Design of a data model for developing laboratory information management and analysis systems for protein production

Data management has emerged as one of the central issues in the high-throughput processes of taking a protein target sequence through to a protein sample. To simplify this task, and following extensive consultation with the international structural genomics community, we describe here a model of the data related to protein production. The model is suitable for both large and small facilities for use in tracking samples, experiments, and results through the many procedures involved. The model is described in Unified Modeling Language (UML). In addition, we present relational database schemas derived from the UML. These relational schemas are already in use in a number of data management projects.     

Human metabolic phenotypes link directly to specific dietary preferences in healthy individuals

Individual human health is determined by a complex interplay between genes, environment, diet, lifestyle, and symbiotic gut microbial activity. Here, we demonstrate a new "nutrimetabonomic" approach in which spectroscopically generated metabolic phenotypes are correlated with behavioral/psychological dietary preference, namely, "chocolate desiring" or "chocolate indifferent". Urinary and plasma metabolic phenotypes are characterized by differential metabolic biomarkers, measured using 1H NMR spectroscopy, including the postprandial lipoprotein profile and gut microbial co-metabolism. These data suggest that specific dietary preferences can influence basal metabolic state and gut microbiome activity that in turn may have long-term health consequences to the host. Nutrimetabonomics appears as a promising approach for the classification of dietary responses in populations and personalized nutritional management.     

Neuromechanics: an integrative approach for understanding motor control

Neuromechanics seeks to understand how muscles, sense organs,motor pattern generators, and brain interact to produce coordinatedmovement, not only in complex terrain but also when confrontedwith unexpected perturbations. Applications of neuromechanicsinclude ameliorating human health problems (including prosthesisdesign and restoration of movement following brain or spinalcord injury), as well as the design, actuation and control ofmobile robots. In animals, coordinated movement emerges fromthe interplay among descending output from the central nervoussystem, sensory input from body and environment, muscle dynamics,and the emergent dynamics of the whole animal. The inevitablecoupling between neural information processing and the emergentmechanical behavior of animals is a central theme of neuromechanics.Fundamentally, motor control involves a series of transformationsof information, from brain and spinal cord to muscles to body,and back to brain. The control problem revolves around the specifictransfer functions that describe each transformation. The transferfunctions depend on the rules of organization and operationthat determine the dynamic behavior of each subsystem (i.e.,central processing, force generation, emergent dynamics, andsensory processing). In this review, we (1) consider the contributionsof muscles, (2) sensory processing, and (3) central networksto motor control, (4) provide examples to illustrate the interplayamong brain, muscles, sense organs and the environment in thecontrol of movement, and (5) describe advances in both roboticsand neuromechanics that have emerged from application of biologicalprinciples in robotic design. Taken together, these studiesdemonstrate that (1) intrinsic properties of muscle contributeto dynamic stability and control of movement, particularly immediatelyafter perturbations; (2) proprioceptive feedback reinforcesthese intrinsic self-stabilizing properties of muscle; (3) controlsystems must contend with inevitable time delays that can simplifyor complicate control; and (4) like most animals under a varietyof circumstances, some robots use a trial and error processto tune central feedforward control to emergent body dynamics.     

Trophic network models explain instability of Early Triassic terrestrial communities

Studies of the end-Permian mass extinction have emphasized potential abiotic causes and their direct biotic effects. Less attention has been devoted to secondary extinctions resulting from ecological crises and the effect of community structure on such extinctions. Here we use a trophic network model that combines topological and dynamic approaches to simulate disruptions of primary productivity in palaeocommunities. We apply the model to Permian and Triassic communities of the Karoo Basin, South Africa, and show that while Permian communities bear no evidence of being especially susceptible to extinction, Early Triassic communities appear to have been inherently less stable. Much of the instability results from the faster post-extinction diversification of amphibian guilds relative to amniotes. The resulting communities differed fundamentally in structure from their Permian predecessors. Additionally, our results imply that changing community structures over time may explain long-term trends like declining rates of Phanerozoic background extinction.     

HIV-1 Neutralizing Antibody Signatures and Application to Epitope-Targeted Vaccine Design

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Potent inhibitors of malarial P. Falciparum protein kinase G: Improving the cell activity of a series of imidazopyridines

Development of a class of bicyclic inhibitors of the Plasmodium falciparum cyclic GMP-dependent protein kinase (PfPKG), starting from known compounds with activity against a related parasite PKG orthologue, is reported. Examination of key sub-structural elements led to new compounds with good levels of inhibitory activity against the recombinant kinase and in vitro activity against the parasite. Key examples were shown to possess encouraging in vitro ADME properties, and computational analysis provided valuable insight into the origins of the observed activity profiles.     

Selective estrogen receptor degraders with novel structural motifs induce regression in a tamoxifen-resistant breast cancer xenograft

Potent estrogen receptor ligands typically contain a phenolic hydrogen-bond donor. The indazole of the selective estrogen receptor degrader (SERD) ARN-810 is believed to mimic this. Disclosed herein is the discovery of ARN-810 analogs which lack this hydrogen-bond donor. These SERDs induced tumor regression in a tamoxifen-resistant breast cancer xenograft, demonstrating that the indazole NH is not necessary for robust ER-modulation and anti-tumor activity.