Cluster validation by measurement of clustering characteristics relevant to the user

There are many cluster analysis methods that can produce quite different clusterings on the same dataset. Cluster validation is about the evaluation of the quality of a clustering; "relative cluster validation" is about using such criteria to compare clusterings. This can be used to select one of a set of clusterings from different methods, or from the same method ran with different parameters such as different numbers of clusters. There are many cluster validation indexes in the literature. Most of them attempt to measure the overall quality of a clustering by a single number, but this can be inappropriate. There are various different characteristics of a clustering that can be relevant in practice, depending on the aim of clustering, such as low within-cluster distances and high between-cluster separation. In this paper, a number of validation criteria will be introduced that refer to different desirable characteristics of a clustering, and that characterise a clustering in a multidimensional way. In specific applications the user may be interested in some of these criteria rather than others. A focus of the paper is on methodology to standardise the different characteristics so that users can aggregate them in a suitable way specifying weights for the various criteria that are relevant in the clustering application at hand.Comment: 20 pages 2 figure

Oxazaphosphorine Metabolism by the Human Cytochrome P450s and Some Commonly Expressed P450 Polymorphic Variants.

The oxazaphosphorines, cyclophosphamide (CPA) and ifosfamide (IFO), are commonly used cancer therapeutics. Hallmarks of oxazaphosphorine-treatment include variable patient response and severe adverse drug reactions. These deleterious effects are related to the metabolism of the oxazaphosphorines. Improved understanding of CPA and IFO metabolism is important for the optimization of treatment regimens utilizing these drugs. This dissertation has focused on advancing our knowledge of the two primary metabolic pathways for oxazaphosphorine metabolism, hydroxylation and N-dechloroethylation, by the human cytochrome P450s (P450s) (CYP2B6, CYP2C9, CYP2C19 and CYP3A4). Hydroxylation of the oxazaphosphorines activates the drugs, whereas N-dechloroethylation results in inactivation and the formation of toxic metabolites. We demonstrated that CYP2B6 is 38-fold more efficient than the other P450s for the activation of CPA and that only CYP3A4 catalyzed the inactivation of CPA. For IFO, CYP3A4 was 2.8-fold more efficient at activation of IFO than the other P450s and multiple P450s catalyzed the inactivation of IFO. As the P450s are highly polymorphic enzymes, and polymorphic variants may have altered catalytic activities, we assessed commonly expressed variants for alterations in the rate of oxazaphosphorine metabolism. We observed statistically significant differences in the activation of both of the drugs by some of the polymorphic variants when compared to the wild type enzymes. We also evaluated the ability to favor the activation pathway of oxazaphosphorine metabolism in two ways; specific P450 inhibition in human liver microsomes (HLM) and deuterium labeling of the oxazaphosphorines. Inhibition of P450s in HLM was effective for favoring the activation of CPA, but not IFO. Deuterium labeling of CPA and IFO, resulted in inhibition of inactivation for both drugs but it was more evident with IFO, likely because IFO undergoes inactivation more readily than CPA. Thus, different methods are better for increasing the ratio of activation to inactivation for of each the drugs. Taken together, the work compiled in this thesis has enhanced our mechanistic understanding of the metabolism of the oxazaphosphorines. Our hope is that this information will encourage future investigations focused on the improvement of current cancer chemotherapies and the use of pharmacogenomics to design enhanced chemotherapeutic regimens.PHDPharmacologyUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99932/1/calinski_1.pd

An Interdisciplinary Experience focused on Pharmacogenetics: Engaging pharmacy and physician assistant students in conversations about antiplatelet therapy with respect to CYP2C19 genotype

Objective: The goals of the interdisciplinary laboratory were to educate and engage pharmacy and physician assistant (PA) students in a discussion focused on the collection, interpretation, and application of pharmacogenetic data. Design: Interdisciplinary teams participated in a one-hour, case-based discussion and provided a therapeutic recommendation using the Clinical Pharmacogenetics Implementation Consortium guidelines. Assessment: All students were surveyed before and after the laboratory on knowledge and application of pharmacogenetics and working in interdisciplinary teams. The interdisciplinary laboratory successfully enhanced the student’s knowledge about sample collection and interpretation of pharmacogenetic information. Additionally, the laboratory improved student confidence in working in interdisciplinary teams to apply pharmacogenetic information to clinical decision making. Furthermore, the majority of students indicated that the interdisciplinary laboratory is valuable and useful in healthcare curriculums. Conclusion: The laboratory highlighted the differences between pharmacy and PA education regarding PGt, and brought to light several important uncertainties: (1) What is the depth of PGt knowledge that healthcare practitioners need? (2) What are best practices for conveying PGt information?   Type: Case Stud

Feature Evaluation for Effective Bearing Prognostics.

International audienceRolling element bearing failure is one of the foremost causes of breakdown in rotating machinery. It is not uncommon to replace a defected/used bearing with a new one that has shorter remaining useful life than the defected one. Thus, prognostics of bearing plays critical role for increased availability and reduced cost. Effective prognostics highly depend on the quality of the extracted features. Diagnostics is basically a classification problem, whereas the prognostics is the process of forecasting the future health states. The quality of the features for classification has been studied thoroughly. However, evaluation of the quality of features for prognostics is a relatively new problem. This paper presents an evaluation method for the goodness of the features for prognostics and presents results on bearings run until failure in a lab environment

Dynamic Clustering of Histogram Data Based on Adaptive Squared Wasserstein Distances

This paper deals with clustering methods based on adaptive distances for histogram data using a dynamic clustering algorithm. Histogram data describes individuals in terms of empirical distributions. These kind of data can be considered as complex descriptions of phenomena observed on complex objects: images, groups of individuals, spatial or temporal variant data, results of queries, environmental data, and so on. The Wasserstein distance is used to compare two histograms. The Wasserstein distance between histograms is constituted by two components: the first based on the means, and the second, to internal dispersions (standard deviation, skewness, kurtosis, and so on) of the histograms. To cluster sets of histogram data, we propose to use Dynamic Clustering Algorithm, (based on adaptive squared Wasserstein distances) that is a k-means-like algorithm for clustering a set of individuals into $K$ classes that are apriori fixed. The main aim of this research is to provide a tool for clustering histograms, emphasizing the different contributions of the histogram variables, and their components, to the definition of the clusters. We demonstrate that this can be achieved using adaptive distances. Two kind of adaptive distances are considered: the first takes into account the variability of each component of each descriptor for the whole set of individuals; the second takes into account the variability of each component of each descriptor in each cluster. We furnish interpretative tools of the obtained partition based on an extension of the classical measures (indexes) to the use of adaptive distances in the clustering criterion function. Applications on synthetic and real-world data corroborate the proposed procedure

Clustering Nominal and Numerical Data: A New Distance Concept for a Hybrid Genetic Algorithm

As intrinsic structures, like the number of clusters, is, for real data, a major issue of the clustering problem, we propose, in this paper, CHyGA (Clustering Hybrid Genetic Algorithm) an hybrid genetic algorithm for clustering. CHyGA treats the clustering problem as an optimization problem and searches for an optimal number of clusters characterized by an optimal distribution of instances into the clusters. CHyGA introduces a new representation of solutions and uses dedicated operators, such as one iteration of K-means as a mutation operator. In order to deal with nominal data, we propose a new definition of the cluster center concept and demonstrate its properties. Experimental results on classical benchmarks are given

Quantificação de Bisfenol-A livre em sangue de cordão umbilical humano a nível de traços

El Bisfenol-A (BPA) es ampliamente utilizado en la producción de plásticos de policarbonato, por lo que está presente en productos de uso masivo. Es un disruptor endócrino e incide en el desarrollo gonadal y del sistema nervioso central. La exposición de mujeres embarazadas al BPA es particularmente preocupante para el feto en desarrollo, debido a que atraviesa la placenta pasando a la sangre de cordón y al líquido amniótico. Esto se suma a la escasa o nula actividad enzimática fetal para biotransformarlo en BPAglucurónido inactivo, causando posibles efectos nocivos a la descendencia a dosis muy bajas y sostenidas. Con el propósito de estudiar la exposición al BPA y sus efectos en la población de Argentina se desarrolló y validó un método analítico por cromatografía líquida acoplada a espectrometría de masa, que permite la cuantificación de trazas de BPA libre (forma estrogénica, activa) en plasma de cordón umbilical. La técnica consiste en la precipitación de proteínas de la sangre de cordón por agregado de acetonitrilo y posterior centrifugado e inyección del sobrenadante. Se utilizó una elución isocrática en la cromatografía líquida, y la espectrometría de masa se realizó empleando Electrospray negativo en modo de monitoreo de reacciones múltiples. Los valores de BPA libre cuantificados están en el rango de 1,0 a 12,1 ng/mL, límite de detección: 0,6 ng/mL.Bisphenol-A (BPA) is widely used in the production of polycarbonate plastics and therefore, it is present in products of massive use. It is known as an endocrine disruptor and has an impact on gonadal and central nervous system development. Exposure of pregnant women to BPA is particularly worrying for the developing fetus because it crosses the placenta into the cord blood and amniotic fluid, coupled with little or no fetal enzymatic activity to biotransform it into inactive BPA-glucuronide, causing possible harmful effects to the offspring at very low and sustained doses. With the aim to study the exposure to BPA and its effects on the population of Argentina, an analytical method was developed and validated by liquid chromatography coupled to mass spectrometry, which allows the quantification of trace amounts of free BPA (estrogenic, active form) in plasma of umbilical cord. The method involves protein precipitation by the addition of acetonitrile and subsequent centrifugation and injection of supernatant. An isocratic elution was used in liquid chromatography, and mass spectrometry was performed using negative Electrospray mode in multiple reaction monitoring. Quantified free BPA values are in the range of 1.0 to 12.1 ng/mL, Detection Limit: 0,6 ng/mL.Fil: Cases, Gabriel Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Unidad de Microanálisis y Métodos Físicos en Química Orgánica. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Unidad de Microanálisis y Métodos Físicos en Química Orgánica; Argentina. Hospital Italiano; ArgentinaFil: Calinski, Gustavo J.. Hospital Italiano; ArgentinaFil: Méndez, Mariana L.. Hospital Italiano; ArgentinaFil: Vidal, Flavia A.. Hospital Italiano; ArgentinaFil: Otaño, Lucas. Hospital Italiano; ArgentinaFil: Mariani, Gonzalo L.. Hospital Italiano; ArgentinaFil: Figar, Silvana. Hospital Italiano; ArgentinaFil: Giménez, María I.. Hospital Italiano; Argentin