A Jupiter-mass planet around the K0 giant HD 208897

For over 10 years, we have carried out a precise radial velocity (RV) survey to find substellar companions around evolved G,K-type stars to extend our knowledge of planet formation and evolution. We performed high precision RV measurements for the giant star HD 208897 using an iodine (I2) absorption cell. The measurements were made at T\"UB\.ITAK National Observatory (TUG, RTT150) and Okayama Astrophysical Observatory (OAO). For the origin of the periodic variation seen in the RV data of the star, we adopted a Keplerian motion caused by an unseen companion. We found that the star hosts a planet with a minimum mass of m2sini=1.40MJ, which is relatively low compared to those of known planets orbiting evolved intermediate-mass stars. The planet is in a nearly circular orbit with a period of P=353 days at about 1 AU distance from the host star. The star is metal rich and located at the early phase of ascent along the red giant branch. The photometric observations of the star at Ankara University Kreiken Observatory (AUKR) and the HIPPARCOS photometry show no sign of variation with periods associated with the RV variation. Neither bisector velocity analysis nor analysis of the Ca II and Halpha lines shows any correlation with the RV measurements

Extracción asistida por microondas de compuestos no polares de cáscaras de pistacho y caracterización de los extractos

Soxhlet and microwave assisted extraction (MAE) methods were used to obtain non-polar compounds from pistachio hull. MAE parameters (liquid to solid ratio, microwave power, and extraction time) were studied to obtain maximum extraction yield. The optimal conditions were found to be liquid to solid ratio of 15:1 (v/w), microwave power of 250 W and extraction time of 12.5 min. The extraction yields were 9.81 and 9.50% for MAE and Soxhlet methods, respectively. The total phenolic content, antioxidant activity and tocopherol content of the extract obtained by MAE was found to be significantly higher than those of the Soxhlet extract (p < 0.05). The results showed that the extract contained α-tocopherols (567.65 mg/kg) and oleic acid (48.46%) as the major tocopherols and fatty acids. These findings propose that hull extracts can be considered as a good source of natural bioactive compounds and MAE can be a good alternative to the traditional Soxhlet method.Se utilizó la extracción mediante Soxhlet y métodos de extracción asistida mediante microondas (MAE) para obtener compuestos no polares de las cascaras de pistacho. Se estudiaron los parámetros para la MAE (relación líquido-sólido, potencia de microondas y tiempo de extracción) para obtener el máximo rendimiento de la extracción. Se encontró que las condiciones óptimas eran una relación líquido a sólido de 15:1 (v/p), potencia de microondas de 250 W y un tiempo de extracción de 12,5 minutos. Los rendimientos de extracción fueron 9.81 y 9.50% para los métodos MAE y Soxhlet, respectivamente. El contenido fenólico total, la actividad antioxidante y el contenido de tocoferoles de los extractos obtenidos por MAE fueron significativamente más altos que los de los extractos de Soxhlet (p < 0,05). Los resultados muestran que el extracto contiene α-tocoferol (567.65 mg/kg) y ácido oleico (48.46%) como los principales tocoferoles y ácidos grasos, respectivamente. Estos hallazgos proponen que los extractos de las cascaras pueden considerarse como una buena fuente de compuestos bioactivos naturales y MAE puede ser una buena alternativa al método Soxhlet tradicional

Database for CO2 separation performances of MOFs based on computational materials screening

Metal-organic frameworks (MOFs) are potential adsorbents for CO2 capture. Because thousands of MOFs exist, computational studies become very useful in identifying the top performing materials for target applications in a time-effective manner. In this study, molecular simulations were performed to screen the MOF database to identify the best materials for CO2 separation from flue gas (CO2/N-2) and landfill gas (CO2/CH4) under realistic operating conditions. We validated the accuracy of our computational approach by comparing the simulation results for the CO2 uptakes, CO2/N-2 and CO2/CH4 selectivities of various types of MOFs with the available experimental data. Binary CO2/N-2 and CO2/CH4 mixture adsorption data were then calculated for the entire MOF database. These data were then used to predict selectivity, working capacity, regenerability, and separation potential of MOFs. The top performing MOF adsorbents that can separate CO2/N-2 and CO2/CH4 with high performance were identified. Molecular simulations for the adsorption of a ternary CO2/N-2/CH4 mixture were performed for these top materials to provide a more realistic performance assessment of MOF adsorbents. The structure-performance analysis showed that MOFs with Delta Q(st)(0) > 30 kJ/mol, 3.8 angstrom 1 g/cm(3) are the best candidates for selective separation of CO2 from flue gas and landfill gas. This information will be very useful to design novel MOFs exhibiting high CO2 separation potentials. Finally, an online, freely accessible database https://cosmoserc.ku.edu.tr was established, for the first time in the literature, which reports all of the computed adsorbent metrics of 3816 MOFs for CO2/N-2, CO2/CH4, and CO2/N-2/CH4 separations in addition to various structural properties of MOFs.European Research Counci

What tweets tell us about MOOC participation

In this research paper, the authors analyze the collected Twitter data output during MobiMOOC 2011. This six-week data stream includes all tweets that contain the MOOC's hashtag (#mobiMOOC) and it has been analyzed using qualitative methodology. The analysis sought to examine the emotive vocabulary used, to determine if there was content-sharing via tweets, and to analyze the folksonomic trends of the tweets. In Addition sought a deeper understanding of what, and how, MOOC participants share what they share on the MOOC's Twitter channel. The aim of this study is to provide a little more insight into MOOC learner behaviors on Twitter so that future MOOC designers and facilitators can better engage with their learners.Facultad de Ciencias Exacta

What tweets tell us about MOOC participation

In this research paper, the authors analyze the collected Twitter data output during MobiMOOC 2011. This six-week data stream includes all tweets that contain the MOOC's hashtag (#mobiMOOC) and it has been analyzed using qualitative methodology. The analysis sought to examine the emotive vocabulary used, to determine if there was content-sharing via tweets, and to analyze the folksonomic trends of the tweets. In Addition sought a deeper understanding of what, and how, MOOC participants share what they share on the MOOC's Twitter channel. The aim of this study is to provide a little more insight into MOOC learner behaviors on Twitter so that future MOOC designers and facilitators can better engage with their learners.Facultad de Ciencias Exacta

Poly-ε-Caprolactone/Fibrin-Alginate Scaffold: A New Pro-Angiogenic Composite Biomaterial for the Treatment of Bone Defects

We hypothesized that a composite of 3D porous melt-electrowritten poly-ɛ-caprolactone (PCL) coated throughout with a porous and slowly biodegradable fibrin/alginate (FA) matrix would accelerate bone repair due to its angiogenic potential. Scanning electron microscopy showed that the open pore structure of the FA matrix was maintained in the PCL/FA composites. Fourier transform infrared spectroscopy and differential scanning calorimetry showed complete coverage of the PCL fibres by FA, and the PCL/FA crystallinity was decreased compared with PCL. In vitro cell work with osteoprogenitor cells showed that they preferentially bound to the FA component and proliferated on all scaffolds over 28 days. A chorioallantoic membrane assay showed more blood vessel infiltration into FA and PCL/FA compared with PCL, and a significantly higher number of bifurcation points for PCL/FA compared with both FA and PCL. Implantation into a rat cranial defect model followed by microcomputed tomography, histology, and immunohistochemistry after 4- and 12-weeks post operation showed fast early bone formation at week 4, with significantly higher bone formation for FA and PCL/FA compared with PCL. However, this phenomenon was not extrapolated to week 12. Therefore, for long-term bone regeneration, tuning of FA degradation to ensure syncing with new bone formation is likely necessary

Regression applied to protein binding site prediction and comparison with classification

<p>Abstract</p> <p>Background</p> <p>The structural genomics centers provide hundreds of protein structures of unknown function. Therefore, developing methods enabling the determination of a protein function automatically is imperative. The determination of a protein function can be achieved by studying the network of its physical interactions. In this context, identifying a potential binding site between proteins is of primary interest. In the literature, methods for predicting a potential binding site location generally are based on classification tools. The aim of this paper is to show that regression tools are more efficient than classification tools for patches based binding site predictors. For this purpose, we developed a patches based binding site localization method usable with either regression or classification tools.</p> <p>Results</p> <p>We compared predictive performances of regression tools with performances of machine learning classifiers. Using leave-one-out cross-validation, we showed that regression tools provide better predictions than classification ones. Among regression tools, Multilayer Perceptron ranked highest in the quality of predictions. We compared also the predictive performance of our patches based method using Multilayer Perceptron with the performance of three other methods usable through a web server. Our method performed similarly to the other methods.</p> <p>Conclusion</p> <p>Regression is more efficient than classification when applied to our binding site localization method. When it is possible, using regression instead of classification for other existing binding site predictors will probably improve results. Furthermore, the method presented in this work is flexible because the size of the predicted binding site is adjustable. This adaptability is useful when either false positive or negative rates have to be limited.</p

Composite structural motifs of binding sites for delineating biological functions of proteins

Most biological processes are described as a series of interactions between proteins and other molecules, and interactions are in turn described in terms of atomic structures. To annotate protein functions as sets of interaction states at atomic resolution, and thereby to better understand the relation between protein interactions and biological functions, we conducted exhaustive all-against-all atomic structure comparisons of all known binding sites for ligands including small molecules, proteins and nucleic acids, and identified recurring elementary motifs. By integrating the elementary motifs associated with each subunit, we defined composite motifs which represent context-dependent combinations of elementary motifs. It is demonstrated that function similarity can be better inferred from composite motif similarity compared to the similarity of protein sequences or of individual binding sites. By integrating the composite motifs associated with each protein function, we define meta-composite motifs each of which is regarded as a time-independent diagrammatic representation of a biological process. It is shown that meta-composite motifs provide richer annotations of biological processes than sequence clusters. The present results serve as a basis for bridging atomic structures to higher-order biological phenomena by classification and integration of binding site structures.Comment: 34 pages, 7 figure

Specialized dynamical properties of promiscuous residues revealed by simulated conformational ensembles

The ability to interact with different partners is one of the most important features in proteins. Proteins that bind a large number of partners (hubs) have been often associated with intrinsic disorder. However, many examples exist of hubs with an ordered structure, and evidence of a general mechanism promoting promiscuity in ordered proteins is still elusive. An intriguing hypothesis is that promiscuous binding sites have specific dynamical properties, distinct from the rest of the interface and pre-existing in the protein isolated state. Here, we present the first comprehensive study of the intrinsic dynamics of promiscuous residues in a large protein data set. Different computational methods, from coarse-grained elastic models to geometry-based sampling methods and to full-atom Molecular Dynamics simulations, were used to generate conformational ensembles for the isolated proteins. The flexibility and dynamic correlations of interface residues with a different degree of binding promiscuity were calculated and compared considering side chain and backbone motions, the latter both on a local and on a global scale. The study revealed that (a) promiscuous residues tend to be more flexible than nonpromiscuous ones, (b) this additional flexibility has a higher degree of organization, and (c) evolutionary conservation and binding promiscuity have opposite effects on intrinsic dynamics. Findings on simulated ensembles were also validated on ensembles of experimental structures extracted from the Protein Data Bank (PDB). Additionally, the low occurrence of single nucleotide polymorphisms observed for promiscuous residues indicated a tendency to preserve binding diversity at these positions. A case study on two ubiquitin-like proteins exemplifies how binding promiscuity in evolutionary related proteins can be modulated by the fine-tuning of the interface dynamics. The interplay between promiscuity and flexibility highlighted here can inspire new directions in protein-protein interaction prediction and design methods. © 2013 American Chemical Society