The nonnegative MINQUE estimate

AbstractThe purpose of this paper is to give a characterization of the nonnegative MINQUE estimate for variance components. A similar characterization has been given by Pukelsheim but only in some special cases. The proof presented here uses results from convex programming and emphasizes certain geometrical aspects of the nonnegative MINQUE estimate problem

Electron localization by self-assembled GaSb/GaAs quantum dots.

We have studied the photoluminescence from type-II GaSb/GaAs self-assembled quantum dots in magnetic fields up to 50 T. Our results show that at low laser power, electrons are more weakly bound to the dots than to the wetting layer, but that at high laser power, the situation is reversed. We attribute this effect to an enhanced Coulomb interaction between a single electron and dots that are multiply charged with holes

\u3ci\u3eIn-situ\u3c/i\u3e-Investigation of Enzyme Immobilization on Polymer Brushes

Herein, we report on the use of a combined setup of quartz-crystal microbalance, with dissipation monitoring and spectroscopic ellipsometry, to comprehensively investigate the covalent immobilization of an enzyme to a polymer layer. All steps of the covalent reaction of the model enzyme glucose oxidase with the poly(acrylic acid) brush by carbodiimide chemistry, were monitored in-situ. Data were analyzed using optical and viscoelastic modeling. A nearly complete collapse of the polymer chains was found upon activation of the carboxylic acid groups with N-(3-Dimethylaminopropyl)-N′-ethylcarbodiimide and N-Hydroxysuccinimide. The reaction with the amine groups of the enzyme occurs simultaneously with re-hydration of the polymer layer. Significantly more enzyme was immobilized on the surface compared to physical adsorption at similar conditions, at the same pH. It was found that the pH responsive swelling behavior was almost not affected by the presence of the enzyme

PyNEST: A Convenient Interface to the NEST Simulator

The neural simulation tool NEST (http://www.nest-initiative.org) is a simulator for heterogeneous networks of point neurons or neurons with a small number of compartments. It aims at simulations of large neural systems with more than 104 neurons and 107 to 109 synapses. NEST is implemented in C++ and can be used on a large range of architectures from single-core laptops over multi-core desktop computers to super-computers with thousands of processor cores. Python (http://www.python.org) is a modern programming language that has recently received considerable attention in Computational Neuroscience. Python is easy to learn and has many extension modules for scientific computing (e.g. http://www.scipy.org). In this contribution we describe PyNEST, the new user interface to NEST. PyNEST combines NEST's efficient simulation kernel with the simplicity and flexibility of Python. Compared to NEST's native simulation language SLI, PyNEST makes it easier to set up simulations, generate stimuli, and analyze simulation results. We describe how PyNEST connects NEST and Python and how it is implemented. With a number of examples, we illustrate how it is used

PyNN: A Common Interface for Neuronal Network Simulators

Computational neuroscience has produced a diversity of software for simulations of networks of spiking neurons, with both negative and positive consequences. On the one hand, each simulator uses its own programming or configuration language, leading to considerable difficulty in porting models from one simulator to another. This impedes communication between investigators and makes it harder to reproduce and build on the work of others. On the other hand, simulation results can be cross-checked between different simulators, giving greater confidence in their correctness, and each simulator has different optimizations, so the most appropriate simulator can be chosen for a given modelling task. A common programming interface to multiple simulators would reduce or eliminate the problems of simulator diversity while retaining the benefits. PyNN is such an interface, making it possible to write a simulation script once, using the Python programming language, and run it without modification on any supported simulator (currently NEURON, NEST, PCSIM, Brian and the Heidelberg VLSI neuromorphic hardware). PyNN increases the productivity of neuronal network modelling by providing high-level abstraction, by promoting code sharing and reuse, and by providing a foundation for simulator-agnostic analysis, visualization and data-management tools. PyNN increases the reliability of modelling studies by making it much easier to check results on multiple simulators. PyNN is open-source software and is available from http://neuralensemble.org/PyNN

In Situ Monitoring of Linear RGD-Peptide Bioconjugation with Nanoscale Polymer Brushes

Bioinspired materials mimicking the native extracellular matrix environment are promising for biotechnological applications. Particularly, modular biosurface engineering based on the functionalization of stimuli-responsive polymer brushes with peptide sequences can be used for the development of smart surfaces with biomimetic cues. The key aspect of this study is the in situ monitoring and analytical verification of the biofunctionalization process on the basis of three complementary analytical techniques. In situ spectroscopic ellipsometry was used to quantify the amount of chemisorbed GRGDS at both the homopolymer poly(acrylic acid) (PAA) brush and the binary poly(N-isopropylacrylamide) (PNIPAAm)− PAA brushes, which was finally confirmed by an acidic hydrolysis combined with a subsequent reverse-phase high-performance liquid chromatography analysis. In situ attenuated total reflection-Fourier transform infrared spectroscopy provided a step-by-step detection of the biofunctionalization process so that an optimized protocol for the bioconjugation of GRGDS could be identified. The optimized protocol was used to create a temperature-responsive binary brush with a high amount of chemisorbed GRGDS, which is a promising candidate for the temperature-sensitive control of GRGDS presentation in further cell-instructive studies

Impaired aldehyde dehydrogenase 1 subfamily member 2A-dependent retinoic acid signaling is related with a mesenchymal-like phenotype and an unfavorable prognosis of head and neck squamous cell carcinoma

Background: An inverse correlation between expression of the aldehyde dehydrogenase 1 subfamily A2 (ALDH1A2) and gene promoter methylation has been identified as a common feature of oropharyngeal squamous cell carcinoma (OPSCC). Moreover, low ALDH1A2 expression was associated with an unfavorable prognosis of OPSCC patients, however the causal link between reduced ALDH1A2 function and treatment failure has not been addressed so far. Methods: Serial sections from tissue microarrays of patients with primary OPSCC (n = 101) were stained by immunohistochemistry for key regulators of retinoic acid (RA) signaling, including ALDH1A2. Survival with respect to these regulators was investigated by univariate Kaplan-Meier analysis and multivariate Cox regression proportional hazard models. The impact of ALDH1A2-RAR signaling on tumor-relevant processes was addressed in established tumor cell lines and in an orthotopic mouse xenograft model. Results: Immunohistochemical analysis showed an improved prognosis of ALDH1A2high OPSCC only in the presence of CRABP2, an intracellular RA transporter. Moreover, an ALDH1A2highCRABP2high staining pattern served as an independent predictor for progression-free (HR: 0.395, p = 0.007) and overall survival (HR: 0.303, p = 0.002), suggesting a critical impact of RA metabolism and signaling on clinical outcome. Functionally, ALDH1A2 expression and activity in tumor cell lines were related to RA levels. While administration of retinoids inhibited clonogenic growth and proliferation, the pharmacological inhibition of ALDH1A2-RAR signaling resulted in loss of cell-cell adhesion and a mesenchymal-like phenotype. Xenograft tumors derived from FaDu cells with stable silencing of ALDH1A2 and primary tumors from OPSCC patients with low ALDH1A2 expression exhibited a mesenchymal-like phenotype characterized by vimentin expression. Conclusions: This study has unraveled a critical role of ALDH1A2-RAR signaling in the pathogenesis of head and neck cancer and our data implicate that patients with ALDH1A2low tumors might benefit from adjuvant treatment with retinoids

Calcium-sensing soluble adenylyl cyclase mediates TNF signal transduction in human neutrophils

Through chemical screening, we identified a pyrazolone that reversibly blocked the activation of phagocyte oxidase (phox) in human neutrophils in response to tumor necrosis factor (TNF) or formylated peptide. The pyrazolone spared activation of phox by phorbol ester or bacteria, bacterial killing, TNF-induced granule exocytosis and phox assembly, and endothelial transmigration. We traced the pyrazolone's mechanism of action to inhibition of TNF-induced intracellular Ca2+ elevations, and identified a nontransmembrane (“soluble”) adenylyl cyclase (sAC) in neutrophils as a Ca2+-sensing source of cAMP. A sAC inhibitor mimicked the pyrazolone's effect on phox. Both compounds blocked TNF-induced activation of Rap1A, a phox-associated guanosine triphosphatase that is regulated by cAMP. Thus, TNF turns on phox through a Ca2+-triggered, sAC-dependent process that may involve activation of Rap1A. This pathway may offer opportunities to suppress oxidative damage during inflammation without blocking antimicrobial function

Classification of advanced stages of Parkinson's disease: translation into stratified treatments.

Advanced stages of Parkinson's disease (advPD) still impose a challenge in terms of classification and related stage-adapted treatment recommendations. Previous concepts that define advPD by certain milestones of motor disability apparently fall short in addressing the increasingly recognized complexity of motor and non-motor symptoms and do not allow to account for the clinical heterogeneity that require more personalized approaches. Therefore, deep phenotyping approaches are required to characterize the broad-scaled, continuous and multidimensional spectrum of disease-related motor and non-motor symptoms and their progression under real-life conditions. This will also facilitate the reasoning for clinical care and therapeutic decisions, as neurologists currently have to refer to clinical trials that provide guidance on a group level; however, this does not always account for the individual needs of patients. Here, we provide an overview on different classifications for advPD that translate into critical phenotypic patterns requiring the differential therapeutic adjustments. New concepts refer to precision medicine approaches also in PD and first studies on genetic stratification for therapeutic outcomes provide a potential for more objective treatment recommendations. We define novel treatment targets that align with this concept and make use of emerging device-based assessments of real-life information on PD symptoms. As these approaches require empowerment of patients and integration into treatment decisions, we present communication strategies and decision support based on new technologies to adjust treatment of advPD according to patient demands and safety

Integrated meta-omic analyses of the gastrointestinal tract microbiome in patients undergoing allogeneic hematopoietic stem cell transplantation.

In patients undergoing allogeneic hematopoietic stem cell transplantation (allo-HSCT), treatment-induced changes to the gastrointestinal tract (GIT) microbiome have been linked to adverse outcomes, most notably graft-versus-host disease (GvHD). However, it is presently unknown whether this relationship is causal or consequential. Here, we performed an integrated meta-omic analysis to probe deeper into the GIT microbiome changes during allo-HSCT and its accompanying treatments. We used 16S and 18S rRNA gene amplicon sequencing to resolve archaea, bacteria, and eukaryotes within the GIT microbiomes of 16 patients undergoing allo-HSCT for the treatment of hematologic malignancies. These results revealed a major shift in the GIT microbiome after allo-HSCT including a marked reduction in bacterial diversity, accompanied by only limited changes in eukaryotes and archaea. An integrated analysis of metagenomic and metatranscriptomic data was performed on samples collected from a patient before and after allo-HSCT for acute myeloid leukemia. This patient developed severe GvHD, leading to death 9 months after allo-HSCT. In addition to drastically decreased bacterial diversity, the post-treatment microbiome showed a higher overall number and higher expression levels of antibiotic resistance genes (ARGs). One specific Escherichia coli strain causing a paravertebral abscess was linked to GIT dysbiosis, suggesting loss of intestinal barrier integrity. The apparent selection for bacteria expressing ARGs suggests that prophylactic antibiotic administration may adversely affect the overall treatment outcome. We therefore assert that such analyses including information about the selection of pathogenic bacteria expressing ARGs may assist clinicians in "personalizing" regimens for individual patients to improve overall outcomes