Drosophila_plate02_control

COLLECTION TITLE: * 2020_ACC_RP_DrosophilaBloodCells ARTICLE (when using these files, please, cite the following article): * A. Szkalisity, F. Piccinini, A. Beleon, T. Balassa, I.G. Varga, E. Migh, C. Molnar, L. Paavolainen, S. Timonen, I. Banerjee, E. Ikonen, Y. Yamauchi, I. Ando, J. Peltonen, V. Pietiäinen, V. Honti, P. Horvath, Regression plane concept for analysing continuous cellular processes with machine learning. Nature Communications, 2021 KEYWORDS: * High-Throughput Screening, Fluorescence Microscopy, Drosophila Blood Cells, Machine Learning, Differentiation, Hematopoiesis CATEGORIES: * Bioinformatics, Biological Techniques BIOLOGICAL APPLICATION: * In the blood cell differentiation study, the immune response of Drosophila melanogaster larvae - the differentiation of lamellocytes - were induced by wounding with an insect pin. * The larvae were bled 12 hours after the wounding, and hemocytes were cultured in a well of an 8 well µ-slide (Ibidi, Cat:80826) in Schneider’s medium (Lonza, Cat: 04-351 Q) supplemented with 10% FBS (Gibco, Cat: 10270), 0,01 mg/ml gentamicin (Sigma, Cat: G3632), 0,065 mg/ml penicillin (Sigma, Cat: P7794) and 0,1 mg/ml streptamicin (Sigma, Cat: S6501) at 25 °C. * The transdifferentiation of plasmatocytes into lamellocytes was monitored by cell type specific transgenes (eaterGFP for plasmatocytes, and MSNF9MOmCherry for lamellocytes as described in Anderl et al., Transdifferentiation and proliferation in two distinct hemocyte lineages in Drosophila melanogaster larvae after wasp infection. PLoS Pathogens, 12, 7, e1005746 2016). IMAGES: * 15-frame RGB image sequence/field (141 fields), representing the brightfield, mCherry, EGFP channels, with 2 hours gap between subsequent frames. * Images were acquired with an high-content screening microscope (Operetta, Perkin Elmer) with a 60x high-numeric-aperture objective and a digital high resolution 14-bit CCD camera, for a total of 4230 images (2 plates, 2115 images in each). * The image size is 1360x1024 pixels and 8-bit per channel RGB TIFF format. * In this dataset the images are already prepared for being directly analysed in Advanced Cell Classifier (ACC). FORMAT OF THE FILES: * The files in this collection follow the Advanced Cell Classifier (ACC) standard. HOW TO OPEN THE DATASET IN ACC: * Download a plate ("plate01_induced" or "plate02_control") into a folder (this parent folder is termed ACC Project Folder) * Download the corresponding trained project file ("Test_ACC_Project.mat"). * Launch ACC (freely available for download at cellclassifier.org) * Click 'Open project' in the toolbar and select the downloaded trained project file. When you are asked for a new datapath specify your ACC project folder ("plate01_induced" or "plate02_control"). IMAGING INFO: * These images were generated by Viktor Honti, Istvan Gergely Varga, and Istvan Ando at the Biological Research Centre (BRC), Szeged, Hungary. * Image features were extracted by Peter Horvath at BRC. * Please contact Viktor Honti ([e-mail]) or Peter Horvath ([e-mail]) for more information. MAIN CONTACTS: * Viktor Honti, Biological Research Centre (BRC), Szeged, Hungary. Email: [e-mail] * Peter Horvath, Biological Research Centre (BRC), Szeged, Hungary. Email: [e-mail] COPYRIGHT: * Copyright (c) 2020, Viktor Honti, Istvan Gergely Varga, Istvan Ando, Peter Horvath * Biological Research Centre (BRC), Szeged, Hungary * All rights reserved. * * Redistribution and use of the material, with or without modification, is provided for academic research purpose only. * * This material is free; you can redistribute it and/or modify it under the terms of the GNU General Public License version 3 (or higher) as published by the Free Software Foundation. * This material is distributed WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. * See the GNU General Public License for more details.数据集标题：* 2020_ACC_RP_果蝇血细胞 文章（使用本数据集文件时，请务必引用以下文献）：* A. Szkalisity, F. Piccinini, A. Beleon, T. Balassa, I.G. Varga, E. Migh, C. Molnar, L. Paavolainen, S. Timonen, I. Banerjee, E. Ikonen, Y. Yamauchi, I. Ando, J. Peltonen, V. Pietiäinen, V. Honti, P. Horvath, 用于通过机器学习分析连续细胞过程的回归平面概念. Nature Communications, 2021 关键词：* 高通量筛选（High-Throughput Screening）、荧光显微镜（Fluorescence Microscopy）、果蝇血细胞（Drosophila Blood Cells）、机器学习（Machine Learning）、细胞分化（Differentiation）、造血作用（Hematopoiesis） 分类：* 生物信息学、生物学实验技术 生物学应用：* 本研究针对黑腹果蝇（Drosophila melanogaster）幼虫的免疫反应展开，通过昆虫针穿刺伤口诱导其片足细胞（lamellocytes）的分化。* 幼虫于穿刺伤口后12小时采血，血细胞被接种于8孔μ-slide（Ibidi，货号：80826）的培养孔中，使用Schneider’s培养基（Lonza，货号：04-351 Q）进行培养，该培养基添加了10%胎牛血清（FBS，Gibco，货号：10270）、0.01 mg/ml庆大霉素（Sigma，货号：G3632）、0.065 mg/ml青霉素（Sigma，货号：P7794）及0.1 mg/ml链霉素（Sigma，货号：S6501），培养温度设置为25℃。* 浆血细胞（plasmatocytes）向片足细胞的转分化通过细胞类型特异性转基因进行监测：浆血细胞使用eaterGFP标记，片足细胞使用MSNF9MOmCherry标记，具体实验方案详见Anderl等人2016年发表于PLoS Pathogens的文章：Transdifferentiation and proliferation in two distinct hemocyte lineages in Drosophila melanogaster larvae after wasp infection. PLoS Pathogens, 12, 7, e1005746 2016。 图像信息：* 每个视野包含15帧RGB图像序列（共141个视野），涵盖明场、mCherry及EGFP三个通道，相邻帧之间的时间间隔为2小时。* 图像采用高内涵筛选显微镜（Operetta，珀金埃尔默（Perkin Elmer））采集，搭配60倍高数值孔径物镜及14位高分辨率CCD相机，总计采集4230张图像（2块检测板，每板2115张）。* 图像分辨率为1360×1024像素，单通道为8位RGB TIFF格式。* 本数据集内的图像已完成预处理，可直接用于高级细胞分类器（Advanced Cell Classifier, ACC）分析。 文件格式：* 本数据集内的所有文件均符合高级细胞分类器（ACC）的标准格式。 在ACC中打开数据集的方法：* 将单块板的数据（"plate01_induced"或"plate02_control"）下载至指定文件夹（该父文件夹称为ACC项目文件夹）* 下载对应的已训练项目文件"Test_ACC_Project.mat"。* 启动ACC（可从cellclassifier.org免费下载）* 点击工具栏中的“打开项目”选项，选择已下载的已训练项目文件。当系统提示指定新数据路径时，请选择您的ACC项目文件夹（"plate01_induced"或"plate02_control"）。 成像相关信息：* 本批图像由匈牙利塞格德生物研究中心（BRC）的Viktor Honti、Istvan Gergely Varga及Istvan Ando完成拍摄。* 图像特征由BRC的Peter Horvath提取。* 如需获取更多相关信息，请联系Viktor Honti（邮箱：[e-mail]）或Peter Horvath（邮箱：[e-mail]）。 主要联系人：* Viktor Honti，匈牙利塞格德生物研究中心（BRC），邮箱：[e-mail]* Peter Horvath，匈牙利塞格德生物研究中心（BRC），邮箱：[e-mail] 版权声明：* 版权所有 © 2020 Viktor Honti、Istvan Gergely Varga、Istvan Ando、Peter Horvath* 匈牙利塞格德生物研究中心（BRC）* 保留所有权利。* * 本材料的再分发与使用（无论是否修改）仅可用于学术研究目的。* * 本材料为免费分发材料；您可根据自由软件基金会发布的GNU通用公共许可证第3版（或更高版本）的条款对其进行再分发和修改。* 本材料按“现状”提供，不附带任何明示或默示的担保，包括但不限于适销性或特定用途适用性的担保。* 有关详细信息，请参阅GNU通用公共许可证。