The Role of the Arched Helicases in Exosome-Mediated Function

RNA processing and degradation are two important functions that control gene expression and promote RNA fidelity in the cell. A major ribonuclease complex, called the exosome, is involved in both of these processes. The exosome is composed of ten essential proteins with only one catalytically active subunit, called Rrp44. While the same ten essential subunits make up both the nuclear and cytoplasmic exosome, there are nuclear and cytoplasmic exosome cofactors that promote specific exosome functions in each of the cell compartments. To date, it is unclear how the exosome distinguishes between RNA substrates. We hypothesize that compartment specific cofactors may promote the substrate specificity of the exosome. In this work, I characterize several cofactors of the exosome, both nuclear and cytoplasmic. First, I describe the arch domain, which is a unique domain in a nuclear and a cytoplasmic cofactor of the exosome. Specifically, I show that the arch domain of the nuclear exosome cofactor, Mtr4, is required for specific exosome-mediated activities and overlaps functionally with the exosome-associated exonuclease, Rrp6. Further, I show that the arch domain of Ski2 is required for the degradation of normal and aberrant mRNAs. Additionally, this work describes in detail the Mtr4 domains involved in the physical association with other RNA processing proteins. Further, I characterize the minimal Mtr4-binding region in a third exosome cofactor, Trf5. Understanding how exosome cofactors synergistically promote exosome function will provide us a better understanding of how the exosome complex precisely regulates its catalytic activities. As described here, cofactors play a major role in determining the substrate specificity of the nuclear and cytoplasmic exosome. Moreover, specific accessory domains, which are not involved in the catalytic function of the cofactor, are required for substrate targeting of the eukaryotic RNA exosome.

High Fidelity Models for Near-Earth Object Dynamics

Motivado por los últimos hallazgos realizados gracias a los recientes avances tecnológicos y misiones espaciales, el estudio de los asteroides ha despertado el interés de la comunidad científica. Tal es así que las misiones a asteroides han proliferado en los últimos años (Hayabusa, Dawn, OSIRIX-REx, ARM, AIMS-DART, ...) incentivadas por su enorme interés científico. Los asteroides son constituyentes fundamentales en la evolución del Sistema Solar, son además grandes concentraciones de valiosos recursos naturales, y también pueden considerarse como objectivos estratégicos para la futura exploración espacial. Desde hace tiempo se viene especulando con la posibilidad de capturar objetos próximos a la Tierra (NEOs en su acrónimo anglosajón) y acercarlos a nuestro planeta, permitiendo así un acceso asequible a los mismos para estudiarlos in-situ, explotar sus recursos u otras finalidades. Por otro lado, las asteroides se consideran con frecuencia como posibles peligros de magnitud planetaria, ya que impactos de estos objetos con la Tierra suceden constantemente, y un asteroide suficientemente grande podría desencadenar eventos catastróficos. Pese a la gravedad de tales acontecimientos, lo cierto es que son ciertamente difíciles de predecir. De hecho, los ricos aspectos dinámicos de los asteroides, su modelado complejo y las incertidumbres observaciones hacen que predecir su posición futura con la precisión necesaria sea todo un reto. Este hecho se hace más relevante cuando los asteroides sufren encuentros próximos con la Tierra, y más aún cuando estos son recurrentes. En tales situaciones en las cuales fuera necesario tomar medidas para mitigar este tipo de riesgos, saber estimar con precisión sus trayectorias y probabilidades de colisión es de una importancia vital. Por ello, se necesitan herramientas avanzadas para modelar su dinámica y predecir sus órbitas con precisión, y son también necesarios nuevos conceptos tecnológicos para manipular sus órbitas llegado el caso. El objetivo de esta Tesis es proporcionar nuevos métodos, técnicas y soluciones para abordar estos retos. Las contribuciones de esta Tesis se engloban en dos áreas: una dedicada a la propagación numérica de asteroides, y otra a conceptos de deflexión y captura de asteroides. Por lo tanto, la primera parte de este documento presenta novedosos avances de apliación a la propagación dinámica de alta precisión de NEOs empleando métodos de regularización y perturbaciones, con especial énfasis en el método DROMO, mientras que la segunda parte expone ideas innovadoras para la captura de asteroides y comenta el uso del “ion beam shepherd” (IBS) como tecnología para deflectarlos. Abstract Driven by the latest discoveries enabled by recent technological advances and space missions, the study of asteroids has awakened the interest of the scientific community. In fact, asteroid missions have become very popular in the recent years (Hayabusa, Dawn, OSIRIX-REx, ARM, AIMS-DART, ...) motivated by their outstanding scientific interest. Asteroids are fundamental constituents in the evolution of the Solar System, can be seen as vast concentrations of valuable natural resources, and are also considered as strategic targets for the future of space exploration. For long it has been hypothesized with the possibility of capturing small near-Earth asteroids and delivering them to the vicinity of the Earth in order to allow an affordable access to them for in-situ science, resource utilization and other purposes. On the other side of the balance, asteroids are often seen as potential planetary hazards, since impacts with the Earth happen all the time, and eventually an asteroid large enough could trigger catastrophic events. In spite of the severity of such occurrences, they are also utterly hard to predict. In fact, the rich dynamical aspects of asteroids, their complex modeling and observational uncertainties make exceptionally challenging to predict their future position accurately enough. This becomes particularly relevant when asteroids exhibit close encounters with the Earth, and more so when these happen recurrently. In such situations, where mitigation measures may need to be taken, it is of paramount importance to be able to accurately estimate their trajectories and collision probabilities. As a consequence, advanced tools are needed to model their dynamics and accurately predict their orbits, as well as new technological concepts to manipulate their orbits if necessary. The goal of this Thesis is to provide new methods, techniques and solutions to address these challenges. The contributions of this Thesis fall into two areas: one devoted to the numerical propagation of asteroids, and another to asteroid deflection and capture concepts. Hence, the first part of the dissertation presents novel advances applicable to the high accuracy dynamical propagation of near-Earth asteroids using regularization and perturbations techniques, with a special emphasis in the DROMO method, whereas the second part exposes pioneering ideas for asteroid retrieval missions and discusses the use of an “ion beam shepherd” (IBS) for asteroid deflection purposes.

Dynamical properties of a strongly correlated model for quarter-filled layered organic molecular crystals

The dynamical properties of an extended Hubbard model, which is relevant to quarter-filled layered organic molecular crystals, are analyzed. We have computed the dynamical charge correlation function, spectral density, and optical conductivity using Lanczos diagonalization and large-N techniques. As the ratio of the nearest-neighbor Coulomb repulsion, V, to the hopping integral, t, increases there is a transition from a metallic phase to a charge-ordered phase. Dynamical properties close to the ordering transition are found to differ from the ones expected in a conventional metal. Large-N calculations display an enhancement of spectral weight at low frequencies as the system is driven closer to the charge-ordering transition in agreement with Lanczos calculations. As V is increased the charge correlation function displays a collective mode which, for wave vectors close to (pi,pi), increases in amplitude and softens as the charge-ordering transition is approached. We propose that inelastic x-ray scattering be used to detect this mode. Large-N calculations predict superconductivity with d(xy) symmetry close to the ordering transition. We find that this is consistent with Lanczos diagonalization calculations, on lattices of 20 sites, which find that the binding energy of two holes becomes negative close to the charge-ordering transition.

Dynamical creation of entanglement by homodyne-mediated feedback

For two two-level atoms coupled to a single Bosonic mode that is driven and heavily damped, the steady state can be entangled by resonantly driving the system [S. Schneider and G. J. Milburn, Phys. Rev. A 65, 042107 (2002)]. We present a scheme to significantly increase the steady-state entanglement by using homodyne-mediated feedback, in which the Bosonic mode is that of an electromagnetic cavity, the output of which is measured and the resulting homodyne photocurrent is used to modulate the field driving the qubits. Such feedback can increase the nonlinear response to both the decoherence process of the two-qubit system and the coherent evolution of individual qubits. We present the properties of the entangled states using the SO(3) Q function.

Inhibition of S/G(2) phase CDK4 reduces mitotic fidelity

Cyclin-dependent kinase 4 (CDK4)/cyclin D has a key role in regulating progression through late G(1) into S phase of the cell cycle. CDK4-cyclin D complexes then persist through the latter phases of the cell cycle, although little is known about their potential roles. We have developed small molecule inhibitors that are highly selective for CDK4 and have used these to define a role for CDK4-cyclin D in G(2) phase. The addition of the CDK4 inhibitor or small interfering RNA knockdown of cyclin D3, the cyclin D partner, delayed progression through G(2) phase and mitosis. The G(2) phase delay was independent of ATM/ATR and p38 MAPK but associated with elevated Wee1. The mitotic delay was because of failure of chromosomes to migrate to the metaphase plate. However, cells eventually exited mitosis, with a resultant increase in cells with multiple or micronuclei. Inhibiting CDK4 delayed the expression of the chromosomal passenger proteins survivin and borealin, although this was unlikely to account for the mitotic phenotype. These data provide evidence for a novel function for CDK4-cyclin D3 activity in S and G(2) phase that is critical for G(2)/M progression and the fidelity of mitosis.

Approximate Bayesian techniques for inference in stochastic dynamical systems

This thesis is concerned with approximate inference in dynamical systems, from a variational Bayesian perspective. When modelling real world dynamical systems, stochastic differential equations appear as a natural choice, mainly because of their ability to model the noise of the system by adding a variant of some stochastic process to the deterministic dynamics. Hence, inference in such processes has drawn much attention. Here two new extended frameworks are derived and presented that are based on basis function expansions and local polynomial approximations of a recently proposed variational Bayesian algorithm. It is shown that the new extensions converge to the original variational algorithm and can be used for state estimation (smoothing). However, the main focus is on estimating the (hyper-) parameters of these systems (i.e. drift parameters and diffusion coefficients). The new methods are numerically validated on a range of different systems which vary in dimensionality and non-linearity. These are the Ornstein-Uhlenbeck process, for which the exact likelihood can be computed analytically, the univariate and highly non-linear, stochastic double well and the multivariate chaotic stochastic Lorenz '63 (3-dimensional model). The algorithms are also applied to the 40 dimensional stochastic Lorenz '96 system. In this investigation these new approaches are compared with a variety of other well known methods such as the ensemble Kalman filter / smoother, a hybrid Monte Carlo sampler, the dual unscented Kalman filter (for jointly estimating the systems states and model parameters) and full weak-constraint 4D-Var. Empirical analysis of their asymptotic behaviour as a function of observation density or length of time window increases is provided.

Recursive self-organizing map as a contractive iterative function system

Recently, there has been a considerable research activity in extending topographic maps of vectorial data to more general data structures, such as sequences or trees. However, the representational capabilities and internal representations of the models are not well understood. We rigorously analyze a generalization of the Self-Organizing Map (SOM) for processing sequential data, Recursive SOM (RecSOM [1]), as a non-autonomous dynamical system consisting off a set of fixed input maps. We show that contractive fixed input maps are likely to produce Markovian organizations of receptive fields o the RecSOM map. We derive bounds on parameter $\beta$ (weighting the importance of importing past information when processing sequences) under which contractiveness of the fixed input maps is guaranteed.

Quantifying simulator discrepancy in discrete-time dynamical simulators

When making predictions with complex simulators it can be important to quantify the various sources of uncertainty. Errors in the structural specification of the simulator, for example due to missing processes or incorrect mathematical specification, can be a major source of uncertainty, but are often ignored. We introduce a methodology for inferring the discrepancy between the simulator and the system in discrete-time dynamical simulators. We assume a structural form for the discrepancy function, and show how to infer the maximum-likelihood parameter estimates using a particle filter embedded within a Monte Carlo expectation maximization (MCEM) algorithm. We illustrate the method on a conceptual rainfall-runoff simulator (logSPM) used to model the Abercrombie catchment in Australia. We assess the simulator and discrepancy model on the basis of their predictive performance using proper scoring rules. This article has supplementary material online. © 2011 International Biometric Society.

A new variational radial basis function approximation for inference in multivariate diffusions

In this paper we present a radial basis function based extension to a recently proposed variational algorithm for approximate inference for diffusion processes. Inference, for state and in particular (hyper-) parameters, in diffusion processes is a challenging and crucial task. We show that the new radial basis function approximation based algorithm converges to the original algorithm and has beneficial characteristics when estimating (hyper-)parameters. We validate our new approach on a nonlinear double well potential dynamical system.

Approximating differentiable relationships between delay embedded dynamical systems with radical basis functions

This thesis is about the study of relationships between experimental dynamical systems. The basic approach is to fit radial basis function maps between time delay embeddings of manifolds. We have shown that under certain conditions these maps are generically diffeomorphisms, and can be analysed to determine whether or not the manifolds in question are diffeomorphically related to each other. If not, a study of the distribution of errors may provide information about the lack of equivalence between the two. The method has applications wherever two or more sensors are used to measure a single system, or where a single sensor can respond on more than one time scale: their respective time series can be tested to determine whether or not they are coupled, and to what degree. One application which we have explored is the determination of a minimum embedding dimension for dynamical system reconstruction. In this special case the diffeomorphism in question is closely related to the predictor for the time series itself. Linear transformations of delay embedded manifolds can also be shown to have nonlinear inverses under the right conditions, and we have used radial basis functions to approximate these inverse maps in a variety of contexts. This method is particularly useful when the linear transformation corresponds to the delay embedding of a finite impulse response filtered time series. One application of fitting an inverse to this linear map is the detection of periodic orbits in chaotic attractors, using suitably tuned filters. This method has also been used to separate signals with known bandwidths from deterministic noise, by tuning a filter to stop the signal and then recovering the chaos with the nonlinear inverse. The method may have applications to the cancellation of noise generated by mechanical or electrical systems. In the course of this research a sophisticated piece of software has been developed. The program allows the construction of a hierarchy of delay embeddings from scalar and multi-valued time series. The embedded objects can be analysed graphically, and radial basis function maps can be fitted between them asynchronously, in parallel, on a multi-processor machine. In addition to a graphical user interface, the program can be driven by a batch mode command language, incorporating the concept of parallel and sequential instruction groups and enabling complex sequences of experiments to be performed in parallel in a resource-efficient manner.

Dynamical Systems in Description of Nonlinear Recursive Regression Transformers

The task of approximation-forecasting for a function, represented by empirical data was investigated. Certain class of the functions as forecasting tools: so called RFT-transformers, – was proposed. Least Square Method and superposition are the principal composing means for the function generating. Besides, the special classes of beam dynamics with delay were introduced and investigated to get classical results regarding gradients. These results were applied to optimize the RFT-transformers. The effectiveness of the forecast was demonstrated on the empirical data from the Forex market.

Dynamical interplay between ground and excited states in quantum dot laser

Full text: Semiconductor quantum dot lasers are attractive for multipletechnological applications in biophotonics. Simultaneous two-state lasing ofground state (GS) and excited state (ES) electrons and holes in QD lasers ispossible under a certain parameter range. It has already been investigated in steady-stateoperations and in dynamical regimes and is currently a subject of the intesiveresearch. It has been shown that the relaxation frequency in the two-state lasingregime is not a function of the total intensity [1], as could be traditionallyexpected.In this work we study damping relaxation oscillations in QD lasersimultaneously operating at two transitions, and find that under variouspumping conditions, the frequency of oscillations may decrease, increase orstay without change in time as shown in Fig1.The studied QD laser structure wasgrown on a GaAs substrate by molecular-beam epitaxy. The active region includedfive layers of self-assembled InAs QDs separated with a GaAs spacer from a5.3nm thick covering layer of InGaAs and processed into 4mm-wide mesa stripe devices. The 2.5mm long lasers withhigh-and antireflection coatings on the rear and front facets lasesimultaneously at the GS (around 1265nm) and ES (around 1190nm) in the wholerange of pumping. Pulsed electrical pumping obtained from a high power (up to2A current) pulse source was used to achieve high output power operation. We simultaneously detect the total output and merely ES output using aBragg filter transmitting the short-wavelength and reflecting the long-wavelengthradiation. Typical QD does not demonstrate relaxation oscillations frequencybecause of the strong damping [2]. It is confirmed for the low (I<0.68A) andhigh (I>1.2 A) range of the pump currents in our experiments. The situationis different for a short range of the medium currents (0.68A

Dynamical Resonances and SSF Singularities for a Magnetic Schrödinger Operator

We consider the Hamiltonian H of a 3D spinless non-relativistic quantum particle subject to parallel constant magnetic and non-constant electric field. The operator H has infinitely many eigenvalues of infinite multiplicity embedded in its continuous spectrum. We perturb H by appropriate scalar potentials V and investigate the transformation of these embedded eigenvalues into resonances. First, we assume that the electric potentials are dilation-analytic with respect to the variable along the magnetic field, and obtain an asymptotic expansion of the resonances as the coupling constant ϰ of the perturbation tends to zero. Further, under the assumption that the Fermi Golden Rule holds true, we deduce estimates for the time evolution of the resonance states with and without analyticity assumptions; in the second case we obtain these results as a corollary of suitable Mourre estimates and a recent article of Cattaneo, Graf and Hunziker [11]. Next, we describe sets of perturbations V for which the Fermi Golden Rule is valid at each embedded eigenvalue of H; these sets turn out to be dense in various suitable topologies. Finally, we assume that V decays fast enough at infinity and is of definite sign, introduce the Krein spectral shift function for the operator pair (H+V, H), and study its singularities at the energies which coincide with eigenvalues of infinite multiplicity of the unperturbed operator H.

Relationship Between Orofacial Function, Dentofacial Morphology, And Bite Force In Young Subjects.

The aim was to evaluate the relationship between orofacial function, dentofacial morphology, and bite force in young subjects. Three hundred and sixteen subjects were divided according to dentition stage (early, intermediate, and late mixed and permanent dentition). Orofacial function was screened using the Nordic Orofacial Test-Screening (NOT-S). Orthodontic treatment need, bite force, lateral and frontal craniofacial dimensions and presence of sleep bruxism were also assessed. The results were submitted to descriptive statistics, normality and correlation tests, analysis of variance, and multiple linear regression to test the relationship between NOT-S scores and the studied independent variables. The variance of NOT-S scores between groups was not significant. The evaluation of the variables that significantly contributed to NOT-S scores variation showed that age and presence of bruxism related to higher NOT-S total scores, while the increase in overbite measurement and presence of closed lip posture related to lower scores. Bite force did not show a significant relationship with scores of orofacial dysfunction. No significant correlations between craniofacial dimensions and NOT-S scores were observed. Age and sleep bruxism were related to higher NOT-S scores, while the increase in overbite measurement and closed lip posture contributed to lower scores of orofacial dysfunction.

Impaired Compensatory Beta-cell Function And Growth In Response To High-fat Diet In Ldl Receptor Knockout Mice.

In this study, we investigated the effect of low density lipoprotein receptor (LDLr) deficiency on gap junctional connexin 36 (Cx36) islet content and on the functional and growth response of pancreatic beta-cells in C57BL/6 mice fed a high-fat (HF) diet. After 60 days on regular or HF diet, the metabolic state and morphometric islet parameters of wild-type (WT) and LDLr-/- mice were assessed. HF diet-fed WT animals became obese and hypercholesterolaemic as well as hyperglycaemic, hyperinsulinaemic, glucose intolerant and insulin resistant, characterizing them as prediabetic. Also they showed a significant decrease in beta-cell secretory response to glucose. Overall, LDLr-/- mice displayed greater susceptibility to HF diet as judged by their marked cholesterolaemia, intolerance to glucose and pronounced decrease in glucose-stimulated insulin secretion. HF diet induced similarly in WT and LDLr-/- mice, a significant decrease in Cx36 beta-cell content as revealed by immunoblotting. Prediabetic WT mice displayed marked increase in beta-cell mass mainly due to beta-cell hypertrophy/replication. Nevertheless, HF diet-fed LDLr-/- mice showed no significant changes in beta-cell mass, but lower islet-duct association (neogenesis) and higher beta-cell apoptosis index were seen as compared to controls. The higher metabolic susceptibility to HF diet of LDLr-/- mice may be explained by a deficiency in insulin secretory response to glucose associated with lack of compensatory beta-cell expansion.