Spectral and kinetic characterization of 7,8-diaminopelargonic acid synthase from Mycobacterium tuberculosis

The indispensability of biotin for crucial processes like lipid biosynthesis coupled to the absence of the biotin biosynthesis pathway in humans make the enzymes of this pathway, attractive targets for development of novel drugs against numerous pathogens including M. tuberculosis. We report the spectral and kinetic characterization of the Mycobacterium tuberculosis 7,8-Diamino-pelargonic acid (DAPA) synthase, the second enzyme of the biotin biosynthesis pathway. In contrast to the E. coli enzyme, no quinonoid intermediate was detected during the steady state reaction between the enzyme and S-adenosyl-L-methionine (SAM). The second order rate constant for this half of the reaction was determined to be 1.75 +/- 0.11 M-1 s(-1). The K-m values for 7-keto-8-aminopelargonic acid (KAPA) and SAM are 2.83 mu M and 308.28 mu M, respectively whereas the V-max and k(cat) values for the enzyme are 0.02074 mu moles/min/ml and 0.003 s(-1), respectively. Our initial studies pave the way for further detailed mechanistic and kinetic characterization of the enzyme.

The Line Spectral Frequency Model of a Finite-Length Sequence

The line spectral frequency (LSF) of a causal finite length sequence is a frequency at which the spectrum of the sequence annihilates or the magnitude spectrum has a spectral null. A causal finite-length sequencewith (L + 1) samples having exactly L-LSFs, is referred as an Annihilating (AH) sequence. Using some spectral properties of finite-length sequences, and some model parameters, we develop spectral decomposition structures, which are used to translate any finite-length sequence to an equivalent set of AH-sequences defined by LSFs and some complex constants. This alternate representation format of any finite-length sequence is referred as its LSF-Model. For a finite-length sequence, one can obtain multiple LSF-Models by varying the model parameters. The LSF-Model, in time domain can be used to synthesize any arbitrary causal finite-length sequence in terms of its characteristic AH-sequences. In the frequency domain, the LSF-Model can be used to obtain the spectral samples of the sequence as a linear combination of spectra of its characteristic AH-sequences. We also summarize the utility of the LSF-Model in practical discrete signal processing systems.

Structure of Ce1-xSnxO2 and its relation to oxygen storage property from first-principles analysis

CeO2-SnO2 solid solution has been reported to possess high oxygen storage/release property which possibly originates from local structural distortion. We have performed first-principles based density functional calculations of Ce1-xSnxO2 structure (x=0, 0.25, 0.5, 1) to understand its structural stability in fluorite in comparison to rutile structure of the other end-member SnO2, and studied the local structural distortion induced by the dopant Sn ion. Analysis of relative energies of fluorite and rutile phases of CeO2, SnO2, and Ce1-xSnxO2 indicates that fluorite structure is the most stable for Ce1-xSnxO2 solid solution. An analysis of local structural distortions reflected in phonon dispersion show that SnO2 in fluorite structure is highly unstable while CeO2 in rutile structure is only weakly unstable. Thus, Sn in Ce1-xSnxO2-fluorite structure is associated with high local structural distortion whereas Ce in Ce1-xSnxO2-rutile structure, if formed, will show only marginal local distortion. Determination of M-O (M=Ce or Sn) bond lengths and analysis of Born effective charges for the optimized structure of Ce1-xSnxO2 show that local coordination of these cations changes from ideal eightfold coordination expected of fluorite lattice to 4+4 coordination, leading to generation of long and short Ce-O and Sn-O bonds in the doped structure. Bond valence analyses for all ions show the presence of oxygen with bond valence similar to 1.84. These weakly bonded oxygen ions are relevant for enhanced oxygen storage/release properties observed in Ce1-xSnxO2 solid solution. (C) 2010 American Institute of Physics.

Modelling and Forecasting Property Rents and Returns (summary section only)

Recently, focus of real estate investment has expanded from the building-specific level to the aggregate portfolio level. The portfolio perspective requires investment analysis for real estate which is comparable with that of other asset classes, such as stocks and bonds. Thus, despite its distinctive features, such as heterogeneity, high unit value, illiquidity and the use of valuations to measure performance, real estate should not be considered in isolation. This means that techniques which are widely used for other assets classes can also be applied to real estate. An important part of investment strategies which support decisions on multi-asset portfolios is identifying the fundamentals of movements in property rents and returns, and predicting them on the basis of these fundamentals. The main objective of this thesis is to find the key drivers and the best methods for modelling and forecasting property rents and returns in markets which have experienced structural changes. The Finnish property market, which is a small European market with structural changes and limited property data, is used as a case study. The findings in the thesis show that is it possible to use modern econometric tools for modelling and forecasting property markets. The thesis consists of an introduction part and four essays. Essays 1 and 3 model Helsinki office rents and returns, and assess the suitability of alternative techniques for forecasting these series. Simple time series techniques are able to account for structural changes in the way markets operate, and thus provide the best forecasting tool. Theory-based econometric models, in particular error correction models, which are constrained by long-run information, are better for explaining past movements in rents and returns than for predicting their future movements. Essay 2 proceeds by examining the key drivers of rent movements for several property types in a number of Finnish property markets. The essay shows that commercial rents in local markets can be modelled using national macroeconomic variables and a panel approach. Finally, Essay 4 investigates whether forecasting models can be improved by accounting for asymmetric responses of office returns to the business cycle. The essay finds that the forecast performance of time series models can be improved by introducing asymmetries, and the improvement is sufficient to justify the extra computational time and effort associated with the application of these techniques.

Elastic property estimation using Ultrasound Assisted Optical Elastography through Remote Palpation - A simulation study - art. no. 61640Q

We propose an effective elastography technique in which an acoustic radiation force is used for remote palpation to generate localized tissue displacements, which are directly correlated to localized variations of tissue stiffness and are measured using a light probe in the same direction of ultrasound propagation. The experimental geometry has provision to input light beam along the ultrasound propagation direction, and hence it can be prealigned to ensure proper interception of the focal region by the light beam. Tissue-mimicking phantoms with homogeneous and isotropic mechanical properties of normal and malignant breast tissue are considered for the study. Each phantom is insonified by a focusing ultrasound transducer (1 MHz). The focal volume of the transducer and the ultrasound radiation force in the region are estimated through solving acoustic wave propagation through medium assuming average acoustic properties. The forward elastography problem is solved for the region of insonification assuming the Lame's parameters and Poisson's ratio, under Dirichlet boundary conditions which gives a distribution of displacement vectors. The direction of displacement, though presented spatial variation, is predominantly towards the ultrasound propagation direction. Using Monte Carlo (MC) simulation we have traced the photons through the phantom and collected the photons arriving at the detector on the boundary of the object in the direction of ultrasound. The intensity correlations are then computed from detected photons. The intensity correlation function computed through MC simulation showed a modulation whose strength is found to be proportional to the amplitude of displacement and inversely related to the storage (elastic) modulus. It is observed that when the storage modulus in the focal region is increased the computed displacement magnitude, as indicated by the depth of modulation in the intensity autocorrelation, decreased and the trend is approximately exponential.

Anti-amyloidogenic property of leaf aqueous extract of Caesalpinia crista

Amyloid beta (A beta) is the major etiological factor implicated in Alzheimer's disease (AD). A beta(42) self-assembles to form oligomers and fibrils via multiple aggregation process. The recent studies aimed to decrease A beta levels or prevention of A beta aggregation which are the major targets for therapeutic intervention. Natural products as alternatives for AD drug discovery are a current trend. We evidenced that Caesalpinia crista leaf aqueous extract has anti-amyloidogenic potential. The studies on pharmacological properties of C. crista are very limited. Our study focused on ability of C. crista leaf aqueous extract on the prevention of (i) the formation of oligomers and aggregates from monomers (Phase I: A beta(42) + extract co-incubation); (ii) the formation of fibrils from oligomers (Phase II: extract added after oligomers formation); and (iii) dis-aggregation of pre-formedfibrils (Phase III: aqueous extract added to matured fibrils and incubated for 9 days). The aggregation kinetics was monitored using thioflavin-T assay and transmission electron microscopy (TEM). The results showed that C. crista aqueous extract could able to inhibit the A beta(42) aggregation from monomers and oligomers and also able todis-aggregate the pre-formed fibrils. The study provides an insight on finding new natural products for AD therapeutics. (C) 2010 Elsevier Ireland Ltd. All rights reserved.

Crystal structure of 2-thiophene-2-yl-3(thiophene-2-carboxylideneamino)-1,2-dihydroquinazolin-4(3H)-one and the synthesis, spectral and thermal studies of its transition metal(II) complexes

The synthesis of manganese(II), cobalt(II), nickel(II), copper(II), zinc(II) and cadmium(II) complexes of a new ligand 2-thiophene-2-yl-3(thiophene-2-carboxylidene-amino)-1,2-dihydroquinazolin-4(3H)-one (TTCADQ) is described. The ligand and metal complexes were characterized by elemental analysis, conductivity measurements, spectral (u.v.-vis., i.r., 1D n.m.r., 2D hetcor and e.p.r.) and thermal studies. The formation of 1,2-dihydroquinazolin-4(3H)-one rather than hydrazone, in the reaction of aromatic aldehyde and o-aminobenzoylhydrazide is proved by single crystal X-ray diffraction and 2D hetcor n.m.r. studies. On the basis of elemental analysis, u.v.-vis.spectroscopy and magnetic moment studies, six coordinate geometry for all the complexes was proposed. The i.r. spectral studies reveal the bidentate behaviour of the ligand.

Wave propagation analysis in carbon nanotube embedded composite using wavelet based spectral finite elements

In this paper, elastic wave propagation is studied in a nanocomposite reinforced with multiwall carbon nanotubes (CNTs). Analysis is performed on a representative volume element of square cross section. The frequency content of the exciting signal is at the terahertz level. Here, the composite is modeled as a higher order shear deformable beam using layerwise theory, to account for partial shear stress transfer between the CNTs and the matrix. The walls of the multiwall CNTs are considered to be connected throughout their length by distributed springs, whose stiffness is governed by the van der Waals force acting between the walls of nanotubes. The analyses in both the frequency and time domains are done using the wavelet-based spectral finite element method (WSFEM). The method uses the Daubechies wavelet basis approximation in time to reduce the governing PDE to a set of ODEs. These transformed ODEs are solved using a finite element (FE) technique by deriving an exact interpolating function in the transformed domain to obtain the exact dynamic stiffness matrix. Numerical analyses are performed to study the spectrum and dispersion relations for different matrix materials and also for different beam models. The effects of partial shear stress transfer between CNTs and matrix on the frequency response function (FRF) and the time response due to broadband impulse loading are investigated for different matrix materials. The simultaneous existence of four coupled propagating modes in a double-walled CNT-composite is also captured using modulated sinusoidal excitation.

Structural and spectral perspectives of a novel thiosemicarbazone synthesized from di-2-pyridyl ketone and 4-phenyl-3-thiosemicarbazide

A new thiosemicarbazone, HL is synthesized from di-2-pyridyl ketone and 4-phenyl-3-thiosemicarbazide and structurally and spectrochemically characterized. H-1 NMR, C-13 NMR, COSY, HMQC and IR spectra of the compound are studied and the proton magnetic resonance spectrum reveals some unprecedented observations. The thione form is predominant in the solid state, as supported by the crystal structure and IR data, while a thiol-thione equilibrium is proposed in the solution state by NMR studies. The compound crystallizes into a monoclinic lattice with space group C2/c and the ZE conformation is exhibited by the thiosemicarbazone. Intra- and intermolecular hydrogen-bonding interactions give rise to a two-dimensional packing in the crystal lattice

Composite signal decomposition by digital inverse filtering

Inverse filters are conventionally used for resolving overlapping signals of identical waveshape. However, the inverse filtering approach is shown to be useful for resolving overlapping signals, identical or otherwise, of unknown waveshapes. Digital inverse filter design based on autocorrelation formulation of linear prediction is known to perform optimum spectral flattening of the input signal for which the filter is designed. This property of the inverse filter is used to accomplish composite signal decomposition. The theory has been presented assuming constituent signals to be responses of all-pole filters. However, the approach may be used for a general situation.