Semi-automated detection of single cell signatures from a dielectrophoretic cytometer
We present a semi-automated event identification method for collecting the dielectrophoretic signatures of cells flowing through a dieletrophoretic cytometer. The marker free dielectrophoresis (DEP) cytometer presented in this study is capable of detecting electronic signatures of cells which identi...
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| creator | Rizi, Bahareh Saboktakin Bhide, Ashlesha Cabel, Tim Nikolic-Jaric, Marija Salimi, Elham Braasch, Katrin Butler, Michael Bridges, Greg E. Thomson, Douglas J. |
| description | We present a semi-automated event identification method for collecting the dielectrophoretic signatures of cells flowing through a dieletrophoretic cytometer. The marker free dielectrophoresis (DEP) cytometer presented in this study is capable of detecting electronic signatures of cells which identifies Claussius-Mossotti factor (CMF). The CMF can in turn be used to determine properties of the cell such as the viability. In past work the DEP cytometer signals were manually sorted by going through the entire recorded signals, which is very time-consuming. In the semi-automated method of collection, events are identified and displayed in the user interface to be accepted or rejected. We present results using semi-automated method on Hamster Chinese Ovary (CHO) cells in a batch culture and compared them with the manual analysis. The automated approach identified over 80% of the events identified manually and produced event histogram distributions nearly identical to the manual method. |
| doi_str_mv | 10.1109/I2MTC.2013.6555581 |
| format | Conference Proceeding |
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The marker free dielectrophoresis (DEP) cytometer presented in this study is capable of detecting electronic signatures of cells which identifies Claussius-Mossotti factor (CMF). The CMF can in turn be used to determine properties of the cell such as the viability. In past work the DEP cytometer signals were manually sorted by going through the entire recorded signals, which is very time-consuming. In the semi-automated method of collection, events are identified and displayed in the user interface to be accepted or rejected. We present results using semi-automated method on Hamster Chinese Ovary (CHO) cells in a batch culture and compared them with the manual analysis. The automated approach identified over 80% of the events identified manually and produced event histogram distributions nearly identical to the manual method.</description><identifier>ISSN: 1091-5281</identifier><identifier>ISBN: 9781467346214</identifier><identifier>ISBN: 1467346217</identifier><identifier>EISBN: 1467346233</identifier><identifier>EISBN: 9781467346238</identifier><identifier>DOI: 10.1109/I2MTC.2013.6555581</identifier><language>eng</language><publisher>IEEE</publisher><subject>Chinese Hamster Ovary (CHO) ; classification ; cytometer ; Dielectrophoresis ; Electric fields ; Electrodes ; Force ; Indexes ; Manuals ; microfluidic ; semi-automate ; viability</subject><ispartof>2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2013, p.1083-1087</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6555581$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,778,782,787,788,2054,27908,54903</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6555581$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Rizi, Bahareh Saboktakin</creatorcontrib><creatorcontrib>Bhide, Ashlesha</creatorcontrib><creatorcontrib>Cabel, Tim</creatorcontrib><creatorcontrib>Nikolic-Jaric, Marija</creatorcontrib><creatorcontrib>Salimi, Elham</creatorcontrib><creatorcontrib>Braasch, Katrin</creatorcontrib><creatorcontrib>Butler, Michael</creatorcontrib><creatorcontrib>Bridges, Greg E.</creatorcontrib><creatorcontrib>Thomson, Douglas J.</creatorcontrib><title>Semi-automated detection of single cell signatures from a dielectrophoretic cytometer</title><title>2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)</title><addtitle>I2MTC</addtitle><description>We present a semi-automated event identification method for collecting the dielectrophoretic signatures of cells flowing through a dieletrophoretic cytometer. The marker free dielectrophoresis (DEP) cytometer presented in this study is capable of detecting electronic signatures of cells which identifies Claussius-Mossotti factor (CMF). The CMF can in turn be used to determine properties of the cell such as the viability. In past work the DEP cytometer signals were manually sorted by going through the entire recorded signals, which is very time-consuming. In the semi-automated method of collection, events are identified and displayed in the user interface to be accepted or rejected. We present results using semi-automated method on Hamster Chinese Ovary (CHO) cells in a batch culture and compared them with the manual analysis. The automated approach identified over 80% of the events identified manually and produced event histogram distributions nearly identical to the manual method.</description><subject>Chinese Hamster Ovary (CHO)</subject><subject>classification</subject><subject>cytometer</subject><subject>Dielectrophoresis</subject><subject>Electric fields</subject><subject>Electrodes</subject><subject>Force</subject><subject>Indexes</subject><subject>Manuals</subject><subject>microfluidic</subject><subject>semi-automate</subject><subject>viability</subject><issn>1091-5281</issn><isbn>9781467346214</isbn><isbn>1467346217</isbn><isbn>1467346233</isbn><isbn>9781467346238</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1kM1OwzAQhI0AiVLyAnDxCyR47cR2jijip1IRB8K5cpxNMUriynEPfXssUeayO9Lsp9UQcg-sAGD144a_t03BGYhCVkkaLsgtlFKJUnIhLklWK_3vobwiq3QFecU13JBsWX4YYwkkBVMr8vWJk8vNMfrJROxpjxFtdH6mfqCLm_cjUovjmPb9bOIx4EKH4CdqaO9wTNngD98-YHSW2lPCJEC4I9eDGRfMznNN2pfntnnLtx-vm-ZpmztQVcxrULUyBmT6BSsplNAdYCllZ7lSRnWao-iG2lohpAYYeqg5clamsJYg1uThD-sQcXcIbjLhtDuXIn4Bqe1Twg</recordid><startdate>201305</startdate><enddate>201305</enddate><creator>Rizi, Bahareh Saboktakin</creator><creator>Bhide, Ashlesha</creator><creator>Cabel, Tim</creator><creator>Nikolic-Jaric, Marija</creator><creator>Salimi, Elham</creator><creator>Braasch, Katrin</creator><creator>Butler, Michael</creator><creator>Bridges, Greg E.</creator><creator>Thomson, Douglas J.</creator><general>IEEE</general><scope>6IE</scope><scope>6IH</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIO</scope></search><sort><creationdate>201305</creationdate><title>Semi-automated detection of single cell signatures from a dielectrophoretic cytometer</title><author>Rizi, Bahareh Saboktakin ; Bhide, Ashlesha ; Cabel, Tim ; Nikolic-Jaric, Marija ; Salimi, Elham ; Braasch, Katrin ; Butler, Michael ; Bridges, Greg E. ; Thomson, Douglas J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-91797aa16630e563738b1e466bc277a7b82e3bf9cc336811fd192e204e568613</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Chinese Hamster Ovary (CHO)</topic><topic>classification</topic><topic>cytometer</topic><topic>Dielectrophoresis</topic><topic>Electric fields</topic><topic>Electrodes</topic><topic>Force</topic><topic>Indexes</topic><topic>Manuals</topic><topic>microfluidic</topic><topic>semi-automate</topic><topic>viability</topic><toplevel>online_resources</toplevel><creatorcontrib>Rizi, Bahareh Saboktakin</creatorcontrib><creatorcontrib>Bhide, Ashlesha</creatorcontrib><creatorcontrib>Cabel, Tim</creatorcontrib><creatorcontrib>Nikolic-Jaric, Marija</creatorcontrib><creatorcontrib>Salimi, Elham</creatorcontrib><creatorcontrib>Braasch, Katrin</creatorcontrib><creatorcontrib>Butler, Michael</creatorcontrib><creatorcontrib>Bridges, Greg E.</creatorcontrib><creatorcontrib>Thomson, Douglas J.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan (POP) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP) 1998-present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Rizi, Bahareh Saboktakin</au><au>Bhide, Ashlesha</au><au>Cabel, Tim</au><au>Nikolic-Jaric, Marija</au><au>Salimi, Elham</au><au>Braasch, Katrin</au><au>Butler, Michael</au><au>Bridges, Greg E.</au><au>Thomson, Douglas J.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Semi-automated detection of single cell signatures from a dielectrophoretic cytometer</atitle><btitle>2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC)</btitle><stitle>I2MTC</stitle><date>2013-05</date><risdate>2013</risdate><spage>1083</spage><epage>1087</epage><pages>1083-1087</pages><issn>1091-5281</issn><isbn>9781467346214</isbn><isbn>1467346217</isbn><eisbn>1467346233</eisbn><eisbn>9781467346238</eisbn><abstract>We present a semi-automated event identification method for collecting the dielectrophoretic signatures of cells flowing through a dieletrophoretic cytometer. The marker free dielectrophoresis (DEP) cytometer presented in this study is capable of detecting electronic signatures of cells which identifies Claussius-Mossotti factor (CMF). The CMF can in turn be used to determine properties of the cell such as the viability. In past work the DEP cytometer signals were manually sorted by going through the entire recorded signals, which is very time-consuming. In the semi-automated method of collection, events are identified and displayed in the user interface to be accepted or rejected. We present results using semi-automated method on Hamster Chinese Ovary (CHO) cells in a batch culture and compared them with the manual analysis. The automated approach identified over 80% of the events identified manually and produced event histogram distributions nearly identical to the manual method.</abstract><pub>IEEE</pub><doi>10.1109/I2MTC.2013.6555581</doi><tpages>5</tpages></addata></record> |
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| identifier | ISSN: 1091-5281 |
| ispartof | 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), 2013, p.1083-1087 |
| issn | 1091-5281 |
| language | eng |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Chinese Hamster Ovary (CHO) classification cytometer Dielectrophoresis Electric fields Electrodes Force Indexes Manuals microfluidic semi-automate viability |
| title | Semi-automated detection of single cell signatures from a dielectrophoretic cytometer |
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