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Local and Global Cytosolic Ca-2+ Oscillations Evoked by Agonists and Inositol Trisphosphate
No full textThe agonists acetylcholine (ACh) and cholecystokinin (CCK) evoke oscillating cytosolic Ca2+ signals in pancreatic acinar cells. Low agonist concentrations evoke local cytosolic Ca2+ spikes confined to the secretory pole region and intracellular inositol trisphosphate application can mimick this action. These spikes can occur alone, repetitively or precede longer lasting Ca2+ transients that spread throughout the cell. ACh and CCK evoke different Ca2+ signal patterns also influenced by the resting cytosolic Ca2+ concentration ([Ca2+]i). Ca2+ pump-mediated Ca2+ extrusion occurs in a pulsatile manner and is synchronous with the transient elevations of [Ca2+]i.LSENSUniv cambridge,dept zool,afrc,molec signalling lab,cambridge cb2 3ej,england
Surface optimization of RBa2Cu3O7-delta (R = Y, Nd) epitaxial high T-c films for in situ photoemission studies
No full textOne of the intrinsic difficulties for in situ photoemission studies of high T-c oxide films is the surface volatility, especially the oxygen loss. In order to solve this problem, we have constructed a dedicated system for high T-c film surface studies, in particular for ARPES measurements. Here we briefly describe our pulsed laser deposition (PLD) system that is linked to the photoemission chamber at the Synchrotron Radiation Center (SRC) in Wisconsin, and discuss crystallographic and electronic properties measured on epitaxial YBa2Cu3O7-delta (YBCO) and NdBa2Cu3O7-delta (NBCO) films. Resistivity and XRD studies show that the best c axis epitaxial films, with T-c (onset) = 92 K (T-c0 = 90.5 K), are monophase and single crystalline with crystal coherence up to almost 1 mum. Initial core level photoemission study indicates that, for YBCO on SrTiO3 (without any buffer layer), the Ba oxide layer tends to be the dominant surface layer. Further experiments are underway to reproducibly detect sharp Fermi edge and perform ARPES study on optimally doped film surfaces.LPR
Combining physics-based and data-driven models: advancing the frontiers of research with scientific machine learning
No full textScientific Machine Learning (SciML) is a recently emerged research field which combines physics-based and data-driven models for the numerical approximation of differential problems. Physics-based models rely on the physical understanding of the problem at hand, subsequent mathematical formulation, and numerical approximation. Data-driven models instead aim to extract relations between input and output data without arguing any causality principle underlining the available data distribution. In recent years, data-driven models have been rapidly developed and popularised. Such a diffusion has been triggered by a huge availability of data (the so-called big data), an increasingly cheap computing power, and the development of powerful Machine Learning (ML) algorithms. SciML leverages the physical awareness of physics-based models and, at the same time, the efficiency of data-driven algorithms. With SciML, we can inject physics and mathematical knowledge into ML algorithms. Yet, we can rely on data-driven algorithms’ capability to discover complex and nonlinear patterns from data and improve the descriptive capacity of physics-based models. After recalling the mathematical foundations of digital modelling and ML algorithms, and presenting the most popular ML architectures, we discuss the great potential of a broad variety of SciML strategies in solving complex problems governed by Partial Differential Equations (PDEs). Finally, we illustrate the successful application of SciML to the simulation of the human cardiac function, a field of significant socio-economic importance that poses numerous challenges on both the mathematical and computational fronts. The corresponding mathematical model is a complex system of nonlinear ordinary and PDEs describing the electromechanics, valve dynamics, blood circulation, perfusion in the coronary tree, and torso potential. Despite the robustness and accuracy of physics-based models, certain aspects, such as unveiling constitutive laws for cardiac cells and myocardial material properties, as well as devising efficient reduced-order models to dominate the extraordinary computational complexity, have been successfully tackled by leveraging data-driven models.PH-S
General coordinate invariance in quantum many-body systems
No full textWe extend the notion of general coordinate invariance to many-body, not necessarily relativistic, systems. As an application, we investigate nonrelativistic general covariance in Galilei-invariant systems. The peculiar transformation rules for the background metric and gauge fields, first introduced by Son and Wingate in 2005 and refined in subsequent works, follow naturally from our framework. Our approach makes it clear that Galilei or Poincare symmetry is by no means a necessary prerequisite for making the theory invariant under coordinate diffeomorphisms. General covariance merely expresses the freedom to choose spacetime coordinates at will, whereas the true, physical symmetries of the system can be separately implemented as "internal" symmetries within the vielbein formalism. A systematic way to implement such symmetries is provided by the coset construction. We illustrate this point by applying our formalism to nonrelativistic s-wave superfluids.LPPCLPT
Identification techniques for highly boosted W bosons that decay into hadrons
No full textIn searches for new physics in the energy regime of the LHC, it is becoming increasingly important to distinguish single-jet objects that originate from the merging of the decay products of W bosons produced with high transverse momenta from jets initiated by single partons. Algorithms are defined to identify such W jets for different signals of interest, using techniques that are also applicable to other decays of bosons to hadrons that result in a single jet, such as those from highly boosted Z and Higgs bosons. The efficiency for tagging W jets is measured in data collected with the CMS detector at a center-of-mass energy of 8 TeV, corresponding to an integrated luminosity of 19.7 fb. The performance of W tagging in data is compared with predictions from several Monte Carlo simulators.LPH
Feasible optimality implies Hack's law
No full textWe analyze the elongation (the scaling properties of drainage area with mainstream length) in optimal channel networks (OCNs) obtained through different algorithms searching for the minimum of a functional computing the total energy dissipation of the drainage system. The algorithms have different capabilities to overcome the imprinting of initial and boundary conditions, and thus they have different chances of attaining the global optimum. We find that suboptimal shapes, i.e., dynamically accessible states characterized by locally stationary total potential energy, show the robust type of elongation that is consistently observed in nature. This suggestive and directly measurable property is not found in the so-called ground state, i.e., the global minimum, whose features, including elongation, are known exactly. The global minimum is shown to be too regular and symmetric to be dynamically accessible in nature, owing to features and constraints of erosional processes. Thus Hack's law is seen as a signature of feasible optimality thus yielding further support to the suggestion that optimality of the system as a whole explains the dynamic origin of fractal forms in nature.ECH
Wdr1 and cofilin are necessary mediators of immune-cell-specific apoptosis triggered by Tecfidera
No full textThe mechanism-of-action of many electrohilic drugs remains poorly understood. Here, the authors use a redox-targeting approach to elucidate the basis for the innate immune cell toxicity of dimethyl fumarate, showing that it modifies Keap1 to trigger mitochondrial-targeted neutrophil/macrophage apoptosis.Despite the emerging importance of reactive electrophilic drugs, deconvolution of their principal targets remains difficult. The lack of genetic tractability/interventions and reliance on secondary validation using other non-specific compounds frequently complicate the earmarking of individual binders as functionally- or phenotypically-sufficient pathway regulators. Using a redox-targeting approach to interrogate how on-target binding of pleiotropic electrophiles translates to a phenotypic output in vivo, we here systematically track the molecular components attributable to innate immune cell toxicity of the electrophilic-drug dimethyl fumarate (Tecfidera (R)). In a process largely independent of canonical Keap1/Nrf2-signaling, Keap1-specific modification triggers mitochondrial-targeted neutrophil/macrophage apoptosis. On-target Keap1-ligand-engagement is accompanied by dissociation of Wdr1 from Keap1 and subsequent coordination with cofilin, intercepting Bax. This phagocytic-specific cell-killing program is recapitulated by whole-animal administration of dimethyl fumarate, where individual depletions of the players identified above robustly suppress apoptosis.LEAG
Synthesis and characterization of bifunctional probes for the specific labeling of fusion proteins
No full textLabeling proteins with synthetic probes is important for studying and characterizing protein function. We have recently introduced a general method for the specific in vivo and in vitro labeling of fusion proteins that is based on the reaction of O6-alkylguanine-DNA alkyltransferase (AGT) with O6-benzylguanine derivs. Here we report two complementary routes for the synthesis of O6-benzylguanine derivs., which allow for the labeling of AGT fusion proteins with bifunctional synthetic probes and demonstrate the specific labeling of AGT fusion proteins with these probes. These mols. should become useful tools for various applications in functional proteomics. [on SciFinder (R)]LI