Fluorescence Microscopy Imaging Denoising with Log-Euclidean Priors and Photobleaching Compensation

Fluorescent protein microscopy imaging is nowadays one of the most important tools in biomedical research. However, the resulting images present a low signal to noise ratio and a time intensity decay due to the photobleaching effect. This phenomenon is a consequence of the decreasing on the radiation emission efficiency of the tagging protein. This occurs because the fluorophore permanently loses its ability to fluoresce, due to photochemical reactions induced by the incident light. The Poisson multiplicative noise that corrupts these images, in addition with its quality degradation due to photobleaching, make long time biological observation processes very difficult. In this paper a denoising algorithm for Poisson data, where the photobleaching effect is explicitly taken into account, is described. The algorithm is designed in a Bayesian framework where the data fidelity term models the Poisson noise generation process as well as the exponential intensity decay caused by the photobleaching. The prior term is conceived with Gibbs priors and log-Euclidean potential functions, suitable to cope with the positivity constrained nature of the parameters to be estimated. Monte Carlo tests with synthetic data are presented to characterize the performance of the algorithm. One example with real data is included to illustrate its application.

Estudo comparativo de procedimentos experimentais e computacionais para cálculo da lipofilia molecular

Introdução – A lipofilia é uma das propriedades físico-químicas que mais influencia a capacidade de uma molécula se movimentar através de compartimentos biológicos. O coeficiente de partição octanol/água (log P) permite, assim, obter uma estimativa da absorção dos fármacos no organismo. A existência de métodos indirectos para um cálculo rápido do log P pode revelar-se de grande importância na análise de listas de compostos com potencial acção farmacológica, reduzindo-as àqueles que se prevêem ter um melhor comportamento biológico. Objectivos – O propósito deste estudo é dar a conhecer um método cromatográfico de RP-HPLC desenvolvido para a determinação indirecta da lipofilia molecular e avaliar a performance de vários programas de cálculo computacional desse mesmo parâmetro. Metodologias – Seleccionaram-se 25 compostos químicos, avaliou-se o log P de cada um deles por RP-HPLC e confrontaram-se os resultados obtidos com os de sete programas computacionais. Resultados – O método RP-HPLC testado demonstrou ser vantajoso em comparação com o convencional shake flask. O programa de cálculo indirecto que proporcionou resultados mais próximos dos experimentais foi o ALOGPS© 2.1. Conclusões – A escolha ideal para a determinação da lipofilia de compostos cujo log P estimado esteja entre 0 e 6 é, sobretudo no que diz respeito à rapidez e simplicidade do processo, o método experimental indirecto RP-HPLC. Quanto aos métodos computacionais concluiu-se que nenhum dos programas, incluindo o ALOGPS© 2.1, demonstrou ser eficaz na avaliação de isómeros pelo que, para estes compostos, será sempre necessário recorrer ao método shake flask ou RP-HPLC.

An electro-rheological study of the nematic liquid crystal 4-n-heptyl-4'-cyanobiphenyl

An experimental and theoretical study of the electro-rheological effects observed in the nematic phase of 4-n-heptyl-4'-cyanobiphenyl has been conducted. This liquid crystal appears to be a model system, in which the observed rheological behaviour can be interpreted by the Leslie-Ericksen continuum theory for low molecular weight liquid crystals. Flow curves are illustrated at different temperatures and under the influence of an external electric field ranging from 0 to 3 kV mm-1, applied perpendicular to the direction of flow. Also presented is the apparent viscosity as a function of temperature, over similar values of electric field, obtained at different shear rates. A master flow curve has been constructed for each temperature by dividing the shear rate by the square of the electric field and multiplying by the square of a reference value of electric field. In a log-log plot, two Newtonian plateaux are found to appear at low and high shear rates, connected by a shear-thinning region. We have applied the Leslie-Ericksen continuum theory, in which the director alignment angle is a function of the electric field and the flow field boundary conditions are neglected, to determine viscoelastic parameters and the dielectric anisotropy.

Desenvolvimento de quelantes macrocíclicos para complexação de iões metálicos de transição e lantanídeos com interesse em aplicações médicas

A investigação de novos compostos macrocíclicos tetraaza tem sido intensificada ao longo das últimas décadas, uma vez que estes estão entre os melhores ligandos para complexação de iões metálicos. Desta forma, tanto a síntese destes compostos, como as propriedades dos seus complexos com iões metálicos provocaram o seu crescente interesse em variadíssimas áreas, das quais são exemplo a medicina, a biologia, a catálise, e a química analítica. Procuram-se ligandos específicos para determinados iões metálicos, mas que ao mesmo tempo se preparem por processos de síntese simples e eficazes que permitam uma maior utilização ao nível industrial. Com este trabalho procurou-se dar continuidade aos estudos desenvolvidos nesta área desde 1980 pelo grupo de investigação onde me encontro inserida e assim obter ligandos novos com vista à formação de complexos com iões metálicos estáveis e aplicáveis ao nível da medicina e da farmacologia, com destaque para as aplicações relacionadas com o diagnóstico e a terapia de tumores. Assim, foram sintetizados quatro novos ligandos derivados de macrociclos tetraaza com 12 átomos no anel, dois deles com ponte cruzada curta tipo etano. A síntes baseou-se na funcionalização destes macrociclos com braços pendentes metilnitrofenol ou metilfenol, originando assim os seguintes compostos: cb-do2nph, do2nph, cb-do2ph e do do2ph. Todos os compostos sintetizados foram caracterizados por diversas técnicas analíticas. Os compostos cb-do2nph e do2nph mostraram reduzida solubilidade em água e em metanol:água, pelo que não foi possível a determinação de constantes por potenciometria. Preparam-se alguns complexos que se estudaram em solução por espectroscopia electrónica e no estado sólido por difracção de raios X. O composto do2ph só se obteve em pequena quantidade sem revelar a pureza necessária e, a sua síntese ainda terá de ser optimizada. Finalmente, o composto cb-do2ph foi sintetizado em quantidade suficiente para se poderem determinar as suas constantes de protonação e as constantes de estabilidade dos seus complexos com Cu 2+ e Zn 2+, pelo método potenciomátrico, em solução aquosa, à temperatura de 298,2 K e à força iónica 0,10M em N(CH 3)4NO3. Determinaram-se ainda por potenciometria as constantes de protonação bem como as constantes de estabilidade dos complexos com Mg2+, Cu2+, Zn 2+, Fe3+, Ga3+, In3+, Gd3+, do composto cbdbf-do2a, igualmente em solução aquosa, à temperatura de 298,2K e à força iónica 0,10M em N(CH 3)4NO3. Para ambos os compostos, cb-do2ph e cbdbf-do2a, recorreu-se a titulações por espectroscopia de RMN de 1H para a determinação da primeira constante, por esta ter um valor muito elevado (log K1 ≥ 14), ou seja, estes compostos comportaram-se como “esponjas de protão”. Para obter informações estruturais dos complexos de alguns ligandos com cobre (II) realizaram-se estudos por espectroscopia de absorção de UV-Vis e de RPE, tendo-se ainda obtido cristais de tamanho suficiente para a determinação de estruturas por difracção de raios X de alguns compostos e complexos de cobre (II) e Zinco(II).

Programa estruturado de enriquecimento conceptual e lexical

Dissertação apresentada à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ciências da Educação - Especialidade Educação Especial

Particle agglomeration study in rf silane plasmas: In situ study by polarization-sensitive laser light scattering

To determine self-consistently the time evolution of particle size and their number density in situ multi-angle polarization-sensitive laser light scattering was used. Cross-polarization intensities (incident and scattered light intensities with opposite polarization) measured at 135 degrees and ex situ transmission electronic microscopy analysis demonstrate the existence of nonspherical agglomerates during the early phase of agglomeration. Later in the particle time development both techniques reveal spherical particles again. The presence of strong cross-polarization intensities is accompanied by low-frequency instabilities detected on the scattered light intensities and plasma emission. It is found that the particle radius and particle number density during the agglomeration phase can be well described by the Brownian free molecule coagulation model. Application of this neutral particle coagulation model is justified by calculation of the particle charge whereby it is shown that particles of a few tens of nanometer can be considered as neutral under our experimental conditions. The measured particle dispersion can be well described by a Brownian free molecule coagulation model including a log-normal particle size distribution. (C) 1996 American Institute of Physics.

Gamma radiation effects on microbial inactivation of two medicinal plants

The consumption of natural products has become a public health problem, since these medicinal teas are prepared using natural plants without an effective hygienic and sanitary control. The aim of this study was to assess the effects of gamma radiation, on the microbial burden of two medicinal plants: Melissa officinalis and Lippia citriodora. Dried samples of the two plants were irradiated at a Co-60 experimental equipment. The applied gamma radiation doses were 1, 3, and 5 kGy at a dose rate of 1.34 kGy/h. Non-irradiated samples followed all the experiments. Bacterial and fungal counts were assessed before and after irradiation by membrane filtration method. Challenging tests with Escherichia coli were performed in order to evaluate the disinfection efficiency of gamma radiation treatment. Characterization of M. officinalis and L. citriadora microbiota indicated an average bioburden value of 102CFU/g. The inactivation studies of the bacterial mesophilic population of both dried plants pointed out to a one log reduction of microbial load after irradiation at 5 kGy. Regarding the fungal population, the initial load of 30 CFU/g was only reduced by 0.5 log by an irradiation dose of 5 kGy. The dynamics with radiation doses of plants microbial population’s phenotypes indicated the prevalence of gram-positive rods for M. officinalis before and after irradiation, and the increase of the frequency of gram-negative rods with irradiation for L. citriadora. Among fungal population of both plants, Mucor, Neoscytalidium, Aspergillus and Alternaria were the most isolated genera. The results obtained in the challenging tests with E. coli on plants pointed out to an inactivation efficiency of 99.5% and 99.9% to a dose of 2 kGy, for M.officinalis and L. citriadora, respectively. The gamma radiation treatment can be a significant tool for the microbial control in medicinal plants.

A Spatial Econometrics Analysis for Road Accidents in Lisbon

This paper presents a spatial econometrics analysis for the number of road accidents with victims in the smallest administrative divisions of Lisbon, considering as a baseline a log-Poisson model for environmental factors. Spatial correlation on data is investigated for data alone and for the residuals of the baseline model without and with spatial-autocorrelated and spatial-lagged terms. In all the cases no spatial autocorrelation was detected.

Insights into the mechanims underlyng the antiproliferative potential of a Co(II) coordination compound bearing 1,10-Phenanthroline-5,6-Dione: DNA and protein interaction studies

The very high antiproliferative activity of [Co(Cl)(H2O)(phendione)(2)][BF4] (phendione is 1,10-phenanthroline-5,6-dione) against three human tumor cell lines (half-maximal inhibitory concentration below 1 mu M) and its slight selectivity for the colorectal tumor cell line compared with healthy human fibroblasts led us to explore the mechanisms of action underlying this promising antitumor potential. As previously shown by our group, this complex induces cell cycle arrest in S phase and subsequent cell death by apoptosis and it also reduces the expression of proteins typically upregulated in tumors. In the present work, we demonstrate that [Co(Cl)(phendione)(2)(H2O)][BF4] (1) does not reduce the viability of nontumorigenic breast epithelial cells by more than 85 % at 1 mu M, (2) promotes the upregulation of proapoptotic Bax and cell-cycle-related p21, and (3) induces release of lactate dehydrogenase, which is partially reversed by ursodeoxycholic acid. DNA interaction studies were performed to uncover the genotoxicity of the complex and demonstrate that even though it displays K (b) (+/- A standard error of the mean) of (3.48 +/- A 0.03) x 10(5) M-1 and is able to produce double-strand breaks in a concentration-dependent manner, it does not exert any clastogenic effect ex vivo, ruling out DNA as a major cellular target for the complex. Steady-state and time-resolved fluorescence spectroscopy studies are indicative of a strong and specific interaction of the complex with human serum albumin, involving one binding site, at a distance of approximately 1.5 nm for the Trp214 indole side chain with log K (b) similar to 4.7, thus suggesting that this complex can be efficiently transported by albumin in the blood plasma.

Design and optimization of na ultra wideband and compact microwave antenna for radiometric monitoring of brain temperature

We present the modeling efforts on antenna design and frequency selection to monitor brain temperature during prolonged surgery using noninvasive microwave radiometry. A tapered log-spiral antenna design is chosen for its wideband characteristics that allow higher power collection from deep brain. Parametric analysis with the software HFSS is used to optimize antenna performance for deep brain temperature sensing. Radiometric antenna efficiency (eta) is evaluated in terms of the ratio of power collected from brain to total power received by the antenna. Anatomical information extracted from several adult computed tomography scans is used to establish design parameters for constructing an accurate layered 3-D tissue phantom. This head phantom includes separate brain and scalp regions, with tissue equivalent liquids circulating at independent temperatures on either side of an intact skull. The optimized frequency band is 1.1-1.6 GHz producing an average antenna efficiency of 50.3% from a two turn log-spiral antenna. The entire sensor package is contained in a lightweight and low-profile 2.8 cm diameter by 1.5 cm high assembly that can be held in place over the skin with an electromagnetic interference shielding adhesive patch. The calculated radiometric equivalent brain temperature tracks within 0.4 degrees C of the measured brain phantom temperature when the brain phantom is lowered 10. C and then returned to the original temperature (37 degrees C) over a 4.6-h experiment. The numerical and experimental results demonstrate that the optimized 2.5-cm log-spiral antenna is well suited for the noninvasive radiometric sensing of deep brain temperature.

Machine learning Vasicek model calibration with Gaussian processes

In this article, we calibrate the Vasicek interest rate model under the risk neutral measure by learning the model parameters using Gaussian processes for machine learning regression. The calibration is done by maximizing the likelihood of zero coupon bond log prices, using mean and covariance functions computed analytically, as well as likelihood derivatives with respect to the parameters. The maximization method used is the conjugate gradients. The only prices needed for calibration are zero coupon bond prices and the parameters are directly obtained in the arbitrage free risk neutral measure.

Numerical 3D modeling of heat transfer in human tissues for microwave radiometry monitoring of Brown fat metabolismo

Background: Brown adipose tissue (BAT) plays an important role in whole body metabolism and could potentially mediate weight gain and insulin sensitivity. Although some imaging techniques allow BAT detection, there are currently no viable methods for continuous acquisition of BAT energy expenditure. We present a non-invasive technique for long term monitoring of BAT metabolism using microwave radiometry. Methods: A multilayer 3D computational model was created in HFSS™ with 1.5 mm skin, 3-10 mm subcutaneous fat, 200 mm muscle and a BAT region (2-6 cm3) located between fat and muscle. Based on this model, a log-spiral antenna was designed and optimized to maximize reception of thermal emissions from the target (BAT). The power absorption patterns calculated in HFSS™ were combined with simulated thermal distributions computed in COMSOL® to predict radiometric signal measured from an ultra-low-noise microwave radiometer. The power received by the antenna was characterized as a function of different levels of BAT metabolism under cold and noradrenergic stimulation. Results: The optimized frequency band was 1.5-2.2 GHz, with averaged antenna efficiency of 19%. The simulated power received by the radiometric antenna increased 2-9 mdBm (noradrenergic stimulus) and 4-15 mdBm (cold stimulus) corresponding to increased 15-fold BAT metabolism. Conclusions: Results demonstrated the ability to detect thermal radiation from small volumes (2-6 cm3) of BAT located up to 12 mm deep and to monitor small changes (0.5°C) in BAT metabolism. As such, the developed miniature radiometric antenna sensor appears suitable for non-invasive long term monitoring of BAT metabolism.

Vertex component analysis: a geometric-based approach to unmix hyperspectral data

Hyperspectral remote sensing exploits the electromagnetic scattering patterns of the different materials at specific wavelengths [2, 3]. Hyperspectral sensors have been developed to sample the scattered portion of the electromagnetic spectrum extending from the visible region through the near-infrared and mid-infrared, in hundreds of narrow contiguous bands [4, 5]. The number and variety of potential civilian and military applications of hyperspectral remote sensing is enormous [6, 7]. Very often, the resolution cell corresponding to a single pixel in an image contains several substances (endmembers) [4]. In this situation, the scattered energy is a mixing of the endmember spectra. A challenging task underlying many hyperspectral imagery applications is then decomposing a mixed pixel into a collection of reflectance spectra, called endmember signatures, and the corresponding abundance fractions [8–10]. Depending on the mixing scales at each pixel, the observed mixture is either linear or nonlinear [11, 12]. Linear mixing model holds approximately when the mixing scale is macroscopic [13] and there is negligible interaction among distinct endmembers [3, 14]. If, however, the mixing scale is microscopic (or intimate mixtures) [15, 16] and the incident solar radiation is scattered by the scene through multiple bounces involving several endmembers [17], the linear model is no longer accurate. Linear spectral unmixing has been intensively researched in the last years [9, 10, 12, 18–21]. It considers that a mixed pixel is a linear combination of endmember signatures weighted by the correspondent abundance fractions. Under this model, and assuming that the number of substances and their reflectance spectra are known, hyperspectral unmixing is a linear problem for which many solutions have been proposed (e.g., maximum likelihood estimation [8], spectral signature matching [22], spectral angle mapper [23], subspace projection methods [24,25], and constrained least squares [26]). In most cases, the number of substances and their reflectances are not known and, then, hyperspectral unmixing falls into the class of blind source separation problems [27]. Independent component analysis (ICA) has recently been proposed as a tool to blindly unmix hyperspectral data [28–31]. ICA is based on the assumption of mutually independent sources (abundance fractions), which is not the case of hyperspectral data, since the sum of abundance fractions is constant, implying statistical dependence among them. This dependence compromises ICA applicability to hyperspectral images as shown in Refs. [21, 32]. In fact, ICA finds the endmember signatures by multiplying the spectral vectors with an unmixing matrix, which minimizes the mutual information among sources. If sources are independent, ICA provides the correct unmixing, since the minimum of the mutual information is obtained only when sources are independent. This is no longer true for dependent abundance fractions. Nevertheless, some endmembers may be approximately unmixed. These aspects are addressed in Ref. [33]. Under the linear mixing model, the observations from a scene are in a simplex whose vertices correspond to the endmembers. Several approaches [34–36] have exploited this geometric feature of hyperspectral mixtures [35]. Minimum volume transform (MVT) algorithm [36] determines the simplex of minimum volume containing the data. The method presented in Ref. [37] is also of MVT type but, by introducing the notion of bundles, it takes into account the endmember variability usually present in hyperspectral mixtures. The MVT type approaches are complex from the computational point of view. Usually, these algorithms find in the first place the convex hull defined by the observed data and then fit a minimum volume simplex to it. For example, the gift wrapping algorithm [38] computes the convex hull of n data points in a d-dimensional space with a computational complexity of O(nbd=2cþ1), where bxc is the highest integer lower or equal than x and n is the number of samples. The complexity of the method presented in Ref. [37] is even higher, since the temperature of the simulated annealing algorithm used shall follow a log( ) law [39] to assure convergence (in probability) to the desired solution. Aiming at a lower computational complexity, some algorithms such as the pixel purity index (PPI) [35] and the N-FINDR [40] still find the minimum volume simplex containing the data cloud, but they assume the presence of at least one pure pixel of each endmember in the data. This is a strong requisite that may not hold in some data sets. In any case, these algorithms find the set of most pure pixels in the data. PPI algorithm uses the minimum noise fraction (MNF) [41] as a preprocessing step to reduce dimensionality and to improve the signal-to-noise ratio (SNR). The algorithm then projects every spectral vector onto skewers (large number of random vectors) [35, 42,43]. The points corresponding to extremes, for each skewer direction, are stored. A cumulative account records the number of times each pixel (i.e., a given spectral vector) is found to be an extreme. The pixels with the highest scores are the purest ones. N-FINDR algorithm [40] is based on the fact that in p spectral dimensions, the p-volume defined by a simplex formed by the purest pixels is larger than any other volume defined by any other combination of pixels. This algorithm finds the set of pixels defining the largest volume by inflating a simplex inside the data. ORA SIS [44, 45] is a hyperspectral framework developed by the U.S. Naval Research Laboratory consisting of several algorithms organized in six modules: exemplar selector, adaptative learner, demixer, knowledge base or spectral library, and spatial postrocessor. The first step consists in flat-fielding the spectra. Next, the exemplar selection module is used to select spectral vectors that best represent the smaller convex cone containing the data. The other pixels are rejected when the spectral angle distance (SAD) is less than a given thresh old. The procedure finds the basis for a subspace of a lower dimension using a modified Gram–Schmidt orthogonalizati on. The selected vectors are then projected onto this subspace and a simplex is found by an MV T pro cess. ORA SIS is oriented to real-time target detection from uncrewed air vehicles using hyperspectral data [46]. In this chapter we develop a new algorithm to unmix linear mixtures of endmember spectra. First, the algorithm determines the number of endmembers and the signal subspace using a newly developed concept [47, 48]. Second, the algorithm extracts the most pure pixels present in the data. Unlike other methods, this algorithm is completely automatic and unsupervised. To estimate the number of endmembers and the signal subspace in hyperspectral linear mixtures, the proposed scheme begins by estimating sign al and noise correlation matrices. The latter is based on multiple regression theory. The signal subspace is then identified by selectin g the set of signal eigenvalue s that best represents the data, in the least-square sense [48,49 ], we note, however, that VCA works with projected and with unprojected data. The extraction of the end members exploits two facts: (1) the endmembers are the vertices of a simplex and (2) the affine transformation of a simplex is also a simplex. As PPI and N-FIND R algorithms, VCA also assumes the presence of pure pixels in the data. The algorithm iteratively projects data on to a direction orthogonal to the subspace spanned by the endmembers already determined. The new end member signature corresponds to the extreme of the projection. The algorithm iterates until all end members are exhausted. VCA performs much better than PPI and better than or comparable to N-FI NDR; yet it has a computational complexity between on e and two orders of magnitude lower than N-FINDR. The chapter is structure d as follows. Section 19.2 describes the fundamentals of the proposed method. Section 19.3 and Section 19.4 evaluate the proposed algorithm using simulated and real data, respectively. Section 19.5 presents some concluding remarks.