Reconstruction of the yeast Snf1 kinase regulatory network reveals its role as a global energy regulator

Highly conserved among eukaryotic cells, the AMP-activated kinase (AMPK) is a central regulator of carbon metabolism. To map the complete network of interactions around AMPK in yeast (Snf1) and to evaluate the role of its regulatory subunit Snf4, we measured global mRNA, protein and metabolite levels in wild type, Δsnf1, Δsnf4, and Δsnf1Δsnf4 knockout strains. Using four newly developed computational tools, including novel DOGMA sub-network analysis, we showed the benefits of three-level ome-data integration to uncover the global Snf1 kinase role in yeast. We for the first time identified Snf1's global regulation on gene and protein expression levels, and showed that yeast Snf1 has a far more extensive function in controlling energy metabolism than reported earlier. Additionally, we identified complementary roles of Snf1 and Snf4. Similar to the function of AMPK in humans, our findings showed that Snf1 is a low-energy checkpoint and that yeast can be used more extensively as a model system for studying the molecular mechanisms underlying the global regulation of AMPK in mammals, failure of which leads to metabolic diseases

How Many Subpopulations is Too Many? Exponential Lower Bounds for Inferring Population Histories

Reconstruction of population histories is a central problem in population genetics. Existing coalescent-based methods, like the seminal work of Li and Durbin (Nature, 2011), attempt to solve this problem using sequence data but have no rigorous guarantees. Determining the amount of data needed to correctly reconstruct population histories is a major challenge. Using a variety of tools from information theory, the theory of extremal polynomials, and approximation theory, we prove new sharp information-theoretic lower bounds on the problem of reconstructing population structure -- the history of multiple subpopulations that merge, split and change sizes over time. Our lower bounds are exponential in the number of subpopulations, even when reconstructing recent histories. We demonstrate the sharpness of our lower bounds by providing algorithms for distinguishing and learning population histories with matching dependence on the number of subpopulations. Along the way and of independent interest, we essentially determine the optimal number of samples needed to learn an exponential mixture distribution information-theoretically, proving the upper bound by analyzing natural (and efficient) algorithms for this problem.Comment: 38 pages, Appeared in RECOMB 201

Ab-initio Quantum Enhanced Optical Phase Estimation Using Real-time Feedback Control

Optical phase estimation is a vital measurement primitive that is used to perform accurate measurements of various physical quantities like length, velocity and displacements. The precision of such measurements can be largely enhanced by the use of entangled or squeezed states of light as demonstrated in a variety of different optical systems. Most of these accounts however deal with the measurement of a very small shift of an already known phase, which is in stark contrast to ab-initio phase estimation where the initial phase is unknown. Here we report on the realization of a quantum enhanced and fully deterministic phase estimation protocol based on real-time feedback control. Using robust squeezed states of light combined with a real-time Bayesian estimation feedback algorithm, we demonstrate deterministic phase estimation with a precision beyond the quantum shot noise limit. The demonstrated protocol opens up new opportunities for quantum microscopy, quantum metrology and quantum information processing.Comment: 5 figure

An empirical model for estimating fracture toughness using the DCDC geometry

The double cleavage drilled compression (DCDC) geometry is useful for creating large cracks in a material in a controlled manner. Several models for estimating fracture toughness from DCDC measurements have been proposed, but each is suitable for a subset of geometries and material properties. In this work, a series of finite element fracture simulations are performed over a range of sample widths, hole sizes, heights, Young's moduli, Poisson's ratios, critical stress intensity factors, and boundary conditions. Analyzing the simulation results, fracture toughness is found to be a simple function of sample width, hole size, and an extrapolated stress at zero crack length obtained from a linear fit of the data. Experimental results in the literature are found to agree with this simple relationship. © 2014 Springer Science+Business Media Dordrecht

Evolution of Th2 responses : Characterization of IL-4/13 in sea bass (Dicentrarchus labrax L.) and studies of expression and biological activity

Acknowledgements This research was funded by the European Commission under the 7th Framework Programme for Research and Technological Development (FP7) of the European Union (Grant Agreement 311993 TARGETFISH). T.W. received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland). MASTS is funded by the Scottish Funding Council (grant reference number HR09011) and contributing institutions.Peer reviewedPublisher PD

Crack healing in cross-ply composites observed by dynamic mechanical analysis

Cross-ply composites with healable polymer matrices are characterized using dynamic mechanical analysis (DMA). The [90,0]s samples are prepared by embedding layers of unidirectional glass or carbon fibers in 2MEP4FS, a polymer with thermally reversible covalent cross-links, which has been shown to be capable of healing internal cracks and fully recovering fracture toughness when the crack surfaces are kept in contact. After fabrication, cracks in the composites' transverse plies are observed due to residual thermal stresses introduced during processing. Single cantilever bending DMA measurements show the samples exhibit periods of increasing storage moduli with increasing temperature. These results are accurately modeled as a one-dimensional composite, which captures the underlying physics of the phenomenon. The effect of cracks on the stiffness is accounted for by a shear-lag model. The predicted crack density of the glass fiber composite is shown to fall within a range observed from microscopy images. Crack healing occurs as a function of temperature, with chemistry and mechanics-based rationales given for the onset and conclusion of healing. The model captures the essential physics of the phenomenon and yields results in accord with experimental observations

Cumulate causes for the low contents of sulfide-loving elements in the continental crust

Despite the economic importance of chalcophile (sulfide-loving) and siderophile (metal-loving) elements (CSEs), it is unclear how they become enriched or depleted in the continental crust, compared with the oceanic crust. This is due in part to our limited understanding of the partitioning behaviour of the CSEs. Here I compile compositional data for mid-ocean ridge basalts and subduction-related volcanic rocks. I show that the mantle-derived melts that contribute to oceanic and continental crust formation rarely avoid sulfide saturation during cooling in the crust and, on average, subduction-zone magmas fractionate sulfide at the base of the continental crust prior to ascent. Differentiation of mantle-derived melts enriches lower crustal sulfide- and silicate-bearing cumulates in some CSEs compared with the upper crust. This storage predisposes the cumulate-hosted compatible CSEs (such as Cu and Au) to be recycled back into the mantle during subduction and delamination, resulting in their low contents in the bulk continental crust and potentially contributing to the scarcity of ore deposits in the upper continental crust. By contrast, differentiation causes the upper oceanic and continental crust to become enriched in incompatible CSEs (such as W) compared with the lower oceanic and continental crust. Consequently, incompatible CSEs are predisposed to become enriched in subduction-zone magmas that contribute to continental crust formation and are less susceptible to removal from the continental crust via delamination compared with the compatible CSEs

Cross modal perception of body size in domestic dogs (Canis familiaris)

While the perception of size-related acoustic variation in animal vocalisations is well documented, little attention has been given to how this information might be integrated with corresponding visual information. Using a cross-modal design, we tested the ability of domestic dogs to match growls resynthesised to be typical of either a large or a small dog to size- matched models. Subjects looked at the size-matched model significantly more often and for a significantly longer duration than at the incorrect model, showing that they have the ability to relate information about body size from the acoustic domain to the appropriate visual category. Our study suggests that the perceptual and cognitive mechanisms at the basis of size assessment in mammals have a multisensory nature, and calls for further investigations of the multimodal processing of size information across animal species