Staphylococcus aureus Exfoliative Toxin E,Oligomeric State and Flip of P186: Implications for Its Action Mechanism

Staphylococcal exfoliative toxins (ETs) are glutamyl endopeptidases that specifically cleave the Glu381-Gly382 bond in the ectodomains of desmoglein 1 (Dsg1) via complex action mechanisms. To date, four ETs have been identified in different Staphylococcus aureus strains and ETE is the most recently characterized. The unusual properties of ETs have been attributed to a unique structural feature, i.e., the 180° flip of the carbonyl oxygen (O) of the nonconserved residue 192/186 (ETA/ETE numbering), not conducive to the oxyanion hole formation. We report the crystal structure of ETE determined at 1.61 Å resolution, in which P186(O) adopts two conformations displaying a 180° rotation. This finding, together with free energy calculations, supports the existence of a dynamic transition between the conformations under the tested conditions. Moreover, enzymatic assays showed no significant differences in the esterolytic efficiency of ETE and ETE/P186G, a mutant predicted to possess a functional oxyanion hole, thus downplaying the influence of the flip on the activity. Finally, we observed the formation of ETE homodimers in solution and the predicted homodimeric structure revealed the participation of a characteristic nonconserved loop in the interface and the partial occlusion of the protein active site, suggesting that monomerization is required for enzymatic activity.     

DeepHP: A New Gastric Mucosa Histopathology Dataset for Helicobacter pylori Infection Diagnosis

Emerging deep learning-based applications in precision medicine include computational histopathological analysis. However, there is a lack of the required training image datasets to generate classification and detection models. This phenomenon occurs mainly due to human factors that make it difficult to obtain well-annotated data. The present study provides a curated public collection of histopathological images (DeepHP) and a convolutional neural network model for diagnosing gastritis. Images from gastric biopsy histopathological exams were used to investigate the performance of the proposed model in detecting gastric mucosa with Helicobacter pylori infection. The DeepHP database comprises 394,926 histopathological images, of which 111 K were labeled as Helicobacter pylori positive and 283 K were Helicobacter pylori negative. We investigated the classification performance of three Convolutional Neural Network architectures. The models were tested and validated with two distinct image sets of 15% (59K patches) chosen randomly. The VGG16 architecture showed the best results with an Area Under the Curve of 0.998%. The results showed that CNN could be used to classify histopathological images from gastric mucosa with marked precision. Our model evidenced high potential and application in the computational pathology field.     

Nickel Activation for Hydrogenolysis Reaction on USY Zeolite

The effects of the SAR (14 and 38) and of the methodology of introduction of nickel (wetness impregnation and ion exchange) on catalyst activation were investigated in Ni/USY model catalysts submitted to two activation treatments: reduction (A) and reduction/calcination/reduction, successively (B). the catalysts prepared by wetness impregnation, a marked increase in the catalytic activity after treatment B was observed. On the basis of the catalyst efficiency toward ethane hydrogenolysis, the lower SAR catalyst presents a threefold higher activity. On the contrary, the catalysts prepared by ion exchange, as well as a model catalyst prepared by wetness impregnation over a USY exhaustively exchanged with nickel ions, do not present measurable increasing of the catalytic activity under the same activation conditions. Monitoring the catalyst activation by EXAFS indicates the formation of nickel clusters in the impregnated catalysts after activation treatment B, which should be responsible for the high catalytic activity. However, TEM images reveal a bimodal particle size distribution, with large (ca. 20 nm) and small nickel particles. Temperature-programmed reduction performed under the same conditions of catalyst activation suggests that only the small nickel particles are activated under the experimental conditions adopted in this work.     

The catalytic activity of the Pr2Zr2−xFexO7±δ system for the CO oxidation reaction

One of the alternatives to decrease the concentration of CO is its oxidation reaction to CO₂, which can be made more efficient using catalysts. In this work, it is shown that pyrochlore structures are a promising candidate to act as heterogeneous catalysts due to their chemical and physical properties. For use as a catalyst in this reaction, the Pr₂Zr_2−xFe_xO_7±δ (x = 0, 0.05, 0.10, and 0.15) system was synthesized by the solvothermal method, firing the powder obtained at temperatures of 1200 and 1400°C. The diffraction patterns confirmed the pyrochlore structure as the single phase in all the nominal compositions. The Brunauer–Emmett–Teller method and dynamic light-scattering analysis showed an increase in the particle size and a decrease in the specific surface area when increasing the iron concentration and increasing the calcination temperature. The compositions that presented the best catalytic activity were the samples with the highest iron concentration. Moreover, these samples were able to convert all the CO oxidation reactions in a narrower temperature range than a conventional CeO₂ sample. The presence of vacancies and the redox behavior of the elements present are the key factors for the catalysis of this system in the CO oxidation reaction.     

Sintering of porous alumina obtained by biotemplate fibers for low thermal conductivity applications

In this research report, a sintering process of porous ceramic materials based on Al₂O₃ was employed using a method where a cation precursor solution is embedded in an organic fibrous cotton matrix. For porous green bodies, the precursor solution and cotton were annealed at temperatures in the range of 100–1600 °C using scanning electron microscopy (SEM) and thermogravimetric (TG) analysis to obtain a porous body formation and disposal process containing organic fibers and precursor solution. In a structure consisting of open pores and interconnected nanometric grains, despite the low porosity of around 40% (calculated geometrically), nitrogen physisorption determined a specific surface area of 14 m²/g, which shows much sintering of porous bodies. Energy dispersive X-ray (EDX) and X-ray diffraction (XRD) analytical methods revealed a predominant amount of α-Al₂O₃ in the sintered samples. Thermal properties of the sintered Al₂O₃ fibers were obtained by using the Laser Flash which resulted in the lower thermal conductivity obtained by α-Al₂O₃ and therefore improved its potential use as an insulating material.     

A systematic comparison of PCA‐based Statistical Process Monitoring methods for high‐dimensional,time‐dependent Processes

High‐dimensional and time‐dependent data pose significant challenges to Statistical Process Monitoring. Most of the high‐dimensional methodologies to cope with these challenges rely on some form of Principal Component Analysis (PCA) model, usually classified as nonadaptive and adaptive. Nonadaptive methods include the static PCA approach and Dynamic Principal Component Analysis (DPCA) for data with autocorrelation. Methods, such as DPCA with Decorrelated Residuals, extend DPCA to further reduce the effects of autocorrelation and cross‐correlation on the monitoring statistics. Recursive Principal Component Analysis and Moving Window Principal Component Analysis, developed for nonstationary data, are adaptive. These fundamental methods will be systematically compared on high‐dimensional, time‐dependent processes (including the Tennessee Eastman benchmark process) to provide practitioners with guidelines for appropriate monitoring strategies and a sense of how they can be expected to perform. The selection of parameter values for the different methods is also discussed. Finally, the relevant challenges of modeling time‐dependent data are discussed, and areas of possible further research are highlighted. © 2016 American Institute of Chemical Engineers AIChE J, 62: 1478–1493, 2016     

Effect of Annealing Temperature on TiO2 Nanorod Films Prepared by dc Reactive Magnetron Sputtering for Dye-Sensitized Solar Cells

Anatase TiO₂ nanorod films have been prepared on ITO coated glass substrates at room temperature by dc reactive magnetron sputtering technique. The nanorods are highly ordered and are perpendicular to the substrate. XRD measurements show that the anatase nanorods have a preferred orientation along the [110] direction. The prepared nanorods were annealed at different temperatures (200?C500 °C) in air for 1 h. The dye-sensitized solar cells (DSSC) have been made using the as-deposited and annealed TiO₂ nanorods as working electrodes. It has been found that annealing improves the efficiency of the DSSC. An optimum conversion efficiency of 2.13%, at 100 mW/cm² light intensity has been achieved with TiO₂ nanorods annealed at 300 °C.     

A Perinatal Palatable High-Fat Diet Increases Food Intake and Promotes Hypercholesterolemia in Adult Rats

The main goal of the present study was to evaluate the long-term effects of a perinatal palatable high-fat diet on the food intake and cholesterol profile of adult rats. Male Wistar rats (aged 22 days) were divided into two groups according to their mother’s diet during gestation and lactation (C _p, n = 10; pups from control mothers; and HL_p n = 10; pups from mothers fed a palatable high-fat diet). At the 76th day, pups were housed individually for 14 days, and daily food consumption was determined during a period of 6 days. Blood from 100-day-old rats was sampled by cardiac puncture. Fasting (12 h) serum glucose, total cholesterol, LDL-C, HDL-C, triglycerides (TG), and VLDL-C levels were determined. The measurement of food intake was higher in the animals submitted to a hyperlipidic diet during the perinatal period. Serum total cholesterol, LDL-C, HDL-C, TG, VLDL-C and glycemia were increased in the HL_p group compared to the control group. Our findings show that an early life environment with a high-fat diet can contribute to metabolic disease in later life.