Low-grade pelvic masses with spindle cell and fibroblastic proliferation: a case report

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Fabrication and characterization of Ni-Ce-Zr ternary disk-shaped catalyst and its application for low-temperature CO2 methanation

© 2019 Elsevier Ltd This study optimized a Ni-Ce-Zr catalyst and its contents for a CO2 methanation reaction by selecting a disk shape with a high mechanical strength, good durability, and thermal emission resistance. The physical and chemical properties of the obtained catalysts were determined by X-ray diffraction, scanning electron microscopy, Brunauer–Emmett–Teller, hydrogen temperature-programmed reduction, and temperature-programmed desorption of CO2 analyses. In addition, the activity and stability of the obtained catalysts were then evaluated and compared. It was determined that the combined Ni-Ce-Zr catalyst positively affects the conversion of CO2 to CH4. Furthermore, a CO2 methanation experiment was performed under atmospheric pressure conditions at 200–350 °C. The CO2 conversion was 82% at 300 °C, and the CH4 selectivity was 100%. A durability test revealed a difference in the conversion of approximately 6% for 1000 h, which indicates that the catalytic performance was maintained for a significant period

Aplastic anemia associated with interferon alpha 2a in a patient with chronic hepatitis C virus infection: a case report

<p>Abstract</p> <p>Introduction</p> <p>Hepatitis-associated aplastic anemia is a common syndrome in patients with bone marrow failure. However, hepatitis-associated aplastic anemia is an immune-mediated disease that does not appear to be caused by any of the known hepatitis viruses including hepatitis C virus. In addition, to the best of our knowledge there are no reported cases of patients with chronic hepatitis C virus infection developing aplastic anemia associated with pegylated interferon alpha 2a treatment.</p> <p>Case presentation</p> <p>We report the case of a 46-year-old Greek man who developed severe aplastic anemia during treatment with pegylated interferon alpha 2a for chronic hepatitis C virus infection. He presented with generalized purpura and bruising, as well as pallor of the skin and mucous membranes. His blood tests showed pancytopenia. He underwent allogeneic bone marrow transplantation after completing two courses of immunosuppressive therapy with antithymocyte globulin and cyclosporin A.</p> <p>Conclusions</p> <p>The combination of a specific environmental precipitant represented by the hepatitis C virus infection, an altered metabolic detoxification pathway due to treatment with pegylated interferon alpha 2a and a facilitating genetic background such as polymorphism in metabolic detoxification pathways and specific human leukocyte antigen genes possibly conspired synergistically in the development of aplastic anemia in this patient. Our case clearly shows that the causative role of pegylated interferon alpha 2a in the development of aplastic anemia must not be ignored.</p

Dependence of cancer cell adhesion kinetics on integrin ligand surface density measured by a high-throughput label-free resonant waveguide grating biosensor

A novel high-throughput label-free resonant waveguide grating (RWG) imager biosensor, the Epic® BenchTop (BT), was utilized to determine the dependence of cell spreading kinetics on the average surface density (vRGD) of integrin ligand RGD-motifs. vRGD was tuned over four orders of magnitude by co-adsorbing the biologically inactive PLL-g-PEG and the RGD-functionalized PLL-g-PEG-RGD synthetic copolymers from their mixed solutions onto the sensor surface. Using highly adherent human cervical tumor (HeLa) cells as a model system, cell adhesion kinetic data of unprecedented quality were obtained. Spreading kinetics were fitted with the logistic equation to obtain the spreading rate constant (r) and the maximum biosensor response (Δλmax), which is assumed to be directly proportional to the maximum spread contact area (Amax). r was found to be independent of the surface density of integrin ligands. In contrast, Δλmax increased with increasing RGD surface density until saturation at high densities. Interpreting the latter behavior with a simple kinetic mass action model, a 2D dissociation constant of 1753 ± 243 μm−2 (corresponding to a 3D dissociation constant of ~30 μM) was obtained for the binding between RGD-specific integrins embedded in the cell membrane and PLL-g-PEG-RGD. All of these results were obtained completely noninvasively without using any labels

The Saccadic and Neurological Deficits in Type 3 Gaucher Disease

Our objective was to characterize the saccadic eye movements in patients with type 3 Gaucher disease (chronic neuronopathic) in relationship to neurological and neurophysiological abnormalities. For approximately 4 years, we prospectively followed a cohort of 15 patients with Gaucher type 3, ages 8–28 years, by measuring saccadic eye movements using the scleral search coil method. We found that patients with type 3 Gaucher disease had a significantly higher regression slope of duration vs amplitude and peak duration vs amplitude compared to healthy controls for both horizontal and vertical saccades. Saccadic latency was significantly increased for horizontal saccades only. Downward saccades were more affected than upward saccades. Saccade abnormalities increased over time in some patients reflecting the slowly progressive nature of the disease. Phase plane plots showed individually characteristic patterns of abnormal saccade trajectories. Oculo-manual dexterity scores on the Purdue Pegboard test were low in virtually all patients, even in those with normal cognitive function. Vertical saccade peak duration vs amplitude slope significantly correlated with IQ and with the performance on the Purdue Pegboard but not with the brainstem and somatosensory evoked potentials. We conclude that, in patients with Gaucher disease type 3, saccadic eye movements and oculo-manual dexterity are representative neurological functions for longitudinal studies and can probably be used as endpoints for therapeutic clinical trials

Structural hierarchies define toughness and defect-tolerance despite simple and mechanically inferior brittle building blocks

Mineralized biological materials such as bone, sea sponges or diatoms provide load-bearing and armor functions and universally feature structural hierarchies from nano to macro. Here we report a systematic investigation of the effect of hierarchical structures on toughness and defect-tolerance based on a single and mechanically inferior brittle base material, silica, using a bottom-up approach rooted in atomistic modeling. Our analysis reveals drastic changes in the material crack-propagation resistance (R-curve) solely due to the introduction of hierarchical structures that also result in a vastly increased toughness and defect-tolerance, enabling stable crack propagation over an extensive range of crack sizes. Over a range of up to four hierarchy levels, we find an exponential increase in the defect-tolerance approaching hundred micrometers without introducing additional mechanisms or materials. This presents a significant departure from the defect-tolerance of the base material, silica, which is brittle and highly sensitive even to extremely small nanometer-scale defects

Prediction of protein structural classes for low-homology sequences based on predicted secondary structure

<p>Abstract</p> <p>Background</p> <p>Prediction of protein structural classes (<it>α</it>, <it>β</it>, <it>α </it>+ <it>β </it>and <it>α</it>/<it>β</it>) from amino acid sequences is of great importance, as it is beneficial to study protein function, regulation and interactions. Many methods have been developed for high-homology protein sequences, and the prediction accuracies can achieve up to 90%. However, for low-homology sequences whose average pairwise sequence identity lies between 20% and 40%, they perform relatively poorly, yielding the prediction accuracy often below 60%.</p> <p>Results</p> <p>We propose a new method to predict protein structural classes on the basis of features extracted from the predicted secondary structures of proteins rather than directly from their amino acid sequences. It first uses PSIPRED to predict the secondary structure for each protein sequence. Then, the <it>chaos game representation </it>is employed to represent the predicted secondary structure as two time series, from which we generate a comprehensive set of 24 features using <it>recurrence quantification analysis</it>, <it>K-string based information entropy </it>and <it>segment-based analysis</it>. The resulting feature vectors are finally fed into a simple yet powerful Fisher's discriminant algorithm for the prediction of protein structural classes. We tested the proposed method on three benchmark datasets in low homology and achieved the overall prediction accuracies of 82.9%, 83.1% and 81.3%, respectively. Comparisons with ten existing methods showed that our method consistently performs better for all the tested datasets and the overall accuracy improvements range from 2.3% to 27.5%. A web server that implements the proposed method is freely available at <url>http://www1.spms.ntu.edu.sg/~chenxin/RKS_PPSC/</url>.</p> <p>Conclusion</p> <p>The high prediction accuracy achieved by our proposed method is attributed to the design of a comprehensive feature set on the predicted secondary structure sequences, which is capable of characterizing the sequence order information, local interactions of the secondary structural elements, and spacial arrangements of <it>α </it>helices and <it>β </it>strands. Thus, it is a valuable method to predict protein structural classes particularly for low-homology amino acid sequences.</p