Barbeya oleoides Leaves Extracts: In Vitro Carbohydrate Digestive Enzymes Inhibition and Phytochemical Characterization

This study investigated the in vitro inhibitory potential of different solvent extracts of leaves of Barbeya oleoides on key enzymes related to type 2 diabetes mellitus (α-glucosidase and α-amylase) in combination with an aggregation assay (using 0.01% Triton X-100 detergent) to assess the specificity of action. The methanol extract was the most active in inhibiting α-glucosidase and α-amylase, with IC_{50} values of 6.67 ± 0.30 and 25.62 ± 4.12 µg/mL, respectively. However, these activities were significantly attenuated in the presence of 0.01% Triton X-100. The chemical analysis of the methanol extract was conducted utilizing a dereplication approach combing LC-ESI-MS/MS and database searching. The chemical analysis detected 27 major peaks in the negative ion mode, and 24 phenolic compounds, predominantly tannins and flavonol glycosides derivatives, were tentatively identified. Our data indicate that the enzyme inhibitory activity was probably due to aggregation-based inhibition, perhaps linked to polyphenols

Kuwaitiella rubra gen. et sp. nov. (Bangiales, Rhodophyta), a new filamentous genus and species from the north-western Indian Ocean

ACKNOWLEDGMENTS Many thanks to Bivin Thomas, Pupa Kumai and Hedda Weitz for helping in the laboratory and improving this manuscript, to Ioanna Kosma for diving, to Yusuf Buhadi for assistance during field work, archiving and preparation of herbarium specimens, and to Tatiana Mikhaylova for micrographs of previously collected filamentous red algae from Kuwait. We are grateful to La′ala Kuwait Real Estate Company and especially Mr. Fawaz Al-Marzouq for providing the salinity data. The present work is part of MHH's PhD thesis ‘Macroalgal biodiversity of Kuwait, with special emphasis on the vicinity of desalination plants’ funded by a PhD fellowship from the Kuwait Foundation for the Advancement of Sciences. FCK received support from the Marine Alliance for Science and Technology for Scotland pooling initiative. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. Work of AFP was in part supported by the project IDEALG (France: ANR-10-BTBR-04). Research Funding Agence Nationale de la Recherche. Grant Number: 10-BTBR-04 Kuwait Foundation for the Advancement of Sciences Marine Alliance for Science and Technology for Scotland IDEALG. Grant Number: ANR-10-BTBR-04 Scottish Funding Council. Grant Number: HR09011 Marine Alliance for Science and Technology Kuwait Foundation for the Advancement of SciencesPeer reviewedPublisher PD

Soliton pair dynamics in patterned ferromagnetic ellipses

Confinement alters the energy landscape of nanoscale magnets, leading to the appearance of unusual magnetic states, such as vortices, for example. Many basic questions concerning dynamical and interaction effects remain unanswered, and nanomagnets are convenient model systems for studying these fundamental physical phenomena. A single vortex in restricted geometry, also known as a non-localized soliton, possesses a characteristic translational excitation mode that corresponds to spiral-like motion of the vortex core around its equilibrium position. Here, we investigate, by a microwave reflection technique, the dynamics of magnetic soliton pairs confined in lithographically defined, ferromagnetic Permalloy ellipses. Through a comparison with micromagnetic simulations, the observed strong resonances in the subgigahertz frequency range can be assigned to the translational modes of vortex pairs with parallel or antiparallel core polarizations. Vortex polarizations play a negligible role in the static interaction between two vortices, but their effect dominates the dynamics.Comment: supplemental movies on http://www.nature.com/nphys/journal/v1/n3/suppinfo/nphys173_S1.htm

Memory Lower Bounds of Reductions Revisited

In Crypto 2017, Auerbach et al. initiated the study on memory-tight reductions and proved two negative results on the memory-tightness of restricted black-box reductions from multi-challenge security to single-challenge security for signatures and an artificial hash function. In this paper, we revisit the results by Auerbach et al. and show that for a large class of reductions treating multi-challenge security, it is impossible to avoid loss of memory-tightness unless we sacrifice the efficiency of their running-time. Specifically, we show three lower bound results. Firstly, we show a memory lower bound of natural black-box reductions from the multi-challenge unforgeability of unique signatures to any computational assumption. Then we show a lower bound of restricted reductions from multi-challenge security to single-challenge security for a wide class of cryptographic primitives with unique keys in the multi-user setting. Finally, we extend the lower bound result shown by Auerbach et al. treating a hash function to one treating any hash function with a large domain

A human MAP kinase interactome.

Mitogen-activated protein kinase (MAPK) pathways form the backbone of signal transduction in the mammalian cell. Here we applied a systematic experimental and computational approach to map 2,269 interactions between human MAPK-related proteins and other cellular machinery and to assemble these data into functional modules. Multiple lines of evidence including conservation with yeast supported a core network of 641 interactions. Using small interfering RNA knockdowns, we observed that approximately one-third of MAPK-interacting proteins modulated MAPK-mediated signaling. We uncovered the Na-H exchanger NHE1 as a potential MAPK scaffold, found links between HSP90 chaperones and MAPK pathways and identified MUC12 as the human analog to the yeast signaling mucin Msb2. This study makes available a large resource of MAPK interactions and clone libraries, and it illustrates a methodology for probing signaling networks based on functional refinement of experimentally derived protein-interaction maps

Single-particle structure at N=29 : The structure of Ar 47 and first spectroscopy of S 45

Comprehensive spectroscopy of the N=29 nucleus Ar47 is presented, based on two complementary direct reaction mechanisms: one-neutron pickup onto Ar46 projectiles and one-proton removal from the 1- ground state of K48. The results are compared with shell-model calculations that use the state-of-the-art SDPF-U and SDPF-MU effective interactions. Also, from the Be9(Cl46,S45+γ)X one-proton-removal reaction, we report the first γ-ray transitions observed from S45. By using comparisons with shell-model calculations, and from the observed intensities and energy sums, we propose a first tentative level scheme for S45

Glycogen Synthase Kinase (GSK) 3β phosphorylates and protects nuclear myosin 1c from proteasome-mediated degradation to activate rDNA transcription in early G1 cells

Nuclear myosin 1c (NM1) mediates RNA polymerase I (pol I) transcription activation and cell cycle progression by facilitating PCAF-mediated H3K9 acetylation, but the molecular mechanism by which NM1 is regulated remains unclear. Here, we report that at early G1 the glycogen synthase kinase (GSK) 3β phosphorylates and stabilizes NM1, allowing for NM1 association with the chromatin. Genomic analysis by ChIP-Seq showed that this mechanism occurs on the rDNA as active GSK3β selectively occupies the gene. ChIP assays and transmission electron microscopy in GSK3β-/- mouse embryonic fibroblasts indicated that at G1 rRNA synthesis is suppressed due to decreased H3K9 acetylation leading to a chromatin state incompatible with transcription. We found that GSK3β directly phosphorylates the endogenous NM1 on a single serine residue (Ser-1020) located within the NM1 C-terminus. In G1 this phosphorylation event stabilizes NM1 and prevents NM1 polyubiquitination by the E3 ligase UBR5 and proteasome-mediated degradation. We conclude that GSK3β-mediated phosphorylation of NM1 is required for pol I transcription activation

Fast network centrality analysis using GPUs

<p>Abstract</p> <p>Background</p> <p>With the exploding volume of data generated by continuously evolving high-throughput technologies, biological network analysis problems are growing larger in scale and craving for more computational power. General Purpose computation on Graphics Processing Units (GPGPU) provides a cost-effective technology for the study of large-scale biological networks. Designing algorithms that maximize data parallelism is the key in leveraging the power of GPUs.</p> <p>Results</p> <p>We proposed an efficient data parallel formulation of the All-Pairs Shortest Path problem, which is the key component for shortest path-based centrality computation. A betweenness centrality algorithm built upon this formulation was developed and benchmarked against the most recent GPU-based algorithm. Speedup between 11 to 19% was observed in various simulated scale-free networks. We further designed three algorithms based on this core component to compute closeness centrality, eccentricity centrality and stress centrality. To make all these algorithms available to the research community, we developed a software package <it>gpu</it>-<it>fan </it>(GPU-based Fast Analysis of Networks) for CUDA enabled GPUs. Speedup of 10-50× compared with CPU implementations was observed for simulated scale-free networks and real world biological networks.</p> <p>Conclusions</p> <p><it>gpu</it>-<it>fan </it>provides a significant performance improvement for centrality computation in large-scale networks. Source code is available under the GNU Public License (GPL) at <url>http://bioinfo.vanderbilt.edu/gpu-fan/</url>.</p

Ranked retrieval of Computational Biology models

<p>Abstract</p> <p>Background</p> <p>The study of biological systems demands computational support. If targeting a biological problem, the reuse of existing computational models can save time and effort. Deciding for potentially suitable models, however, becomes more challenging with the increasing number of computational models available, and even more when considering the models' growing complexity. Firstly, among a set of potential model candidates it is difficult to decide for the model that best suits ones needs. Secondly, it is hard to grasp the nature of an unknown model listed in a search result set, and to judge how well it fits for the particular problem one has in mind.</p> <p>Results</p> <p>Here we present an improved search approach for computational models of biological processes. It is based on existing retrieval and ranking methods from Information Retrieval. The approach incorporates annotations suggested by MIRIAM, and additional meta-information. It is now part of the search engine of BioModels Database, a standard repository for computational models.</p> <p>Conclusions</p> <p>The introduced concept and implementation are, to our knowledge, the first application of Information Retrieval techniques on model search in Computational Systems Biology. Using the example of BioModels Database, it was shown that the approach is feasible and extends the current possibilities to search for relevant models. The advantages of our system over existing solutions are that we incorporate a rich set of meta-information, and that we provide the user with a relevance ranking of the models found for a query. Better search capabilities in model databases are expected to have a positive effect on the reuse of existing models.</p