Effect of feedback from peripheral movements on neuron activity in the aplysia abdominal ganglion

We have made reasonably comprehensive measurements of action potential activity in the Aplysia californica abdominal ganglion to determine the amount of feedback the central nervous system (CNS) receives from a movement which it initiates. Voltage-sensitive dye measurements of action potential activity of cells in the ganglion were made during the gill-withdrawal reflex elicited by siphon stimulation. We compared recordings in two situations which differed dramatically in the amount the gill moved. In the control sea water, the gill withdrawal was normal; in low-Ca2+, high-Mg2+ sea water, the gill movement was blocked. Both the timing and the number of spikes of the individual neurons were similar in the two situations. Histograms of the summed spike activity versus time and histograms of the number of active neurons versus time in the two conditions were also similar. Finally, two numerical measures of trial-to-trial differences, a paired t-test and a measure we named fractional similarity, did not indicate larger differences between two trials in the different sea waters than two trials in the same sea water. Feedback from sensory neurons activated by the gill movement itself does not make a large contribution to the spike activity in the abdominal ganglion. Apparently the Aplysia CNS issues the command for the withdrawal and does not make adjustments for the magnitude of the actual withdrawal. It may not even receive the information necessary for such adjustments to be made. A second motivation for these experiments was to test whether removing the feedback might simplify the neuronal activity that occurs during the gill-withdrawal reflex. This did not occur.     

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.     

Continuous production of structured phospholipids in a packed bed reactor with lipase from <Emphasis Type="Italic">Thermomyces lanuginosa</Emphasis>

The possibilities of producing structured phospholipids between soybean phospholipids and caprylic acid by lipase-catalyzed acidolysis were examined in continuous packedbed enzyme reactors. Acidolysis reactions were performed in both a solvent system and a solvent-free system with the commercially immobilized lipase from Thermomyces lanuginosa (Lipozyme TL IM) as catalyst. In the packed bed reactors, different parameters for the lipase-catalyzed acidolysis were elucidated, such as solvent ratio (solvent system), temperature, substrate ratio, residence time, water content, and operation stability. The water content was observed to be very crucial for the acidolysis reaction in packed bed reactors. If no water was added to the substrate during reactions under the solvent-free system, very low incorporation corporation of caprylic acid was observed. In both solvent and solvent-free systems, acyl incorporation was favored by a high substrate ratio between acyl donor and phospholipids, a longer residence time, and a higher reaction temperature. Under certain conditions, the incorporation of around 30% caprylic acid can be obtained in continuous operation with hexane as the solvent. Presented at the 95th American Oil Chemists' Society Annual Meeting and Expo in Cincinnati, Ohio, May 10, 2004.     

Preparation of Vanadium and Vanadium Oxide Clusters by Means of Inert Gas Aggregation

Vanadium clusters were prepared by the inert gas aggregation technique by evaporating V of high purity. Structural characterization was performed by high-resolution transmission electron microscopy. Apart from vanadium clusters of bcc structures in different orientations, crystalline VO clusters of NaCl structures were observed, which was attributed to the reaction with free oxygen present on the amorphous carbon substrates. The latter could be detected by electron energy-loss spectroscopy. The exposure of the samples to air caused a change to amorphous structures, which re-crystallized under the electron beam. This effect was interpreted as a reaction with water present in the air.     

Fixed-Parameter Algorithms for Cluster Vertex Deletion

We initiate the first systematic study of the NP-hard Cluster Vertex Deletion (CVD) problem (unweighted and weighted) in terms of fixed-parameter algorithmics. In the unweighted case, one searches for a minimum number of vertex deletions to transform a graph into a collection of disjoint cliques. The parameter is the number of vertex deletions. We present efficient fixed-parameter algorithms for CVD applying the fairly new iterative compression technique. Moreover, we study the variant of CVD where the maximum number of cliques to be generated is prespecified. Here, we exploit connections to fixed-parameter algorithms for (weighted) Vertex Cover.     

Modulation Spectral Features for Robust Far-Field Speaker Identification

In this paper, auditory inspired modulation spectral features are used to improve automatic speaker identification (ASI) performance in the presence of room reverberation. The modulation spectral signal representation is obtained by first filtering the speech signal with a 23-channel gammatone filterbank. An eight-channel modulation filterbank is then applied to the temporal envelope of each gammatone filter output. Features are extracted from modulation frequency bands ranging from 3-15 H z and are shown to be robust to mismatch between training and testing conditions and to increasing reverberation levels. To demonstrate the gains obtained with the proposed features, experiments are performed with clean speech, artificially generated reverberant speech, and reverberant speech recorded in a meeting room. Simulation results show that a Gaussian mixture model based ASI system, trained on the proposed features, consistently outperforms a baseline system trained on mel-frequency cepstral coefficients. For multimicrophone ASI applications, three multichannel score combination and adaptive channel selection techniques are investigated and shown to further improve ASI performance.     

Active learning for extended finite state machines

We present a black-box active learning algorithm for inferring extended finite state machines (EFSM)s by dynamic black-box analysis. EFSMs can be used to model both data flow and control behavior of software and hardware components. Different dialects of EFSMs are widely used in tools for model-based software development, verification, and testing. Our algorithm infers a class of EFSMs called register automata. Register automata have a finite control structure, extended with variables (registers), assignments, and guards. Our algorithm is parameterized on a particular theory, i.e., a set of operations and tests on the data domain that can be used in guards.Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We also show that, under these conditions, our framework induces a generalization of the classical Nerode equivalence and canonical automata construction to the symbolic setting. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.     

Particle positioning techniques for dusty plasma experiments

Video microscopy is a widely applied diagnostic to investigate the structure and the dynamics of particles in dusty plasmas. Reliable algorithms are required to accurately recover particle positions from the camera images. Here, four different particle positioning techniques have been tested on artificial and experimental data of dusty plasma situations. Two methods that rely on pixel-intensity thresholds were found to be strongly affected by pixel-locking errors and by noise. Two other methods-one applying spatial bandpass filters and the other fitting polynomials to the intensity pattern-yield subpixel resolution under various conditions. These two methods have been shown to be ideally suited to recover particle positions even from small-scale fluctuations that are used to derive the normal mode spectra of finite dust clusters.