Salmonella in companion animals

In an increasingly hygiene concerned society, a major barrier to pet ownership is the perceived role of companion animals in contributing to the risk of exposure to zoonotic bacterial pathogens, such as Salmonella. Manifestations of Salmonella can range from acute gastroenteritis to perfuse enteric fever, in both humans and dogs. Dogs are heavily associated with asymptomatic carriage of Salmonella as the microorganism can persist in the lower intestines of this host which can be then excreted into the environment. Studies in to the asymptomatic carriage of Salmonella in dogs are somewhat dated and there is limited UK data. The current UK carriage rate in dogs was investigated in a randomised dog population and it was revealed that the carriage rate in this population was very low with only one household dog positive for the carriage of Salmonella enterica arizonae (0.2%), out of 490 dogs sampled. Salmonella serotypes share phenotypic and genotypic similarities which are captured in epidemiological typing methods. Therefore, in parallel to the epidemiological investigations, a panel of clinical canine (VLA, UK) and human (Aston University, UK) Salmonella isolates were profiled based on their phenotypic and genotypic characteristics; using API 20E, Biolog Microbial ID System, antibiotic sensitivity testing and PFGE, respectively. Antibiotic sensitivity testing revealed a significant difference between the canine and human isolates with the canine group demonstrating a higher resistance to the panel of antibiotics tested. Further metabolic capabilities of the strains were tested using the Biolog Microbial ID System, which reveal no clear association between the two host groups. However, coupled with Principle Component Analysis two canine isolates were discriminated from the entire population on the basis of a high up-regulation of two carbohydrates. API 20E testing revealed no association between the two host groups. A PFGE harmonised protocol was used to genotypically profile the strains. A dendrogram depicting PFGE profiles of the panel of Salmonella isolates was performed where similarities were calculated by Dice coefficient and represented by UPGMA clustering. Clustering of the profiles from canine isolates and human isolates (HPA, UK) was diverse representing a natural heterogeneity of the genus, additionally, no clear clustering of the isolates was observed between host groups. Clustering was observed with isolates from the same serotype, independent of host origin. Host adaption is a common phenomenon in certain Salmonella serotypes, for example S. Typhi in humans and S. Dublin in cattle. It was of interest to investigate potential host adaptive or restricted strains for canine host by performing adhesion and invasion assays on Dog Intestinal Epithelial Cells (DIECs) (WALTHAM®, UK) and human CaCo-2 (HPA, UK) cell lines. Salmonella arizonae and Enteritidis from an asymptomatic dog and clinical isolate, respectively, demonstrated a significantly high proportion of invasion in DIEC in comparison to human CaCo-2 cells and other tested Salmonella serotypes. This may be suggestive of a potential host restrictive strain as their ability to invade the CaCo-2 cell line was significantly lower than the other serotypes. In conclusion to this thesis the investigations carried out suggest that asymptomatic carriage of Salmonella in UK dogs is low however the microorganism remains as a zoonotic and anthroponotic pathogen based on phenotypic and genotypic characterisation however there may be potential for particular serotype to become host restricted as observed in invasion assays

A Statistical Approach for Multilingual Document Clustering and Topic Extraction from Clusters

2000 Mathematics Subject Classification: 62H30

Analysis of White Latex Paints using Laser Induced Breakdown Spectroscopy for Forensic Applications

The analysis of white latex paint is a problem for forensic laboratories because of difficulty in differentiation between samples. Current methods provide limited information that is not suitable for discrimination. Elemental analysis of white latex paints has resulted in 99% discriminating power when using LA-ICP-MS; however, mass spectrometers can be prohibitively expensive and require a skilled operator. A quick, inexpensive, effective method is needed for the differentiation of white latex paints. In this study, LIBS is used to analyze 24 white latex paint samples. LIBS is fast, easy to operate, and has a low cost. Results show that 98.1% of variation can be accounted for via principle component analysis, while Tukey pairwise comparisons differentiated 95.6% with potassium as the elemental ratio, showing that the discrimination capabilities of LIBS are comparable to those of LA-ICP-MS. Due to the many advantages of LIBS, this instrument should be considered a necessity for forensic laboratories.

Multivariate Techniques in Biomechanical Analysis

This work outlines the theoretical advantages of multivariate methods in biomechanical data, validates the proposed methods and outlines new clinical findings relating to knee osteoarthritis that were made possible by this approach. New techniques were based on existing multivariate approaches, Partial Least Squares (PLS) and Non-negative Matrix Factorization (NMF) and validated using existing data sets. The new techniques developed, PCA-PLS-LDA (Principal Component Analysis – Partial Least Squares – Linear Discriminant Analysis), PCA-PLS-MLR (Principal Component Analysis – Partial Least Squares –Multiple Linear Regression) and Waveform Similarity (based on NMF) were developed to address the challenging characteristics of biomechanical data, variability and correlation. As a result, these new structure-seeking technique revealed new clinical findings. The first new clinical finding relates to the relationship between pain, radiographic severity and mechanics. Simultaneous analysis of pain and radiographic severity outcomes, a first in biomechanics, revealed that the knee adduction moment’s relationship to radiographic features is mediated by pain in subjects with moderate osteoarthritis. The second clinical finding was quantifying the importance of neuromuscular patterns in brace effectiveness for patients with knee osteoarthritis. I found that brace effectiveness was more related to the patient’s unbraced neuromuscular patterns than it was to mechanics, and that these neuromuscular patterns were more complicated than simply increased overall muscle activity, as previously thought.

Multivariate analysis of regional-scale geochemical data for environmental monitoring

A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.

Oil Market Modelling: A Comparative Analysis of Fundamental and Latent Factor Approaches

We formally compare fundamental factor and latent factor approaches to oil price modelling. Fundamental modelling has a long history in seeking to understand oil price movements, while latent factor modelling has a more recent and limited history, but has gained popularity in other financial markets. The two approaches, though competing, have not formally been compared as to effectiveness. For a range of short- medium- and long-dated WTI oil futures we test a recently proposed five-factor fundamental model and a Principal Component Analysis latent factor model. Our findings demonstrate that there is no discernible difference between the two techniques in a dynamic setting. We conclude that this infers some advantages in adopting the latent factor approach due to the difficulty in determining a well specified fundamental model.

Analysis of Molecular Dynamics Simulations of Protein Folding

Microsecond long Molecular Dynamics (MD) trajectories of biomolecular processes are now possible due to advances in computer technology. Soon, trajectories long enough to probe dynamics over many milliseconds will become available. Since these timescales match the physiological timescales over which many small proteins fold, all atom MD simulations of protein folding are now becoming popular. To distill features of such large folding trajectories, we must develop methods that can both compress trajectory data to enable visualization, and that can yield themselves to further analysis, such as the finding of collective coordinates and reduction of the dynamics. Conventionally, clustering has been the most popular MD trajectory analysis technique, followed by principal component analysis (PCA). Simple clustering used in MD trajectory analysis suffers from various serious drawbacks, namely, (i) it is not data driven, (ii) it is unstable to noise and change in cutoff parameters, and (iii) since it does not take into account interrelationships amongst data points, the separation of data into clusters can often be artificial. Usually, partitions generated by clustering techniques are validated visually, but such validation is not possible for MD trajectories of protein folding, as the underlying structural transitions are not well understood. Rigorous cluster validation techniques may be adapted, but it is more crucial to reduce the dimensions in which MD trajectories reside, while still preserving their salient features. PCA has often been used for dimension reduction and while it is computationally inexpensive, being a linear method, it does not achieve good data compression. In this thesis, I propose a different method, a nonmetric multidimensional scaling (nMDS) technique, which achieves superior data compression by virtue of being nonlinear, and also provides a clear insight into the structural processes underlying MD trajectories. I illustrate the capabilities of nMDS by analyzing three complete villin headpiece folding and six norleucine mutant (NLE) folding trajectories simulated by Freddolino and Schulten [1]. Using these trajectories, I make comparisons between nMDS, PCA and clustering to demonstrate the superiority of nMDS. The three villin headpiece trajectories showed great structural heterogeneity. Apart from a few trivial features like early formation of secondary structure, no commonalities between trajectories were found. There were no units of residues or atoms found moving in concert across the trajectories. A flipping transition, corresponding to the flipping of helix 1 relative to the plane formed by helices 2 and 3 was observed towards the end of the folding process in all trajectories, when nearly all native contacts had been formed. However, the transition occurred through a different series of steps in all trajectories, indicating that it may not be a common transition in villin folding. The trajectories showed competition between local structure formation/hydrophobic collapse and global structure formation in all trajectories. Our analysis on the NLE trajectories confirms the notion that a tight hydrophobic core inhibits correct 3-D rearrangement. Only one of the six NLE trajectories folded, and it showed no flipping transition. All the other trajectories get trapped in hydrophobically collapsed states. The NLE residues were found to be buried deeply into the core, compared to the corresponding lysines in the villin headpiece, thereby making the core tighter and harder to undo for 3-D rearrangement. Our results suggest that the NLE may not be a fast folder as experiments suggest. The tightness of the hydrophobic core may be a very important factor in the folding of larger proteins. It is likely that chaperones like GroEL act to undo the tight hydrophobic core of proteins, after most secondary structure elements have been formed, so that global rearrangement is easier. I conclude by presenting facts about chaperone-protein complexes and propose further directions for the study of protein folding.

MORPHOLOGICAL DIVERSITY OF MANGO GERMPLASM FROM THE UPPER ATHI RIVER REGION OF EASTERN KENYA: AN ANALYSIS BASED ON NON- FRUIT DESCRIPTORS

Phenotypic variation in plants can be evaluated by morphological characterization using visual attributes. Fruits have been the major descriptors for identification of different varieties of fruit crops. However, even in their absence, farmers, breeders and interested stakeholders require to distinguish between different mango varieties. This study aimed at determining diversity in mango germplasm from the Upper Athi River (UAR) and providing useful alternative descriptors for the identification of different mango varieties in the absence of fruits. A total of 20 International Plant Genetic Resources Institute (IPGRI) descriptors for mango were selected for use in the visual assessment of 98 mango accessions from 15 sites of the UAR region of eastern Kenya. Purposive sampling was used to identify farmers growing diverse varieties of mangoes. Evaluation of the descriptors was performed on-site and the data collected were then subjected to multivariate analysis including Principal Component Analysis (PCA) and Cluster analysis, one- way analysis of variance (ANOVA) and Chi square tests. Results classified the accessions into two major groups corresponding to indigenous and exotic varieties. The PCA showed the first six principal components accounting for 75.12% of the total variance. A strong and highly significant correlation was observed between the color of fully grown leaves, leaf blade width, leaf blade length and petiole length and also between the leaf attitude, color of young leaf, stem circumference, tree height, leaf margin, growth habit and fragrance. Useful descriptors for morphological evaluation were 14 out of the selected 20; however, ANOVA and Chi square test revealed that diversity in the accessions was majorly as a result of variations in color of young leaves, leaf attitude, leaf texture, growth habit, leaf blade length, leaf blade width and petiole length traits. These results reveal that mango germplasm in the UAR has significant diversity and that other morphological traits apart from fruits can be useful in morphological characterization of mango.

Corporate governance : value creation and performance in credit unions

In this study, we examine the relationship between good corporate governance practices and the creation of value/performance of credit unions from 2010 to 2012. The objective was to create and validate a corporate governance index for credit unions, and to then analyse the relationship between good governance practices and the creation of value/performance. The problem question is: do good corporate governance practices provide value creation for credit unions? The research started by creating indices from factor analysis to identify latent dependent variables related to value creation and performance; next indices were created from the principal component analysis for the creation of independent latent variables related to corporate governance. Finally, based on panel data from regression models, the influence of the variables and indices related to corporate governance on the indices of value creation and performance was verified. Based on the research, it became evident that the Corporate Governance Index (IGC) is mainly impacted by Executive Management, with 40.31% of the IGC value, followed by the Representation and Participation dimension, with 34.07% of the IGC value. The contribution for academics was the creation of the Corporate Governance Index (IGC) applied for credit unions. As for the contribution to the system of credit unions, the highlight was the effectiveness of the mechanisms for economic-financial and asset management adopted by BACEN, credit unions and OCEMG.

Impacto de la dinámica oceanográfica en la variación de azufre inorgánico en sedimentos de la Bahía de Paracas

Las condiciones oceanográficas y geoquímicas asociadas al azufre inorgánico fueron estudiadas en la bahía de Paracas para determinar su impacto en los procesos de sulfato-reducción, el intercambio de sulfuro de hidrógeno en la interfaz agua-sedimento y su movilización hacia la fracción precipitada. Se establecieron tres estaciones de muestreo al interior de la bahía entre abril y junio de 2015. La variación espacio-temporal de las especies de azufre inorgánico disuelto (H2S y SO4-2) y precipitado (Acid Volatile Sulfide AVS y Chromium-Reducible Sulfur CRS) se analizaron en relación a los factores ambientales: velocidad de vientos, oxígeno disuelto, temperatura, pH e indicadores de materia orgánica fresca (Cl-a) y de preservación de materia orgánica (COT y NT), así como azufre total (ST). A partir de los análisis de correlación cruzada, se infiere que en las estaciones más profundas hay una mayor correlación entre el oxígeno disuelto y la temperatura que en la estación somera, la correlación de estas variables con la velocidad de viento no fue significativa (p>0.05). Las aguas de fondo en la bahía muestran alternancia entre condiciones hipóxicas (<1,43 mL/L) y micróxicas (<0.10 mL/L) durante otoño con períodos prolongados y con máximas concentraciones de H2S (4,966.76 uM) en los primeros 20 cm del sedimento. El análisis de componentes principales sugiere condiciones más favorables para la sulfato reducción en abril y una mayor oxigenación en junio, a pesar de esto hay una tendencia de incremento de AVS y CRS hacia junio, posiblemente como una respuesta en desfase de las condiciones iniciales, ocasionando una mayor precipitación de monosulfuros de hierro y pirita hacia junio. A pesar de esta precipitación significativa de azufreexisten importantes flujos difusivos de H2S (en promedio de 574.76 μmol.m².d-1), colocando a la bahía de Paracas bajo un escenario de fuente de H2S, que podría alcanzar una condición más severa (2824.94 μmol.m².d-1) durante un evento de aguas blancas.

Comparative Study of Four Portuguese 16th Century Illuminated Manueline Charters based on Spectroscopy and Chemometrics Analysis

The comparative study based on spectroscopic analysis of the materials used to produce four sixteenth-century Manueline Charters (the Charters of Alcochete, Terena, Alandroal and Evora) was performed following a systematic analytical approach. SEM–EDS, l-Raman and l-FTIR analysis highlighted interesting features between them, namely the use of different pigments and colourants (such as different green and yellow pigments), the presence of pigments alterations and the use of a non-expected extemporaneous material (with the presence of titanium white in the Charter of Alcochete). Principal component analysis restricted to the C–H absorption region (3000–2840 cm-1) was applied to 36 infrared spectra of blue historical samples from the Charters of Alcochete,Terena, Alandroal and Évora, suggesting the use of a mixture of a triglyceride and polysaccharide as binder.

A new approach for computing a flood vulnerability index using cluster analysis

A Flood Vulnerability Index (FloodVI) was developed using Principal Component Analysis (PCA) and a new aggregation method based on Cluster Analysis (CA). PCA simplifies a large number of variables into a few uncorrelated factors representing the social, economic, physical and environmental dimensions of vulnerability. CA groups areas that have the same characteristics in terms of vulnerability into vulnerability classes. The grouping of the areas determines their classification contrary to other aggregation methods in which the areas' classification determines their grouping. While other aggregation methods distribute the areas into classes, in an artificial manner, by imposing a certain probability for an area to belong to a certain class, as determined by the assumption that the aggregation measure used is normally distributed, CA does not constrain the distribution of the areas by the classes. FloodVI was designed at the neighbourhood level and was applied to the Portuguese municipality of Vila Nova de Gaia where several flood events have taken place in the recent past. The FloodVI sensitivity was assessed using three different aggregation methods: the sum of component scores, the first component score and the weighted sum of component scores. The results highlight the sensitivity of the FloodVI to different aggregation methods. Both sum of component scores and weighted sum of component scores have shown similar results. The first component score aggregation method classifies almost all areas as having medium vulnerability and finally the results obtained using the CA show a distinct differentiation of the vulnerability where hot spots can be clearly identified. The information provided by records of previous flood events corroborate the results obtained with CA, because the inundated areas with greater damages are those that are identified as high and very high vulnerability areas by CA. This supports the fact that CA provides a reliable FloodVI.

Analysis of Pancreas Histological Images for Glucose Intolerance Identification using Wavelet Decomposition

Subtle structural differencescan be observed in the islets of Langer-hans region of microscopic image of pancreas cell of the rats having normal glucose tolerance and the rats having pre-diabetic(glucose intolerant)situa-tions. This paper proposes a way to automatically segment the islets of Langer-hans region fromthe histological image of rat's pancreas cell and on the basis of some morphological feature extracted from the segmented region the images are classified as normal and pre-diabetic.The experiment is done on a set of 134 images of which 56 are of normal type and the rests 78 are of pre-diabetictype. The work has two stages: primarily,segmentationof theregion of interest (roi)i.e. islets of Langerhansfrom the pancreatic cell and secondly, the extrac-tion of the morphological featuresfrom the region of interest for classification. Wavelet analysis and connected component analysis method have been used for automatic segmentationof the images. A few classifiers like OneRule, Naïve Bayes, MLP, J48 Tree, SVM etc.are used for evaluation among which MLP performed the best.

Antioxidant Activity Of Hydrophilic And Lipophilic Extracts Of Brazilian Blueberries.

Hydrophilic and lipophilic extracts of ten cultivars of Highbush and Rabbiteye Brazilian blueberries (Vaccinium corymbosum L. and Vacciniumashei Reade, respectively) that are used for commercial production were analysed for antioxidant activity by the FRAP, ORAC, ABTS and β-carotene-linoleate methods. Results were correlated to the amounts of carotenoids, total phenolics and anthocyanins. Brazilian blueberries had relatively high concentration of total phenolics (1,622-3,457 mg gallic acid equivalents per 100 g DW) and total anthocyanins (140-318 mg cyanidin-3-glucoside equivalents per 100 g DW), as well as being a good source of carotenoids. There was a higher positive correlation between the amounts of these compounds and the antioxidant activity of hydrophilic compared to lipophilic extracts. There were also significant differences in the level of bioactive compounds and antioxidant activities between different cultivars, production location and year of cultivation.

Determination Of Flavanones In Orange Juices Obtained From Different Sources By Hplc/dad.

Flavanones (hesperidin, naringenin, naringin, and poncirin) in industrial, hand-squeezed orange juices and from fresh-in-squeeze machines orange juices were determined by HPLC/DAD analysis using a previously described liquid-liquid extraction method. Method validation including the accuracy was performed by using recovery tests. Samples (36) collected from different Brazilian locations and brands were analyzed. Concentrations were determined using an external standard curve. The limits of detection (LOD) and the limits of quantification (LOQ) calculated were 0.0037, 1.87, 0.0147, and 0.0066 mg 100 g(-1) and 0.0089, 7.84, 0.0302, and 0.0200 mg 100 g(-1) for naringin, hesperidin, poncirin, and naringenin, respectively. The results demonstrated that hesperidin was present at the highest concentration levels, especially in the industrial orange juices. Its average content and concentration range were 69.85 and 18.80-139.00 mg 100 g(-1). The other flavanones showed the lowest concentration levels. The average contents and concentration ranges found were 0.019, 0.01-0.30, and 0.12 and 0.1-0.17, 0.13, and 0.01-0.36 mg 100 g(-1), respectively. The results were also evaluated using the principal component analysis (PCA) multivariate analysis technique which showed that poncirin, naringenin, and naringin were the principal elements that contributed to the variability in the sample concentrations.