Relación entre las condiciones de higiene y seguridad y la exposición ambiental a solventes orgánicos en pintores de automóviles de la localidad de barrios unidos, Bogotá 2015

Introducción. Los trabajadores de los talleres de reparación de automóviles conviven diariamente con la exposición a los solventes orgánicos, exposición que se convierte en un riesgo para su salud que generalmente en el corto plazo se presenta como déficits de concentración, memoria y tiempo de reacción y en el largo plazo produciendo graves repercusiones clínicas como efectos mutagénicos y carcinogénicos. Objetivo. Caracterizar las condiciones higiénicas y de seguridad de trabajadores ocupacionalmente expuestos a solventes orgánicos y determinar los niveles ambientales de benceno, tolueno y xileno (BTX) en talleres de lámina y pintura automotriz de la ciudad de Bogotá. Materiales y métodos. Se hizo un estudio de corte transversal en 60 trabajadores que laboran expuestos a solventes orgánicos en talleres de reparación automotriz en Bogotá. Se realizó una encuesta con variables sociodemográficas, laborales y se determinaron los niveles en aire de benceno, tolueno y xileno. Para los muestreos ambientales, las bombas se colocaron en una posición fija representativa del ambiente general, con el objeto de conocer la distribución de los solventes en el área de trabajo. Se realizó un análisis descriptivo por conteos de frecuencia, medidas de tendencia central y dispersión. Se utilizó prueba de bondad de ajuste para distribución normal (Kolmogorov-Smirnov o Shapiro Wilk), prueba t Student para comparación de medias, o en su defecto prueba U de Mann Whitney para comparación de medianas. Para identificar la relación entre las características sociodemográficas y ocupacionales con la exposición a BTX, se utilizaron pruebas de asociación Chi cuadrado o análisis de correlación según la naturaleza de las variables. El nivel de significancia para cada prueba fue 0.05. Resultados. La edad promedio de los trabajadores fue de 43 años y un tiempo total de exposición a solventes de 20 años. Respecto al uso de protección corporal, 45 (75%) de los trabajadores manifestaron que usaban uniforme, mientras que 14 (23,3%) usaban ropa de calle durante la jornada laboral. El 46,7% manifestaron usar protección respiratoria. La concentración de benceno en aire fue entre 0,1 y 0,45 mg/l (mediana de 0,31 mg/l; DE 0,13 mg/l); la de tolueno estuvo entre 8,25 y 27,22 mg/l (mediana de 14,5 mg/l; DE 6.99 mg/l) y la de xileno entre 19,34 y 150,15 mg/l (mediana de 70,12 mg/l; DE 40,82 mg/l). Conclusión. Los pintores de automóviles están expuestos a niveles elevados de solventes en los lugares de trabajo y no cuentan con condiciones de higiene y seguridad industrial adecuados. Un gran número de pintores son informales lo que les impide el acceso a los beneficios del Sistema de Seguridad Social Integral.

Efectividad del tratamiento de lumbalgia con acupuntura

Se realizó un estudio observacional retrospectivo longitudinal en una Institución prestadora de Servicios de Salud de la ciudad de Bogotá, con el objetivo de evaluar la efectividad en el manejo del dolor de la terapia con acupuntura en el tratamiento de lumbalgia. Se tomaron 150 historias clínicas de pacientes con lumbalgia atendidos de enero de 2014 a mayo de 2016, las cuales fueron sometidas a los criterios de inclusión definidos por los autores, arrojando 48 historias sometidas a la prueba de Friedman con el fin de identificar el impacto sobre el dolor del tratamiento con acupuntura en los pacientes seleccionados. Adicionalmente, bajo un muestreo aleatorio simple de distribución normal sobre las 48 historias clínicas evaluadas, se seleccionaron 25 casos a los cuales se les aplicó una encuesta no estructurada, con el fin de obtener información sobre el estado de la patología después de finalizar el tratamiento e identificar las posibles causas de deserción. Con este estudio se concluye que la terapia con acupuntura es efectiva en el manejo del dolor de pacientes con lumbalgia, y que es necesario realizar más estudios que puedan sustentar la inclusión de la terapéutica en el manejo de esta patología.

Cáncer gástrico en pacientes de Méderi – Hospital Universitario Mayor entre los años 2011 - 2014

Introducción: El cáncer gástrico es uno de los más frecuentes a nivel mundial y Colombia se sitúa entre los países de mayor incidencia en este tipo de patología. Objetivo: Describir las características epidemiológicas, clínicas, el tratamiento administrado y los desenlaces inmediatos de los pacientes con diagnóstico de cáncer gástrico atendidos en el Hospital Universitario Mayor de Bogotá entre los años 2011 y 2014. Metodología: Se realizó un estudio observacional descriptivo con diagnóstico de cáncer gástrico. Se realizaron análisis univariados por medio de proporciones para las variables cualitativas y medidas de tendencia central para las variables cuantitativas según la distribución. Resultados: Un total de 189 pacientes fueron analizados. El dolor fue el síntoma más frecuente en los pacientes (30.7%) y el principal signo encontrado fue una masa palpable en abdomen (9,5%). Los pacientes fueron sometidos a diferentes abordajes terapéuticos, la mayoría recibieron manejo paliativo no quirúrgico (52.9%) y la opción quirúrgica más usada en los pacientes fue la gastrectomía total (20.6%), y la subtotal (16,4) seguidas de quimioterapia y/o radiación perioperatoria. Los pacientes que sobrevivieron a los 2 años fueron 7,4% del total. Conclusiones: El registro de los pacientes con cáncer gástrico es bueno en el Méderi-Hospital Universitario Mayor es bueno y permite caracterizar los pacientes, la presentación de la patología y los resultados del tratamiento que concuerdan con los presentados en contextos similares en la literatura.

Spatial variability of satured soil hydraulic conductivity in the region of Araguaia River - Brazil.

This study evaluates the spatial variability of saturated hydraulic conductivity in the soil in an area of 51,850 ha at the headwaters of the Araguaia River MT/GO. This area is highly vulnerable because it is a location of recharging through natural water infiltration of the Guarani Aquifer System and an area of intense increases in agriculture since its adoption by growers in the last 30 years. Soil samples were collected at 383 points, geographically located by GPS. The samples were collected from depths of 0 - 20 cm and 60 - 80 cm. Exploratory statistics and box-plot were used in the descriptive analysis and semivariogram were constructed to determine the spatial model. The exploratory analysis showed that the mean hydraulic conductivity in the superficial layer was less than at the level of 60-80 cm; however, the greatest variability evaluated with a coefficient of variation also was from this layer. Data tended towards a normal distribution. These results can be explained by the greater soil compaction in the superficial layer. The semivariogram models, adjusted for the two layers, were exponential and demonstrated moderate and strong dependence, with ranges of 5000 and 3000 utm respectively. It was concluded that soil use is influencing the spatial distribution model of the hydraulic conductivity in the region.

Advanced Mission Synthesis Algorithms for Vibration-based Accelerated Life-testing

In the field of vibration qualification testing, with the popular Random Control mode of shakers, the specimen is excited by random vibrations typically set in the form of a Power Spectral Density (PSD). The corresponding signals are stationary and Gaussian, i.e. featuring a normal distribution. Conversely, real-life excitations are frequently non-Gaussian, exhibiting high peaks and/or burst signals and/or deterministic harmonic components. The so-called kurtosis is a parameter often used to statistically describe the occurrence and significance of high peak values in a random process. Since the similarity between test input profiles and real-life excitations is fundamental for qualification test reliability, some methods of kurtosis-control can be implemented to synthesize realistic (non-Gaussian) input signals. Durability tests are performed to check the resistance of a component to vibration-based fatigue damage. A procedure to synthesize test excitations which starts from measured data and preserves both the damage potential and the characteristics of the reference signals is desirable. The Fatigue Damage Spectrum (FDS) is generally used to quantify the fatigue damage potential associated with the excitation. The signal synthesized for accelerated durability tests (i.e. with a limited duration) must feature the same FDS as the reference vibration computed for the component’s expected lifetime. Current standard procedures are efficient in synthesizing signals in the form of a PSD, but prove inaccurate if reference data are non-Gaussian. This work presents novel algorithms for the synthesis of accelerated durability test profiles with prescribed FDS and a non-Gaussian distribution. An experimental campaign is conducted to validate the algorithms, by testing their accuracy, robustness, and practical effectiveness. Moreover, an original procedure is proposed for the estimation of the fatigue damage potential, aiming to minimize the computational time. The research is thus supposed to improve both the effectiveness and the efficiency of excitation profile synthesis for accelerated durability tests.

Assessing the fit of unidimensional IRT models for binary data under model misspecification

Model misspecification affects the classical test statistics used to assess the fit of the Item Response Theory (IRT) models. Robust tests have been derived under model misspecification, as the Generalized Lagrange Multiplier and Hausman tests, but their use has not been largely explored in the IRT framework. In the first part of the thesis, we introduce the Generalized Lagrange Multiplier test to detect differential item response functioning in IRT models for binary data under model misspecification. By means of a simulation study and a real data analysis, we compare its performance with the classical Lagrange Multiplier test, computed using the Hessian and the cross-product matrix, and the Generalized Jackknife Score test. The power of these tests is computed empirically and asymptotically. The misspecifications considered are local dependence among items and non-normal distribution of the latent variable. The results highlight that, under mild model misspecification, all tests have good performance while, under strong model misspecification, the performance of the tests deteriorates. None of the tests considered show an overall superior performance than the others. In the second part of the thesis, we extend the Generalized Hausman test to detect non-normality of the latent variable distribution. To build the test, we consider a seminonparametric-IRT model, that assumes a more flexible latent variable distribution. By means of a simulation study and two real applications, we compare the performance of the Generalized Hausman test with the M2 limited information goodness-of-fit test and the Likelihood-Ratio test. Additionally, the information criteria are computed. The Generalized Hausman test has a better performance than the Likelihood-Ratio test in terms of Type I error rates and the M2 test in terms of power. The performance of the Generalized Hausman test and the information criteria deteriorates when the sample size is small and with a few items.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

Multivariate analyses of variance and covariance for simulation studies involving normal time series

Photocopy.

Robust Mixture Modelling Using the t Distribution

Normal mixture models are being increasingly used to model the distributions of a wide variety of random phenomena and to cluster sets of continuous multivariate data. However, for a set of data containing a group or groups of observations with longer than normal tails or atypical observations, the use of normal components may unduly affect the fit of the mixture model. In this paper, we consider a more robust approach by modelling the data by a mixture of t distributions. The use of the ECM algorithm to fit this t mixture model is described and examples of its use are given in the context of clustering multivariate data in the presence of atypical observations in the form of background noise.

Modelling the distribution of stamp paper thickness via finite normal mixtures: The 1872 Hidalgo stamp issue of Mexico revisited

Izenman and Sommer (1988) used a non-parametric Kernel density estimation technique to fit a seven-component model to the paper thickness of the 1872 Hidalgo stamp issue of Mexico. They observed an apparent conflict when fitting a normal mixture model with three components with unequal variances. This conflict is examined further by investigating the most appropriate number of components when fitting a normal mixture of components with equal variances.

Quantitative distribution of parvalbumin, calretinin, and calbindin D-28k immunoreactive neurons in the visual cortex of normal and Alzheimer cases.

The distribution of parvalbumin (PV), calretinin (CR), and calbindin (CB) immunoreactive neurons was studied with the help of an image analysis system (Vidas/Zeiss) in the primary visual area 17 and associative area 18 (Brodmann) of Alzheimer and control brains. In neither of these areas was there a significant difference between Alzheimer and control groups in the mean number of PV, CR, or CB immunoreactive neuronal profiles, counted in a cortical column going from pia to white matter. Significant differences in the mean densities (numbers per square millimeter of cortex) of PV, CR, and CB immunoreactive neuronal profiles were not observed either between groups or areas, but only between superficial, middle, and deep layers within areas 17 and 18. The optical density of the immunoreactive neuropil was also similar in Alzheimer and controls, correlating with the numerical density of immunoreactive profiles in superficial, middle, and deep layers. The frequency distribution of neuronal areas indicated significant differences between PV, CR, and CB immunoreactive neuronal profiles in both areas 17 and 18, with more large PV than CR and CB positive profiles. There were also significantly more small and less large PV and CR immunoreactive neuronal profiles in Alzheimer than in controls. Our data show that, although the brain pathology is moderate to severe, there is no prominent decrease of PV, CR and CB positive neurons in the visual cortex of Alzheimer brains, but only selective changes in neuronal perikarya.

Meaning of the λ parameter of skew–normal and log–skew normal distributions in fluid geochemistry

The literature related to skew–normal distributions has grown rapidly in recent years but at the moment few applications concern the description of natural phenomena with this type of probability models, as well as the interpretation of their parameters. The skew–normal distributions family represents an extension of the normal family to which a parameter (λ) has been added to regulate the skewness. The development of this theoretical field has followed the general tendency in Statistics towards more flexible methods to represent features of the data, as adequately as possible, and to reduce unrealistic assumptions as the normality that underlies most methods of univariate and multivariate analysis. In this paper an investigation on the shape of the frequency distribution of the logratio ln(Cl−/Na+) whose components are related to waters composition for 26 wells, has been performed. Samples have been collected around the active center of Vulcano island (Aeolian archipelago, southern Italy) from 1977 up to now at time intervals of about six months. Data of the logratio have been tentatively modeled by evaluating the performance of the skew–normal model for each well. Values of the λ parameter have been compared by considering temperature and spatial position of the sampling points. Preliminary results indicate that changes in λ values can be related to the nature of environmental processes affecting the data