Method validation using weighted linear regression models for quantification of UV filters in water samples

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fast determination of beef quality parameters with time-domain nuclear magnetic resonance spectroscopy and chemometrics

The noteworthy of this study is to predict seven quality parameters for beef samples using time-domain nuclear magnetic resonance (TD-NMR) relaxometry data and multivariate models. Samples from 61 Bonsmara heifers were separated into five groups based on genetic (breeding composition) and feed system (grain and grass feed). Seven sample parameters were analyzed by reference methods; among them, three sensorial parameters, flavor, juiciness and tenderness and four physicochemical parameters, cooking loss, fat and moisture content and instrumental tenderness using Warner Bratzler shear force (WBSF). The raw beef samples of the same animals were analyzed by TD-NMR relaxometry using Carr-Purcell-Meiboom-Gill (CPMG) and Continuous Wave-Free Precession (CWFP) sequences. Regression models computed by partial least squares (PLS) chemometric technique using CPMG and CWFP data and the results of the classical analysis were constructed. The results allowed for the prediction of aforementioned seven properties. The predictive ability of the method was evaluated using the root mean square error (RMSE) for the calibration (RMSEC) and validation (RMSEP) data sets. The reference and predicted values showed no significant differences at a 95% confidence level.

Programa computacional ODR-ATA para densitometria óssea baseado na densitometria radiografica

Pós-graduação em Ciência Animal - FMVA

Classification of intact açai (Euterpe oleracea Mart.) and jucara (Euterpe edulis Mart) fruits based on dry matter content by means of near infrared spectroscopy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fungos endofíticos em Eugenia brasiliensis: prospecção química, biológica, enzimática e avaliação do co-cultivo e epigenética em Xylaria cubensis, Diaporthe sp. e Colletotrichum sp.

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Determination of dimethyltryptamine and beta-carbolines (ayahuasca alkaloids) in plasma samples by LC-MS/MS

Background: Ayahuasca is a psychoactive plant beverage originally used by indigenous people throughout the Amazon Basin, long before its modern use by syncretic religious groups established in Brazil, the USA and European countries. The objective of this study was to develop a method for quantification of dimethyltryptamine and beta-carbolines in human plasma samples. Results: The analytes were extracted by means of C18 cartridges and injected into LC-MS/MS, operated in positive ion mode and multiple reaction monitoring. The LOQs obtained for all analytes were below 0.5 ng/ml. By using the weighted least squares linear regression, the accuracy of the analytical method was improved at the lower end of the calibration curve (from 0.5 to 100 ng/ml; r(2)> 0.98). Conclusion: The method proved to be simple, rapid and useful to estimate administered doses for further pharmacological and toxicological investigations of ayahuasca exposure.

Electrospray Ionization Mass Spectrometry Fingerprinting of Extracts of the Leaves of Arrabidaea chica

Arrabidaea chica (crajiru) is an important Amazonian plant. Its extracts are used as red pigments, antimicrobial agents and astringents. Three different varieties of this species are cultivated in the Amazon region. In this work, direct infusions of A. chica extracts from these three varieties were analyzed via electrospray ionization mass spectrometry (ESI(+)-MS) fingerprinting. Derived data from the spectra were classified by using a multivariate method (PLS-DA, partial least squares-discriminant analysis). The direct method that is herein presented relies on extraction of dry, powdered leaves with acidified methanol/water solution with no further sample preparation. The resulting supernatants were analyzed by direct infusion ESI(+)-MS, which provides characteristic fingerprints of the sample composition. 3-Deoxyanthocyanidins are important substances in A. chica, their ions were used as markers in the PLS-DA data treatment. PLS-DA was able to differentiate the three varieties. ESI(+)-MS fingerprinting works as a simple and fast method to differentiate varieties of A. chica.

Influence of chest wall on lung mechanics during inspiration

RATIONALE: The interaction between lungs and chest wall influences lung volume, that determines lung history during respiration cycle. In this study, the influence of chest wall mechanics on respiratory system is assessed by the evaluation of inspiration pressure-volume curve (PV curve) under three different situations: closed-chest, open-chest and isolated lung. The PV curve parameters in each situation allow us to further understand the role played by different chest wall elements in the respiratory function. Methods: Twenty-four male Wistar rats (236 ± 29 g) were used. The animals were weighted and then anesthetized with xylazine 2% (O,SmL/kg) and ketamine 10% (0,9mL/kg), exsanguinated and later tracheostomies with a metallic cannula (14 gauge).The cannula was connected to an automatic small animal insufflator. This setup was connected to a pressure transducer (32 samples/s). The 24 animals were randomly separated in three groups:(i) closed chest,(ii) open chest and (iii) isolated lung. The rats were insufflated with 20mL quasi-statically (constant speed of 0,1mUs). lnsufflated volume and measured pressure data were kept and PV curves were obtained for all animals. The PV curves were fitted (non-linear least squares) against the sigmoid equation (1) to obtain the sigmoid equation parameters (a,b,c,d). Elastance measurements were obtained from linear regression of pressure/volume measurements in a 0,8s interval before and after the calculated point. Results: The parameters a,b and c showed no significant change, but the parameter d showed a significant variation among the three groups. The initial elastance also varied between open and closed chest, indicating the need of a higher pressure for the lung expansion, as can be seen in Table 1. Conclusion: A supporting effect of the chest wall was observed at the initial moments of inspiration, observed as a higher initial elastance in open chest situations than in closed chest situations (p=0,00001). The similar initial elastance for the isolated lung and closed chest may be explained by the specific method used for the isolated lung experiment. As the isolated lung is supported by the trachea vertically, the weight of the tissue may have a similar effect of the residual negative pressure in the thorax, responsible for maintaining the residual volume.

Influence of chest wall on lung mechanics during inspiration.

RATIONALE: The interaction between lungs and chest wall influences lung volume, that determines lung history during respiration cycle. In this study, the influence of chest wall mechanics on respiratory system is assessed by the evaluation of inspiration pressure-volume curve (PV curve) under three different situations: closed-chest, open-chest and isolated lung. The PV curve parameters in each situation allow us to further understand the role played by different chest wall elements in the respiratory function. Methods: Twenty-four male Wistar rats (236 ± 29 g) were used. The animals were weighted and then anesthetized with xylazine 2% (0,5mL/kg) and ketamine 10% (0,9mL/kg), exsanguinated and later tracheostomized with a metallic cannula (14 gauge). The cannula was connected to an automatic small animal insufflator. This setup was connected to a pressure transducer (32 samples/s). The 24 animals were randomly separated in three groups: (i) closed chest, (ii) open chest and (iii) isolated lung. The rats were insufflated with 20mL quasi-statically (constant speed of 0,1mL/s). Insufflated volume and measured pressure data were kept and PV curves were obtained for all animals. The PV curves were fitted (non-linear least squares) against the sigmoid equation (1) to obtain the sigmoid equation parameters (a,b,c,d). Elastance measurements were obtained from linear regression of pressure/volume measurements in a 0,8s interval before and after the calculated point. Results: The parameters a, b and c showed no significant change, but the parameter d showed a significant variation among the three groups. The initial elastance also varied between open and closed chest, indicating the need of a higher pressure for the lung expansion, as can be seen in Table 1. Table 1: Mean and Standard Deviation of parameters obtained for each protocol. Protocol: Closed Chest – a (mL) -0.35±0.33; b (mL) 13.93±0.89; c (cm H2O) 21.28±2.37; d (cm H2O) 6.17±0.84; r²** (%) 99.4±0.14; Initial Elastance* (cm H2)/mL) 12.72±6.66; Weight (g) 232.33±5.72. Open Chest - a (mL) 0.01±0.28; b (mL) 14.79±0.54; c (cm H2O) 19.47±1.41; d (cm H2O) 3.50±0.28; r²** (%) 98.8±0.34; Initial Elastance* (cm H2)/mL) 28.68±2.36; Weight (g) 217.33±7.97. Isolated Lung - a (mL) -0.09±0.46; b (mL) 14.22±0.75; c (cm H2O) 21.76±1.43; d (cm H2O) 4.24±0.50; r²** (%) 98.9±0.19; Initial Elastance* (cm H2)/mL) 7.13±8.85; Weight (g) 224.33±16.66. * Elastance measures in the 0-0,1 mL range. ** Goodness of sigmoid fit versus measured data Conclusion: A supporting effect of the chest wall was observed at the initial moments of inspiration, observed as a higher initial elastance in open chest situations than in closed chest situations (p=0,00001). The similar initial elastance for the isolated lung and closed chest may be explained by the specific method used for the isolated lung experiment. As the isolated lung is supported by the trachea vertically, the weight of the tissue may have a similar effect of the residual negative pressure in the thorax, responsible for maintaining the residual volume.

New regularization method for EXAFS analysis: Application to uranium and plutonium sorption onto kaolinite

Die Röntgenabsorptionsspektroskopie (Extended X-ray absorption fine structure (EXAFS) spectroscopy) ist eine wichtige Methode zur Speziation von Schwermetallen in einem weiten Bereich von umweltrelevanten Systemen. Um Strukturparameter wie Koordinationszahl, Atomabstand und Debye-Waller Faktoren für die nächsten Nachbarn eines absorbierenden Atoms zu bestimmen, ist es für experimentelle EXAFS-Spektren üblich, unter Verwendung von Modellstrukturen einen „Least-Squares-Fit“ durchzuführen. Oft können verschiedene Modellstrukturen mit völlig unterschiedlicher chemischer Bedeutung die experimentellen EXAFS-Daten gleich gut beschreiben. Als gute Alternative zum konventionellen Kurven-Fit bietet sich das modifizierte Tikhonov-Regularisationsverfahren an. Ergänzend zur Tikhonov-Standardvariationsmethode enthält der in dieser Arbeit vorgestellte Algorithmus zwei weitere Schritte, nämlich die Anwendung des „Method of Separating Functionals“ und ein Iterationsverfahren mit Filtration im realen Raum. Um das modifizierte Tikhonov-Regularisationsverfahren zu testen und zu bestätigen wurden sowohl simulierte als auch experimentell gemessene EXAFS-Spektren einer kristallinen U(VI)-Verbindung mit bekannter Struktur, nämlich Soddyit (UO2)2SiO4 x 2H2O, untersucht. Die Leistungsfähigkeit dieser neuen Methode zur Auswertung von EXAFS-Spektren wird durch ihre Anwendung auf die Analyse von Proben mit unbekannter Struktur gezeigt, wie sie bei der Sorption von U(VI) bzw. von Pu(III)/Pu(IV) an Kaolinit auftreten. Ziel der Dissertation war es, die immer noch nicht voll ausgeschöpften Möglichkeiten des modifizierten Tikhonov-Regularisationsverfahrens für die Auswertung von EXAFS-Spektren aufzuzeigen. Die Ergebnisse lassen sich in zwei Kategorien einteilen. Die erste beinhaltet die Entwicklung des Tikhonov-Regularisationsverfahrens für die Analyse von EXAFS-Spektren von Mehrkomponentensystemen, insbesondere die Wahl bestimmter Regularisationsparameter und den Einfluss von Mehrfachstreuung, experimentell bedingtem Rauschen, etc. auf die Strukturparameter. Der zweite Teil beinhaltet die Speziation von sorbiertem U(VI) und Pu(III)/Pu(IV) an Kaolinit, basierend auf experimentellen EXAFS-Spektren, die mit Hilfe des modifizierten Tikhonov-Regularisationsverfahren ausgewertet und mit Hilfe konventioneller EXAFS-Analyse durch „Least-Squares-Fit“ bestätigt wurden.

Compressed sensing in digital tomosynthesis reconstruction

In this work we study a model for the breast image reconstruction in Digital Tomosynthesis, that is a non-invasive and non-destructive method for the three-dimensional visualization of the inner structures of an object, in which the data acquisition includes measuring a limited number of low-dose two-dimensional projections of an object by moving a detector and an X-ray tube around the object within a limited angular range. The problem of reconstructing 3D images from the projections provided in the Digital Tomosynthesis is an ill-posed inverse problem, that leads to a minimization problem with an object function that contains a data fitting term and a regularization term. The contribution of this thesis is to use the techniques of the compressed sensing, in particular replacing the standard least squares problem of data fitting with the problem of minimizing the 1-norm of the residuals, and using as regularization term the Total Variation (TV). We tested two different algorithms: a new alternating minimization algorithm (ADM), and a version of the more standard scaled projected gradient algorithm (SGP) that involves the 1-norm. We perform some experiments and analyse the performance of the two methods comparing relative errors, iterations number, times and the qualities of the reconstructed images. In conclusion we noticed that the use of the 1-norm and the Total Variation are valid tools in the formulation of the minimization problem for the image reconstruction resulting from Digital Tomosynthesis and the new algorithm ADM has reached a relative error comparable to a version of the classic algorithm SGP and proved best in speed and in the early appearance of the structures representing the masses.

Assessment of spline-based 2D-3D registration for image-guided spine surgery

2D-3D registration of pre-operative 3D volumetric data with a series of calibrated and undistorted intra-operative 2D projection images has shown great potential in CT-based surgical navigation because it obviates the invasive procedure of the conventional registration methods. In this study, a recently introduced spline-based multi-resolution 2D-3D image registration algorithm has been adapted together with a novel least-squares normalized pattern intensity (LSNPI) similarity measure for image guided minimally invasive spine surgery. A phantom and a cadaver together with their respective ground truths were specially designed to experimentally assess possible factors that may affect the robustness, accuracy, or efficiency of the registration. Our experiments have shown that it is feasible for the assessed 2D-3D registration algorithm to achieve sub-millimeter accuracy in a realistic setup in less than one minute.

Kernel Estimation of Rate Function for Recurrent Event Data

Recurrent event data are largely characterized by the rate function but smoothing techniques for estimating the rate function have never been rigorously developed or studied in statistical literature. This paper considers the moment and least squares methods for estimating the rate function from recurrent event data. With an independent censoring assumption on the recurrent event process, we study statistical properties of the proposed estimators and propose bootstrap procedures for the bandwidth selection and for the approximation of confidence intervals in the estimation of the occurrence rate function. It is identified that the moment method without resmoothing via a smaller bandwidth will produce curve with nicks occurring at the censoring times, whereas there is no such problem with the least squares method. Furthermore, the asymptotic variance of the least squares estimator is shown to be smaller under regularity conditions. However, in the implementation of the bootstrap procedures, the moment method is computationally more efficient than the least squares method because the former approach uses condensed bootstrap data. The performance of the proposed procedures is studied through Monte Carlo simulations and an epidemiological example on intravenous drug users.

Unifying energy minimization and mutual information maximization for robust 2D/3D registration of X-ray and CT images

Similarity measure is one of the main factors that affect the accuracy of intensity-based 2D/3D registration of X-ray fluoroscopy to CT images. Information theory has been used to derive similarity measure for image registration leading to the introduction of mutual information, an accurate similarity measure for multi-modal and mono-modal image registration tasks. However, it is known that the standard mutual information measure only takes intensity values into account without considering spatial information and its robustness is questionable. Previous attempt to incorporate spatial information into mutual information either requires computing the entropy of higher dimensional probability distributions, or is not robust to outliers. In this paper, we show how to incorporate spatial information into mutual information without suffering from these problems. Using a variational approximation derived from the Kullback-Leibler bound, spatial information can be effectively incorporated into mutual information via energy minimization. The resulting similarity measure has a least-squares form and can be effectively minimized by a multi-resolution Levenberg-Marquardt optimizer. Experimental results are presented on datasets of two applications: (a) intra-operative patient pose estimation from a few (e.g. 2) calibrated fluoroscopic images, and (b) post-operative cup alignment estimation from single X-ray radiograph with gonadal shielding.

Radiation metabolomics. 1. Identification of minimally invasive urine biomarkers for gamma-radiation exposure in mice

Gamma-radiation exposure has both short- and long-term adverse health effects. The threat of modern terrorism places human populations at risk for radiological exposures, yet current medical countermeasures to radiation exposure are limited. Here we describe metabolomics for gamma-radiation biodosimetry in a mouse model. Mice were gamma-irradiated at doses of 0, 3 and 8 Gy (2.57 Gy/min), and urine samples collected over the first 24 h after exposure were analyzed by ultra-performance liquid chromatography-time-of-flight mass spectrometry (UPLC-TOFMS). Multivariate data were analyzed by orthogonal partial least squares (OPLS). Both 3- and 8-Gy exposures yielded distinct urine metabolomic phenotypes. The top 22 ions for 3 and 8 Gy were analyzed further, including tandem mass spectrometric comparison with authentic standards, revealing that N-hexanoylglycine and beta-thymidine are urinary biomarkers of exposure to 3 and 8 Gy, 3-hydroxy-2-methylbenzoic acid 3-O-sulfate is elevated in urine of mice exposed to 3 but not 8 Gy, and taurine is elevated after 8 but not 3 Gy. Gene Expression Dynamics Inspector (GEDI) self-organizing maps showed clear dose-response relationships for subsets of the urine metabolome. This approach is useful for identifying mice exposed to gamma radiation and for developing metabolomic strategies for noninvasive radiation biodosimetry in humans.