD38 Expression on Peripheral Blood Immune Cell Subsets in SLE

Given its uniformly high expression on plasma cells, CD38 has been considered as a therapeutic target in patients with systemic lupus erythematosus (SLE). Herein, we investigate the distribution of CD38 expression by peripheral blood leukocyte lineages to evaluate the potential therapeutic effect of CD38-targeting antibodies on these immune cell subsets and to delineate the use of CD38 as a biomarker in SLE. We analyzed the expression of CD38 on peripheral blood leukocyte subsets by flow and mass cytometry in two different cohorts, comprising a total of 56 SLE patients. The CD38 expression levels were subsequently correlated across immune cell lineages and subsets, and with clinical and serologic disease parameters of SLE. Compared to healthy controls (HC), CD38 expression levels in SLE were significantly increased on circulating plasmacytoid dendritic cells, CD14⁺⁺CD16⁺ monocytes, CD56⁺ CD16^dim natural killer cells, marginal zone-like IgD⁺CD27⁺ B cells, and on CD4⁺ and CD8⁺ memory T cells. Correlation analyses revealed coordinated CD38 expression between individual innate and memory T cell subsets in SLE but not HC. However, CD38 expression levels were heterogeneous across patients, and no correlation was found between CD38 expression on immune cell subsets and the disease activity index SLEDAI-2K or established serologic and immunological markers of disease activity. In conclusion, we identified widespread changes in CD38 expression on SLE immune cells that highly correlated over different leukocyte subsets within individual patients, but was heterogenous within the population of SLE patients, regardless of disease severity or clinical manifestations. As anti-CD38 treatment is being investigated in SLE, our results may have important implications for the personalized targeting of pathogenic leukocytes by anti-CD38 monoclonal antibodies.     

Refining Genotypes and Phenotypes in KCNA2-Related Neurological Disorders

Pathogenic variants in KCNA2, encoding for the voltage-gated potassium channel K_v1.2, have been identified as the cause for an evolving spectrum of neurological disorders. Affected individuals show early-onset developmental and epileptic encephalopathy, intellectual disability, and movement disorders resulting from cerebellar dysfunction. In addition, individuals with a milder course of epilepsy, complicated hereditary spastic paraplegia, and episodic ataxia have been reported. By analyzing phenotypic, functional, and genetic data from published reports and novel cases, we refine and further delineate phenotypic as well as functional subgroups of KCNA2-associated disorders. Carriers of variants, leading to complex and mixed channel dysfunction that are associated with a gain- and loss-of-potassium conductance, more often show early developmental abnormalities and an earlier onset of epilepsy compared to individuals with variants resulting in loss- or gain-of-function. We describe seven additional individuals harboring three known and the novel KCNA2 variants p.(Pro407Ala) and p.(Tyr417Cys). The location of variants reported here highlights the importance of the proline(405)–valine(406)–proline(407) (PVP) motif in transmembrane domain S6 as a mutational hotspot. A novel case of self-limited infantile seizures suggests a continuous clinical spectrum of KCNA2-related disorders. Our study provides further insights into the clinical spectrum, genotype–phenotype correlation, variability, and predicted functional impact of KCNA2 variants.     

Spectral Ray Differentials

Light refracted by a dispersive interface leads to beautifully colored patterns that can be rendered faithfully with spectral Monte‐Carlo methods. Regrettably, results often suffer from chromatic noise or banding, requiring high sampling rates and large amounts of memory compared to renderers operating in some trichromatic color space. Addressing this issue, we introduce spectral ray differentials, which describe the change of light direction with respect to changes in the spectrum. In analogy with the classic ray and photon differentials, this information can be used for filtering in the spectral domain. Effectiveness of our approach is demonstrated by filtering for offline spectral light and path tracing as well as for an interactive GPU photon mapper based on splatting. Our results show considerably less chromatic noise and spatial aliasing while retaining good visual similarity to reference solutions with negligible overhead in the order of milliseconds.     

Spatio‐temporal geometry fusion for multiple hybrid cameras using moving least squares surfaces

Multi‐view reconstruction aims at computing the geometry of a scene observed by a set of cameras. Accurate 3D reconstruction of dynamic scenes is a key component for a large variety of applications, ranging from special effects to telepresence and medical imaging. In this paper we propose a method based on Moving Least Squares surfaces which robustly and efficiently reconstructs dynamic scenes captured by a calibrated set of hybrid color+depth cameras. Our reconstruction provides spatio‐temporal consistency and seamlessly fuses color and geometric information. We illustrate our approach on a variety of real sequences and demonstrate that it favorably compares to state‐of‐the‐art methods.     

Approximate Symmetry Detection in Partial 3D Meshes

Symmetry is a common characteristic in natural and man‐made objects. Its ubiquitous nature can be exploited to facilitate the analysis and processing of computational representations of real objects. In particular, in computer graphics, the detection of symmetries in 3D geometry has enabled a number of applications in modeling and reconstruction. However, the problem of symmetry detection in incomplete geometry remains a challenging task. In this paper, we propose a vote‐based approach to detect symmetry in 3D shapes, with special interest in models with large missing parts. Our algorithm generates a set of candidate symmetries by matching local maxima of a surface function based on the heat diffusion in local domains, which guarantee robustness to missing data. In order to deal with local perturbations, we propose a multi‐scale surface function that is useful to select a set of distinctive points over which the approximate symmetries are defined. In addition, we introduce a vote‐based scheme that is aware of the partiality, and therefore reduces the number of false positive votes for the candidate symmetries. We show the effectiveness of our method in a varied set of 3D shapes and different levels of partiality. Furthermore, we show the applicability of our algorithm in the repair and completion of challenging reassembled objects in the context of cultural heritage.     

A method for predicting the probability of business network profitability

In the design phase of business collaboration, it is desirable to be able to predict the profitability of the business-to-be. Therefore, techniques to assess qualities such as costs, revenues, risks, and profitability have been previously proposed. However, they do not allow the modeler to properly manage uncertainty with respect to the design of the considered business collaboration. In many real collaboration projects today, uncertainty regarding the business’ present or future characteristics is so significant that ignoring it becomes problematic. In this paper, we propose an approach based on the predictive, probabilistic architecture modeling framework (P²AMF), capable of advanced and probabilistically sound reasoning about profitability risks. The P²AMF-based approach for profitability risk prediction is also based on the e³-value modeling language and on the object constraint language. The paper introduces the prediction and modeling approach, and a supporting software tool. The use of the approach is illustrated by means of a case study originated from the Stockholm Royal Seaport smart city project.