Antiatherosclerotic and antioxidative effects of captopril in apolipoprotein E-deficient mice

The effect of the angiotensin-converting enzyme (ACE) inhibitor, captopril, on the development of atherosclerosis was determined in the apolipoprotein (apo) E-deficient mice. These mice develop severe hypercholesterolemia and extensive atherosclerotic lesions on chow diet, similar to those found in humans. Furthermore, in these mice, accelerated atherosclerosis is associated with increased plasma lipid peroxidation, a phenomenon that may play a crucial role in the buildup of the atherosclerotic lesions. Mice received either placebo or 50 mg/kg/day of captopril. After 12 weeks of treatment, captopril reduced the aortic-lesion area by 70% compared with that of the placebo-treated group. Captopril also increased the resistance of low-density lipoprotein (LDL) to CuSO4-induced oxidative stress, as shown by a significant reduction in the LDL content of malondialdehyde (MDA) by 30%, as well as by the prolongation of the lag time required for LDL oxidation from 55 min in the placebo-treated mice to 70 min in the captopril-treated mice, and reduction of the maximum LDL oxidation at 150 min by 35%. In vitro studies demonstrated that preincubation of LDL with captopril, inhibited the onset of CuSO4-induced LDL peroxidation up to 120 min, and reduced the LDL content of MDA by 90%. We conclude that captopril attenuates atherosclerosis in the apo E-deficient mice, and this phenomenon may be related to its inhibitory effect on the plasma LDL oxidation.     

Continuous measurement of radiation damage of standard CMOS imagers

In this work we have irradiated a standard CMOS VGA imager with a 24 MeV proton beam at INFN Laboratori Nazionali del Sud, up to a nominal fluence of 10¹⁴ protons/cm². The device under test was fabricated with a 130 nm technology without radiation hardening. During the damaging the detector was fully operational to monitor the progressive damaging of the sensor and the associated on-pixel electronics in terms of detection efficiency, charge collection and noise. We found that the detector is still working at 10¹³ protons/cm², with a moderate increase of the noise (20%).     

Subsidence in the Pontina Plain,Italy

Analysis of borehole data together with two centuries of documentation has allowed the assessment of subsidence evolution in the area of the Pontina Plain, where peats extend to up to 60 m in thickness. This paper discusses the two phenomena (self-weight consolidation and reclamation activities) which have led to ground subsidence of almost 6 m over a period of 200 years.      

The substrate binding site of human liver cytochrome P450 2C9: an NMR study

Purified recombinant human liver cytochrome P450 2C9 was produced, from expression of the corresponding cDNA in yeast, in quantities large enough for UV-visible and 1H NMR experiments. Its interaction with several substrates (tienilic acid and two derivatives, lauric acid and diclofenac) and with a specific inhibitor, sulfaphenazole, was studied by UV-visible and 1H NMR spectroscopy. At 27 degrees C, all those substrates led to an almost complete conversion of CYP 2C9 to high-spin (S = 5/2) CYP 2C9-substrate complexes characterized by a Soret peak at 390 nm; their KD values varied between 1 and 42 microM. On the contrary, sulfaphenazole led to a low-spin (S = 1/2) CYP 2C9 complex upon binding of its NH2 group to CYP 2C9 iron. Interactions of the five substrates with the enzyme were studied by paramagnetic relaxation effects of CYP 2C9-iron(III) on the 1H NMR spectrum of each substrate. Distances between the heme iron atom and substrate protons were calculated from the NMR data, and the orientation of the substrate relative to iron was determined from those distances. Finally, a model for substrate positioning in the CYP 2C9 active site was constructed by molecular modeling studies under the constraint of the iron-proton distances. It points out two structural characteristics for a compound to be selectively recognized by CYP 2C9: (i) the presence of an anionic site able to establish an ionic bond with a putative cationic residue of the protein and (ii) the presence of an hydrophobic zone between the substrate hydroxylation site and the anionic site. Sulfaphenazole was easily included in that model; its very high affinity for CYP 2C9 is due to a third structural feature, the presence of its NH2 function which binds to CYP 2C9 iron.     

Independent factor analysis

We introduce the independent factor analysis (IFA) method for recovering independent hidden sources from their observed mixtures. IFA generalizes and unifies ordinary factor analysis (FA), principal component analysis (PCA), and independent component analysis (ICA), and can handle not only square noiseless mixing but also the general case where the number of mixtures differs from the number of sources and the data are noisy. IFA is a two-step procedure. In the first step, the source densities, mixing matrix, and noise covariance are estimated from the observed data by maximum likelihood. For this purpose we present an expectation-maximization (EM) algorithm, which performs unsupervised learning of an associated probabilistic model of the mixing situation. Each source in our model is described by a mixture of gaussians; thus, all the probabilistic calculations can be performed analytically. In the second step, the sources are reconstructed from the observed data by an optimal nonlinear estimator. A variational approximation of this algorithm is derived for cases with a large number of sources, where the exact algorithm becomes intractable. Our IFA algorithm reduces to the one for ordinary FA when the sources become gaussian, and to an EM algorithm for PCA in the zero-noise limit. We derive an additional EM algorithm specifically for noiseless IFA. This algorithm is shown to be superior to ICA since it can learn arbitrary source densities from the data. Beyond blind separation, IFA can be used for modeling multidimensional data by a highly constrained mixture of gaussians and as a tool for nonlinear signal encoding.     

Speech Enhancement, Gain, and Noise Spectrum Adaptation Using Approximate Bayesian Estimation

This paper presents a new approximate Bayesian estimator for enhancing a noisy speech signal. The speech model is assumed to be a Gaussian mixture model (GMM) in the log-spectral domain. This is in contrast to most current models in frequency domain. Exact signal estimation is a computationally intractable problem. We derive three approximations to enhance the efficiency of signal estimation. The Gaussian approximation transforms the log-spectral domain GMM into the frequency domain using minimal Kullback-Leiber (KL)-divergency criterion. The frequency domain Laplace method computes the maximum a posteriori (MAP) estimator for the spectral amplitude. Correspondingly, the log-spectral domain Laplace method computes the MAP estimator for the log-spectral amplitude. Further, the gain and noise spectrum adaptation are implemented using the expectation-maximization (EM) algorithm within the GMM under Gaussian approximation. The proposed algorithms are evaluated by applying them to enhance the speeches corrupted by the speech-shaped noise (SSN). The experimental results demonstrate that the proposed algorithms offer improved signal-to-noise ratio, lower word recognition error rate, and less spectral distortion.     

An expectation-maximization method for spatio-temporal blind source separation using an AR-MOG source model.

In this paper, we develop a maximum-likelihood (ML) spatio-temporal blind source separation (BSS) algorithm, where the temporal dependencies are explained by assuming that each source is an autoregressive (AR) process and the distribution of the associated independent identically distributed (i.i.d.) innovations process is described using a mixture of Gaussians. Unlike most ML methods, the proposed algorithm takes into account both spatial and temporal information, optimization is performed using the expectation-maximization (EM) method, the source model is adapted to maximize the likelihood, and the update equations have a simple, analytical form. The proposed method, which we refer to as autoregressive mixture of Gaussians (AR-MOG), outperforms nine other methods for artificial mixtures of real audio. We also show results for using AR-MOG to extract the fetal cardiac signal from real magnetocardiographic (MCG) data.     

Symmetric and Asymmetric Conjugated 3,3′‐Bipyridine Derivatives as a New Class of Third‐Order NLO Chromophores with an Enhanced Non‐resonant,Nonlinear Refractive Index in the Picosecond Range

We report on the synthesis and third‐order nonlinear optical (NLO) properties of new asymmetric (push–pull) and symmetric chromophores based on the 3,3′‐bipyridine core. The nonlinear refraction as well as the linear and nonlinear absorption of these compounds has been studied, in solution, by spectroscopy and picosecond single‐shot Z‐scan measurements. The results are very promising in terms of non‐resonant, nonlinear refractive index in the near infrared, particularly with enhancement of the (nonlinear efficiency/transparency) trade‐off afforded by the symmetrization of the chromophores. A new polymer with this structural design has also been investigated.     

Tin Oxide Thin-Film Sensors for Aromatic Hydrocarbons Detection: Effect of Aging Time on Film Microstructure

SnO₂ thin films for gas-sensor devices were deposited by pulsed laser ablation on < h 00> silicon wafers and on substrate heater elements with 200 nm thick Si₃N₄ membranes as physical supports of the sensor stack. Microscopic analysis showed that the thin films were polycrystalline, with ∼40-60 nm equiaxial grains, high porosity, and high specific surface area. The sensors were exposed to gas mixtures containing benzene, wet synthetic air, and CO, with 0.5 ppm of benzene added to 30% relative humidity synthetic air and 20 ppm CO. A 100% relative conductance variation, Delta I / I ₀, of the sensing layer was observed. However, this Delta I / I ₀ value consistently decreased after prolonged testing (up to 2 weeks) in a gas-sensor chamber. The sensing layer was studied using several analytical techniques to understand the aging time effects on sensor performance under working conditions. X-ray diffractometry showed a marked decrease of the residual microstrain after prolonged heat treatments, suggesting a substantial reduction of lattice (point and line) defects. Furthermore, photothermal deflection spectroscopy highlighted a consistent decrease of the sensing layer absorption coefficient near 1 eV that could be related to a reduction of carrier concentration. Because structural defects in SnO₂, such as oxygen vacancies or dislocations, are electrically active and variations in the carrier concentration are, at least in part, related with changes in the defect density, the annealing of these defects might have accounted for the observed worsening of sensor performance with the aging time.     

Rotorcraft Trajectory Optimization with Realizability Considerations

This paper considers the problem of computing optimal trajectories for rotorcraft systems. The vehicle is described through a flight mechanics model, and the optimal control problem is solved by discretizing the vehicle governing equations using a finite-element method, followed by optimization of the resulting finite-dimensional problem. It is found that the computed control policies exhibit oscillations and very high—and therefore unrealistic—time rates, especially for aggressive or emergency maneuvers. Highly oscillatory controls can affect the vehicle trajectory by, for example, exciting short period type oscillations. We argue that this behavior of the computed controls is due to the lack of modeling detail of the vehicle actuators, implied by the classical treatment of the system controls as algebraic variables. We propose a simple, low-cost solution that is based on the recovery of the control time rates through a Galerkin projection. This approach is motivated by the desire to avoid direct modeling of the actuator dynamics, which typically requires one to resolve fine temporal scales in the solution. The recovered control rates can then be constrained to remain within physically acceptable bounds during the solution and can also be included in the optimization cost functions. Numerical experiments are shown to demonstrate that smoother control time histories and vehicle trajectories are computed through this approach.