Structural basis for Dicer-like function of an engineered RNase III variant and insights into the re
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A semi-microscopic model for nucleon pairing in nuclei is presented starting from the ab initio BCS gap equation with the Argonne v{sub 18} force and the self-consistent energy density functional method basis characterized by the bare nucleon mass. The BCS theory is formulated in terms of the model space S{sub 0} with the effective pairing interaction calculated from the first principles in the subsidiary space S{sup '}. This effective interaction is supplemented with a small phenomenological addendum containing one phenomenological parameter, universal for all medium and heavy atomic nuclei. We consider the latter as a phenomenological way to take into account approximately both the many-body corrections to the BCS theory and the effective mass effects. For protons, the Coulomb interaction is introduced directly. Calculations made for several isotopic and isotonic chains of semi-magic nuclei are compared with empirical gap values derived from odd-even mass differences. The average disagreement is of the order of 0.1--0.2 MeV. The role of the self-consistent basis is analyzed.
The great cormorant hemoglobin has been isolated, purified and crystallized and the three dimensional structure is solved using molecular replacement technique. Haemoglobin is the iron-containing oxygen-transport metalloprotein that is present in the red blood cells of all vertebrates. In recent decades, there has been substantial interest in attempting to understand the structural basis and functional diversity of avian haemoglobins. Towards this end, purification, crystallization, preliminary X-ray diffraction and molecular-replacement studies have been carried out on cormorant (Phalacrocorax carbo) haemoglobin. Crystals were grown by the hanging-drop vapour-diffusion method using PEG 3350, NaCl and glycerol as precipitants. The crystals belonged to the trigonal system P3{sub 1}21, with unit-cell parameters a = b = 55.64, c = 153.38 Å, β = 120.00°; a complete data set was collected to a resolution of 3.5 Å. Matthews coefficient analysis indicated that the crystals contained a half-tetramer in the asymmetric unit.
A novel fast scalable parallel algorithm is proposed for the solution of large 3-D scattering problems based on: 1) the double (geometrical and current-approximation) higher order (DHO) method of moments (MoM) in the surface integral equation (SIE) formulation and 2) a direct solver for dense linear systems utilizing hierarchically semiseparable (HSS) structures. Namely, an HSS matrix representation is used for compression, factorization, and solution of the system matrix. In addition, a rank-revealing QR decomposition for memory compression is used, with a stopping criterion in terms of the relative rank tolerance value. One method for geometrical preprocessing of the scatterers based on the cobblestone distance sorting technique is employed in order to enhance the HSS algorithm accuracy and parallelization. Numerical examples show how the accuracy of the DHO HSS-MoM-SIE method is easily controllable by using the relative tolerance for the matrix compression. Furthermore, the examples demonstrate low memory consumption, as well as much faster simulation time, when compared to the direct LU decomposition. The method enables dramatically faster monostatic scattering computations than iterative solvers and reduced number of unknowns when compared to low-order discretizations. Finally, great scalability of the algorithm is demonstrated on more than one thousand processes.
Purpose: To further develop and perform patient testing of an x-ray scatter correction algorithm for dedicated breast computed tomography (BCT). Methods: A previously proposed algorithm for x-ray scatter signal reduction in BCT imaging was modified and tested with a phantom and on patients. A wireless electronic positioner system was designed and added to the BCT system that positions a tungsten plate in and out of the x-ray beam. The interpolation used by the algorithm was replaced with a radial basis function-based algorithm, with automated exclusion of non-valid sampled points due to patient motion or other factors. A 3D adaptive noise reduction filter was also introduced to reduce the impact of scatter quantum noise post-reconstruction. The impact on image quality of the improved algorithm was evaluated using a breast phantom and seven patient breasts, using quantitative metrics such signal difference (SD) and signal difference-to-noise ratios (SDNR) and qualitatively using image profiles. Results: The improvements in the algorithm resulted in a more robust interpolation step, with no introduction of image artifacts, especially at the imaged object boundaries, which was an issue in the previous implementation. Qualitative evaluation of the reconstructed slices and corresponding profiles show excellent homogeneity of both the background and the higher density features throughout the whole imaged object, as well as increased accuracy in the Hounsfield Units (HU) values of the tissues. Profiles also demonstrate substantial increase in both SD and SDNR between glandular and adipose regions compared to both the uncorrected and system-corrected images. Conclusion: The improved scatter correction algorithm can be reliably used during patient BCT acquisitions with no introduction of artifacts, resulting in substantial improvement in image quality. Its impact on actual clinical performance needs to be evaluated in the future. Research Agreement, Koning Corp., Hologic Inc., Barco Corp Consultant Agreement, Fujifilm Medical Systems.
The energy spectra of excited bound states are calculated for the muonic molecules ptμ, pdμ, and dtμ on the basis of the stochastic variational method. The basis wave functions are taken as the Gaussian in shape. The matrix elements of the Hamiltonian are calculated analytically. To perform numerical calculations, computer code is written in MATLAB. Numerical values are obtained for energies of excited P states in the muonic molecules ptμ, pdμ, and dtμ.
The deposition of polyhedral aluminum nanocrystals onto the surface of multiwalled carbon nanotubes (MWCNTs) via metalorganic chemical vapor deposition with the use of triisobutylaluminum as the precursor has been performed for the first time. The new hybrid nanomaterial (Al/MWCNTs) has been characterized by X-ray phase analysis, scanning electron microscopy, and high-resolution transmission electron microscopy. The obtained Al/MWCNTs hybrid materials were tested as the filler for the creation of threedimensional composites on the basis of an AMg2 alloy via powder metallurgy. It has been shown that the use of Al/MWCNTs as the filler increases the hardness of the composites by 18% in comparison with the initial MWCNTs.
In this technical report we investigate efficient methods for numerical simulation of active suspensions. The prototypical system is a suspension of swimming bacteria in a Newtonian fluid. Rheological and other macroscopic properties of such suspensions can differ dramatically from the same properties of the suspending fluid alone or of suspensions of similar but inactive particles. Elongated bacteria, such as E. coli or B. subtilis, swim along their principal axis, propelling themselves with the help of flagella, attached at the anterior of the organism and pushing it forward in the manner of a propeller. They interact hydrodynamically with the surrounding fluid and, because of their asymmetrical shape, have the propensity to align with the local flow. This, along with the dipolar nature of bacteria (the two forces a bacterium exerts on a fluid - one due to self-propulsion and the other opposing drag - have equal magnitude and point in opposite directions), causes nearby bacteria to tend to align, resulting in a intermittent local ordering on the mesoscopic scale, which is between the microscopic scale of an individual bacterium and the macroscopic scale of the suspension (e.g., its container). The local ordering is sometimes called a collective mode or collective swimming. Thanks to self-propulsion, collective modes inject momentum into the fluid in a coherent way. This enhances the local strain rate without changing the macroscopic stress applied at the boundary of the container. The macroscopic effective viscosity of the suspension is defined roughly as the ratio of the applied stress to the bulk strain rate. If local alignment and therefore local strain-rate enhancement, are significant, the effective viscosity can be appreciably lower than that of the corresponding passive suspension or even of the surrounding fluid alone. Indeed, a sevenfold decrease in the effective viscosity was observed in experiments with B. subtilis. More generally, local collective swimming resulting from bacterial alignment can significantly alter other macroscopic properties of the suspension, such as the oxygen diffusivity and mixing rates. In order to understand the unique macroscopic properties of active suspensions the connection between microscopic swimming and alignment dynamics and the mesoscopic pattern formation must be clarified. This is difficult to do analytically in the fully general setting of moderately dense suspensions, because of the large number of bacteria involved (approx. 10 10 cm -3 in experiments) and the complex, time-dependent geometry of the system. Many reduced analytical models of bacterial have been proposed, but all of them require validation. While comparison with experiment is the ultimate test of a model's fidelity, it is difficult to conduct experiments matched to these models assumptions. Numerical simulation of the microscopic dynamics is an acceptable substitute, but it runs into the problem of having to discretize the fluid domain with a fine-grained boundary (the bacteria) and update the discretization as the domain evolves (bacteria move). This leads to a prohibitively high number of degrees of freedom and prohibitively high setup costs per timestep of simulation. In this technical report we propose numerical methods designed to alleviate these two difficulties. We indicate how to (1) construct an optimal discretization in terms of the number of degrees of freedom per digit of accuracy and (2) optimally update the discretization as the simulation evolves. The technical tool here is the derivation of rigorous error bounds on the error in the numerical solution when using our proposed discretization at the initial time as well as after a given elapsed simulation time. These error bounds should guide the construction of practical discretization schemes and update strategies. Our initial construction is carried out by using a theoretically convenient, but practically prohibitive spectral basis, which is a Galerkin basis of functions with global support. At the end of this report we propose localization techniques while maintaining acceptable error bounds. No numerical experiments were conducted as part of this study, but we envision that we may undertake such studies and further development of the method, jointly or individually.
The primary objective of this project is to create an accurate web-based real-time wind-load calculator. This is of paramount importance for (1) the rapid and accurate assessments of the uplift and downforce loads on a PV mounting system, (2) identifying viable solutions from available mounting systems, and therefore helping reduce the cost of mounting hardware and installation. Wind loading calculations for structures are currently performed according to the American Society of Civil Engineers/ Structural Engineering Institute Standard ASCE/SEI 7; the values in this standard were calculated from simplified models that do not necessarily take into account relevant characteristics such as those from full 3D effects, end effects, turbulence generation and dissipation, as well as minor effects derived from shear forces on installation brackets and other accessories. This standard does not include provisions that address the special requirements of rooftop PV systems, and attempts to apply this standard may lead to significant design errors as wind loads are incorrectly estimated. Therefore, an accurate calculator would be of paramount importance for the preliminary assessments of the uplift and downforce loads on a PV mounting system, identifying viable solutions from available mounting systems, and therefore helping reduce the cost of the mounting system and installation. The challenge is that although a full-fledged three-dimensional computational fluid dynamics (CFD) analysis would properly and accurately capture the complete physical effects of air flow over PV systems, it would be impractical for this tool, which is intended to be a real-time web-based calculator. CFD routinely requires enormous computation times to arrive at solutions that can be deemed accurate and grid-independent even in powerful and massively parallel computer platforms.
The Predictive Phenomics Science & Technology Initiative (PPI) at Pacific Northwest National Laboratory are tackling the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems. Research projects within this initiative are divided into three Thrust Areas (TAs): TA1) Enhancing Multi-Scale Phenomics Measurements, TA2) Identifying Molecular Patterns of Biological Function, and TA3) Computational Methods - Phenotypic Signatures. In efforts to enable discovery, reproducibility, and reuse of PPI-funded digital research data generated or used through the course of the proposed research-funded lifecycles, all corresponding digital data assets conducted under the Laboratory Directed Research and Development Program at PNNL are linked to this PPI dataset catalog collection.
The Predictive Phenomics Science & Technology Initiative (PPI) at Pacific Northwest National Laboratory are tackling the grand challenge of understanding and predicting phenotype by identifying the molecular basis of function and enable function-driven design and control of biological systems. Research projects within this initiative are divided into three Thrust Areas (TAs): TA1) Enhancing Multi-Scale Phenomics Measurements, TA2) Identifying Molecular Patterns of Biological Function, and TA3) Computational Methods - Phenotypic Signatures. In efforts to enable discovery, reproducibility, and reuse of PPI-funded digital research data generated or used through the course of the proposed research-funded lifecycles, all corresponding digital data assets conducted under the Laboratory Directed Research and Development Program at PNNL are linked to this PPI dataset catalog collection.
Salmonids are ideal models as many species follow a distinct developmental program from demersal eggs and a large yolk sac to hatching at an advanced developmental stage. Further, these economically important teleosts inhabit both marine- and freshwaters and experience diverse light environments during their life histories. At a genome level, salmonids have undergone a salmonid-specific fourth whole genome duplication event (Ss4R) compared to other teleosts that are already more genetically diverse compared to many non-teleost vertebrates. Thus, salmonids display phenotypically plastic visual systems that appear to be closely related to their anadromous migration patterns. This is most likely due to a complex interplay between their larger, more gene-rich genomes and broad spectrally enriched habitats; however, the molecular basis and functional consequences for such diversity is not fully understood. This study used advances in genome sequencing to identify the repertoire and genome organization of visual opsin genes (those primarily expressed in retinal photoreceptors) from six different salmonids [Atlantic salmon ( Salmo salar ), brown trout ( Salmo trutta ), Chinook salmon ( Oncorhynchus tshawytcha ), coho salmon ( Oncorhynchus kisutch ), rainbow trout ( Oncorhynchus mykiss ), and sockeye salmon ( Oncorhynchus nerka )] compared to the northern pike ( Esox lucius ), a closely related non-salmonid species. Results identified multiple orthologues for all five visual opsin classes, except for presence of a single short-wavelength-sensitive-2 opsin gene. Several visual opsin genes were not retained after the Ss4R duplication event, which is consistent with the concept of salmonid rediploidization. Developmentally, transcriptomic analyzes of Atlantic salmon revealed differential expression within each opsin class, with two of the long-wavelength-sensitive opsins not being expressed before first feeding. Also, early opsin expression in the retina was located centrally, expanding dorsally and ventrally as eye development progressed, with rod opsin being the dominant visual opsin post-hatching. Modeling by spectral tuning analysis and atomistic molecular simulation, predicted the greatest variation in the spectral peak of absorbance to be within the Rh2 class, with a ∼40 nm difference in λ max values between the four medium-wavelength-sensitive photopigments. Overall, it appears that opsin duplication and expression, and their respective spectral tuning profiles, evolved to maximize specialist color vision throughout an anadromous lifecycle, with some visual opsin genes being lost to tailor marine-based vision.
Gaussian processes and other kernel-based methods are used extensively to construct approximations of multivariate data sets. The accuracy of these approximations is dependent on the data used. This paper presents a computationally efficient algorithm to greedily select training samples that minimize the weighted L p error of kernel-based approximations for a given number of data. The method successively generates nested samples, with the goal of minimizing the error in high probability regions of densities specified by users. The algorithm presented is extremely simple and can be implemented using existing pivoted Cholesky factorization methods. Training samples are generated in batches which allows training data to be evaluated (labeled) in parallel. For smooth kernels, the algorithm performs comparably with the greedy integrated variance design but has significantly lower complexity. Numerical experiments demonstrate the efficacy of the approach for bounded, unbounded, multi-modal and non-tensor product densities. We also show how to use the proposed algorithm to efficiently generate surrogates for inferring unknown model parameters from data using Bayesian inference.
The dynamics of vibrations in flexible structures can be conventiently modeled in terms of frequency response models. For structural control such models capture the distributed parameter dynamics of the elastic structural response as an irrational transfer function. For most flexible structures arising in aerospace applications the irrational transfer functions which arise are of a special class of pseudo-meromorphic functions which have only a finite number of right half place poles. Computational algorithms are demonstrated for design of multiloop control laws for such models based on optimal Wiener-Hopf control of the frequency responses. The algorithms employ a sampled-data representation of irrational transfer functions which is particularly attractive for numerical computation. One key algorithm for the solution of the optimal control problem is the spectral factorization of an irrational transfer function. The basis for the spectral factorization algorithm is highlighted together with associated computational issues arising in optimal regulator design. Options for implementation of wide band vibration control for flexible structures based on the sampled-data frequency response models is also highlighted. A simple flexible structure control example is considered to demonstrate the combined frequency response modeling and control algorithms.
Ab initio self-consistent-field plus configuration-interaction calculations are reported for the X(sup 1)Sigma(sup +), A(sup 1)Sigma(sup +), and B(sup 1)Pi states of LiH using a 22(sugma)12(pi)7(delta) function Slater basis set. The resulting dissociation energies, with the experimental values in parentheses, are D(sub e)(X(sup 1)Sigma(sup +)) = 19 972 (20288)/ cm, and D(sub e)(A(sup 1)Sigma(sup +)) = 9042 (8682)/ cm, and D(sup e)(B(sup 1)Pi) = 284 (288) /cm. This is the first ab initio treatment to quantitatively account for the binding in the B(sup 1)Pi state. Calculated dipole moments and electronic transition moments for the X(sup 1)Sigma(sup+)-A(sup 1)Sigma(sup +), X(sup 1)Sigma(sup +)-B((sup 1)Pi, and A(sup 1)Sigma(sup +)- B(sup 1)PI band systems are in excellent agreement with existing theoretical and experimental data. Radiative transition probabilities and lifetimes, including both the bound-bound and bound-free contributions, are computed for all vibrational levels of the A(sup 1)Sigma(sup+) and B(sup 1)Pi states. Comparison with previous results using experimentally based potentials provides insight into the sensitivity of the radiative lifetimes to the detailed nature of the uppermost region of the potentials. Our calculated lifetimes for the lower vibrational levels of the A(sup 1)Sigma(sup +) state are within the experimental uncertainty. Our calculated lifetimes for the three vibrational levels of the B(sup 1)Pi state are in excellent agreement with those of Zemke and Stwalley (values in parentheses), increasing with (upsilon)' from 11.3 (11.3) nsec at (upsilon)' = 0, to 17.0 (17.0) nsec at (upsilon)' = 1, and then to 23.5 (24.0) nsec at (upsilon)' = 2.
We report on our effort to develop algorithms to detect, size, and classify geological features in planetary and asteroidal data sets.
Caffeoyl-coenzyme A 3-O-methyltransferase (CCoAOMT) is an S-adenosyl methionine (SAM)-dependent O-methyltransferase responsible for methylation of the meta-hydroxyl group of caffeoyl-coenzyme A (CoA) on the pathway to monolignols, with their ring methoxylation status characteristic of guaiacyl or syringyl units in lignin. In order to better understand the unique class of type 2 O-methyltransferases from monocots, we have characterized CCoAOMT from sorghum (Sorghum bicolor; SbCCoAOMT), including the SAM binary complex crystal structure and steady-state enzyme kinetics. Key amino acid residues were validated with site-directed mutagenesis. Isothermal titration calorimetry data indicated a sequential binding mechanism for SbCCoAOMT, wherein SAM binds prior to caffeoyl-CoA, and the enzyme showed allosteric behavior with respect to it. 5-Hydroxyferuloyl-CoA was not a substrate for SbCCoAOMT. We propose a catalytic mechanism in which lysine-180 acts as a catalytic base and deprotonates the reactive hydroxyl group of caffeoyl-CoA. This deprotonation is facilitated by the coordination of the reactive hydroxyl group by Ca 2+ in the active site, lowering the pK a of the 3'-OH group. Collectively, these data give a new perspective on the catalytic mechanism of CCoAOMTs and provide a basis for the functional diversity exhibited by type 2 plant OMTs that contain a unique insertion loop (residues 208–231) conferring affinity for phenylpropanoid-CoA thioesters. The structural model of SbCCoAOMT can serve as the basis for protein engineering approaches to enhance the nutritional, agronomic, and industrially relevant properties of sorghum.
The requirements for very accurate ab initio quantum chemical prediction of dissociation energies are examined using a detailed investigation of the nitrogen molecule. Although agreement with experiment to within 1 kcal/mol is not achieved even with the most elaborate multireference CI (configuration interaction) wave functions and largest basis sets currently feasible, it is possible to obtain agreement to within about 2 kcal/mol, or 1 percent of the dissociation energy. At this level it is necessary to account for core-valence correlation effects and to include up to h-type functions in the basis. The effect of i-type functions, the use of different reference configuration spaces, and basis set superposition error were also investigated. After discussing these results, the remaining sources of error in our best calculations are examined.