Multivariate curve resolution applied to sequential injection data. Analysis of amoxicillin anda clavulanic acid

El objetivo de esta tesis ha sido estudiar y desarrollar metodologias analíticasusando un sistema de inyección secuencial (SIA) con un espectrofotómetro de diodos enfila para obtener datos de segundo orden. Para tratar estos datos, las herramientasquimiométricas usadas han sido; resolución de curvas multivariante mediante mínimoscuadrados alternados (MCR-ALS) y otras técnicas relacionadas a ésta como el análisisde componentes principales (PCA) y SIMPLISMA. Además se han aplicado estrategiasde diseño de experimentos para obtener las condiciones experimentales óptimas. Estametodología se aplicó a la determinación de amoxicilina y ácido clavulánico enmedicamentos.El primer capítulo de la tesis contiene una descripción de la amoxicilina y del ácidoclavulánico, una explicación de los fundamentos teóricos tanto del sistema instrumentalcomo de las herramientas quimiométricas usadas y por último, se describen los diseñosde experimentos usados y la función de deseabilidad.En los dos siguientes capítulos, se muestran en forma de artículos científicos lostrabajos experimentales realizados. En un primer artículo, se realizó una clasificación delos medicamentos dependiendo si se tenían interferentes o no, para posteriormenteproponer el tipo de calibrado. Un paso previo a la diferenciación de los medicamentos,fue buscar una secuencia analítica que permitiera obtener un sistema en evolución. Estaetapa se llevó a cabo mediante un diseño de experimentos.En el segundo artículo, se determinó la cantidad de amoxicilina en losmedicamentos que tenían interferentes y además no tenían zonas selectivas. Para llevara cabo de forma correcta la etapa de calibración se realizó un estudio de una serie deparámetros asociados a MCR-ALS. En un tercer artículo se realizó la determinaciónsimultánea del ácido clavulánico y de la amoxicilina que poseían unas característicasácido-base y una sensibilidad espectral similar. Por tal de determinar simultáneamenteambos analitos se rediseñó todo el experimental. En el cuarto artículo se hizo unarevisión bibliográfica de ambas técnicas a partir del año 2004 y se discutió el potencial deusar un sistema de inyección secuencial para generar datos de segundo orden.Con la experimentación realizada se comprobó que el paso clave en estasmetodologias era obtener una buen sistema en evolución, es decir diseñar una buenasecuencia analítica. Por lo que se profundizó en estrategias basadas en diseños deexperimentos. En el quinto artículo, se estudiaron qué factores podían afectar a lasecuencia analítica. También se propusieron respuestas que representaran de una formacuantitativa una buena resolución. Se realizó un diseño Plackett-Burman con el objetivode eliminar los factores no relevantes, para posteriormente modelar una superficie derespuesta a partir de los factores relevantes que permite visualizar las condicionesóptimas de la secuencia analítica.El inconveniente de utilizar la metodología de superficie de respuesta es que enlos casos donde el número de factores relevantes sea superior a 3 o 4, el número deexperiencias aumenta considerablemente. En estos casos, una técnica alternativa essimplex que dio lugar a un sexto artículo.El último capítulo de la tesis contiene las conclusiones. Como una conclusióngeneral, se puede decir que la combinación de un sistema de inyección secuencial (SIA)y una herramienta quimiométrica como la resolución de curvas multivariante mediantemínimos cuadrados alternados (MCR-ALS) puede ser usado tanto para realizar unanálisis cualitativo y cuantitativo ya que proporciona información de los perfiles deconcentración y perfiles espectrales de las diferentes especies a estudio.The objective of this thesis is to study and develop analytical methods to determineamoxicillin and clavulanic acid in pharmaceuticals using sequential injection analysis (SIA)with a diode-array spectrophotometric detector to obtain second-order data. To treat thesedata, the chemometric tool used was; multivariate curve resolution with alternating leastsquares (MCR-ALS) and the techniques involved in the resolution process are: principalanalysis components (PCA) and simple-to-use interactive self-modelling mixture analysis(SIMPLISMA).The first chapter contains a brief description of the theoretical backgrounds thathave been used during this thesis. We explain the characteristics and properties ofamoxicillin and clavulanic acid, we describes the instrumental and the chemometric toolsused and at the end, we introduce the experimental designs used and the desirabilityfunction.In the next two chapters contain the bulk of the work carried out for this thesis andincorporate papers published in journals. In the first paper, the pharmaceuticals wereclassified according to their selective zones in order to propose the type of calibration. In aprevious step, the experimental work was conducted to find an analytical sequence thatallows us to obtain an evolving system. This step was carried out using experimentaldesign. In the second paper, the quantity of amoxicillin in the pharmaceuticals withinterferents or without selective zones was determined. To carry out correctly thecalibration step, we studied different conditions related to the MCR-ALS process.In the third paper, we propose the simultaneous determination of amoxicillin andclavulanic acid which they have the acid-base characteristics and spectral profile similar.To determine both analytes, a new analytical sequence was redesigned. In the fourthpaper, we describe the state of the art of sequential injection analysis (SIA) andmultivariate curve resolution with alternating least squares (MCR-ALS) by reviewing thebibliography since 2004. We discuss the potential of SIA for generating second-orderdata.In previous papers, we found that the most critical step in the development ofanalytical methods based on SIA and MCR-ALS was to obtain an analytical sequence thatprovides an evolving system. To resolve so, we developed the method of experimentaldesign to obtain the optimal analytical sequence.In the forth paper, we studied all the factors and analysed how they affect to theanalytical sequence. We also proposed responses to quantitatively represent a goodresolution. Once these factors and responses were proposed, we used a Plackett-Burmandesign to remove the non-relevant factors and then modelled a response surface. In themaximum of response surface, the optimum conditions for the analytical sequence couldbe visualised. To transform several responses into a single response, we used the overalldesirability function. In the sixth paper, we applied an alternative optimisation methodknows as the simplex approach. We aimed to determine amoxicillin and clavulanic acidsimultaneously when the number of factors and responses was higher than in theprevious paper.The last chapter contains the conclusions of the thesis. In general, we concludethat a combined sequential injection analysis (SIA) with a multivariate detector (i.e. diodearray spectrophotometer) and multivariate curve resolution with alternating least squares(MCR-ALS) can be used for both qualitative and quantitative analyses since, it providesconcentration and spectra profiles for the different species of the sample

Use of a multi-way method to analyze the amino acid composition of a conserved group of orthologous proteins in prokaryotes

BACKGROUND: Amino acids in proteins are not used equally. Some of the differences in the amino acid composition of proteins are between species (mainly due to nucleotide composition and lifestyle) and some are between proteins from the same species (related to protein function, expression or subcellular localization, for example). As several factors contribute to the different amino acid usage in proteins, it is difficult both to analyze these differences and to separate the contributions made by each factor. RESULTS: Using a multi-way method called Tucker3, we have analyzed the amino composition of a set of 64 orthologous groups of proteins present in 62 archaea and bacteria. This dataset corresponds to essential proteins such as ribosomal proteins, tRNA synthetases and translational initiation or elongation factors, which are common to all the species analyzed. The Tucker3 model can be used to study the amino acid variability within and between species by taking into consideration the tridimensionality of the data set. We found that the main factor behind the amino acid composition of proteins is independent of the organism or protein function analyzed. This factor must be related to the biochemical characteristics of each amino acid. The difference between the non-ribosomal proteins and the ribosomal proteins (which are rich in arginine and lysine) is the main factor behind the differences in amino acid composition within species, while G+C content and optimal growth temperature are the main factors behind the differences in amino acid usage between species. CONCLUSION: We show that a multi-way method is useful for comparing the amino acid composition of several groups of orthologous proteins from the same group of species. This kind of dataset is extremely useful for detecting differences between and within species

Supervised semi-automated data analysis software for gas chromatography / differential mobility spectrometry (GC/DMS) metabolomics applications

Modern differential mobility spectrometers (DMS) produce complex and multi-dimensional data streams that allow for near-real-time or post-hoc chemical detection for a variety of applications. An active area of interest for this technology is metabolite monitoring for biological applications, and these data sets regularly have unique technical and data analysis end user requirements. While there are initial publications on how investigators have individually processed and analyzed their DMS metabolomic data, there are no user-ready commercial or open source software packages that are easily used for this purpose. We have created custom software uniquely suited to analyze gas chromatograph / differential mobility spectrometry (GC/DMS) data from biological sources. Here we explain the implementation of the software, describe the user features that are available, and provide an example of how this software functions using a previously-published data set. The software is compatible with many commercial or home-made DMS systems. Because the software is versatile, it can also potentially be used for other similarly structured data sets, such as GC/GC and other IMS modalities

Diabetes and the metabolic syndrome: possibilities of a new breath test in a dolphin model.

Diabetes type-2 and the metabolic syndrome are prevalent in epidemic proportions and result in significant co-morbid disease. Limitations in understanding of dietary effects and cholesterol metabolism exist. Current methods to assess diabetes are essential, though many are invasive; for example, blood glucose and lipid monitoring require regular finger sticks and blood draws. A novel method to study these diseases may be non-invasive breath testing of exhaled compounds. Currently, acetone and lipid peroxidation products have been seen in small scale studies, though other compounds may be significant. As Atlantic bottlenose dolphins (Tursiops truncatus) have been proposed as a good model for human diabetes, applications of dietary manipulations and breath testing in this population may shed important light on how to design human clinical studies. In addition, ongoing studies indicate that breath testing in dolphins is feasible, humane, and yields relevant metabolites. By studying the metabolic and cholesterol responses of dolphins to dietary modifications, researchers may gain insight into human diabetes, improve the design of costly human clinical trials, and potentially discover biomarkers for non-invasive breath monitoring

A rabbit model for assessment of volatile metabolite changes observed from skin: a pressure ulcer case study

Human skin presents a large, easily accessible matrix that is potentially useful for diagnostic applications based on whole body metabolite changes-some of which will be volatile and detected using minimally invasive tools. Unfortunately, identifying skin biomarkers that can be reliably linked to a particular condition is challenging due to a large variability of genetics, dietary intake, and environmental exposures within human populations. This leads to a paucity of clinically validated volatile skin biomarker compounds. Animal models present a very convenient and attractive way to circumvent many of the variability issues. The rabbit (Leporidae) is a potentially logistically useful model to study the skin metabolome, but very limited knowledge of its skin metabolites exists. Here we present the first comprehensive assessment of the volatile fraction of rabbit skin metabolites using polydimethylsiloxane sorbent patch sampling in conjunction with gas chromatography/mass spectrometry. A collection of compounds that are secreted from rabbit skin was documented, and predominantly acyclic long-chain alkyls and alcohols were detected. We then utilized this animal model to study differences between intact skin and skin with early pressure ulcers, as the latter are a major problem in intensive care units. Four New Zealand female white rabbits underwent ulcer formation on one ear with the other ear as a control. Early-stage ulcers were created with neodymium magnets. Histologic analysis showed acute heterophilic dermatitis, edema, and micro-hemorrhage on the ulcerated ears with normal findings on the control ears. The metabolomic analysis revealed subtle but noticeable differences, with several compounds associated with the oxidative stress-related degradation of lipids found to be present in greater abundances in ulcerated ears. The metabolomic findings correlate with histologic evidence of early-stage ulcers. We postulate that the Leporidae model recapitulated the vascular changes associated with ulcer formation. This study illustrates the potential usefulness of the Leporidae model for skin metabolome studies. Additionally, skin metabolome analysis may enhance an understanding of non-skin sources such as urine or breath

SPME-based mobile field device for active sampling of volatiles

Monitoring plant volatile organic compound (VOC) profiles can reveal information regarding the health state of the plant, such as whether it is nutrient stressed or diseased. Typically, plant VOC sampling uses sampling enclosures. Enclosures require time and equipment which are not easily adapted to high throughput sampling in field environments. We have developed a new, easily assembled active sampling device using solid phase microextraction (SPME) that uses a commercial off the shelf (COTS) hand vacuum base to provide rapid and easy mobile plant VOC collection. Calibration curves for three representative plant VOCs (α-pinene, limonene, and ocimene) were developed to verify device functionality and enable the quantification of field-samples from a Meyer lemon tree. We saw that the active sampling allowed us to measure and quantify this chemical in an orchard setting. This device has the potential to be used for VOC sampling as a preliminary diagnostic in precision agriculture applications due to its ease of manufacturing, availability, and low cost of the COTS hand vacuum module

Identification of fungal metabolites from inside Gallus gallus domesticus eggshells by non-invasively detecting volatile organic compounds (VOCs)

The natural porosity of eggshells allows hen eggs to become contaminated with microbes from the nesting material and environment. Those microorganisms can later proliferate due to the humid ambient conditions while stored in refrigerators, causing a potential health hazard to the consumer. The microbes' volatile organic compounds (mVOCs) are released by both fungi and bacteria. We studied mVOCs produced by aging eggs likely contaminated by fungi and fresh eggs using the non-invasive detection method of gas-phase sampling of volatiles followed by gas chromatography/mass spectrometry (GC/MS) analysis. Two different fungal species (Cladosporium macrocarpum and Botrytis cinerea) and two different bacteria species (Stenotrophomas rhizophila and Pseudomonas argentinensis) were identified inside the studied eggs. Two compounds believed to originate from the fungi themselves were identified. One fungus-specific compound was found in both egg and the fungi: trichloromethane. Graphical abstract Trichloromethane is a potential biomarker of fungal contamination of eggs

Citrus tristeza virus infection in sweet orange trees and a mandarin × tangor cross alters low molecular weight metabolites assessed using gas chromatography mass spectrometry (GC/MS)

Citrus tristeza virus (CTV) (genus Closterovirus) is a plant pathogen which infects economically important citrus crops, resulting in devastating crop losses worldwide. In this study, we analyzed leaf metabolite extracts from six sweet orange varieties and a mandarin × tangor cross infected with CTV collected at the Lindcove Research and Extension Center (LREC; Exeter, CA). In order to analyze low volatility small molecules, the extracts of leaf metabolites were derivatized by N-methyl-N-trimethylsilyl-trifluoracetamide (MSTFA). Chemical analysis was performed with gas chromatography/mass spectrometry (GC/MS) to assess metabolite changes induced by CTV infection. Principal Component Analysis (PCA) and Hotelling’s T2 were used to identify outliers within the set of samples. Partial Least Square Discriminant Analysis (PLS-DA) was applied as a regression method. A cross-validation strategy was repeated 300 times to minimize possible bias in the model selection. Afterwards, a representative model was built with a sensitivity of 0.66 and a specificity of 0.71. The metabolites which had the strongest contribution to differentiate between healthy and CTV-infected were found to be mostly saccharides and their derivatives such as inositol, d-fructose, glucaric and quinic acid. These metabolites are known to be endogenously produced by plants, possess important biological functions and often found to be differentially regulated in disease states, maturation processes, and metabolic responses. Based on the information found in this study, a method may be available that can identify CTV infected plants for removal and halt the spread of the virus