Статті в журналах: "Real-time cell analysis"

1

Vogt, Nina. "Real-time behavioral analysis." Nature Methods 18, no. 2 (February 2021): 123. http://dx.doi.org/10.1038/s41592-021-01072-z.

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Pranada, Albert L., Silke Metz, Andreas Herrmann, Peter C. Heinrich, and Gerhard Müller-Newen. "Real Time Analysis of STAT3 Nucleocytoplasmic Shuttling." Journal of Biological Chemistry 279, no. 15 (December 29, 2003): 15114–23. http://dx.doi.org/10.1074/jbc.m312530200.

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3

Jaiswal, Devina, Armin Tahmasbi Rad, Mu-Ping Nieh, Kevin P. Claffey, and Kazunori Hoshino. "Micromagnetic Cancer Cell Immobilization and Release for Real-Time Single Cell Analysis." Journal of Magnetism and Magnetic Materials 427 (April 2017): 7–13. http://dx.doi.org/10.1016/j.jmmm.2016.11.002.

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Fregin, Bob, Fabian Czerwinski, Doreen Biedenweg, Salvatore Girardo, Stefan Groß, Konstanze Aurich, and Oliver Otto. "Dynamic Real-Time Deformability Cytometry - Time-Resolved Mechanical Single Cell Analysis at 100 Cells/s." Biophysical Journal 118, no. 3 (February 2020): 605a. http://dx.doi.org/10.1016/j.bpj.2019.11.3267.

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5

Cerignoli, Fabio, Yama A. Abassi, Brandon J. Lamarche, Garret Guenther, David Santa Ana, Diana Guimet, Wen Zhang, Jing Zhang, and Biao Xi. "In vitro immunotherapy potency assays using real-time cell analysis." PLOS ONE 13, no. 3 (March 2, 2018): e0193498. http://dx.doi.org/10.1371/journal.pone.0193498.

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Rappoport, J. Z. "Real-time analysis of clathrin-mediated endocytosis during cell migration." Journal of Cell Science 116, no. 5 (January 15, 2003): 847–55. http://dx.doi.org/10.1242/jcs.00289.

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7

Ersöz, M., S. Malkoç, EB Küçük, BS Bozkurt, and SS Hakki. "Biocompatibility evaluation of orthodontic composite by real-time cell analysis." Human & Experimental Toxicology 35, no. 8 (July 19, 2016): 833–38. http://dx.doi.org/10.1177/0960327115607944.

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Introduction: The aim of this study was to evaluate the cytotoxic effects of three different light-cured orthodontic composites. Material and methods: Light Bond (Reliance orthodontic products), Grengloo (Ormco corporation), and Kurasper F (Kuraray Europe GmbH) were selected for the experiment. Specimens were prepared according to the manufacturers’ instructions, measuring 5 mm in diameter and 2 mm in thickness. Fibroblast cells were obtained from healthy gingival connective tissues. The composite cylinders were incubated in Dulbecco’s modified Eagle’s culture medium for 72 h according to ISO 10993-5 standards. The xCELLigence method was used to evaluate fibroblast cell vitality. After seeding 200 mL of the cell suspensions into the wells (20,000 cells/well) of the E-plate 96, gingival fibroblasts were treated with bioactive components released by the orthodontic composite materials and monitored every 15 min for 121 h. Results: There were no significant differences between the human gingival fibroblast (HGF) cell indexes of the control and all testing groups ( p > 0.05) at 24 and 48 h. Light Bond demonstrated statistically significant decrease in HGF index ( p < 0.05) at 72 h, but there was no significant difference among the Kurasper F, Grengloo, and untreated control groups ( p > 0.05). Light Bond ( p < 0.001) and Grengloo ( p < 0.05) groups had lower HGF cell index values when compared to untreated control group, but Kurasper F demonstrated no significant differences between the control groups at 96 h ( p > 0.05). Conclusion: Orthodontic composite materials include biologically active components and may change oral tissue. So, biocompatible orthodontic bonding composites should be used.

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Simons, Peter C., Sean M. Biggs, Anna Waller, Terry Foutz, Daniel F. Cimino, Qing Guo, Richard R. Neubig, Wei-Jen Tang, Eric R. Prossnitz, and Larry A. Sklar. "Real-time Analysis of Ternary Complex on Particles." Journal of Biological Chemistry 279, no. 14 (January 15, 2004): 13514–21. http://dx.doi.org/10.1074/jbc.m310306200.

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9

Mazhar, Muhammad Waqar. "Molecular Analysis of Covid-19 Patient Real Time PCR and their Medicational Clinical Trials." Virology & Immunology Journal 5, no. 3 (August 2, 2021): 1–4. http://dx.doi.org/10.23880/vij-16000284.

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The corona name derived from their crown like spike proteins attach with cell receptors. It belongs to corona viradae family and nideo virales order, envelop virus, size range 65-125nm and positive single standard RNA between 26.4 to 31.7 kb and contain7096 amino acid. There are four subtypes that have been detected these are alpha, beta, gamma and delta. The 267 covid -19 blood and nasopharyngeal samples were collected from Multan region. RNA extraction from nasopharyngeal samples and run the PCR. The blood samples use for clinical tests, Lactate dehydrogenase, serum ferritin level, D-Dimer, TG, cholesterol, thyphoidot, HDL, lymphocyte count and CRP. The 127 (47.21%) out of 267 patients were covid-19 PCR positive and showed the amplification ORF1ab, E and N gene while140 individuals were covid-19 PCR negative and not showed the amplification of ORF1ab, E and N gene. The patients with negative Covid-19 PCR, the other analysis tests such as lactate dehydrogenase, HDL, ferritin, ESR,CBP, D. Dimer, Tg, cholesterol, CRP and CT scan. The patients affected covid-19 has higher values of D-Dimer, ESR, Neutrophils, LDH, CRP and ferritin level than normal ranges. But the values of the HDL, cholesterol and lymphocytes were decreased form the normal ranges. Drugs are mentioned in table #3 that is treating for covid 19- patients. These drugs are successful for Covid -19 treatments.

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10

Aoyama, Tadayoshi, Amalka De Zoysa, Qingyi Gu, Takeshi Takaki, and Idaku Ishii. "Vision-Based Real-Time Microflow-Rate Control System for Cell Analysis." Journal of Robotics and Mechatronics 28, no. 6 (December 20, 2016): 854–61. http://dx.doi.org/10.20965/jrm.2016.p0854.

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[abstFig src='/00280006/09.jpg' width='300' text='Snapshots of particle sorting experiment using our system' ] On-chip cell analysis is an important issue for microtechnology research, and microfluidic devices are frequently used in on-chip cell analysis systems. One approach to controlling the fluid flow in microfluidic devices for cell analysis is to use a suitable pumps. However, it is difficult to control the actual flow-rate in a microfluidic device because of the difficulty in placing flow-rate sensors in the device. In this study, we developed a real-time flow-rate control system that uses syringe pumps and high-speed vision to measure the actual fluid flow in microfluidic devices. The developed flow-rate control system was verified through experiments on microparticle velocity control and microparticle sorting.

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11

Barbee, K. A., S. Hong, E. Ergezen, S. Kwoun, and R. Lec. "Real time analysis of cell-surface adhesive interactions using TSM sensor." Journal of Biomechanics 39 (January 2006): S242. http://dx.doi.org/10.1016/s0021-9290(06)83911-4.

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12

Slanina, H., A. König, H. Claus, M. Frosch, and A. Schubert-Unkmeir. "Real-time impedance analysis of host cell response to meningococcal infection." Journal of Microbiological Methods 84, no. 1 (January 2011): 101–8. http://dx.doi.org/10.1016/j.mimet.2010.11.004.

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13

Rehm, Markus, Heiko Düßmann, and Jochen H. M. Prehn. "Real-time single cell analysis of Smac/DIABLO release during apoptosis." Journal of Cell Biology 162, no. 6 (September 15, 2003): 1031–43. http://dx.doi.org/10.1083/jcb.200303123.

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We examined the temporal and causal relationship between Smac/DIABLO release, cytochrome c (cyt-c) release, and caspase activation at the single cell level during apoptosis. Cells treated with the broad-spectrum caspase inhibitor z-VAD-fmk, caspase-3 (Casp-3)–deficient MCF-7 cells, as well as Bax-deficient DU-145 cells released Smac/DIABLO and cyt-c in response to proapoptotic agents. Real-time confocal imaging of MCF-7 cells stably expressing Smac/DIABLO-yellow fluorescent protein (YFP) revealed that the average duration of Smac/DIABLO-YFP release was greater than that of cyt-c-green fluorescent protein (GFP). However, there was no significant difference in the time to the onset of release, and both cyt-c-GFP and Smac/DIABLO-YFP release coincided with mitochondrial membrane potential depolarization. We also observed no significant differences in the Smac/DIABLO-YFP release kinetics when z-VAD-fmk–sensitive caspases were inhibited or Casp-3 was reintroduced. Simultaneous measurement of DEVDase activation and Smac/DIABLO-YFP release demonstrated that DEVDase activation occurred within 10 min of release, even in the absence of Casp-3.

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14

Ramis, G., L. Martínez-Alarcón, J. J. Quereda, L. Mendonça, M. J. Majado, K. Gomez-Coelho, A. Mrowiec, et al. "Optimization of cytotoxicity assay by real-time, impedance-based cell analysis." Biomedical Microdevices 15, no. 6 (July 26, 2013): 985–95. http://dx.doi.org/10.1007/s10544-013-9790-8.

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15

Akere, Millicent T., Kelsee K. Zajac, James D. Bretz, Anvitha R. Madhavaram, Austin C. Horton, and Isaac T. Schiefer. "Real-Time Analysis of Neuronal Cell Cultures for CNS Drug Discovery." Brain Sciences 14, no. 8 (July 30, 2024): 770. http://dx.doi.org/10.3390/brainsci14080770.

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The ability to screen for agents that can promote the development and/or maintenance of neuronal networks creates opportunities for the discovery of novel agents for the treatment of central nervous system (CNS) disorders. Over the past 10 years, advances in robotics, artificial intelligence, and machine learning have paved the way for the improved implementation of live-cell imaging systems for drug discovery. These instruments have revolutionized our ability to quickly and accurately acquire large standardized datasets when studying complex cellular phenomena in real-time. This is particularly useful in the field of neuroscience because real-time analysis can allow efficient monitoring of the development, maturation, and conservation of neuronal networks by measuring neurite length. Unfortunately, due to the relative infancy of this type of analysis, standard practices for data acquisition and processing are lacking, and there is no standardized format for reporting the vast quantities of data generated by live-cell imaging systems. This paper reviews the current state of live-cell imaging instruments, with a focus on the most commonly used equipment (IncuCyte systems). We provide an in-depth analysis of the experimental conditions reported in publications utilizing these systems, particularly with regard to studying neurite outgrowth. This analysis sheds light on trends and patterns that will enhance the use of live-cell imaging instruments in CNS drug discovery.

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16

Santonastaso, Alice, and Claudia Scotti. "Real Time Cell Analysis of Model Target Cell Lines Exposed to Purified Lipoprotein (a)." British Journal of Medicine and Medical Research 16, no. 4 (January 10, 2016): 1–12. http://dx.doi.org/10.9734/bjmmr/2016/26869.

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17

Ozdemir, Aysun, and Mustafa Ark. "xCELLigence Real Time Cell Analysis System: A New Method for Cell Proliferation and Cytotoxicity." Niche Journal 2, no. 2 (September 12, 2014): 15–17. http://dx.doi.org/10.5152/niche.2014.153.

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18

Ye, Julian, Yun Luo, Weijia Fang, Junhang Pan, Zheng Zhang, Yanjun Zhang, Zhiping Chen, and Dazhi Jin. "Real-Time Cell Analysis for Monitoring Cholera Toxin-Induced Human Intestinal Epithelial Cell Response." Current Microbiology 70, no. 4 (December 16, 2014): 536–43. http://dx.doi.org/10.1007/s00284-014-0752-z.

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Di Costanzo, Ezio, Vincenzo Ingangi, Claudia Angelini, Maria Francesca Carfora, Maria Vincenza Carriero, and Roberto Natalini. "A Macroscopic Mathematical Model for Cell Migration Assays Using a Real-Time Cell Analysis." PLOS ONE 11, no. 9 (September 28, 2016): e0162553. http://dx.doi.org/10.1371/journal.pone.0162553.

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20

Lecoeur, Hervé, Alain Langonné, Ludwig Baux, Dominique Rebouillat, Pierre Rustin, Marie-Christine Prévost, Catherine Brenner, Léna Edelman, and Etienne Jacotot. "Real-time flow cytometry analysis of permeability transition in isolated mitochondria." Experimental Cell Research 294, no. 1 (March 2004): 106–17. http://dx.doi.org/10.1016/j.yexcr.2003.10.030.

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21

Yan, Guojun, Qian Du, Xuchao Wei, Jackelyn Miozzi, Chen Kang, Jinnv Wang, Xinxin Han, et al. "Application of Real-Time Cell Electronic Analysis System in Modern Pharmaceutical Evaluation and Analysis." Molecules 23, no. 12 (December 11, 2018): 3280. http://dx.doi.org/10.3390/molecules23123280.

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Objective: We summarized the progress of the xCELLigence real-time cell analysis (RTCA) technology application in recent years for the sake of enriching and developing the application of RTCA in the field of Chinese medicine. Background: The RTCA system is an established electronic cellular biosensor. This system uses micro-electronic biosensor technology that is confirmed for real-time, label-free, dynamic and non-offensive monitoring of cell viability, migration, growth, spreading, and proliferation. Methods: We summarized the relevant experiments and literature of RTCA technology from the principles, characteristics, applications, especially from the latest application progress. Results and conclusion: RTCA is attracting more and more attention. Now it plays an important role in drug screening, toxicology, Chinese herbal medicine and so on. It has wide application prospects in the area of modern pharmaceutical evaluation and analysis.

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Carmichael, Stephen W. "Developmental Dynamics in Real Time." Microscopy Today 17, no. 3 (May 2009): 3–5. http://dx.doi.org/10.1017/s1551929500050021.

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Embryologic development is a dynamic process that has been previously studied by examining static (usually chemically-fixed) specimens at different time periods and then extrapolating results by assembling a series of static images. Recently, Amy McMahon, Willy Supatto, Scott Fraser, and Angelike Stathopoulos have developed new methods to look at developmental migration patterns in real time. They used an optimized imaging approach and quantitative methods to analyze a two hour period during which gastrulation occurred in the embryos of fruitflies (Drosophila). Specifically, they characterized the complex interactions between cells of the ectoderm and mesoderm by tracking the movements of over 1,500 cells, which involved the analysis of over 100,000 cell positions for each embryo!

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23

Gomes, Eliza, Felipe Costa, Carlos De Rolt, Patricia Plentz, and Mario Dantas. "A Survey from Real-Time to Near Real-Time Applications in Fog Computing Environments." Telecom 2, no. 4 (December 3, 2021): 489–517. http://dx.doi.org/10.3390/telecom2040028.

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In this article, we present a comprehensive survey on time-sensitive applications implemented in fog computing environments. The goal is to research what applications are being implemented in fog computing architectures and how the temporal requirements of these applications are being addressed. We also carried out a comprehensive analysis of the articles surveyed and separate them into categories, according to a pattern found in them. Our research is important for the area of real-time systems since the concept of systems that respond in real time has presented various understandings and concepts. This variability of concept has been due to the growing requirements for fast data communication and processing. Therefore, we present different concepts of real-time and near real-time systems found in the literature and currently accepted by the academic-scientific community. Finally, we conduct an analytical discussion of the characteristics and proposal of articles.

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Dow, J. A., J. M. Lackie, and K. V. Crocket. "A simple microcomputer-based system for real-time analysis of cell behaviour." Journal of Cell Science 87, no. 1 (February 1, 1987): 171–82. http://dx.doi.org/10.1242/jcs.87.1.171.

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An image analysis package based on a BBC microcomputer has been developed, which can simultaneously track many moving cells in vitro. Cells (rabbit neutrophil leucocytes, BHK C13 fibroblasts, or PC12 phaeochromocytoma cells) are viewed under phase optics with a monochrome TV camera, and the signal digitized. Successive frames are acquired by the computer as a 640 X 256 pixel array. Under controlled lighting conditions, cells can readily be isolated from the background by binary filtering. In real-time tracking, the positions of a given cell in successive frames are obtained by searching the area around the cell's centroid in the previous frame. A simple box-search algorithm is described, which proves highly successful at low cell densities. The resilience of different search algorithms to various exceptional conditions (such as collisions) is discussed. The success of this system in real-time tracking is largely dependent upon the leisurely speed of movement of cells, and on obtaining a clean, high quality optical image to analyse. The limitations of this technique for different cell types, and the possible configurations of more sophisticated hardware, are outlined. This system provides a versatile and automated solution to the problem of studying the movement of tissue cells.

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25

Toy, Ebubekir, BuketS Bozkurt, SemaS Hakki, Erdem Hatunoglu, and Firat Ozturk. "Real-time cell analysis of cytotoxicity of orthodontic cements on gingival fibroblasts." Journal of Orthodontic Research 2, no. 1 (2014): 32. http://dx.doi.org/10.4103/2321-3825.125922.

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26

Ma, Rui, Zhongliang Li, Elena Breaz, Briois Pascal, and Fei Gao. "Numerical Stiffness Analysis for Solid Oxide Fuel Cell Real-Time Simulation Applications." IEEE Transactions on Energy Conversion 33, no. 4 (December 2018): 1917–28. http://dx.doi.org/10.1109/tec.2018.2849930.

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DEMIREL, Gülbike, Fatma Funda KAYA DEMIRSOY, and Özgür IRMAK. "Cytotoxicity evaluation of eluates from universal adhesives by real-time cell analysis." Dental Materials Journal 39, no. 5 (September 28, 2020): 815–24. http://dx.doi.org/10.4012/dmj.2019-221.

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28

LeFurgey, A., S. D. Davilla, D. A. Kopf, J. R. Sommer, and P. Ingram. "Real-time quantitative elemental analysis and mapping: microchemical imaging in cell physiology." Journal of Microscopy 165, no. 2 (February 1992): 191–223. http://dx.doi.org/10.1111/j.1365-2818.1992.tb01481.x.

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29

Lodygin, Dmitri, and Alexander Flügel. "Intravital real-time analysis of T-cell activation in health and disease." Cell Calcium 64 (June 2017): 118–29. http://dx.doi.org/10.1016/j.ceca.2016.12.007.

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30

Shah, F. J., C. Caviglia, K. Zór, M. Carminati, G. Ferrari, M. Sampietro, A. Martínez-Serrano, J. K. Emnéus, and A. R. Heiskanen. "Impedance-based real-time monitoring of neural stem cell differentiation." Journal of Electrical Bioimpedance 12, no. 1 (January 1, 2021): 34–49. http://dx.doi.org/10.2478/joeb-2021-0006.

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Abstract We present here the first impedance-based characterization of the differentiation process of two human mesencephalic fetal neural stem lines. The two dopaminergic neural stem cell lines used in this study, Lund human mesencephalic (LUHMES) and human ventral mesencephalic (hVM1 Bcl-XL), have been developed for the study of Parkinsonian pathogenesis and its treatment using cell replacement therapy. We show that if only relying on impedance magnitude analysis, which is by far the most usual approach in, e.g., cytotoxicity evaluation and drug screening applications, one may not be able to distinguish whether the neural stem cells in a population are proliferating or differentiating. However, the presented results highlight that equivalent circuit analysis can provide detailed information on cellular behavior, e.g. simultaneous changes in cell morphology, cell-cell contacts, and cell adhesion during formation of neural projections, which are the fundamental behavioral differences between proliferating and differentiating neural stem cells. Moreover, our work also demonstrates the sensitivity of impedance-based monitoring with capability to provide information on changes in cellular behavior in relation to proliferation and differentiation. For both of the studied cell lines, in already two days (one day after induction of differentiation) equivalent circuit analysis was able to show distinction between proliferation and differentiation conditions, which is significantly earlier than by microscopic imaging. This study demonstrates the potential of impedance-based monitoring as a technique of choice in the study of stem cell behavior, laying the foundation for screening assays to characterize stem cell lines and testing the efficacy epigenetic control.

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31

Chigaev, Alexandre, Ann Marie Blenc, Julie V. Braaten, Nateasa Kumaraswamy, Christopher L. Kepley, Ronald P. Andrews, Janet M. Oliver та ін. "Real Time Analysis of the Affinity Regulation of α4-Integrin". Journal of Biological Chemistry 276, № 52 (18 жовтня 2001): 48670–78. http://dx.doi.org/10.1074/jbc.m103194200.

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32

Silberstein, Lev, Masatake Osawa, Charles Lin, Peter Kharchenko, Cristina Lo Celso, Chiaka Aribeana, and David T. Scadden. "Real-Time RT-PCR Analysis of Individual Osteolineage Cells within the Hematopoietic Stem Cell Niche." Blood 118, no. 21 (November 18, 2011): 2389. http://dx.doi.org/10.1182/blood.v118.21.2389.2389.

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Abstract Abstract 2389 Osteolineage cells (OLCs) have been shown to participate in a regulatory bone marrow microenvironment for the hematopoietic stem and progenitor cells (HSPCs) – the endosteal niche. Our previous experiments using live animal imaging have demonstrated that single transplanted HSPCs preferentially home in close proximity to the individual OLCs. We hypothesized that these HSPC-proximal cells represent a distinct subpopulation of OLCs, which is specifically involved in a non-cell autonomous regulation of HSPC quiescence and self-renewal. To test this hypothesis, we developed a novel experimental platform, which allows visualization of HSPC-OLC cell pairs in-vivo and retrieval of the individual OLCs for molecular analysis. We intravenously injected DiI labeled adult bone marrow-derived FACS-sorted Lin−Sca1+c-kit+CD34−Flk2− HSPCs into irradiated newborn collagen 2.3GFP mouse recipients; in this transgenic strain, the majority of the OLCs are labeled with green fluorescent protein (GFP). 48 hours later, we sacrificed the animals and obtained fresh unfixed sections of femoral trabecular bone. Using a combination of differential interference contrast fluorescent microscopy, in-situ enzymatic digestion and micromanipulation, we harvested individual GFP-positive OLCs located within 2 cell diameters (“niche” OLCs) or greater than 5 cell diameters (“control” OLCs) from single DiI-bright HSPCs. Following reverse transcription and cDNA amplification with 29 cycles of PCR, as per the single cell RNA-Seq protocol (Tang et al, Nature Protocols 2010), we performed real-time RT-PCR analysis of 31 samples – 15 niche cells and 16 controls - for the OLC signature genes (osteocalcin, osterix) and for the genes implicated in playing a functional role in the HSPC-OLC cell interaction (osteopontin, CXCL12, angiopoietin 1). Transcripts for GAPDH, collagen 1 and GFP served as positive controls for the amplification. As expected, all cells were positive for GFP and over 85% cells expressed collagen 1. Osteopontin and CXCL12 were expressed at a similar level and frequency in the niche and control OLCs. However, we found that angiopoietin 1 transcripts were detected exclusively in the niche OLCs (3/15 versus 0/16, p <0.05 by Chi-squared). Moreover, niche OLCs were enriched for the osterix-positive cells (7/15 versus 2/16, p <0.05 by Chi-squared) and expressed a lower level of osteocalcin, as normalized for GAPDH expression (1.13 vs. 0.97, p< 0.05 by t-test). Our results suggest that niche OLCs may have a distinct molecular signature and reside within a population of very immature OLCs, as evidenced by the osterix + osteocalcin low phenotype. Further unbiased transcriptome characterization of these cells using genome-wide RNA-Seq assay is therefore likely to provide more evidence in support of our hypothesis and reveal novel non-cell autonomous regulators of HSPC quiescence. To our knowledge, this approach represents the first attempt to define molecular heterogeneity in-vivo at a single cell level using the micro-anatomical relationship between two heterologous cell types. Disclosures: Scadden: Fate Therapeutics: Equity Ownership.

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33

Roberts, Adam, and Lior Pachter. "Streaming fragment assignment for real-time analysis of sequencing experiments." Nature Methods 10, no. 1 (January 2013): 71–73. http://dx.doi.org/10.1038/nmeth.2251.

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Ferracci, Géraldine, Michael Seagar, Courageot Joël, Raymond Miquelis, and Christian Lévêque. "Real time analysis of intact organelles using surface plasmon resonance." Analytical Biochemistry 334, no. 2 (November 2004): 367–75. http://dx.doi.org/10.1016/j.ab.2004.08.002.

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35

Banerjee, Suchitra, K. P. Madhusudanan, Suman P. S. Khanuja, and Sunil K. Chattopadhyay. "Analysis of cell cultures ofTaxus wallichiana using direct analysis in real-time mass spectrometric technique." Biomedical Chromatography 22, no. 3 (2008): 250–53. http://dx.doi.org/10.1002/bmc.919.

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36

Schneider, Joachim, Vera Classen, Monika Philipp, and Simone Helmig. "Rapid analysis of XRCC1 polymorphisms using real-time polymerase chain reaction." Molecular and Cellular Probes 20, no. 3-4 (June 2006): 259–62. http://dx.doi.org/10.1016/j.mcp.2006.01.004.

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Rancurel, Corinne, Trang van Tran, Céline Elie, and Frédérique Hilliou. "SATQPCR: Website for statistical analysis of real-time quantitative PCR data." Molecular and Cellular Probes 46 (August 2019): 101418. http://dx.doi.org/10.1016/j.mcp.2019.07.001.

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38

Liu, Yan, Yunhai Zhang, Qiuling Jiang, Man Rao, Zheya Sheng, Yu Zhang, Weihua Du, et al. "Identification of Valid Housekeeping Genes for Real-Time Quantitative PCR Analysis of Collapsed Lung Tissues of Neonatal Somatic Cell Nuclear Transfer–Derived Cattle." Cellular Reprogramming 17, no. 5 (October 2015): 360–67. http://dx.doi.org/10.1089/cell.2015.0024.

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Warnes, G., and S. Martins. "Real-time flow cytometry for the kinetic analysis of oncosis." Cytometry Part A 79A, no. 3 (January 20, 2011): 181–91. http://dx.doi.org/10.1002/cyto.a.21022.

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Li, Xiaokang, Maria Soler, Crispin Szydzik, Khashayar Khoshmanesh, Julien Schmidt, George Coukos, Arnan Mitchell, and Hatice Altug. "Single Cell Analysis: Label-Free Optofluidic Nanobiosensor Enables Real-Time Analysis of Single-Cell Cytokine Secretion (Small 26/2018)." Small 14, no. 26 (June 2018): 1870119. http://dx.doi.org/10.1002/smll.201870119.

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41

Türker Şener, Leyla, Gürcan Albeni̇z, Bi̇rcan Di̇nç, and Işil Albeni̇z. "iCELLigence real-time cell analysis system for examining the cytotoxicity of drugs to cancer cell lines." Experimental and Therapeutic Medicine 14, no. 3 (July 11, 2017): 1866–70. http://dx.doi.org/10.3892/etm.2017.4781.

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42

Eriksson, Ida, Linda Vainikka, Hans Lennart Persson, and Karin Öllinger. "Real-Time Monitoring of Lysosomal Membrane Permeabilization Using Acridine Orange." Methods and Protocols 6, no. 4 (August 9, 2023): 72. http://dx.doi.org/10.3390/mps6040072.

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Анотація:

Loss of lysosomal membrane integrity results in leakage of lysosomal hydrolases to the cytosol which might harm cell function and induce cell death. Destabilization of lysosomes often precede apoptotic or necrotic cell death and occur during both physiological and pathological conditions. The weak base acridine orange readily enters cells and accumulates in the acidic environment of lysosomes. Vital staining with acridine orange is a well-proven technique to observe lysosomal destabilization using fluorescence microscopy and flow cytometry. These analyses are, however, time consuming and only adapted for discrete time points, which make them unsuitable for large-scale approaches. Therefore, we have developed a time-saving, high-throughput microplate reader-based method to follow destabilization of the lysosomal membrane in real-time using acridine orange. This protocol can easily be adopted for patient samples since the number of cells per sample is low and the time for analysis is short.

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43

Toy, Ebubekir, Siddik Malkoc, Bayram Corekci, Buket S. Bozkurt, and Sema S. Hakki. "Real-time cell analysis of the cytotoxicity of orthodontic brackets on gingival fibroblasts." Journal of Applied Biomaterials & Functional Materials 12, no. 3 (2014): 248–55. http://dx.doi.org/10.5301/jabfm.5000165.

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Biwer, Christopher M., Andres Quan, Larissa Q. Huston, Blake T. Sturtevant, and Christine M. Sweeney. "Cinema:Snap: Real-time tools for analysis of dynamic diamond anvil cell experiment data." Review of Scientific Instruments 92, no. 10 (October 1, 2021): 103901. http://dx.doi.org/10.1063/5.0057878.

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45

Stockinger, Walter, Adam B. Castoreno, Yan Wang, Joanne C. Pagnon, and Axel Nohturfft. "Real-time analysis of endosomal lipid transport by live cell scintillation proximity assay." Journal of Lipid Research 45, no. 11 (August 16, 2004): 2151–58. http://dx.doi.org/10.1194/jlr.d400011-jlr200.

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46

Sanchez-Freire, Veronica, Antje D. Ebert, Tomer Kalisky, Stephen R. Quake, and Joseph C. Wu. "Microfluidic single-cell real-time PCR for comparative analysis of gene expression patterns." Nature Protocols 7, no. 5 (April 5, 2012): 829–38. http://dx.doi.org/10.1038/nprot.2012.021.

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47

Wettstein, P., M. Strausbauch, T. Therneau, and N. Borson. "The application of real-time PCR to the analysis of T cell repertoires." Nucleic Acids Research 36, no. 21 (October 23, 2008): e140-e140. http://dx.doi.org/10.1093/nar/gkn634.

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Prasad, Brinda, Shan Du, Wael Badawy, and Karan V. I. S. Kaler. "A real-time multiple-cell tracking platform for dielectrophoresis (DEP)-based cellular analysis." Measurement Science and Technology 16, no. 4 (February 26, 2005): 909–24. http://dx.doi.org/10.1088/0957-0233/16/4/003.

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Hewett, P. J., M. L. Texler, D. Anderson, Grant King, and B. E. Chatterton. "In vivo real-time analysis of intraperitoneal radiolabeled tumor cell movement during laparoscopy." Diseases of the Colon & Rectum 42, no. 7 (July 1999): 868–75. http://dx.doi.org/10.1007/bf02237091.

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Chen, Jiao, Tianhong Pan, Bharathi Devi Devendran, Zhankun Xi, Swanand Khare, Biao Huang, Weiping Zhang, Stephan Gabos, Dorothy Yu Huang, and Can Jin. "Analysis of inter-/intra-E-plate repeatability in the real-time cell analyzer." Analytical Biochemistry 477 (May 2015): 98–104. http://dx.doi.org/10.1016/j.ab.2015.01.026.

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