Prevalence of mixed neuropathologies in autopsied older adults and associations with clinical disease progression

Thesis (Ph.D.)--University of Washington, 2016-06

Caracterización sociodemográfica de las enfermedades huérfanas en Colombia

Las enfermedades huérfanas en Colombia, se definen como aquellas crónicamente debilitantes, que amenazan la vida, de baja prevalencia (menor 1/5000) y alta complejidad. Se estima que a nivel mundial existen entre 6000 a 8000 enfermedades raras diferentes(1). Varios países a nivel mundial individual o colectivamente, en los últimos años han creado políticas e incentivos para la investigación y protección de los pacientes con enfermedades raras. Sin embargo, a pesar del creciente número de publicaciones; la información sobre su etiología, fisiología, historia natural y datos epidemiológicos persiste escasa o ausente. Los registros de pacientes, son una valiosa herramienta para la caracterización de las enfermedades, su manejo y desenlaces con o sin tratamiento. Permiten mejorar políticas de salud pública y cuidado del paciente, contribuyendo a mejorar desenlaces sociales, económicos y de calidad de vida. En Colombia, bajo el decreto 1954 de 2012 y las resoluciones 3681 de 2013 y 0430 de 2013 se creó el fundamento legal para la creación de un registro nacional de enfermedades huérfanas. El presente estudio busca determinar la caracterización socio-demográfica y la prevalencia de las enfermedades huérfanas en Colombia en el periodo 2013. Métodos: Se realizó un estudio observacional de corte transversal de fuente secundaria sobre pacientes con enfermedades huérfanas en el territorio nacional; basándose en el registro nacional de enfermedades huérfanas obtenido por el Ministerio de Salud y Protección Social en el periodo 2013 bajo la normativa del decreto 1954 de 2012 y las resoluciones 3681 de 2013 y 0430 de 2013. Las bases de datos obtenidas fueron re-categorizadas en Excel versión 15.17 para la extracción de datos y su análisis estadístico posterior, fue realizado en el paquete estadístico para las ciencias sociales (SPSS v.20, Chicago, IL). Resultados: Se encontraron un total de 13173 pacientes con enfermedades huérfanas para el 2013. De estos, el 53.96% (7132) eran de género femenino y el 46.03% (6083) masculino; la mediana de la edad fue de 28 años con un rango inter-cuartil de 39 años, el 9% de los pacientes presentaron discapacidad. El registro contenía un total de 653 enfermedades huérfanas; el 34% del total de las enfermedades listadas en nuestro país (2). Las patologías más frecuentes fueron el Déficit Congénito del Factor VIII, Miastenia Grave, Enfermedad de Von Willebrand, Estatura Baja por Anomalía de Hormona de Crecimiento y Displasia Broncopulmonar. Discusión: Se estimó que aproximadamente 3.3 millones de colombianos debían tener una enfermedad huérfana para el 2013. El registro nacional logró recolectar datos de 13173 (0.4%). Este bajo número de pacientes, marca un importante sub-registro que se debe al uso de los códigos CIE-10, desconocimiento del personal de salud frente a las enfermedades huérfanas y clasificación errónea de los pacientes. Se encontraron un total de 653 enfermedades, un 34% de las enfermedades reportadas en el listado nacional de enfermedades huérfanas (2) y un 7% del total de enfermedades reportadas en ORPHANET para el periodo 2013 (3). Conclusiones: La recolección de datos y la sensibilización sobre las enfermedades huérfanas al personal de salud, es una estrategia de vital importancia para el diagnóstico temprano, medidas específicas de control e intervenciones de los pacientes. El identificar apropiadamente a los pacientes con este tipo de patologías, permite su ingreso en el registro y por ende mejora el sub-registro de datos. Sin embargo, cabe aclarar que el panorama ideal sería, el uso de un sistema de recolección diferente al CIE-10 y que abarque en mayor medida la totalidad de las enfermedades huérfanas.

Climate change impact assessment: Uncertainty modeling with imprecise probability

Hydrologic impacts of climate change are usually assessed by downscaling the General Circulation Model (GCM) output of large-scale climate variables to local-scale hydrologic variables. Such an assessment is characterized by uncertainty resulting from the ensembles of projections generated with multiple GCMs, which is known as intermodel or GCM uncertainty. Ensemble averaging with the assignment of weights to GCMs based on model evaluation is one of the methods to address such uncertainty and is used in the present study for regional-scale impact assessment. GCM outputs of large-scale climate variables are downscaled to subdivisional-scale monsoon rainfall. Weights are assigned to the GCMs on the basis of model performance and model convergence, which are evaluated with the Cumulative Distribution Functions (CDFs) generated from the downscaled GCM output (for both 20th Century [20C3M] and future scenarios) and observed data. Ensemble averaging approach, with the assignment of weights to GCMs, is characterized by the uncertainty caused by partial ignorance, which stems from nonavailability of the outputs of some of the GCMs for a few scenarios (in Intergovernmental Panel on Climate Change [IPCC] data distribution center for Assessment Report 4 [AR4]). This uncertainty is modeled with imprecise probability, i.e., the probability being represented as an interval gray number. Furthermore, the CDF generated with one GCM is entirely different from that with another and therefore the use of multiple GCMs results in a band of CDFs. Representing this band of CDFs with a single valued weighted mean CDF may be misleading. Such a band of CDFs can only be represented with an envelope that contains all the CDFs generated with a number of GCMs. Imprecise CDF represents such an envelope, which not only contains the CDFs generated with all the available GCMs but also to an extent accounts for the uncertainty resulting from the missing GCM output. This concept of imprecise probability is also validated in the present study. The imprecise CDFs of monsoon rainfall are derived for three 30-year time slices, 2020s, 2050s and 2080s, with A1B, A2 and B1 scenarios. The model is demonstrated with the prediction of monsoon rainfall in Orissa meteorological subdivision, which shows a possible decreasing trend in the future.

Meteorological Buoy Sensor Workshop, Solomons, Maryland, April 19-21, 2006: workshop proceedings

The co-organized Alliance for Coastal Technologies (ACT) and National Data Buoy Center (NDBC) Workshop "Meteorological Buoy Sensors Workshop" convened in Solomons, Maryland, April 19 to 21,2006, sponsored by the University of Maryland Center for Environmental Science (UMCES) Chesapeake Bay Laboratory (CBL), an ACT partner institution. Participants from various sectors including resource managers and industry representatives collaborated to focus on technologies and sensors that measure the near surface variables of wind speed and direction, barometric pressure, humidity and air temperature. The vendor list was accordingly targeted at companies that produced these types of sensors. The managers represented a cross section of federal, regional and academic marine observing interests from around the country. Workshop discussions focused on the challenges associated with making marine meteorological observations in general and problems that were specific to a particular variable. Discussions also explored methods to mitigate these challenges through the adoption of best practices, improved technologies and increased standardization. Some of the key workshop outcomes and recommendations included: 0cean.US should establish a committee devoted to observations. The committee would have a key role in developing observing standards. The community should adopt the target cost, reliability and performance standards drafted for a typical meteorological package to be used by a regional observing system. A forum should be established to allow users and manufacturers to share best practices for the employment of marine meteorological sensors. The ACT website would host the forum. Federal activities that evaluate meteorological sensors should make their results publicly available. ACT should extend their evaluation process to include meteorological sensors. A follow on workshop should be conducted that covers the observing of meteorological variables not addressed by this workshop. (pdf contains 18 pages)

Validation of RADARSAT-2 fully polarimetric SAR measurements of ocean surface waves

C band RADARSAT-2 fully polarimetric (fine quad-polarization mode, HH+VV+HV+VH) synthetic aperture radar (SAR) images are used to validate ocean surface waves measurements using the polarimetric SAR wave retrieval algorithm, without estimating the complex hydrodynamic modulation transfer function, even under large radar incidence angles. The linearly polarized radar backscatter cross sections (RBCS) are first calculated with the copolarization (HH, VV) and cross-polarization (HV, VH) RBCS and the polarization orientation angle. Subsequently, in the azimuth direction, the vertically and linearly polarized RBCS are used to measure the wave slopes. In the range direction, we combine horizontally and vertically polarized RBCS to estimate wave slopes. Taken together, wave slope spectra can be derived using estimated wave slopes in azimuth and range directions. Wave parameters extracted from the resultant wave slope spectra are validated with colocated National Data Buoy Center (NDBC) buoy measurements (wave periods, wavelengths, wave directions, and significant wave heights) and are shown to be in good agreement.

Presión arterial en preescolares de la localidad de Usaquén en Bogotá

Introducción: La hipertensión arterial es un problema de salud pública tanto en países industrializados como en vía de desarrollo. Su prevalencia en la infancia viene en aumento por lo que es relevante determinarla en niños preescolares a nivel local. Objetivo: Determinar la prevalencia de hipertensión arterial en niños de tres a cinco años de una cohorte de 14 hogares infantiles del ICBF de la localidad de Usaquén en Bogotá. Materiales y métodos: Se realizó un estudio de corte transversal analítico, utilizando la base de datos de un ensayo aleatorizado y controlado del año 200913, y se evaluaron las cifras de tensión arterial de acuerdo a sexo, edad, talla y su correlación con el IMC con un nivel de confianza del 95% y precisión del 1%. Se calcularon las medias, desviaciones estándar, percentiles y prevalencia. Resultados: Se obtuvo una muestra de 1035 casos, encontrándose una prevalencia de 4,5% de HTA sistólica, 10,4% de diastólica, ambas en estadio I; teniendo en cuenta tanto sistólica como diastólica, fue de 11,6% en estadio I. Se determinaron los valores de presión arterial sistólica y diastólica en cuartiles de acuerdo a edad, sexo y talla. El coeficiente de correlación entre el IMC y los niveles de presión arterial sistólica y diastólica fueron de 0.0992 y 0.0362 respectivamente. Conclusión: La prevalencia de HTA general fue de 11,6%, predominando la diastólica en estadio I en niños preescolares. No se encontró correlación entre el IMC y las cifras de tensión arterial sistólica y diastólica.

The combined influences of westerly phase of the quasi biennial oscillation and 11-year solar maximum conditions on the Northern Hemisphere extratropical winter circulation

The combined influences of the westerly phase of the quasi-biennial oscillation (QBO-W) and solar maximum (Smax) conditions on the Northern Hemisphere extratropical winter circulation are investigated using reanalysis data and Center for Climate System Research/National Institute for Environmental Studies chemistry climate model (CCM) simulations. The composite analysis for the reanalysis data indicates strengthened polar vortex in December followed by weakened polar vortex in February–March for QBO-W during Smax (QBO-W/Smax) conditions. This relationship need not be specific to QBO-W/Smax conditions but may just require strengthened vortex in December, which is more likely under QBO-W/Smax. Both the reanalysis data and CCM simulations suggest that dynamical processes of planetary wave propagation and meridional circulation related to QBO-W around polar vortex in December are similar in character to those related to Smax; furthermore, both processes may work in concert to maintain stronger vortex during QBO-W/Smax. In the reanalysis data, the strengthened polar vortex in December is associated with the development of north–south dipole tropospheric anomaly in the Atlantic sector similar to the North Atlantic oscillation (NAO) during December–January. The structure of the north–south dipole anomaly has zonal wavenumber 1 (WN1) component, where the longitude of anomalous ridge overlaps with that of climatological ridge in the North Atlantic in January. This implies amplification of the WN1 wave and results in the enhancement of the upward WN1 propagation from troposphere into stratosphere in January, leading to the weakened polar vortex in February–March. Although WN2 waves do not play a direct role in forcing the stratospheric vortex evolution, their tropospheric response to QBO-W/Smax conditions appears to be related to the maintenance of the NAO-like anomaly in the high-latitude troposphere in January. These results may provide a possible explanation for the mechanisms underlying the seasonal evolution of wintertime polar vortex anomalies during QBO-W/Smax conditions and the role of troposphere in this evolution.

Gulf of Mexico's Offshore Oil Platform Wind Potential

There are over 6000 natural resource drilling platforms in the Gulf of Mexico, all of which will become obsolete once their deposits are extracted. This study examined one of the possible alternate uses for these platforms, wind power potential. Using ArcGIS the number of platforms was reduced by weighting their distance from National Data Buoy Center wind speed collection points and water depth. Calculations were done to assess the optimal sites remaining, as well as provide an estimate of the energy potential for each site. Data for this project was obtained from the Minerals Management Service (MMS), United States Geological Service (USGS), and National Data Buoy Center (NDBC). A major limitation of this project was a lack of NDBC wind speed buoys, creating large data gaps and excluding many oil rigs that have otherwise high energy potential.