O Gladstone Institutes Dr Katherine Pollard laboratuvarında tatilde iken LeafJ JNM tarafından yazılmıştır. Bu çalışma, Ulusal Bilim Vakfı (Hibe numarası IOS-0923752) tarafından sağlanan hibe ile desteklenmiştir.

1. Bitki Materyalleri Bu bitki büyüme protokolü gölge kaçınma yanıtını tespit için amaçlanmıştır unutmayın. En sevdiğiniz koşul altında bitkiler büyüyebilir. <ol><li> Karanlıkta dört gün boyunca 4 az 9 cm Petri kapları ve mağaza (tabakalandırmak) onları ° C filtre kağıtları batırılmış su Arabidopsis thaliana tohumu serpin. </li><li> Simüle güneş koşulları bu petri aktarın: 1.86 FR oranı: 80-100 μE fotosentetik aktif radyasyon (PAR) ve uzak-kırmızı takviyesi R getirmek. Uzun bir günün koşullarında (16 saat aydınlık / 8 saat karanlık) ve 22 sabit sıcaklık ° C kullanın Tohumların çimlenmeye izin vermek üzere üç gün için bu durum içinde inkübe edin. </li><li> Toprağa çimlenmiş tohum aktarın ve güneş koşullarında bitkiler tutmak. Büyük ölçekli deneyler için, etiket yapmak için Microsoft Word 2004 (veya üstü) olarak birleştirme Yöneticisi Veri kullanarak her bitki etiketleme için küçük etiketler hazırlamak öneririz. </li><li> Onbir gün sonra trToprağa ansfer, gölge durumuna bitkilerin yarısı hareket: güneş gibi ama 0.52 ile R / FR oranı getirmek için ek uzak kırmızı ışık ile aynı. </li><li> Ek bir on iki gün sonra, bitkilerin yaprak görüntüleme için hazırdır. Eğer bir gelişme anlık yakalamak böylece genç yapraklar hala genişleyen ise bu aşamada büyük yaprakları tamamen olgunlaşmıştır. İhtiyaçlarınıza bağlı olarak, farklı bir gelişme süresini seçmek isteyebilirsiniz. </li></ol> 2. Dissected Yaprak Görüntü Yakalama <ol><li> Beş dikdörtgen çerçeveli bitki genotipi ve büyüme durumu ile etiketlenmiş şeffaflık yaprak hazırlayın. Bir frame bir bitki yaprakları karşılık gelir. Microsoft Excel etiket ile tutarlı bir ızgara baskı için de kullanılabilir. </li><li> Yirmi altı gün eski bitkilerin yaprakları teşrih. </li><li> Tarama düz yataklı tarayıcıya 600 dpi bırakır. Bir bitkinin yaprakları Not şeffaf tabaka arasında bir sandviç siyah bir pencere içinde dikey olarak yerleştirilmelidir. Dokunmaktan yaprakları kaçınınAşağıdaki yordamlar hataları verecektir siyah bir pencere çerçevesi ve örtüşen yaprakları için. </li></ol> 3. LeafJ tarafından Yaprak Görüntü Analizi <ol><li> İndir ImageJ ImageJ ve plugins klasörüne LeafJ.jar dosya sürükleyin. </li><li> ImageJ 1.45s veya sonraki 14 bir resim dosyası açın. </li><li> &quot;&gt; Split Kanallar Görüntü&gt; Renk&quot; üç renk kanalları (kırmızı, yeşil ve mavi) içine görüntü Split ve mavi kanalda görüntüye eşik uygulayın. </li><li> Bir dikdörtgen aracı (Şekil 1A) tek bitki yapraklarının tümünü seçin. </li><li> Eklenti menüsünden &quot;LeafJ&quot; seçeneğini seçin. </li><li> Görüntülenen iletişim kutusunda bu bitki için açıklama bilgisini seçin. You can&quot;Bu düzenleme seçenekleri&quot; buraya tıklayarak görüntülenen varsayılan değerleri düzenlemek. </li><li> LeafJ eklenti çalıştırdıktan sonra ve &quot;OK&quot; butonuna tıklamadan önce, faiz (ROI) yöneticisi penceresi (; Şekil 1B gerekirse) bölgesinden takip hatları düzenleyin. Bir dokunmatik ekranlı tablet (örneğin bir iPad gibi) bu işlem için yararlıdır. iPad&#39;ler Air Display yazılımı kullanarak harici bir monitör olarak bir bilgisayara bağlanabilir. </li><li> Ölçüm sonuçları ve Microsoft Excel veya eşdeğer yazılım ilişkili bilgileri (dosya adları, çiçekli zamanı ile disseke, ölçülen, vb) aktarın. </li></ol> 4. ImageJ Yaprak Hücre Görüntü Analizi <ol><li> Disseke Fix olarak (adım 2) taramadan sonra referans 15&#39;te açıklandığı bırakır. FAA sabit yaprakları en az 6 ay süreyle 4 ° C&#39;de muhafaza edilebilir. </li><li> Mikroskobik gözlem 15 önce 1 ~ 2 saat süreyle kloral hidrat çözeltisi ve inkübe yaprakları FAA fiksatif değiştirerek yaprakları temizleyin. </li><li> Dağı mil üzerinde bırakırmikroskop tüyler yukarı bakacak şekilde kayar. Tüyler veya damar yakın hücre kaçınarak, ana damar her iki tarafında her bir yaprak merkezinin bir bileşik mikroskop, görüntü mezofil tabaka üzerinde 40x büyütme kullanılması. </li><li> Trace yaprak hücresindeki dokunmatik ekranlı tablet ve bir kalemle (olarak 3. adımda açıklandığı gibi) yardımı ile ImageJ ROI yöneticisi aracı tarafından özetliyor. Hücre görüntü analizi ImageJ ve yerleşik özellikler kullanır ama LeafJ gerektirmez. </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>

Çıkar çatışması ilan etti.

Bizim &quot;LeafJ&quot; eklentisi manuel ölçüm fazla verim yaklaşık 6 kat artarak, yarı-otomatik sapı uzunluğu ölçüm sağlar. Yaprak sapı uzunluğu SAS önemli bir göstergesi ve aynı zamanda batıklık direnci ve hyponastic büyüme 17 gibi diğer olayların, bir dönüm noktası olduğunu. Bu nedenle, bu eklenti bitki araştırmacılar geniş bir yararlı olabilir. Bizim eklentisi köklü bir java tabanlı ücretsiz yazılım, ImageJ uygulanmaktadır. Bu kolay çapr...

<html><table border="1"><tbody><tr><td> Reaktif Adı </td><td> Şirket </td><td> Katalog numarası </td><td></td></tr><tr><td> far-kırmızı LED ışığı </td><td> Orbitec </td><td> ısmarlama </td><td></td></tr><tr><td> şeffaflık </td><td> İKON </td><td> HSCA / 5 </td><td></td></tr><tr><td> tarayıcı </td><td> Epson </td><td> Epson Perfection V700 PHOTO </td><td></td></tr><tr><td> Görüntü 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> görenek </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> Hava Ekran </td><td> Avatron Software Inc </td><td></td><td>blank &quot;&gt; http://avatron.com/ </td></tr><tr><td> iPad2 </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

Yüksek verim fenotipleme (phenomics) (yorum 1 ve yeni örnekler 2-4 bakın) işlevlerine genleri bağlantı için güçlü bir araçtır. Yapraklar birincil fotosentetik organı vardır, ve boyutu ve şekli, bir bitki içinde gelişimsel olarak ve çevresel olarak değişir. Bu nedenlerden dolayı yaprak morfolojisi üzerine çalışmaları iyi yarı otomatik phenomics araçlar 5,6 yapılır sayısız yaprakları, birden fazla parametre ölçüm gerektirir. Canopy gölge bitki mimarisi ve yaşam öyküsü etkileyen önemli bir çevresel işaret olduğunu; yanıtların paketi topluca gölgede kaçınma sendromu (SAS) 7 denir. SAS yanıtları arasında, gölge uyarılmış yaprak sapı uzama ve bıçak alan değişiklikleri indeksleri 8 olarak özellikle yararlı olmaktadır. Bugüne kadar, yaprak şekli programlar (örn. SHAPE 9, LAMINA 10, LeafAnalyzer 11, LEAFPROCESSOR 12) yaprak anahatları ölçmek ve yaprak şekilleri kategorilere ayırabilirsinizAma yaprak sapı uzunluğu çıkışını alamazsınız. Yaprak sapı büyük ölçekli ölçüm sistemlerinin eksikliği SAS araştırma phenomics yaklaşımlar inhibe etmiştir. Bu yazıda, hızla model bitki Arabidopsis thaliana sapı uzunluğu ve yaprak ayası parametreleri ölçebilen LeafJ adlandırılan, yeni geliştirilmiş ImageJ eklentisi, tarif. Sapı / yaprak ayası sınır gerekli manuel düzeltme biz bir dokunmatik ekranlı tablet kullanılan sıra yaprak için. Ayrıca, yaprak hücre şekli ve yaprak hücre sayıları yaprak boyutu 13 önemli belirleyicileri. LeafJ ayırın biz de hücre şekli, alanı ve boyutunu ölçmek için bir dokunmatik ekranlı tablet kullanmak için bir protokol mevcut. Bizim yaprak sürekli ölçüm sistemi gölge-kaçınma araştırma ile sınırlı değildir ve yaprak fenotipleme tarafından birçok mutantlar ve tarama bitkilerin yaprak fenotipleme hızlandıracaktır.

1. Yaprak sapı ve Yaprak Blade Sınır tahminleri gösteriliyor Yaprak Görüntü ve Bunları Ölçme Pencere LeafJ en kullanışlı özelliklerinden biri yaprak ayası / sapı sınır (Şekil 1) otomatik algılama olduğunu. Aşağıdaki gibi LeafJ algoritması çalışır: yerleşik ImageJ ParticleAnalyzer özelliğe kullanıcının seçim içinde yaprakların yönlendirme bulmak ve belirlemek için kullanılır. Her yaprak için yaprak genişliği yaprağın tüm eksen boyu...

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

Yüksek verimlilik yaprak ölçümler için anahtar yöntemleri gösterilmesi. Bu yöntemler, yaprak fenotip ile pek çok bitki mutant ya da başka tarama bitki incelenirken yaprak fenotipleme hızlandırmak için kullanılabilir.

LeafJ: Yarı otomatik Yaprak Shape Ölçüm için bir ImageJ Plugin

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 Görüntüleme.  University of California Davis. Yüksek verimlilik yaprak ölçümler için anahtar yöntemleri gösterilmesi. Bu yöntemler, yaprak fenotip ile pek çok bitki mutant ya da başka tarama bitki incelenirken yaprak fenotipleme hızlandırmak için kullanılabilir.

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.

Küçük Kalpler Yarı-otomatik Optik Heartbeat Analizi

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

Biyoloji

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.

Yüksek verim SHAPE kullanarak RNA İkincil Yapısı Tahmin

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.

Exosome Kantifikasyon ve Boyut Ölçüm Yenilikçi Yöntem

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.

Uçuş Performans Doğru ve hızlı ölçüm için geliştirilmiş Yöntemi<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.

Zebra balığı Embriyolar Doku spesifik Floresans yarı otomatik Görüntüleme

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.

Yaprak Fonksiyonel Özellikleri için ağıza ait iletkenlik İlişkin

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.

ImageJ Eklentileri Kullanma Hücre Sayım Usul Otomatik Niceleme ve Analizi

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.

Görüntü Analizi için Saat Tarama Protokolü: ImageJ Eklentileri

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 ...

Murin Beyaz Yağ Dokusunun Yarı Otomatik İzolasyonu

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.

Yazar Spotlight: Murin Beyaz Yağ Dokusundan Stromal Vasküler Fraksiyonun Bir Doku Ayrıştırıcı Kullanılarak Yarı Otomatik İzolasyonu  

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.

Bir Doku Dissosiyatör Kullanarak Stromal Vasküler Fraksiyonun Murin Beyaz Yağ Dokusundan Yarı Otomatik İzolasyonu

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