Analytical Validation of Quantitative High-Performance Liquid Chromatographic Methods in Pharmaceutical Analysis: A Practical Approach

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

Orbifloxacin: A Review of Properties, Its Antibacterial Activities, Pharmacokinetic/Pharmacodynamic Characteristics, Therapeutic Use, and Analytical Methods

Orbifloxacin is a third generation of fluoroquinolone that exhibits increased antibacterial activity against the Enterobacteriaceae, gram-negative and gram-positive bacteria, anaerobes, and mycobacteria. This drug was synthesized in 1987 and developed as a veterinary chemotherapeutic to use for livestock and domestic pets. Orbifloxacin is labeled for the treatment of skin, soft tissue, and urinary tract infections in dogs, and skin and soft tissue infections in cats, but in some countries, orbifloxacin has been given for the treatment of gastrointestinal and respiratory infections in cattle and swine and other animals. The in vitro activity and clinical efficacy of orbifloxacin against naturally occurring bacterial infections of the skin, ear, soft tissue, udder, and gastrointestinal and respiratory systems in different animals have been evaluated and good responses have been found. The minimum inhibitory concentration of orbifloxacin has been determined in various different pathogens and the results found in the literature are shown in this work. The pharmacokinetics of orbifloxacin has been evaluated by different routes of administration in goats, horses, pigs, rabbits, dogs, cats, camels, cattle, sheep, and fish. Orbifloxacin exhibits excellent pharmacokinetic parameters that suggest that this drug may have good clinical effects on various bacterial infections in these species. All methods described in the scientific literature for determination of orbifloxacin in different matrices were collected and discussed. © 2013 Copyright Taylor and Francis Group, LLC.

Evaluation of the detection and quantification limits in electroanalysis using two popular methods: application in the case study of paraquat determination

In this work, the reduction reaction of paraquat herbicide was used to obtain analytical signals using electrochemical techniques of differential pulse voltammetry, square wave voltammetry and multiple square wave voltammetry. Analytes were prepared with laboratory purified water and natural water samples (from Mogi-Guacu River, SP). The electrochemical techniques were applied to 1.0 mol L-1 Na2SO4 solutions, at pH 5.5, and containing different concentrations of paraquat, in the range of 1 to 10 mu mol L-1, using a gold ultramicroelectrode. 5 replicate experiments were conducted and in each the mean value for peak currents obtained -0.70 V vs. Ag/AgCl yielded excellent linear relationships with pesticide concentrations. The slope values for the calibration plots (method sensitivity) were 4.06 x 10(-3), 1.07 x 10(-2) and 2.95 x 10(-2) A mol(-1) L for purified water by differential pulse voltammetry, square wave voltammetry and multiple square wave voltammetry, respectively. For river water samples, the slope values were 2.60 x 10(-3), 1.06 x 10(-2) and 3.35 x 10(-2) A mol(-1) L, respectively, showing a small interference from the natural matrix components in paraquat determinations. The detection limits for paraquat determinations were calculated by two distinct methodologies, i.e., as proposed by IUPAC and a statistical method. The values obtained with multiple square waves voltammetry were 0.002 and 0.12 mu mol L-1, respectively, for pure water electrolytes. The detection limit from IUPAC recommendations, when inserted in the calibration curve equation, an analytical signal (oxidation current) is smaller than the one experimentally observed for the blank solution under the same experimental conditions. This is inconsistent with the definition of detection limit, thus the IUPAC methodology requires further discussion. The same conclusion can be drawn by the analyses of detection limits obtained with the other techniques studied.

CHEMICAL PROFILE COMPARISON OF SUGARCANE SPIRITS FROM THE SAME WINE DISTILLED IN ALEMBICS AND COLUMNS

CHEMICAL PROFILE COMPARISON OF SUGARCANE SPIRITS FROM THE SAME WINE DISTILLED IN ALEMBICS AND COLUMNS. Six wines were distilled in two different distillation apparatus (alembic and column) producing 24 distillates (6 for each alembic fraction - head, heart and tail; 6 column distillates). The chemical composition of distillates from the same wine was determined using chromatographic techniques. Analytical data were subjected to Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) allowing discrimination of four clusters according to chemical profiles. Both distillation processes influenced the sugarcane spirits chemical quality since two types of distillates with different quantitative chemical profiles were produced after the elimination of fermentation step influence.

An environmentally friendly analytical procedure for nickel determination by atomic and molecular spectrometry after cloud point extraction in different samples

Cloud point extraction (CPE) was employed for separation and preconcentration prior to the determination of nickel by graphite furnace atomic absorption spectrometry (GFAAS), flame atomic absorption spectrometry (FAAS) or UV-Vis spectrophotometry. Di-2-pyridyl ketone salicyloylhydrazone (DPKSH) was used for the first time as a complexing agent in CPE. The nickel complex was extracted from the aqueous phase using the Triton X-114 surfactant. Under optimized conditions, limits of detection obtained with GFAAS, FAAS and UV-Vis spectrophotometry were 0.14, 0.76 and 1.5 mu g L-1, respectively. The extraction was quantitative and the enrichment factor was estimated to be 27. The method was applied to natural waters, hemodialysis concentrates, urine and honey samples. Accuracy was evaluated by analysis of the NIST 1643e Water standard reference material.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Self-organizing cultured neural networks: Image analysis techniques for longitudinal tracking and modeling of the underlying network structure (versión actualizada)

Esta tesis estudia la evolución estructural de conjuntos de neuronas como la capacidad de auto-organización desde conjuntos de neuronas separadas hasta que forman una red (clusterizada) compleja. Esta tesis contribuye con el diseño e implementación de un algoritmo no supervisado de segmentación basado en grafos con un coste computacional muy bajo. Este algoritmo proporciona de forma automática la estructura completa de la red a partir de imágenes de cultivos neuronales tomadas con microscopios de fase con una resolución muy alta. La estructura de la red es representada mediante un objeto matemático (matriz) cuyos nodos representan a las neuronas o grupos de neuronas y los enlaces son las conexiones reconstruidas entre ellos. Este algoritmo extrae también otras medidas morfológicas importantes que caracterizan a las neuronas y a las neuritas. A diferencia de otros algoritmos hasta el momento, que necesitan de fluorescencia y técnicas inmunocitoquímicas, el algoritmo propuesto permite el estudio longitudinal de forma no invasiva posibilitando el estudio durante la formación de un cultivo. Además, esta tesis, estudia de forma sistemática un grupo de variables topológicas que garantizan la posibilidad de cuantificar e investigar la progresión de las características principales durante el proceso de auto-organización del cultivo. Nuestros resultados muestran la existencia de un estado concreto correspondiente a redes con configuracin small-world y la emergencia de propiedades a micro- y meso-escala de la estructura de la red. Finalmente, identificamos los procesos físicos principales que guían las transformaciones morfológicas de los cultivos y proponemos un modelo de crecimiento de red que reproduce el comportamiento cuantitativamente de las observaciones experimentales. ABSTRACT The thesis analyzes the morphological evolution of assemblies of living neurons, as they self-organize from collections of separated cells into elaborated, clustered, networks. In particular, it contributes with the design and implementation of a graph-based unsupervised segmentation algorithm, having an associated very low computational cost. The processing automatically retrieves the whole network structure from large scale phase-contrast images taken at high resolution throughout the entire life of a cultured neuronal network. The network structure is represented by a mathematical object (a matrix) in which nodes are identified neurons or neurons clusters, and links are the reconstructed connections between them. The algorithm is also able to extract any other relevant morphological information characterizing neurons and neurites. More importantly, and at variance with other segmentation methods that require fluorescence imaging from immunocyto- chemistry techniques, our measures are non invasive and entitle us to carry out a fully longitudinal analysis during the maturation of a single culture. In turn, a systematic statistical analysis of a group of topological observables grants us the possibility of quantifying and tracking the progression of the main networks characteristics during the self-organization process of the culture. Our results point to the existence of a particular state corresponding to a small-world network configuration, in which several relevant graphs micro- and meso-scale properties emerge. Finally, we identify the main physical processes taking place during the cultures morphological transformations, and embed them into a simplified growth model that quantitatively reproduces the overall set of experimental observations.

Characterisation of indoor air organic pollutants in Brisbane

The occurrence and levels of airborne polycyclic aromatic hydrocarbons and volatile organic compounds in selected non-industrial environments in Brisbane have been investigated as part of an integrated indoor air quality assessment program. The most abundant and most frequently encountered compounds include, nonanal, decanal, texanol, phenol, 2-ethyl-1-hexanol, ethanal, naphthalene, 2,6-tert-butyl-4-methyl-phenol (BHT), salicylaldehyde, toluene, hexanal, benzaldehyde, styrene, ethyl benzene, o-, m- and pxylenes, benzene, n-butanol, 1,2-propandiol, and n-butylacetate. Many of the 64 compounds usually included in the European Collaborative Action method of TVOC analysis were below detection limits in the samples analysed. In order to extract maximum amount of information from the data collected, multivariate data projection methods have been employed. The implications of the information extracted on source identification and exposure control are discussed.

Tris[4,4,4-trifluoro-1-(2-thienyl)butane-1,3-dionato]aluminium(III)-tris[4,4,4-trifluoro-1-(2-thienyl)butane-1,3-dionato]iron(III) (3/1)

In the title compound, [Al(C8H4F3O2S)3]3[Fe(C8H4F3O2S)3], the metal centre is statistically occupied by AlIII and FeIII cations in a 3:1 ratio. The metal centre is within an octahedral O6 donor set defined by three chelating substituted acetoacetonate anions. The ligands are arranged around the periphery of the molecule with a mer geometry of the S atoms.

Fluorescence spectrometric study on the interactions of isoprocarb and sodium 2-isopropylphenate with bovine serum albumin

The binding interaction of the pesticide Isoprocarb and its degradation product, sodium 2-isopropylphenate, with bovine serum albumin (BSA) was studied by spectrofluorimetry under simulated physiological conditions. Both Isoprocarb and sodium 2-isopropylphenate quenched the intrinsic fluorescence of BSA. This quenching proceeded via a static mechanism. The thermodynamic parameters (ΔH°, ΔS° and ΔG°) obtained from the fluorescence data measured at two different temperatures showed that the binding of Isoprocarb to BSA involved hydrogen bonds and that of sodium 2-isopropylphenate to BSA involved hydrophobic and electrostatic interactions. Synchronous fluorescence spectroscopy of the interaction of BSA with either Isoprocarb or sodium 2-isopropylphenate showed that the molecular structure of the BSA was changed significantly, which is consistent with the known toxicity of the pesticide, i.e., the protein is denatured. The sodium 2-isopropylphenate, was estimated to be about 4–5 times more toxic than its parent, Isoprocarb. Synchronous fluorescence spectroscopy and the resolution of the three-way excitation–emission fluorescence spectra by the PARAFAC method extracted the relative concentration profiles of BSA, Isoprocab and sodium 2-isopropylphenate as a function of the added sodium 2-isopropylphenate. These profiles showed that the degradation product, sodium 2-isopropylphenate, displaced the pesticide in a competitive reaction with the BSA protein.