Este trabajo está financiado por el NIH subvención 1R03AI090465.

1. Obtención de datos <ol><li> Trayectoria de datos se pueden recoger con unidades GPS portátiles, GPS habilitados para aplicaciones de rastreo de teléfonos inteligentes, así como A-GPS (GPS asistido) dispositivos como el empleado en nuestro estudio, un dispositivo secundario de seguimiento comercial. </li><li> Trayectoria de datos se suelen guardar en términos de registros de tiempo de latitud y longitud. Un intervalo de tiempo deseado debe establecerse en función de las necesidades de la aplicación. A menudo, el intervalo más frecuente es deseado para estudios de actividad de espacio-tiempo. </li><li> Convertir los datos en valores separados por comas, o. Csv con columnas separadas para los ID de registro, la latitud, la longitud y el tiempo, respectivamente. A continuación, convertir los archivos. CSV en uso común Sistemas de Información Geográfica (SIG), el formato de archivo (por ejemplo ESRI shapefile 8). </li><li> Cargar en un archivo de formas de polígonos edificio y otro de la frontera de la zona de estudio con el analizador de trayectoria. Establecer la &quot;extrusión&quot; de los edificios propiamente para un di 3Dsplay y establecer la &quot;extrusión&quot; y &quot;transparencia&quot; de la capa límite bien para mostrar un cubo de espacio-tiempo 6, 9 con la x, Y Dimensiones representan el espacio y la dimensión z representa el tiempo. </li></ol> 2. Pre-procesamiento <ol><li> Hay dos opciones disponibles para el pre-procesamiento de los datos ruidosos trayectoria primas. Uno puede elegir de la lista desplegable del menú de pre-procesamiento. </li><li> Si &#39;interactivo&#39; que se elija, una proyección 2D de la trayectoria 3D es creado para facilitar la visualización y selección. Manipular la pantalla 3D para examinar la trayectoria de crudo en el espacio y el tiempo. Identificar errores en los datos sobre la base de la forma, la velocidad y / o la topología de segmentos de pista. Generalmente los puntos de track (vértices) con una velocidad poco realista alto o cambio de dirección brusco significar errores. Seleccione y librarlas de las trayectorias originales. Seleccione y eliminarlos ya sea de la trayectoria 3D o su proyección 2D. </li><li> Un grupo de puntos de track con punta shapes (Figura 1) espacial y temporal de larga duración significan los errores que más probablemente causados ​​por instalaciones interiores donde la señal GPS es débil. Si un grupo de estos puntos es seleccionado, el programa puede calcular el centroide espacio-temporal de los puntos seleccionados y ajustar la pista para ir a través del centroide. </li><li> Alternativamente, si &#39;Automatic&#39; se elige en el menú de pre-procesamiento, ajuste la entrada y ubicaciones de salida, así como parámetros empíricos que determinan la velocidad de giro anormal alta y abrupta de puntos. El programa busca a través de los datos de trayectoria cargadas y se ejecuta automáticamente sobre la base de un algoritmo que imita el enfoque de detección de error visual. </li></ol> 3. Trayectoria Segmentación y caracterización de la actividad espacial <ol><li> Trayectoria segmentación requiere la capa de edificios, garantizando así el archivo de forma edificio está cargado. </li><li> Haga clic en la herramienta de segmentación en la barra de herramientas para iniciar la función.Ajuste la entrada y salida y encuentra el archivo de formas de construcción como la capa de referencia. Utilice los nombres de los edificios para marcar la trayectoria segmentada. El algoritmo identifica segmentos interiores basados ​​en criterios establecidos por defecto o como la velocidad, duración, etc de puntos de seguimiento, así como la topología espacial con relación a los edificios. </li><li> Haga clic en el espacio de actividad herramienta de integración para cargar en trayectorias segmentadas y calcular los atributos seleccionados resumen para caracterizar un espacio de actividad, como la radio actividad total, el radio en un determinado periodo de tiempo, la proporción del tiempo total empleado en interiores frente al aire libre, y así sucesivamente. </li><li> Los atributos se pueden exportar a una hoja de cálculo para aplicaciones de modelado cuantitativo. </li></ol> 4. Densidad de mapeo de la superficie <ol><li> Superficie de densidad muestra la densidad de las actividades en el espacio con la dimensión temporal contraído. Hay tres opciones disponibles en la lista desplegable del menú de densidad de mapeo de la superficie. </li><li> Si la opción &quot;Densidad de pista punto &#39;se selecciona, rellene el cuadro de diálogo con información de entrada y salida y optar por mostrar, ya sea en 3D o 2D. Todos los vértices de los datos de trayectoria se utilizan para calcular las densidades del núcleo de los puntos. Figura 2 muestra una superficie de densidad. </li><li> Si la &quot;densidad ruta Track &#39;se activa, el algoritmo calcula y muestra la densidad de caminos individuales viajó (Figura 3). </li><li> Si la opción &#39;densidad Re-muestreo punto&#39; se activa, el algoritmo vuelve a las muestras de los datos de trayectoria utilizando un intervalo de tiempo y mapas de la densidad de puntos distribuidos uniformemente en el tiempo. Esta opción está diseñado para dispositivos de seguimiento que recogen puntos de seguimiento en intervalos de tiempo irregulares debido a la variación de sensibilidad de los dispositivos bajo diversas condiciones físicas o trayectorias segmentados. Figura 4 muestra las superficies de densidad 2D y 3D de trayectorias segmentados. </li><li> Si &#39;Temporal centrada&#39; es seleccionada para unny de las opciones anteriores, temporal enfoque 10 se realizó para examinar los patrones de actividad en períodos de tiempo diferentes. Por ejemplo, las superficies de densidad de actividad en diferentes momentos de un día se puede visualizar para una fácil identificación de los puntos calientes a través del tiempo (Figura 5). </li></ol> 5. Densidad Estimaciones Volumen y Volumen Rendering <ol><li> Densidad de visualización volumen utiliza la noción de un cubo de espacio-tiempo como en la visualización de trayectorias. El núcleo de la visualización de los tales es el desglose de los voxels en el espacio 11. Nuestro enfoque para la visualización de volumen densidad primero estima el volumen de densidad en voxels individuales mediante el recuento del número de pistas de espacio-tiempo que se cruzan con los vóxeles. Uno puede hacer clic en &quot;calcular el volumen de densidad&quot; en el menú de visualización densidad de volumen para este paso. </li><li> Los mismos tres opciones están disponibles para visualización densidad de volumen como para la visualización de la densidad superficial. </li><li> Haga clic en Next &#39;rendering de volumen&#39; para iniciar la interfaz volumen de visualización 3D para la renderización de volumen interactivo 12. Al establecer el número de divisiones a lo largo de cada eje, se pueden examinar las agrupaciones en diferentes escalas. Un z-factor se utiliza para establecer la exageración vertical para una mejor visualización. Una capa de referencia, tales como los edificios se pueden cargar a ayudar a la visualización también. Los resultados de la representación de volumen se puede ajustar interactivamente mediante la manipulación de la función de transferencia que controla la asignación de densidad de color. (Figura 6). </li></ol> 6. Otros análisis exploratorio de datos (EDA) y visualizaciones <ol><li> Un procedimiento está disponible para crear series de animación que se mostrará en Google Earth. En &#39;Otros&#39;, haga clic en &quot;Exportar a KML para EDA &#39;para acceder a este procedimiento. Se crea un archivo kml 13 que se abre en Google Earth para la animación interactiva de la trayectoria. </li><li> Se puede seguir la trayectoria a travel el entorno en tiempo de desplazamiento a lo largo de la línea de tiempo en Google Earth. </li><li> Un procedimiento está disponible para visualizar las conexiones entre los lugares de interés a través de &quot;análisis de Conexión &#39;. Por ejemplo, las conexiones entre los diferentes edificios en un campus de la universidad se derivan de datos de trayectoria segmentados que fueron recogidos por los estudiantes (Figura 7). </li><li> Sobre la base de las conexiones derivadas, puntos de acceso, como los edificios con más tráfico saliente o entrante y hubs que conectan los lugares con más tráfico para su identificación. </li></ol>

<ol>
	<li>Stoddard, S. T., Morrison, A. C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+role+of+human+movement+in+the+transmission+of+vector-borne+pathogens.">The role of human movement in the transmission of vector-borne pathogens.</a> PLoS Negl. Trop. Dis. 3 (7), e10 (2009).</li><li>Morens, D. M., Folkers, G. K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+challenge+of+emerging+and+re-emerging+infectious+diseases.">The challenge of emerging and re-emerging infectious diseases.</a> Nature. 430, 242-249 (2004).</li><li>Viboud, C., Bjornstad, O. N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Synchrony,+waves,+and+spatial+hierarchies+in+the+spread+of+influenza.">Synchrony, waves, and spatial hierarchies in the spread of influenza.</a> Science. 312, 447-451 (2006).</li><li>Shoval, N., Isaacson, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+Application+of+tracking+technologies+to+the+study+of+pedestrian+spatial+behaviour.">The Application of tracking technologies to the study of pedestrian spatial behaviour.</a> The Professional Geographer. 58 (2), 172-183 (2006).</li><li>Yu, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Spatio-temporal+GIS+design+for+exploring+interactions+of+human+activities.">Spatio-temporal GIS design for exploring interactions of human activities.</a> Cartography and Geographic Information Science. 33 (1), 3-19 (2006).</li><li>Kwan, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Interactive+geovisualization+of+activity-travel+patterns+using+three-dimensional+geographical+information+systems:+a+methodological+exploration+with+a+large+data+set.">Interactive geovisualization of activity-travel patterns using three-dimensional geographical information systems: a methodological exploration with a large data set.</a> Transportation Research Part C. 8, 185-203 (2000).</li><li>Dem&#353;ar, U., Virrantaus, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Space-time+density+of+trajectories:+exploring+spatio-temporal+patterns+in+movement+data.">Space-time density of trajectories: exploring spatio-temporal patterns in movement data.</a> International Journal of Geographical Information Science. 24 (10), 1527-1542 (2010).</li><li>Kraak, M., Koussoulakous, A., Fisher, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> A visualization environment for the space-time cube. , 189-200 (2004).</li><li>MacEachren, A. M., Polsky, C., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Visualizing+spatial+relationships+among+health,+environmental,+and+demographic+statistics:+interface+design+issues.">Visualizing spatial relationships among health, environmental, and demographic statistics: interface design issues.</a> , 880-887 (1997).</li><li>Levory, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Display+of+surfaces+from+volume+data.">Display of surfaces from volume data.</a> IEEE Computer Graphics and Application. 8 (5), 29-37 (1998).</li><li>Drebin, R. A., Carpenter, L., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Volume+Rendering.">Volume Rendering.</a> Computer Graphics. , (1998).</li><li>Lee, W., Krumm, J., Zheng, Y., Zhou, X. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Trajectory+preprocessing.">Trajectory preprocessing.</a> Computing with Spatial Trajectories. , 3-34 (2011).</li><li>Han, B., Comaniciu, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Sequential+kernel+density+approximation+and+its+application+to+real-time+visual+tracking.">Sequential kernel density approximation and its application to real-time visual tracking.</a> IEEE Transactions on Pattern Analysis and Machine Intelligence. , (2007).</li></ol>

No hay conflictos de interés declarado.

Se utilizó complemento en el mecanismo de ArcGIS para desarrollar la interfaz. Todas las operaciones se llevaron a cabo utilizando interactivas C + +. Todo el procesamiento automático y funciones de análisis se desarrollaron usando Python. AGPS datos, o los datos recogidos por GPS peatonal presenta desafío único en el preprocesamiento ya que los errores pueden ser masivas debido a la adyacencia a los edificios y las frecuentes paradas interiores. Además, el enfoque de procesamiento pre...

<table border="1"><tbody><tr><td> Nombre del reactivo </td><td> Empresa </td><td> Número de catálogo </td><td> Comentarios (opcional) </td></tr><tr><td> WorldTracker GPRS </td><td> Seguimiento del mundo </td><td></td><td></td></tr><tr><td> Una computadora personal para ejecutar el análisis </td><td></td><td></td><td></td></tr><tr><td> ArcGIS software </td><td> ESRI </td><td></td><td></td></tr><tr><td> Trayectoria Extensión Analizador </td><td></td><td></td><td></td></tr></tbody></table>

trajectory data analyses for pedestrian space-time activity study

Es bien reconocido que el movimiento humano en las dimensiones espacial y temporal tiene influencia directa en la transmisión de enfermedades 1-3. Una enfermedad infecciosa generalmente se propaga a través de contacto entre personas infectadas y susceptibles en sus espacios de actividad superpuestas. Por lo tanto, la movilidad cotidiana-actividad de información se puede utilizar como un indicador para medir la exposición a factores de riesgo de infección. Sin embargo, una dificultad importante y por lo tanto la razón de la escasez de estudios sobre la transmisión de enfermedades infecciosas a escala micro derivarse de la falta de datos detallados de movilidad individual. Anteriormente, en el transporte y el turismo detallados de la investigación del espacio-tiempo los datos de actividad a menudo se basó en la técnica de diario del tiempo-espacio, que requiere que los sujetos para registrar activamente sus actividades en el tiempo y el espacio. Esto es muy exigente para los participantes y la colaboración de los participantes afecta en gran medida la calidad de los datos 4. Modernotecnologías como el GPS y las comunicaciones móviles han hecho posible la recopilación automática de datos de trayectoria. Los datos recogidos, sin embargo, no es ideal para el modelado de humanos de espacio-tiempo, las actividades limitadas por la precisión de los dispositivos existentes. Tampoco hay una herramienta disponible para un procesamiento eficiente de los datos para estudiar el comportamiento humano. Presentamos aquí una serie de métodos y un sistema integrado de ArcGIS desktop basado en interfaz visual para el análisis de pre-procesamiento y espacio-temporal de los datos de trayectoria. Proporcionamos ejemplos de cómo este tratamiento se puede utilizar para modelar humanos del espacio-tiempo actividades, especialmente con error ricos en datos peatonales trayectoria, que podrían ser útiles en los estudios de salud pública tales como el modelado de la transmisión de enfermedades infecciosas. El procedimiento presentado incluye pre-procesamiento, segmentación de trayectoria, la caracterización de la actividad espacial, la estimación de la densidad y la visualización, y algunos otros métodos de análisis exploratorios. Pre-procesamieng es la limpieza de ruidosos datos de trayectoria primas. Se introduce una visual interactiva pre-procesamiento de interfaz, así como un módulo automático. Trayectoria 5 segmentación consiste en la identificación de las partes interiores y exteriores de pre-procesado de espacio-tiempo seco. Una vez más, tanto la segmentación interactiva visual y segmentación automática son compatibles. Segmentados de espacio-tiempo pistas se analizan luego para derivar características de espacio de la propia actividad tales como la estimación actividad radio de densidad, etc y la visualización se utilizan para examinar gran cantidad de datos de trayectoria para modelar los puntos calientes y las interacciones. Demostramos tanto mapeo de la superficie ganadera 6 y renderizado densidad de volumen 7. También incluimos un par de otros análisis de datos exploratorios (EDA) y las herramientas visuales reducidas, como el apoyo animación Google Earth y análisis conexión. El conjunto de análisis, así como métodos visuales presentados en este documento se pueden aplicar a los datos de trayectoria para stiempo-ritmo estudios de actividad.

Trayectoria datos fueron recogidos por el voluntariado a los estudiantes de pregrado de la Universidad de Kean (Nueva Jersey, EE.UU.) en la primavera de 2010. El objetivo fue estudiar los patrones de actividad de los estudiantes que contrajeron la gripe (diagnosticada por el médico o por cuenta propia diagnostica-) en comparación con aquellos que no lo hicieron. Con el fin de ilustrar los métodos y procedimientos presentados en este trabajo tomamos las trayectorias recogidas en la zona del campus suburbano de generar...

Watch this Scientific Journal Video about Trajectory Data Analyses for Pedestrian Space-time Activity Study at JoVE.com

Trajectory Data Analyses for Pedestrian Space-time Activity Study

Un conjunto de métodos de procesamiento espaciotemporales se presentan para analizar los datos de trayectoria humanos, tales como la recogida usando un dispositivo GPS, con el fin de modelar peatonales de espacio-tiempo actividades.

Los análisis de trayectoria de datos para el estudio de peatones Actividad espacio-tiempo

It is well recognized that human movement in the  spatial and temporal dimensions has direct influence on disease transmission1-3.  An infectious disease ...

trajectory-data-analyses-for-pedestrian-space-time-activity-study

Research

Education

JoVE Core

JoVE Journal

Civil Engineering

Biology

Unit 1

Global Positioning System (GPS)

SCIENTISTS IN ACTION

13.4K vistas.  Kean University. Un conjunto de métodos de procesamiento espaciotemporales se presentan para analizar los datos de trayectoria humanos, tales como la recogida usando un dispositivo GPS, con el fin de modelar peatonales de espacio-tiempo actividades.

Video: Trajectory Data Analyses for Pedestrian Space-time Activity Study

Testing Visual Sensitivity to the Speed and Direction of Motion in Lizards

Testing visual sensitivity in any species provides basic information regarding behaviour, evolution, and ecology. However, testing specific features of the visual system provide more empirical evidence for functional applications. Investigation into the sensory system provides information about the sensory capacity, learning and memory ability, and establishes known baseline behaviour in which to gauge deviations (Burghardt, 1977). However, unlike mammalian or avian systems, testing for learning and memory in a reptile species is difficult. Furthermore, using an operant paradigm as a psychophysical measure of sensory ability is likewise as difficult. Historically, reptilian species have responded poorly to conditioning trials because of issues related to motivation, physiology, metabolism, and basic biological characteristics. Here, I demonstrate an operant paradigm used a novel model lizard species, the Jacky dragon (Amphibolurus muricatus) and describe how to test peripheral sensitivity to salient speed and motion characteristics. This method uses an innovative approach to assessing learning and sensory capacity in lizards. I employ the use of random-dot kinematograms (RDKs) to measure sensitivity to speed, and manipulate the level of signal strength by changing the proportion of dots moving in a coherent direction. RDKs do not represent a biologically meaningful stimulus, engages the visual system, and is a classic psychophysical tool used to measure sensitivity in humans and other animals. Here, RDKs are displayed to lizards using three video playback systems. Lizards are to select the direction (left or right) in which they perceive dots to be moving. Selection of the appropriate direction is reinforced by biologically important prey stimuli, simulated by computer-animated invertebrates.

Testing visual sensitivity in lizards using an operant conditioning paradigm that employs video playback of random-dot kinematograms and computer-generated invertebrates.

Prueba de sensibilidad visual a la velocidad y dirección del movimiento en lagartos

Testing visual sensitivity in any species provides basic information regarding behaviour, evolution, and ecology. However, testing specific features of ...

Investigación

Biología

Computer-Generated Animal Model Stimuli

Communication between animals is diverse and complex. Animals may communicate using auditory, seismic, chemosensory, electrical, or visual signals. In particular, understanding the constraints on visual signal design for communication has been of great interest. Traditional methods for investigating animal interactions have used basic observational techniques, staged encounters, or physical manipulation of morphology. Less intrusive methods have tried to simulate conspecifics using crude playback tools, such as mirrors, still images, or models. As technology has become more advanced, video playback has emerged as another tool in which to examine visual communication (Rosenthal, 2000). However, to move one step further, the application of computer-animation now allows researchers to specifically isolate critical components necessary to elicit social responses from conspecifics, and manipulate these features to control interactions. Here, I provide detail on how to create an animation using the Jacky dragon as a model, but this process may be adaptable for other species. In building the animation, I elected to use Lightwave  3D to alter object morphology, add texture, install bones, and provide comparable weight shading that prevents exaggerated movement. The animation is then matched to select motor patterns to replicate critical movement features. Finally, the sequence must rendered into an individual clip for presentation. Although there are other adaptable techniques, this particular method had been demonstrated to be effective in eliciting both conspicuous and social responses in staged interactions.

Computer-generated stimuli using the Jacky dragon as a model.

Los estímulos generados por ordenador Modelo animal

Communication between animals is diverse and complex. Animals may communicate using auditory, seismic, chemosensory, electrical, or visual signals. In ...

Bioelectric Analyses of an Osseointegrated Intelligent Implant Design System for Amputees

The projected number of American amputees is expected to rise to 3.6 million by 2050.  Many of these individuals depend on artificial limbs to perform routine activities, but prosthetic suspensions using traditional socket technology can prove to be cumbersome and uncomfortable for a person with limb loss.  Moreover, for those with high proximal amputations, limited residual limb length may prevent exoprosthesis attachment all together. Osseointegrated implant technology is a novel operative procedure which allows firm skeletal attachment between the host bone and an implant. Preliminary results in European amputees with osseointegrated implants have shown improved clinical outcomes by allowing direct transfer of loads to the bone-implant interface.  Despite the apparent advantages of osseointegration over socket technology, the current rehabilitation procedures require long periods of restrictive load bearing prior which may be reduced with expedited skeletal attachment via electrical stimulation.  The goal of the osseointegrated intelligent implant design (OIID) system is to make the implant part of an electrical system to accelerate skeletal attachment and help prevent periprosthetic infection. To determine optimal electrode size and placement, we initiated proof of concept with computational modeling of the electric fields and current densities that arise during electrical stimulation of amputee residual limbs.  In order to provide insure patient safety, subjects with retrospective computed tomography scans were selected and three dimensional reconstructions were created using customized software programs to ensure anatomical accuracy (Seg3D and SCIRun) in an IRB and HIPAA approved study.  These software packages supported the development of patient specific models and allowed for interactive manipulation of electrode position and size. Preliminary results indicate that electric fields and current densities can be generated at the implant interface to achieve the homogenous electric field distributions   required to induce osteoblast migration, enhance skeletal fixation and may help prevent periprosthetic infections.  Based on the electrode configurations experimented with in the model, an external two band configuration will be advocated in the future.

There is a need to develop alternative prosthesis attachment due to limb loss attributed to vascular occlusive diseases and trauma. The goal of the work is to introduce an osseointegrated intelligent implant design system to increase skeletal fixation and reduce periprosthetic infection rates for patients needing osseointegrated technology.

Los análisis bioeléctricos de una osteointegrados Sistema Inteligente diseño de los implantes para Amputados

The projected number of American amputees is expected to rise to 3.6 million by 2050.  Many of these individuals depend on artificial limbs to perform ...

Isolation and Purification of Drosophila Peripheral Neurons by Magnetic Bead Sorting

The Drosophila peripheral nervous system (PNS) is a powerful model for investigating the complex processes of neuronal development and dendrite morphogenesis at the functional and molecular levels. To aid in these analyses, we have developed a strategy for the isolation of a subclass of PNS neurons called dendritic arborization (da) neurons that have been widely used for studying dendrite morphogenesis1,2. These neurons are very difficult to isolate as a pure population, due in part to their extremely low occurrence and their difficult-to-reach location below the tough chitinous larval cuticle. Our newly developed method overcomes these challenges, and is based on a fast and specific cell enrichment using antibody-coated magnetic beads. For our magnetic bead sorting studies, we have used age-matched third instar larvae expressing a mouse CD8 tagged GFP fusion protein (UAS-mCD8-GFP)3 under the control of either the class IV dendritic arborization (da) neuron-specific pickpocket (ppk)-GAL4 driver4 or the control of the pan-da neuron-specific GAL421-7 driver5. Although this protocol has been optimized for isolating PNS cells which are attached to the inner wall of the larval cuticle, by varying a few parameters, the same protocol could be used to isolate many different cell types attached to the cuticle at larval or pupal stages of development (e.g. epithelia, muscle, oenocytes etc.), or other cell types from larval organs depending upon the GAL4-specific driver expression pattern. The RNA isolated by this method is of high quality and can be readily used for downstream genomic analyses such as microarray gene expression profiling studies. This approach offers a powerful new tool to perform studies on isolated Drosophila dendritic arborization (da) neurons thereby providing novel insights into the molecular mechanisms underlying dendrite morphogenesis.

Isolation and Purification of Drosophila Peripheral Neurons by Magnetic Bead Sorting

In this video-article we present a method for the isolation and purification of Drosophila peripheral neurons using a fast magnetic bead assisted cell sorting strategy. RNA obtained from the isolated cells can be readily used for downstream applications including microarray analyses.

Aislamiento y purificación de Drosophila Clasificación de las neuronas periféricas por bolas magnéticas

The Drosophila peripheral nervous system (PNS) is a powerful model for investigating the complex processes of neuronal development and dendrite ...

Evisceration of Mouse Vitreous and Retina for Proteomic Analyses

While the mouse retina has emerged as an important genetic model for inherited retinal disease, the mouse vitreous remains to be explored. The vitreous is a highly aqueous extracellular matrix overlying the retina where intraocular as well as extraocular proteins accumulate during disease.1-3 Abnormal interactions between vitreous and retina underlie several diseases such as retinal detachment, proliferative diabetic retinopathy, uveitis, and proliferative vitreoretinopathy.1,4 The relative mouse vitreous volume is significantly smaller than the human vitreous (Figure 1), since the mouse lens occupies nearly 75% of its eye.5 This has made biochemical studies of mouse vitreous challenging. In this video article, we present a technique to dissect and isolate the mouse vitreous from the retina, which will allow use of transgenic mouse models to more clearly define the role of this extracellular matrix in the development of vitreoretinal diseases.

The dissection technique illustrates evisceration of the vitreous, retina, and lens from the mouse eye, separation by centrifugation, and characterization with protein assays.

Evisceración de vítreo y retina del ratón para análisis proteómico

While the mouse retina has emerged as an important genetic model for inherited retinal disease, the mouse vitreous remains to be explored. The vitreous is ...

Do-It-Yourself Device for Recovery of Cryopreserved Samples Accidentally Dropped into Cryogenic Storage Tanks

Liquid nitrogen is colorless, odorless, extremely cold (-196 &deg;C) liquid kept under pressure. It is commonly used as a cryogenic fluid for long term storage of biological materials such as blood, cells and tissues 1,2. The cryogenic nature of liquid nitrogen, while ideal for sample preservation, can cause rapid freezing of live tissues on contact - known as 'cryogenic burn'2, which may lead to severe frostbite in persons closely involved in storage and retrieval of samples from Dewars. Additionally, as liquid nitrogen evaporates it reduces the oxygen concentration in the air and might cause asphyxia, especially in confined spaces2.
In laboratories, biological samples are often stored in cryovials or cryoboxes stacked in stainless steel racks within the Dewar tanks1. These storage racks are provided with a long shaft to prevent boxes from slipping out from the racks and into the bottom of Dewars during routine handling. All too often, however, boxes or vials with precious samples slip out and sink to the bottom of liquid nitrogen filled tank. In such cases, samples could be tediously retrieved after transferring the liquid nitrogen into a spare container or discarding it. The boxes and vials can then be relatively safely recovered from emptied Dewar. However, the cryogenic nature of liquid nitrogen and its expansion rate makes sunken sample retrieval hazardous. It is commonly recommended by Safety Offices that sample retrieval be never carried out by a single person. Another alternative is to use commercially available cool grabbers or tongs to pull out the vials3. However, limited visibility within the dark liquid filled Dewars poses a major limitation in their use.
In this article, we describe the construction of a Cryotolerant DIY retrieval device, which makes sample retrieval from Dewar containing cryogenic fluids both safe and easy.

Here we present a low cost, durable cryotolerant device for sample retrieval from Dewar tanks filled with liquid nitrogen. The ease of construction and modular design of the device makes the process of sample retrieval from cryogenic tanks safe and easy.

Do-It-Yourself de dispositivos para la recuperación de las muestras criopreservadas de caída accidental en los tanques de almacenamiento criogénicos

Liquid nitrogen is colorless, odorless, extremely cold (-196 &deg;C) liquid kept under pressure. It is commonly used as a cryogenic fluid for long term ...

Improved Swiss-rolling Technique for Intestinal Tissue Preparation for Immunohistochemical and Immunofluorescent Analyses

Understanding the role of factors that regulate intestinal epithelial homeostasis and response to injury and regeneration is important. The current literature describes several different methodological approaches to obtain images of intestinal tissues for data validation. In this paper, we delineate a common protocol relating to the derivation and processing of mouse intestinal tissues. Proper fixation of intestinal tissues and Swiss-roll techniques that enhance intestinal epithelial morphology are discussed. Postresection processing and reorientation of embedded intestinal tissues are critical in obtaining paraffin-embedded blocks that display intact intestinal structural features after sectioning. The Swiss-rolling technique helps in histological assessment of the complete intestinal or colonic sections examined. An ability to differentiate intestinal structural features can be vital in quantitative measurements of intestinal inflammation and tumorigenesis along the entire length. Finally, paraffin-embedded sections are ideal for robust processing using both immunohistochemical and immunofluorescent detection methods. Nonfluorescent immunohistochemical sections provide a vibrant image of the tissue detailing different cellular structural features but do not provide flexibility for intracellular co-localization experiments. Multiple fluorescent channels can be appropriately utilized with immunofluorescent detection for co-localization experiments, lending support to mechanistic studies.

Accurate identification and location of epithelial cells along the intestinal mucosal lining are essential to define different cell lineages. Proper imaging of intestinal tissues is crucial for identification of protein expression patterns with maximum resolution. This study aims to delineate the optimal methods and conditions for processing mouse intestinal tissues.

Mejora Técnica Swiss-laminación para la preparación del tejido intestinal para inmunohistoquímica y análisis de inmunofluorescencia

Understanding the role of factors that regulate intestinal epithelial homeostasis and response to injury and regeneration is important. The current ...

In Vitro SUMOylation Assay to Study SUMO E3 Ligase Activity

Small ubiquitin-like modifier (SUMO) modification is an important post-translational modification (PTM) that mediates signal transduction primarily through modulating protein-protein interactions. Similar to ubiquitin modification, SUMOylation is directed by a sequential enzyme cascade including E1-activating enzyme (SAE1/SAE2), E2-conjugation enzyme (Ubc9), and E3-ligase (i.e., PIAS family, RanBP2, and Pc2). However, different from ubiquitination, an E3 ligase is non-essential for the reaction but does provide precision and efficacy for SUMO conjugation. Proteins modified by SUMOylation can be identified by in vivo assay via immunoprecipitation with substrate-specific antibodies and immunoblotting with SUMO-specific antibodies. However, the demonstration of protein SUMO E3 ligase activity requires in vitro reconstitution of SUMOylation assays using purified enzymes, substrate, and SUMO proteins. Since in the in vitro reactions, usually SAE1/SAE2 and Ubc9, alone are sufficient for SUMO conjugation, enhancement of SUMOylation by a putative E3 ligase is not always easy to detect. Here, we describe a modified in vitro SUMOylation protocol that consistently identifies SUMO modification using an in vitro reconstituted system. A step-by-step protocol to purify catalytically active K-bZIP, a viral SUMO-2/3 E3 ligase, is also presented. The SUMOylation activities of the purified K-bZIP are shown on p53, a well-known target of SUMO. This protocol can not only be employed for elucidating novel SUMO E3 ligases, but also for revealing their SUMO paralog specificity.

In Vitro SUMOylation Assay to Study SUMO E3 Ligase Activity

Unlike ubiquitin ligases, few E3 SUMO ligases have been identified. This modified in vitro SUMOylation protocol is able to identify novel SUMO E3 ligases by an in vitro reconstitution assay.

In Vitro Ensayo de la sumoilación estudiar SUMO E3 ligasa actividad

Small ubiquitin-like modifier (SUMO) modification is an important post-translational modification (PTM) that mediates signal transduction primarily ...

Application of Electrophysiology Measurement to Study the Activity of Electro-Neutral Transporters

The transport of ions through cell membranes ensures the fine control of ion content within and outside the cell that is indispensable for cell survival. These transport mechanisms are mediated by the activities of specialized transporter proteins. Specifically,pH dynamics are finely controlled by plasma membrane proton (H+) extrusion systems, such as the Na+/H+ exchanger (NHE) protein family. Despite extensive efforts to study the mechanisms underlying NHE regulation, our current understanding of the biophysical and molecular properties of the NHE family is inadequate because of the limited availability of methods to effectively measure NHE activity. In this manuscript, we used H+-selective electrodes during whole-cell patch clamping recording to measure NHE-induced H+ flux. We proposed this approach to overcome some limitations of typically used methods to measure NHE activity, such as radioactive uptake and fluorescent membrane permeants. Measurement of NHE activity using the described method enables high sensitivity and time resolution and more efficient control of intracellular H+ concentrations. H+-selective electrodes are based on the fact that transporter activity creates an ion gradient in close proximity to the cell membrane. An H+-selective electrode moving up to and away from the cell membrane in a repetitive, oscillatory fashion records a voltage difference that is dependent on H+ flux. While H+-selective electrodes are used to detect H+ flux moving out of the cell, the patch clamp method in the whole-cell configuration is used to control the intracellular ion composition. Moreover, application of the giant patch clamp technique allows modification of the intracellular composition of not only ions but also lipids. The transporter activity of NHE isoform 3 (NHE3) was measured using this technical approach to study the molecular basis of NHE3 regulation by phosphoinositides.

This manuscript describes the applications of proton-selective electrodes and patch clamping methods to measure the activity of proton transport systems. These methods overcome some limitations of techniques commonly used to study proton transport activity, such as moderate sensitivity, time resolution and insufficient intracellular milieu control.

Aplicación de medición de electrofisiología para estudiar la actividad de transportadores de Electro-neutro

The transport of ions through cell membranes ensures the fine control of ion content within and outside the cell that is indispensable for cell survival. ...

Tissue Collection of Bats for -Omics Analyses and Primary Cell Culture

As high-throughput sequencing technologies advance, standardized methods for high quality tissue acquisition and preservation allow for the extension of these methods to non-model organisms. A series of protocols to optimize tissue collection from bats has been developed for a series of high-throughput sequencing approaches. Outlined here are protocols for the capture of bats, desired demographics to be collected for each bat, and optimized methods to minimize stress on a bat during tissue collection. Specifically outlined are methods for collecting and treating tissue to obtain (i) DNA for high molecular weight genomic analyses, (ii) RNA for tissue-specific transcriptomes, and (iii) proteins for proteomic-level analyses. Lastly, also outlined is a method to avoid lethal sampling by creating viable primary cell cultures from wing clips. A central motivation of these methods is to maximize the amount of potential molecular and morphological data for each bat and suggest optimal ways to preserve tissues so they retain their value as new methods develop in the future. This standardization has become particularly important as initiatives to sequence chromosome-level, error-free genomes of species across the world have emerged, in which multiple scientific parties are spearheading the sequencing of different taxonomic groups. The protocols outlined herein define the ideal tissue collection and tissue preservation methods for Bat1K, the consortium that is sequencing the genomes of every species of bat.

This is a protocol for the optimal tissue preparation for genomic, transcriptomic, and proteomic analyses of bats caught in the wild. It includes protocols for bat capture and dissection, tissue preservation, and cell culturing of bat tissue.

Colección de tejidos de murciélagos para análisis de émica y cultivo celular primario

As high-throughput sequencing technologies advance, standardized methods for high quality tissue acquisition and preservation allow for the extension of ...