LeafJ fue escrito por JNM mientras estaba en su año sabático en el laboratorio de la Dra. Katherine Pollard en los Institutos Gladstone. Este trabajo fue apoyado por una beca de la Fundación Nacional de Ciencia (número de concesión IOS-0923752).

1. Materiales vegetales Tenga en cuenta que este protocolo tiene como objetivo el crecimiento de plantas para la detección de tono de respuesta de evitación. Usted puede crecer las plantas en su condición de favorito. <ol><li> Espolvorear semillas de Arabidopsis thaliana en el agua empapados papeles de filtro en placas de Petri de 9 cm y almacén (estratificar) los a 4 ° C durante cuatro días en la oscuridad. </li><li> Transfiera estas placas de Petri para condiciones de sol simulados: 80-100 μE radiación fotosintéticamente activa (PAR) y suplemento rojo lejano para llevar el R: FR proporción a 1,86. Utilice las condiciones de día largo (16 h de luz / 8 h oscuridad) y temperatura constante de 22 º C. Incubar en este estado durante tres días para permitir que las semillas germinen. </li><li> Traslado de semillas germinadas en el suelo y mantener las plantas en condiciones dom. Para los experimentos a gran escala, se recomienda la preparación de pequeñas etiquetas para etiquetar cada una las plantas mediante el uso de datos Administrador de combinación de Microsoft Word 2004 (o posterior) para la fabricación de etiquetas. </li><li> Once días después de transfer al suelo, mover la mitad de las plantas a condiciones de sombra: lo mismo que sol, pero con suplemento luz roja lejana para que la relación R / FR a 0,52. </li><li> Después de un período adicional de doce días, las plantas están listas para la formación de imágenes hoja. En esta etapa, las hojas más viejas han madurado completamente, mientras que las hojas más jóvenes están todavía en expansión, por lo que permite capturar una instantánea del desarrollo. Es posible que desee elegir un momento diferente de desarrollo en función de sus necesidades. </li></ol> 2. La captura de imágenes disecados Leaf <ol><li> Prepare hojas de transparencias marcados con genotipo de la planta y las condiciones de crecimiento con cinco marcos rectangulares. Un cuadro corresponde a las hojas de una planta. Microsoft Excel puede ser utilizado para imprimir una rejilla coherente con las etiquetas. </li><li> Diseccionar hojas de las plantas veintiséis días de edad. </li><li> Scan sale a 600 ppp en un escáner de cama plana. Tenga en cuenta que las hojas de una planta se debe colocar verticalmente dentro de una ventana de color negro en un sándwich de láminas transparentes. Evite tocar las hojasa un marco de ventana de color negro y las hojas se solapan, lo que dará errores en los procedimientos siguientes. </li></ol> 3. Hoja de Análisis de Imágenes por LeafJ <ol><li> Descargar ImageJ Arrastre el archivo LeafJ.jar en la carpeta plugins de ImageJ. </li><li> Abra un archivo de imagen en ImageJ 1.45s ó 14 después. </li><li> Dividir la imagen en tres canales de color (rojo, verde, y azul) por &quot;Color&gt;&gt; Canales de split&quot; y aplicar umbral a la imagen en el canal azul. </li><li> Seleccionar todas las hojas de una planta con una herramienta rectángulo (Figura 1A). </li><li> Seleccione &quot;LeafJ&quot; del menú plugin. </li><li> Seleccione información de anotación para esta planta desde el cuadro de diálogo que aparece. Usted puedeeditar los valores predeterminados que aparecen aquí haciendo clic en &quot;editar estas opciones&quot;. </li><li> Después de ejecutar plugins LeafJ y antes de hacer clic en &quot;OK&quot;, editar líneas trazadas desde la región de la ventana del administrador de interés (ROI) (si es necesario; fig. 1B). Una tableta con pantalla táctil (como el iPad) es útil para este procedimiento. iPads se puede conectar a un ordenador y un monitor externo usando software Air Display. </li><li> Exportación de resultados de las mediciones y la información asociada (nombres de archivo, tiempo de floración, disectadas por, medidos por, etc) para Microsoft Excel o software equivalente. </li></ol> 4. Célula de la hoja de análisis de imágenes ImageJ en <ol><li> Fijar diseccionado hojas como se describe en la referencia 15 después de la digitalización (paso 2). FAA hojas fijas se pueden mantener en 4 ° C durante al menos 6 meses. </li><li> Limpiar las hojas cambiando fijador FAA para solución hidrato de cloral y las hojas se incuban durante 1 ~ 2 horas antes de la observación microscópica 15. </li><li> Mount deja en micopio desliza con tricomas hacia arriba. Uso de un aumento de 40x en un microscopio compuesto, la imagen de la capa de mesófilo el centro de cada hoja en cada lado de la vena principal, evitando las células cerca de tricomas o venas. </li><li> Célula de seguimiento hoja describe por la herramienta de ImageJ gerente ROI con la ayuda de la tableta de la pantalla táctil y un lápiz óptico (como se describe en el paso 3). Análisis de imagen celular utiliza las funciones incorporadas de ImageJ, pero no requiere LeafJ. </li></ol>

<ol>
	<li>Furbank, R. T., Tester, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Phenomics--technologies+to+relieve+the+phenotyping+bottleneck.">Phenomics--technologies to relieve the phenotyping bottleneck.</a> Trends Plant Sci. 16, 635-644 (2011).</li><li>Berger, B., Parent, B., Tester, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-throughput+shoot+imaging+to+study+drought+responses.">High-throughput shoot imaging to study drought responses.</a> J. Exp. Bot. 61, 3519-3528 (2010).</li><li>Borevitz, J. O. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Natural+genetic+variation+for+growth+and+development+revealed+by+high-throughput+phenotyping+in+Arabidopsis+thaliana.">Natural genetic variation for growth and development revealed by high-throughput phenotyping in Arabidopsis thaliana.</a> G3 (Bethesda). 2, 29-34 (2012).</li><li>Albrecht, D. R., Bargmann, C. I. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=High-content+behavioral+analysis+of+Caenorhabditis+elegans+in+precise+spatiotemporal+chemical+environments.">High-content behavioral analysis of Caenorhabditis elegans in precise spatiotemporal chemical environments.</a> Nat. Methods. 8, 599-605 (2011).</li><li>Chitwood, D. H., 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=Native+environment+modulates+leaf+size+and+response+to+simulated+foliar+shade+across+wild+tomato+species.">Native environment modulates leaf size and response to simulated foliar shade across wild tomato species.</a> PLoS ONE. 7, e29570 (2012).</li><li>Chitwood, D. H., 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+developmental+trajectory+of+leaflet+morphology+in+wild+tomato+species.">The developmental trajectory of leaflet morphology in wild tomato species.</a> Plant Physiol. 158, 1230-1240 (2012).</li><li>Casal, J. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Shade+Avoidance.">Shade Avoidance.</a> The Arabidopsis Book. , e0157 (2012).</li><li>Smith, H., Kendrick, R. E., Kronenberg, G. H. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=.">.</a> Photomorphogenesis in Plants. , 377-416 (1994).</li><li>Iwata, H., Ukai, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=SHAPE:+a+computer+program+package+for+quantitative+evaluation+of+biological+shapes+based+on+elliptic+Fourier+descriptors.">SHAPE: a computer program package for quantitative evaluation of biological shapes based on elliptic Fourier descriptors.</a> J. Hered. 93, 384-385 (2002).</li><li>Bylesjo, M., 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=LAMINA:+a+tool+for+rapid+quantification+of+leaf+size+and+shape+parameters.">LAMINA: a tool for rapid quantification of leaf size and shape parameters.</a> BMC Plant Biol. 8, 82 (2008).</li><li>Weight, C., Parnham, D., Waites, R. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=LeafAnalyser:+a+computational+method+for+rapid+and+large-scale+analyses+of+leaf+shape+variation.">LeafAnalyser: a computational method for rapid and large-scale analyses of leaf shape variation.</a> Plant J. 53, 578-586 (2008).</li><li>Backhaus, A., 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=LEAFPROCESSOR:+a+new+leaf+phenotyping+tool+using+contour+bending+energy+and+shape+cluster+analysis.">LEAFPROCESSOR: a new leaf phenotyping tool using contour bending energy and shape cluster analysis.</a> New Phytol. 187, 251-261 (2010).</li><li>Tsukaya, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Mechanisms+of+Leaf-shape+determination.">Mechanisms of Leaf-shape determination.</a> Annual Review of Plant Biology. 57, 477-496 (2006).</li><li>Abramoff, M. D., Magalhaes, P. J., Ram, S. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Image+Processing+with+ImageJ.">Image Processing with ImageJ.</a> Biophotonics International. 11, 36-42 (2004).</li><li>Horiguchi, G., Fujikura, U., Ferjani, A., Ishikawa, N., Tsukaya, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Large-scale+histological+analysis+of+leaf+mutants+using+two+simple+leaf+observation+methods:+identification+of+novel+genetic+pathways+governing+the+size+and+shape+of+leaves.">Large-scale histological analysis of leaf mutants using two simple leaf observation methods: identification of novel genetic pathways governing the size and shape of leaves.</a> Plant. J. 48, 638-644 (2006).</li><li>Horiguchi, G., Ferjani, A., Fujikura, U., Tsukaya, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Coordination+of+cell+proliferation+and+cell+expansion+in+the+control+of+leaf+size+in+Arabidopsis+thaliana.">Coordination of cell proliferation and cell expansion in the control of leaf size in Arabidopsis thaliana.</a> J. Plant. Res. 119, 37-42 (2006).</li><li>Pierik, R., de Wit, M., Voesenek, L. A. C. J. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Growth-mediated+stress+escape:+convergence+of+signal+transduction+pathways+activated+upon+exposure+to+two+different+environmental+stresses.">Growth-mediated stress escape: convergence of signal transduction pathways activated upon exposure to two different environmental stresses.</a> New. Phytol. 189, 122-134 (2011).</li></ol>

No hay conflictos de interés declarado.

Nuestro &quot;LeafJ&quot; plugin permite la medición de la longitud del pecíolo semi-automáticamente, aumentando el rendimiento casi 6 veces la medición manual. Longitud del peciolo es un índice importante de SAS y es también un punto de referencia de otros fenómenos, como la resistencia a la inmersión y el crecimiento hyponastic 17. Por lo tanto este plugin puede ser útil para una amplia gama de investigadores de la planta. Nuestro plugin se ejecuta en un sistema bien es...

<html><table border="1"><tbody><tr><td> Nombre del reactivo </td><td> Empresa </td><td> Número de catálogo </td><td></td></tr><tr><td> la luz roja lejana LED </td><td> Orbitec </td><td> encargo </td><td></td></tr><tr><td> transparencia </td><td> IKON </td><td> HSCA / 5 </td><td></td></tr><tr><td> escáner </td><td> Epson </td><td> Epson Perfection V700 Photo </td><td></td></tr><tr><td> Image J </td><td> NIH </td><td></td><td> <a href="http://rsbweb.nih.gov/ij/" target="_blank">http://rsbweb.nih.gov/ij/</a> </td></tr><tr><td> LeafJ </td><td> costumbre </td><td></td><td> <a href="http://www.openwetware.org/wiki/Maloof_Lab" target="_blank">http://www.openwetware.org/wiki/Maloof_Lab</a> </td></tr><tr><td> Air Display </td><td> Avatron Software Inc. </td><td></td><td>blank &quot;&gt; http://avatron.com/ </td></tr><tr><td> iPad 2 </td><td> Apple Inc. </td><td></td><td> <a href="http://www.apple.com/" target="_blank">http://www.apple.com/</a> </td></tr></tbody></table>

leafj: an imagej plugin for semi-automated leaf shape measurement

Fenotipado de alto rendimiento (phenomics) es una herramienta poderosa para la vinculación de genes a sus funciones (véase la revisión 1 y ejemplos recientes 2-4). Las hojas son el órgano fotosintética primaria, y su tamaño y forma pueden variar de desarrollo y el medio ambiente dentro de una planta. Por estas razones, los estudios sobre morfología de las hojas requieren la medición de varios parámetros de numerosas hojas, que no hay nada mejor semi-herramientas automatizadas phenomics 5,6. Sombra Canopy es una señal importante del medio ambiente que afecta a la arquitectura de planta y la historia de vida, el conjunto de las respuestas se conocen colectivamente como el síndrome de evitación sombra (SAS) 7. Entre las respuestas de SAS, sombra hoja inducida alargamiento pecíolo y los cambios en la zona de la cuchilla son particularmente útiles como índices 8. Hasta la fecha, los programas de hoja de forma (por ejemplo, forma 9, lámina 10, LeafAnalyzer 11, LEAFPROCESSOR 12) se pueden medir los contornos de hojas y categorizar formas de hojas, Pero no puede dar salida a la longitud del pecíolo. La falta de sistemas de medición a gran escala de los pecíolos de las hojas ha inhibido enfoques phenomics a SAS investigación. En este trabajo se describe un nuevo desarrollo de plug-ImageJ, llamado LeafJ, que rápidamente se puede medir la longitud del pecíolo y los parámetros de láminas foliares de la planta modelo Arabidopsis thaliana. Para la hoja ocasional que la corrección manual requerido de la frontera hoja peciolo / hoja se utilizó una tableta de pantalla táctil. Además, la forma de la hoja móvil y el número de hojas móviles son determinantes importantes del tamaño de la hoja 13. A parte de LeafJ también presentamos un protocolo para el uso de una tableta con pantalla táctil para la medición de la forma celular, el área y tamaño. Nuestro rasgo hoja sistema de medición no se limita a la investigación de evitar la sombra y acelerará fenotipificación hoja de muchos mutantes y plantas de detección por fenotipificación hoja.

1. Imágenes de hoja que muestra estimaciones del pecíolo y lámina de la hoja de Fronteras, y su ventana de medición Una de las características más útiles de LeafJ es la detección automática de la hoja de cuchilla / pecíolo límite (Figura 1). El algoritmo LeafJ funciona como sigue: la incorporada en el ImageJ funcionalidad ParticleAnalyzer se utiliza para buscar y determinar la orientación de las hojas en el interior de la selección del usuario. Para cada hoja de la...

Watch this Scientific Journal Video about LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement at JoVE.com

LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement

Demostración de métodos clave para la alta mediciones de rendimiento de hoja. Estos métodos se pueden utilizar para acelerar fenotipificación hoja al estudiar muchos mutantes de plantas o de otra manera las plantas de selección por fenotipo hoja.

LeafJ: Un Plugin para ImageJ Semi-automático Medición Hoja Forma

High throughput phenotyping (phenomics) is a powerful tool for linking genes to their functions (see review1 and recent examples2-4). Leaves are the ...

leafj-an-imagej-plugin-for-semi-automated-leaf-shape-measurement

Research

JoVE Journal

Biology

28.1K vistas.  University of California Davis. Demostración de métodos clave para la alta mediciones de rendimiento de hoja. Estos métodos se pueden utilizar para acelerar fenotipificación hoja al estudiar muchos mutantes de plantas o de otra manera las plantas de selección por fenotipo hoja.

Video: LeafJ: An ImageJ Plugin for Semi-automated Leaf Shape Measurement

Semi-automated Optical Heartbeat Analysis of Small Hearts

We have developed a method for analyzing high speed optical recordings from Drosophila, zebrafish and embryonic mouse hearts (Fink, et. al., 2009). Our Semi-automatic Optical Heartbeat Analysis (SOHA) uses a novel movement detection algorithm that is able to detect cardiac movements associated with individual contractile and relaxation events. The program provides a host of physiologically relevant readouts including systolic and diastolic intervals, heart rate, as well as qualitative and quantitative measures of heartbeat arrhythmicity. The program also calculates heart diameter measurements during both diastole and systole from which fractional shortening and fractional area changes are calculated. Output is provided as a digital file compatible with most spreadsheet programs. Measurements are made for every heartbeat in a record increasing the statistical power of the output. We demonstrate each of the steps where user input is required and show the application of our methodology to the analysis of heart function in all three genetically tractable heart models.

We have developed a Semi-automated Optical Heartbeat Analysis method (SOHA) for analyzing high speed optical recordings from Drosophila, zebrafish and embryonic mouse hearts. We demonstrate the application of our methodology to the analysis of heart function in fruit fly and embryonic mouse hearts.

Semi-automatizado de análisis óptico latido de los corazones pequeños

We have developed a method for analyzing high speed optical recordings from Drosophila, zebrafish and embryonic mouse hearts (Fink, et. al., 2009). Our ...

Investigación

Biología

RNA Secondary Structure Prediction Using High-throughput SHAPE

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed "high-throughput selective 2' hydroxyl acylation analyzed by primer extension", or SHAPE, allows prediction of RNA secondary structure with single nucleotide resolution. This approach utilizes chemical probing agents that preferentially acylate single stranded or flexible regions of RNA in aqueous solution. Sites of chemical modification are detected by reverse transcription of the modified RNA, and the products of this reaction are fractionated by automated capillary electrophoresis (CE). Since reverse transcriptase pauses at those RNA nucleotides modified by the SHAPE reagents, the resulting cDNA library indirectly maps those ribonucleotides that are single stranded in the context of the folded RNA. Using ShapeFinder software, the electropherograms produced by automated CE are processed and converted into nucleotide reactivity tables that are themselves converted into pseudo-energy constraints used in the RNAStructure (v5.3) prediction algorithm. The two-dimensional RNA structures obtained by combining SHAPE probing with in silico RNA secondary structure prediction have been found to be far more accurate than structures obtained using either method alone.

High-throughput selective 2' hydroxyl acylation analyzed by primer extension (SHAPE) utilizes a novel chemical probing technology, reverse transcription, capillary electrophoresis and secondary structure prediction software to determine the structures of RNAs from several hundred to several thousand nucleotides at single nucleotide resolution.

ARN de predicción de estructura secundaria Utilizando SHAPE de alto rendimiento

Understanding the function of RNA involved in biological processes requires a thorough knowledge of RNA structure. Toward this end, the methodology dubbed ...

An Innovative Method for Exosome Quantification and Size Measurement

Although the biological importance of exosomes has recently gained an increasing amount of scientific and clinical attention, much is still unknown about their complex pathways, their bioavailability and their diverse functions in health and disease. Current work focuses on the presence and the behavior of exosomes (in vitro as well as in vivo) in the context of different human disorders, especially in the fields of oncology, gynecology and cardiology.
Unfortunately, neither a consensus regarding a gold standard for exosome isolation exists, nor is there an agreement on such a method for their quantitative analysis. As there are many methods for the purification of exosomes and also many possibilities for their quantitative and qualitative analysis, it is difficult to determine a combination of methods for the ideal approach. 
Here, we demonstrate nanoparticle tracking analysis (NTA), a semi-automated method for the characterization of exosomes after isolation from human plasma by ultracentrifugation. The presented results show that this approach for isolation, as well as the determination of the average number and size of exosomes, delivers reproducible and valid data, as confirmed by other methods, such as scanning electron microscopy (SEM).

A method for isolation of exosomes from whole blood and further analysis by nanoparticle tracking using a semi-automatic instrument is presented in this article. The presented technology provides an extremely sensitive method for visualizing and analyzing particles in liquid suspension.

Un método innovador para exosome cuantificación y medición de tamaño

Although the biological importance of exosomes has recently gained an increasing amount of scientific and clinical attention, much is still unknown about ...

An Improved Method for Accurate and Rapid Measurement of Flight Performance in Drosophila

Drosophila has proven to be a useful model system for analysis of behavior, including flight. The initial flight tester involved dropping flies into an oil-coated graduated cylinder; landing height provided a measure of flight performance by assessing how far flies will fall before producing enough thrust to make contact with the wall of the cylinder. Here we describe an updated version of the flight tester with four major improvements. First, we added a &#34;drop tube&#34; to ensure that all flies enter the flight cylinder at a similar velocity between trials, eliminating variability between users. Second, we replaced the oil coating with removable plastic sheets coated in Tangle-Trap, an adhesive designed to capture live insects. Third, we use a longer cylinder to enable more accurate discrimination of flight ability. Fourth we use a digital camera and imaging software to automate the scoring of flight performance. These improvements allow for the rapid, quantitative assessment of flight behavior, useful for large datasets and large-scale genetic screens.

An Improved Method for Accurate and Rapid Measurement of Flight Performance in Drosophila

Here we describe a method for rapid and accurate measurement of flight performance in Drosophila, enabling high-throughput screening.

Un método mejorado para la rápida y precisa medición de rendimiento en vuelo<em&gt; Drosophila</em

Drosophila has proven to be a useful model system for analysis of behavior, including flight. The initial flight tester involved dropping flies into an ...

Semi-automated Imaging of Tissue-specific Fluorescence in Zebrafish Embryos

Zebrafish embryos are a powerful tool for large-scale screening of small molecules. Transgenic zebrafish that express fluorescent reporter proteins are frequently used to identify chemicals that modulate gene expression. Chemical screens that assay fluorescence in live zebrafish often rely on expensive, specialized equipment for high content screening. We describe a procedure using a standard epifluorescence microscope with a motorized stage to automatically image zebrafish embryos and detect tissue-specific fluorescence. Using transgenic zebrafish that report estrogen receptor activity via expression of GFP, we developed a semi-automated procedure to screen for estrogen receptor ligands that activate the reporter in a tissue-specific manner. In this video we describe procedures for arraying zebrafish embryos at 24-48 hours post fertilization (hpf) in a 96-well plate and adding small molecules that bind estrogen receptors. At 72-96 hpf, images of each well from the entire plate are automatically collected and manually inspected for tissue-specific fluorescence. This protocol demonstrates the ability to detect estrogens that activate receptors in heart valves but not in liver.

Described here is a protocol for semi-automated imaging of tissue-specific fluorescence in zebrafish embryos.

Imaging semi-automatizado de fluorescencia específica de tejido en embriones de pez cebra

Zebrafish embryos are a powerful tool for large-scale screening of small molecules. Transgenic zebrafish that express fluorescent reporter proteins are ...

Relating Stomatal Conductance to Leaf Functional Traits

Leaf functional traits are important because they reflect physiological functions, such as transpiration and carbon assimilation. In particular, morphological leaf traits have the potential to summarize plants strategies in terms of water use efficiency, growth pattern and nutrient use. The leaf economics spectrum (LES) is a recognized framework in functional plant ecology and reflects a gradient of increasing specific leaf area (SLA), leaf nitrogen, phosphorus and cation content, and decreasing leaf dry matter content (LDMC) and carbon nitrogen ratio (CN). The LES describes different strategies ranging from that of short-lived leaves with high photosynthetic capacity per leaf mass to long-lived leaves with low mass-based carbon assimilation rates. However, traits that are not included in the LES might provide additional information on the species&#39; physiology, such as those related to stomatal control. Protocols are presented for a wide range of leaf functional traits, including traits of the LES, but also traits that are independent of the LES. In particular, a new method is introduced that relates the plants&#8217; regulatory behavior in stomatal conductance to vapor pressure deficit. The resulting parameters of stomatal regulation can then be compared to the LES and other plant functional traits. The results show that functional leaf traits of the LES were also valid predictors for the parameters of stomatal regulation. For example, leaf carbon concentration was positively related to the vapor pressure deficit (vpd) at the point of inflection and the maximum of the conductance-vpd curve. However, traits that are not included in the LES added information in explaining parameters of stomatal control: the vpd at the point of inflection of the conductance-vpd curve was lower for species with higher stomatal density and higher stomatal index. Overall, stomata and vein traits were more powerful predictors for explaining stomatal regulation than traits used in the LES.

Unraveling how physiology and morphology are linked allows a deeper understanding of mechanistic functioning of plant leaves. We present both a procedure to derive parameters of stomatal regulation from stomatal conductance measurements and correlations with traditional functional leaf traits.

Relacionar estomática conductancia de la hoja Rasgos funcionales

Leaf functional traits are important because they reflect physiological functions, such as transpiration and carbon assimilation. In particular, ...

Automated Quantification and Analysis of Cell Counting Procedures Using ImageJ Plugins

The National Institute of Health&#39;s ImageJ is a powerful, freely available image processing software suite. ImageJ has comprehensive particle analysis algorithms which can be used effectively to count various biological particles. When counting large numbers of cell samples, the hemocytometer presents a bottleneck with regards to time. Likewise, counting membranes from migration/invasion assays with the ImageJ plugin Cell Counter, although accurate, is exceptionally labor intensive, subjective, and infamous for causing wrist pain. To address this need, we developed two plugins within ImageJ for the sole task of automated hemocytometer (or known volume) and migration/invasion cell counting. Both plugins rely on the ability to acquire high quality micrographs with minimal background. They are easy to use and optimized for quick counting and analysis of large sample sizes with built-in analysis tools to help calibration of counts. By combining the core principles of Cell Counter with an automated counting algorithm and post-counting analysis, this greatly increases the ease with which migration assays can be processed without any loss of accuracy.

This paper describes the quantification of hemocytometer and migration/invasion micrographs through two new open-source ImageJ plugins Cell Concentration Calculator and migration assay Counter. Furthermore, it describes image acquisition and calibration protocols as well as discusses in detail the input requirements of the plugins.

Automatizado de cuantificación y análisis de los procedimientos de recuento de células usando ImageJ Plugins

The National Institute of Health&#39;s ImageJ is a powerful, freely available image processing software suite. ImageJ has comprehensive particle analysis ...

Clock Scan Protocol for Image Analysis: ImageJ Plugins

The clock scan protocol for image analysis is an efficient tool to quantify the average pixel intensity within, at the border, and outside (background) a closed or segmented convex-shaped region of interest, leading to the generation of an averaged integral radial pixel-intensity profile. This protocol was originally developed in 2006, as a visual basic 6 script, but as such, it had limited distribution. To address this problem and to join similar recent efforts by others, we converted the original clock scan protocol code into two Java-based plugins compatible with NIH-sponsored and freely available image analysis programs like ImageJ or Fiji ImageJ. Furthermore, these plugins have several new functions, further expanding the range of capabilities of the original protocol, such as analysis of multiple regions of interest and image stacks. The latter feature of the program is especially useful in applications in which it is important to determine changes related to time and location. Thus, the clock scan analysis of stacks of biological images may potentially be applied to spreading of Na+ or Ca++ within a single cell, as well as to the analysis of spreading activity (e.g., Ca++ waves) in populations of synaptically-connected or gap junction-coupled cells. Here, we describe these new clock scan plugins and show some examples of their applications in image analysis.

This paper describes two novel ImageJ plugins for &#39;Clock Scan&#39; image analysis. These plugins expand the functionality of the original visual basic 6 program and, most importantly, make the program available to a large research community by bundling it with the ImageJ free image analysis software package.

Protocolo de análisis de reloj para análisis de imagen: Plugins de ImageJ

The clock scan protocol for image analysis is an efficient tool to quantify the average pixel intensity within, at the border, and outside (background) a ...

Aislamiento semiautomatizado de tejido adiposo blanco murino

Semi-Automated Isolation of the Stromal Vascular Fraction from Murine White Adipose Tissue Using a Tissue Dissociator

The in vitro study of white, brown, and beige adipocyte differentiation enables the investigation of cell-autonomous functions of adipocytes and their mechanisms. Immortalized white preadipocyte cell lines are publicly available and widely used. However, the emergence of beige adipocytes in white adipose tissue in response to external cues is difficult to recapitulate to the full extent using publicly available white adipocyte cell lines. Isolation of the stromal vascular fraction (SVF) from murine adipose tissue is commonly executed to obtain primary preadipocytes and perform adipocyte differentiation. However, mincing and collagenase digestion of adipose tissue by hand can result in experimental variation and is prone to contamination. Here, we present a modified semi-automated protocol that utilizes a tissue dissociator for collagenase digestion to achieve easier isolation of the SVF, with the aim of reducing experimental variation, reducing contamination, and increasing reproducibility. The obtained preadipocytes and differentiated adipocytes can be used for functional and mechanistic analyses.

Autor destacado: Aislamiento semiautomatizado de la fracción vascular estromal a partir de tejido adiposo blanco murino mediante un disociador de tejidos  

This protocol describes the semi-automated isolation of the stromal vascular fraction (SVF) from murine adipose tissue to obtain preadipocytes and achieve adipocyte differentiation in vitro. Using a tissue dissociator for collagenase digestion reduces experimental variation and increases reproducibility.

Aislamiento semiautomático de la fracción vascular estromal del tejido adiposo blanco murino utilizando un disociador tisular

The in vitro study of white, brown, and beige adipocyte differentiation enables the investigation of cell-autonomous functions of adipocytes and their ...