Microsatellite markers in leukaemia and lymphoma: comments on a timely topic

Microsatellites are unique highly polymorphic and informative genetic markers dispersed in the human genome. Their detection by PCR is rapid and a wide variety of DNA sources including archival material are available for diagnostic purposes. Microsatellite typing of haematological neoplasms may be applied to the search for loss of heterozygosity at loci possibly harbouring tumour suppressor genes, for example in acute lymphoblastic leukaemia. The technique may detect submicroscopical chromosomal deletions which are not visible in the leukaemic karyotype. RER+ tumours exhibiting microsatellite instability appear to be rare among haematological cancers with the possible exception of lymphoid tumours in immunosuppressed patients and lymphomas derived from mucosa-associated lymphoid tissue. An X-chromosomal microsatellite near the human androgen receptor gene (HUMARA) may be used for clonal X-inactivation analysis. Microsatellites therefore represent a collection of powerful genetic markers suitable to tackle questions relevant to basic research and clinical problems in leukaemia and lymphoma.     

Morphological and functional polymorphism within clonal thyroid nodules

Thirty-nine thyroid nodules, removed because of recent growth, were analyzed morphologically by serial histological sections for the classical histomorphological hallmarks of follicular cell replication and for immunohistochemically demonstrable overexpression of the growth-associated ras-gene product p21ras. Clonal analysis was performed using the highly informative probe M27 beta that detects polymorphisms on the locus DXS255 of the X-chromosome. Twenty-four nodules were of clonal and 15 nodules were of poly-clonal origin. Only 3 out of the 24 clonal nodules were histomorphologically uniform. In all others, the structural hallmarks of active growth and the P21ras growth-marker expression were remarkably heterogeneous throughout the tumors. There were no histomorphological characteristics distinguishing these clonal tumors from polyclonal nodules. Even if a clonal thyroid tumor may be originally homogeneous in respect to the parameters studied here, mechanisms must exist that create wide heterogeneity of growth and of morphogenetic potential among the individual follicular cells during further expansion of the nodule. Thus, clonal nodules are much more common in nodular goiters than hitherto assumed on grounds of the classical morphological criteria. The diagnosis of a true monoclonal nodule can no longer rely on morphological and functional criteria alone but requires molecular or cytogenetic analysis of clonality.     

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.     

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.     

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.     

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.     

Model development and validation: Co-combustion of residual char, gases and volatile fuels in the fast fluidized combustion chamber of a dual fluidized bed biomass gasifier

A one-dimensional steady state model has been developed for the combustion reactor of a dual fluidized bed biomass steam gasification system. The combustion reactor is operated as fast fluidized bed (riser) with staged air introduction (bottom, primary and secondary air). The main fuel i.e., residual biomass char (from the gasifier), is introduced together with the circulating bed material at the bottom of the riser. The riser is divided into two zones: bottom zone (modelled according to modified two phase theory) and upper zone (modelled with core-annulus approach). The model consists of sub-model for bed hydrodynamic, conversion and conservation. Biomass char is assumed to be a homogeneous matrix of C, H and O and is modelled as partially volatile fuel. The exit gas composition and the temperature profile predicted by the model are in good agreement with the measured value.